| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| datasets: |
| - gokulsrinivasagan/processed_book_corpus-ld |
| metrics: |
| - accuracy |
| model-index: |
| - name: tinybert_train_book_v2 |
| results: |
| - task: |
| name: Masked Language Modeling |
| type: fill-mask |
| dataset: |
| name: gokulsrinivasagan/processed_book_corpus-ld |
| type: gokulsrinivasagan/processed_book_corpus-ld |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.6905521643636598 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # tinybert_train_book_v2 |
| |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the gokulsrinivasagan/processed_book_corpus-ld dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4246 |
| - Accuracy: 0.6906 |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| More information needed |
| |
| ## Training and evaluation data |
| |
| More information needed |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 160 |
| - eval_batch_size: 160 |
| - seed: 10 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 10000 |
| - num_epochs: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-------:|:------:|:---------------:|:--------:| |
| | 5.6396 | 0.7025 | 10000 | 5.4784 | 0.1645 | |
| | 5.5513 | 1.4051 | 20000 | 5.4083 | 0.1660 | |
| | 2.9289 | 2.1076 | 30000 | 2.5488 | 0.5214 | |
| | 2.5686 | 2.8102 | 40000 | 2.2269 | 0.5650 | |
| | 2.3542 | 3.5127 | 50000 | 2.0268 | 0.5945 | |
| | 2.2044 | 4.2153 | 60000 | 1.8924 | 0.6152 | |
| | 2.1102 | 4.9178 | 70000 | 1.8025 | 0.6296 | |
| | 2.0378 | 5.6203 | 80000 | 1.7395 | 0.6393 | |
| | 1.9881 | 6.3229 | 90000 | 1.6945 | 0.6467 | |
| | 1.9469 | 7.0254 | 100000 | 1.6552 | 0.6526 | |
| | 1.919 | 7.7280 | 110000 | 1.6279 | 0.6572 | |
| | 1.8899 | 8.4305 | 120000 | 1.6012 | 0.6613 | |
| | 1.8634 | 9.1331 | 130000 | 1.5849 | 0.6641 | |
| | 1.8481 | 9.8356 | 140000 | 1.5630 | 0.6679 | |
| | 1.8315 | 10.5381 | 150000 | 1.5476 | 0.6703 | |
| | 1.8209 | 11.2407 | 160000 | 1.5394 | 0.6716 | |
| | 1.8038 | 11.9432 | 170000 | 1.5250 | 0.6740 | |
| | 1.7932 | 12.6458 | 180000 | 1.5107 | 0.6761 | |
| | 1.7826 | 13.3483 | 190000 | 1.5058 | 0.6770 | |
| | 1.7736 | 14.0509 | 200000 | 1.4952 | 0.6785 | |
| | 1.7635 | 14.7534 | 210000 | 1.4862 | 0.6799 | |
| | 1.7549 | 15.4560 | 220000 | 1.4782 | 0.6815 | |
| | 1.7497 | 16.1585 | 230000 | 1.4737 | 0.6821 | |
| | 1.7407 | 16.8610 | 240000 | 1.4675 | 0.6832 | |
| | 1.7334 | 17.5636 | 250000 | 1.4612 | 0.6843 | |
| | 1.7288 | 18.2661 | 260000 | 1.4568 | 0.6849 | |
| | 1.7265 | 18.9687 | 270000 | 1.4519 | 0.6858 | |
| | 1.7179 | 19.6712 | 280000 | 1.4469 | 0.6868 | |
| | 1.7156 | 20.3738 | 290000 | 1.4428 | 0.6873 | |
| | 1.7086 | 21.0763 | 300000 | 1.4389 | 0.6882 | |
| | 1.7064 | 21.7788 | 310000 | 1.4334 | 0.6892 | |
| | 1.7009 | 22.4814 | 320000 | 1.4309 | 0.6895 | |
| | 1.6989 | 23.1839 | 330000 | 1.4292 | 0.6896 | |
| | 1.6971 | 23.8865 | 340000 | 1.4262 | 0.6902 | |
| | 1.6958 | 24.5890 | 350000 | 1.4239 | 0.6906 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.46.1 |
| - Pytorch 2.2.0+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.1 |
|
|
