| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: Bio_ClinicalBERT_fold_2_binary_v1 |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # Bio_ClinicalBERT_fold_2_binary_v1 |
| |
| This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.9317 |
| - F1: 0.7921 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 290 | 0.4221 | 0.7856 | |
| | 0.4062 | 2.0 | 580 | 0.5184 | 0.7949 | |
| | 0.4062 | 3.0 | 870 | 0.6854 | 0.7840 | |
| | 0.1775 | 4.0 | 1160 | 0.9834 | 0.7840 | |
| | 0.1775 | 5.0 | 1450 | 1.3223 | 0.7804 | |
| | 0.0697 | 6.0 | 1740 | 1.2896 | 0.7923 | |
| | 0.0265 | 7.0 | 2030 | 1.4620 | 0.7914 | |
| | 0.0265 | 8.0 | 2320 | 1.5554 | 0.7835 | |
| | 0.0102 | 9.0 | 2610 | 1.7009 | 0.7880 | |
| | 0.0102 | 10.0 | 2900 | 1.6163 | 0.7923 | |
| | 0.015 | 11.0 | 3190 | 1.6851 | 0.7841 | |
| | 0.015 | 12.0 | 3480 | 1.7493 | 0.7901 | |
| | 0.0141 | 13.0 | 3770 | 1.8819 | 0.7827 | |
| | 0.0133 | 14.0 | 4060 | 1.7535 | 0.7939 | |
| | 0.0133 | 15.0 | 4350 | 1.6613 | 0.7966 | |
| | 0.0067 | 16.0 | 4640 | 1.6807 | 0.7999 | |
| | 0.0067 | 17.0 | 4930 | 1.6703 | 0.7978 | |
| | 0.0053 | 18.0 | 5220 | 1.7309 | 0.8013 | |
| | 0.0037 | 19.0 | 5510 | 1.8058 | 0.7942 | |
| | 0.0037 | 20.0 | 5800 | 1.8233 | 0.7916 | |
| | 0.0023 | 21.0 | 6090 | 1.8206 | 0.7913 | |
| | 0.0023 | 22.0 | 6380 | 1.8466 | 0.7949 | |
| | 0.0012 | 23.0 | 6670 | 1.8531 | 0.7985 | |
| | 0.0012 | 24.0 | 6960 | 1.9211 | 0.7944 | |
| | 0.0001 | 25.0 | 7250 | 1.9317 | 0.7921 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
