Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/bert_base_km_50_v1_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_km_50_v1_mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/bert_base_km_50_v1_mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_km_50_v1_mrpc") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/bert_base_km_50_v1_mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from Hartunka/bert_base_km_50_v1_mrpc: direct link, hf CLI and curl.
- Browser
- Download file 4.61 kB
-
https://huggingface.co/Hartunka/bert_base_km_50_v1_mrpc/resolve/main/trainer_state.json
- Command line
-
hf download hf://Hartunka/bert_base_km_50_v1_mrpc/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/Hartunka/bert_base_km_50_v1_mrpc/resolve/main/trainer_state.json
4.61 kB
| { | |
| "best_global_step": 30, | |
| "best_metric": 0.5893518924713135, | |
| "best_model_checkpoint": "bert_base_km_50_v1_mrpc/checkpoint-30", | |
| "epoch": 7.0, | |
| "eval_steps": 500, | |
| "global_step": 105, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "grad_norm": 1.1089715957641602, | |
| "learning_rate": 4.9e-05, | |
| "loss": 0.6263, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.6887254901960784, | |
| "eval_combined_score": 0.7452987825395369, | |
| "eval_f1": 0.8018720748829953, | |
| "eval_loss": 0.5977591872215271, | |
| "eval_runtime": 0.2712, | |
| "eval_samples_per_second": 1504.571, | |
| "eval_steps_per_second": 7.375, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 1.4218831062316895, | |
| "learning_rate": 4.8e-05, | |
| "loss": 0.572, | |
| "step": 30 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.7034313725490197, | |
| "eval_combined_score": 0.7587817385018524, | |
| "eval_f1": 0.8141321044546851, | |
| "eval_loss": 0.5893518924713135, | |
| "eval_runtime": 0.2717, | |
| "eval_samples_per_second": 1501.661, | |
| "eval_steps_per_second": 7.361, | |
| "step": 30 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "grad_norm": 1.491407871246338, | |
| "learning_rate": 4.7e-05, | |
| "loss": 0.5108, | |
| "step": 45 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.7034313725490197, | |
| "eval_combined_score": 0.7552244582043344, | |
| "eval_f1": 0.8070175438596491, | |
| "eval_loss": 0.6016624569892883, | |
| "eval_runtime": 0.2743, | |
| "eval_samples_per_second": 1487.603, | |
| "eval_steps_per_second": 7.292, | |
| "step": 45 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "grad_norm": 2.704878091812134, | |
| "learning_rate": 4.600000000000001e-05, | |
| "loss": 0.4158, | |
| "step": 60 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_accuracy": 0.6838235294117647, | |
| "eval_combined_score": 0.737373677185623, | |
| "eval_f1": 0.7909238249594813, | |
| "eval_loss": 0.6796642541885376, | |
| "eval_runtime": 0.2784, | |
| "eval_samples_per_second": 1465.639, | |
| "eval_steps_per_second": 7.185, | |
| "step": 60 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "grad_norm": 4.1070427894592285, | |
| "learning_rate": 4.5e-05, | |
| "loss": 0.2727, | |
| "step": 75 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.6446078431372549, | |
| "eval_combined_score": 0.6872946105816629, | |
| "eval_f1": 0.7299813780260708, | |
| "eval_loss": 0.8248001337051392, | |
| "eval_runtime": 0.2734, | |
| "eval_samples_per_second": 1492.086, | |
| "eval_steps_per_second": 7.314, | |
| "step": 75 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "grad_norm": 2.6518099308013916, | |
| "learning_rate": 4.4000000000000006e-05, | |
| "loss": 0.1534, | |
| "step": 90 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "eval_accuracy": 0.6176470588235294, | |
| "eval_combined_score": 0.6659663865546219, | |
| "eval_f1": 0.7142857142857143, | |
| "eval_loss": 1.088710904121399, | |
| "eval_runtime": 0.2757, | |
| "eval_samples_per_second": 1479.813, | |
| "eval_steps_per_second": 7.254, | |
| "step": 90 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "grad_norm": 4.282205581665039, | |
| "learning_rate": 4.3e-05, | |
| "loss": 0.083, | |
| "step": 105 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "eval_accuracy": 0.6593137254901961, | |
| "eval_combined_score": 0.7062110368125936, | |
| "eval_f1": 0.7531083481349912, | |
| "eval_loss": 1.1340426206588745, | |
| "eval_runtime": 0.289, | |
| "eval_samples_per_second": 1411.96, | |
| "eval_steps_per_second": 6.921, | |
| "step": 105 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "step": 105, | |
| "total_flos": 3377819728711680.0, | |
| "train_loss": 0.37630167575109574, | |
| "train_runtime": 60.942, | |
| "train_samples_per_second": 3009.42, | |
| "train_steps_per_second": 12.307 | |
| } | |
| ], | |
| "logging_steps": 1, | |
| "max_steps": 750, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 50, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "EarlyStoppingCallback": { | |
| "args": { | |
| "early_stopping_patience": 5, | |
| "early_stopping_threshold": 0.0 | |
| }, | |
| "attributes": { | |
| "early_stopping_patience_counter": 5 | |
| } | |
| }, | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 3377819728711680.0, | |
| "train_batch_size": 256, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |