| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: Bio_ClinicalBERT_fold_1_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_1_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: 1.7063 |
| - F1: 0.8114 |
| |
| ## 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 | 288 | 0.4168 | 0.7949 | |
| | 0.3981 | 2.0 | 576 | 0.4124 | 0.8137 | |
| | 0.3981 | 3.0 | 864 | 0.6691 | 0.8002 | |
| | 0.1779 | 4.0 | 1152 | 0.8402 | 0.8122 | |
| | 0.1779 | 5.0 | 1440 | 0.9786 | 0.8007 | |
| | 0.082 | 6.0 | 1728 | 1.0425 | 0.7981 | |
| | 0.0332 | 7.0 | 2016 | 1.2070 | 0.8006 | |
| | 0.0332 | 8.0 | 2304 | 1.3305 | 0.8028 | |
| | 0.0149 | 9.0 | 2592 | 1.4515 | 0.8009 | |
| | 0.0149 | 10.0 | 2880 | 1.3826 | 0.8160 | |
| | 0.01 | 11.0 | 3168 | 1.5267 | 0.7963 | |
| | 0.01 | 12.0 | 3456 | 1.5158 | 0.8112 | |
| | 0.0084 | 13.0 | 3744 | 1.5919 | 0.7998 | |
| | 0.0027 | 14.0 | 4032 | 1.6206 | 0.8060 | |
| | 0.0027 | 15.0 | 4320 | 1.6861 | 0.8014 | |
| | 0.0061 | 16.0 | 4608 | 1.6660 | 0.8001 | |
| | 0.0061 | 17.0 | 4896 | 1.5061 | 0.8054 | |
| | 0.0133 | 18.0 | 5184 | 1.5813 | 0.8025 | |
| | 0.0133 | 19.0 | 5472 | 1.6314 | 0.7968 | |
| | 0.0032 | 20.0 | 5760 | 1.6282 | 0.8117 | |
| | 0.0007 | 21.0 | 6048 | 1.6378 | 0.8153 | |
| | 0.0007 | 22.0 | 6336 | 1.6710 | 0.8033 | |
| | 0.0018 | 23.0 | 6624 | 1.6999 | 0.8066 | |
| | 0.0018 | 24.0 | 6912 | 1.7045 | 0.8109 | |
| | 0.0001 | 25.0 | 7200 | 1.7063 | 0.8114 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
