| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: Bio_ClinicalBERT_fold_4_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_4_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: 1.4627 |
| - F1: 0.8342 |
| |
| ## 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 | 289 | 0.3641 | 0.8394 | |
| | 0.3953 | 2.0 | 578 | 0.3729 | 0.8294 | |
| | 0.3953 | 3.0 | 867 | 0.6156 | 0.8126 | |
| | 0.189 | 4.0 | 1156 | 0.7389 | 0.8326 | |
| | 0.189 | 5.0 | 1445 | 0.8925 | 0.8322 | |
| | 0.0783 | 6.0 | 1734 | 1.0909 | 0.8196 | |
| | 0.0219 | 7.0 | 2023 | 1.1241 | 0.8346 | |
| | 0.0219 | 8.0 | 2312 | 1.2684 | 0.8130 | |
| | 0.0136 | 9.0 | 2601 | 1.2615 | 0.8202 | |
| | 0.0136 | 10.0 | 2890 | 1.2477 | 0.8401 | |
| | 0.0143 | 11.0 | 3179 | 1.3211 | 0.8254 | |
| | 0.0143 | 12.0 | 3468 | 1.2627 | 0.8286 | |
| | 0.0165 | 13.0 | 3757 | 1.3804 | 0.8264 | |
| | 0.006 | 14.0 | 4046 | 1.3213 | 0.8414 | |
| | 0.006 | 15.0 | 4335 | 1.3152 | 0.8427 | |
| | 0.0117 | 16.0 | 4624 | 1.3373 | 0.8368 | |
| | 0.0117 | 17.0 | 4913 | 1.3599 | 0.8406 | |
| | 0.0021 | 18.0 | 5202 | 1.4072 | 0.8237 | |
| | 0.0021 | 19.0 | 5491 | 1.3893 | 0.8336 | |
| | 0.0045 | 20.0 | 5780 | 1.4331 | 0.8391 | |
| | 0.0049 | 21.0 | 6069 | 1.4128 | 0.8370 | |
| | 0.0049 | 22.0 | 6358 | 1.4660 | 0.8356 | |
| | 0.0029 | 23.0 | 6647 | 1.4721 | 0.8388 | |
| | 0.0029 | 24.0 | 6936 | 1.4636 | 0.8329 | |
| | 0.0023 | 25.0 | 7225 | 1.4627 | 0.8342 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
