| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: Bio_ClinicalBERT_fold_9_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_9_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: 1.6976 |
| - F1: 0.8065 |
| |
| ## 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 | 291 | 0.4002 | 0.7826 | |
| | 0.4094 | 2.0 | 582 | 0.3968 | 0.8212 | |
| | 0.4094 | 3.0 | 873 | 0.6130 | 0.7984 | |
| | 0.1977 | 4.0 | 1164 | 0.5853 | 0.8227 | |
| | 0.1977 | 5.0 | 1455 | 0.9401 | 0.8143 | |
| | 0.0837 | 6.0 | 1746 | 1.1764 | 0.8059 | |
| | 0.0274 | 7.0 | 2037 | 1.1515 | 0.8112 | |
| | 0.0274 | 8.0 | 2328 | 1.2614 | 0.8065 | |
| | 0.0113 | 9.0 | 2619 | 1.3404 | 0.8002 | |
| | 0.0113 | 10.0 | 2910 | 1.3926 | 0.8088 | |
| | 0.0125 | 11.0 | 3201 | 1.4539 | 0.8010 | |
| | 0.0125 | 12.0 | 3492 | 1.5460 | 0.7998 | |
| | 0.0101 | 13.0 | 3783 | 1.5920 | 0.8060 | |
| | 0.0107 | 14.0 | 4074 | 1.5631 | 0.8059 | |
| | 0.0107 | 15.0 | 4365 | 1.6323 | 0.8020 | |
| | 0.0127 | 16.0 | 4656 | 1.6183 | 0.8008 | |
| | 0.0127 | 17.0 | 4947 | 1.6351 | 0.8033 | |
| | 0.0068 | 18.0 | 5238 | 1.5608 | 0.8121 | |
| | 0.0047 | 19.0 | 5529 | 1.6339 | 0.8141 | |
| | 0.0047 | 20.0 | 5820 | 1.6039 | 0.8091 | |
| | 0.0029 | 21.0 | 6111 | 1.5676 | 0.8085 | |
| | 0.0029 | 22.0 | 6402 | 1.6489 | 0.8139 | |
| | 0.0036 | 23.0 | 6693 | 1.6824 | 0.8087 | |
| | 0.0036 | 24.0 | 6984 | 1.6773 | 0.8106 | |
| | 0.0008 | 25.0 | 7275 | 1.6976 | 0.8065 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.21.0 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
| |
