Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/tiny_bert_rand_50_v2_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/tiny_bert_rand_50_v2_mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/tiny_bert_rand_50_v2_mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/tiny_bert_rand_50_v2_mrpc") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/tiny_bert_rand_50_v2_mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download trainer_state.json from Hartunka/tiny_bert_rand_50_v2_mrpc: direct link, hf CLI and curl.
- Browser
- Download file 4.61 kB
-
https://huggingface.co/Hartunka/tiny_bert_rand_50_v2_mrpc/resolve/main/trainer_state.json
- Command line
-
hf download hf://Hartunka/tiny_bert_rand_50_v2_mrpc/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/Hartunka/tiny_bert_rand_50_v2_mrpc/resolve/main/trainer_state.json
4.61 kB
| { | |
| "best_global_step": 30, | |
| "best_metric": 0.5925365090370178, | |
| "best_model_checkpoint": "tiny_bert_rand_50_v2_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": 0.746475338935852, | |
| "learning_rate": 4.9e-05, | |
| "loss": 0.6271, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.696078431372549, | |
| "eval_combined_score": 0.7526546003016591, | |
| "eval_f1": 0.8092307692307692, | |
| "eval_loss": 0.6033073663711548, | |
| "eval_runtime": 0.1315, | |
| "eval_samples_per_second": 3102.082, | |
| "eval_steps_per_second": 15.206, | |
| "step": 15 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 1.2179274559020996, | |
| "learning_rate": 4.8e-05, | |
| "loss": 0.5912, | |
| "step": 30 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.6985294117647058, | |
| "eval_combined_score": 0.7542106100554595, | |
| "eval_f1": 0.8098918083462133, | |
| "eval_loss": 0.5925365090370178, | |
| "eval_runtime": 0.1343, | |
| "eval_samples_per_second": 3037.538, | |
| "eval_steps_per_second": 14.89, | |
| "step": 30 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "grad_norm": 0.8887869715690613, | |
| "learning_rate": 4.7e-05, | |
| "loss": 0.5551, | |
| "step": 45 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.6862745098039216, | |
| "eval_combined_score": 0.7428237752781364, | |
| "eval_f1": 0.799373040752351, | |
| "eval_loss": 0.6018652319908142, | |
| "eval_runtime": 0.1392, | |
| "eval_samples_per_second": 2931.211, | |
| "eval_steps_per_second": 14.369, | |
| "step": 45 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "grad_norm": 2.3352513313293457, | |
| "learning_rate": 4.600000000000001e-05, | |
| "loss": 0.5148, | |
| "step": 60 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_accuracy": 0.6421568627450981, | |
| "eval_combined_score": 0.6817654542733125, | |
| "eval_f1": 0.7213740458015268, | |
| "eval_loss": 0.6426445245742798, | |
| "eval_runtime": 0.2016, | |
| "eval_samples_per_second": 2023.814, | |
| "eval_steps_per_second": 9.921, | |
| "step": 60 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "grad_norm": 3.087498426437378, | |
| "learning_rate": 4.5e-05, | |
| "loss": 0.43, | |
| "step": 75 | |
| }, | |
| { | |
| "epoch": 5.0, | |
| "eval_accuracy": 0.6225490196078431, | |
| "eval_combined_score": 0.6665376676986584, | |
| "eval_f1": 0.7105263157894737, | |
| "eval_loss": 0.6741282343864441, | |
| "eval_runtime": 0.1361, | |
| "eval_samples_per_second": 2998.698, | |
| "eval_steps_per_second": 14.7, | |
| "step": 75 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "grad_norm": 5.535114765167236, | |
| "learning_rate": 4.4000000000000006e-05, | |
| "loss": 0.3406, | |
| "step": 90 | |
| }, | |
| { | |
| "epoch": 6.0, | |
| "eval_accuracy": 0.6372549019607843, | |
| "eval_combined_score": 0.6897075903532144, | |
| "eval_f1": 0.7421602787456446, | |
| "eval_loss": 0.8507905006408691, | |
| "eval_runtime": 0.1912, | |
| "eval_samples_per_second": 2134.365, | |
| "eval_steps_per_second": 10.463, | |
| "step": 90 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "grad_norm": 3.9563608169555664, | |
| "learning_rate": 4.3e-05, | |
| "loss": 0.2595, | |
| "step": 105 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "eval_accuracy": 0.6740196078431373, | |
| "eval_combined_score": 0.7237218993219094, | |
| "eval_f1": 0.7734241908006815, | |
| "eval_loss": 0.9303423762321472, | |
| "eval_runtime": 0.1535, | |
| "eval_samples_per_second": 2657.434, | |
| "eval_steps_per_second": 13.027, | |
| "step": 105 | |
| }, | |
| { | |
| "epoch": 7.0, | |
| "step": 105, | |
| "total_flos": 673316591603712.0, | |
| "train_loss": 0.4740510032290504, | |
| "train_runtime": 20.1601, | |
| "train_samples_per_second": 9097.158, | |
| "train_steps_per_second": 37.202 | |
| } | |
| ], | |
| "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": 673316591603712.0, | |
| "train_batch_size": 256, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |