| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: Bio_ClinicalBERT_fold_3_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_3_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: 1.8860 |
| - F1: 0.8051 |
| |
| ## 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 | 0.4493 | 0.7916 | |
| | 0.3975 | 2.0 | 578 | 0.4608 | 0.7909 | |
| | 0.3975 | 3.0 | 867 | 0.8364 | 0.7726 | |
| | 0.1885 | 4.0 | 1156 | 1.0380 | 0.7902 | |
| | 0.1885 | 5.0 | 1445 | 1.1612 | 0.7921 | |
| | 0.0692 | 6.0 | 1734 | 1.3894 | 0.7761 | |
| | 0.0295 | 7.0 | 2023 | 1.3730 | 0.7864 | |
| | 0.0295 | 8.0 | 2312 | 1.4131 | 0.7939 | |
| | 0.0161 | 9.0 | 2601 | 1.5538 | 0.7929 | |
| | 0.0161 | 10.0 | 2890 | 1.6417 | 0.7931 | |
| | 0.006 | 11.0 | 3179 | 1.5745 | 0.7974 | |
| | 0.006 | 12.0 | 3468 | 1.7212 | 0.7908 | |
| | 0.0132 | 13.0 | 3757 | 1.7349 | 0.7945 | |
| | 0.0062 | 14.0 | 4046 | 1.7593 | 0.7908 | |
| | 0.0062 | 15.0 | 4335 | 1.7420 | 0.8035 | |
| | 0.0073 | 16.0 | 4624 | 1.7620 | 0.8007 | |
| | 0.0073 | 17.0 | 4913 | 1.8286 | 0.7908 | |
| | 0.0033 | 18.0 | 5202 | 1.7863 | 0.7977 | |
| | 0.0033 | 19.0 | 5491 | 1.9275 | 0.7919 | |
| | 0.0035 | 20.0 | 5780 | 1.8481 | 0.8042 | |
| | 0.0035 | 21.0 | 6069 | 1.9465 | 0.8012 | |
| | 0.0035 | 22.0 | 6358 | 1.8177 | 0.8044 | |
| | 0.005 | 23.0 | 6647 | 1.8615 | 0.8030 | |
| | 0.005 | 24.0 | 6936 | 1.8427 | 0.8054 | |
| | 0.0011 | 25.0 | 7225 | 1.8860 | 0.8051 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
