readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_5_ternary_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_5_ternary_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: 2.0233
  - F1: 0.7849
  
  ## 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  | 0.6352          | 0.7286 |
  | 0.5477        | 2.0   | 582  | 0.5965          | 0.7682 |
  | 0.5477        | 3.0   | 873  | 0.7696          | 0.7554 |
  | 0.2383        | 4.0   | 1164 | 1.0119          | 0.7631 |
  | 0.2383        | 5.0   | 1455 | 1.1300          | 0.7772 |
  | 0.1068        | 6.0   | 1746 | 1.3515          | 0.7734 |
  | 0.0401        | 7.0   | 2037 | 1.4935          | 0.7721 |
  | 0.0401        | 8.0   | 2328 | 1.5418          | 0.7875 |
  | 0.0213        | 9.0   | 2619 | 1.6902          | 0.7746 |
  | 0.0213        | 10.0  | 2910 | 1.7091          | 0.7721 |
  | 0.014         | 11.0  | 3201 | 1.7422          | 0.7836 |
  | 0.014         | 12.0  | 3492 | 1.8603          | 0.7772 |
  | 0.012         | 13.0  | 3783 | 1.8419          | 0.7734 |
  | 0.0104        | 14.0  | 4074 | 1.9616          | 0.7657 |
  | 0.0104        | 15.0  | 4365 | 1.9342          | 0.7823 |
  | 0.005         | 16.0  | 4656 | 1.9646          | 0.7746 |
  | 0.005         | 17.0  | 4947 | 1.9943          | 0.7772 |
  | 0.0075        | 18.0  | 5238 | 1.9882          | 0.7798 |
  | 0.0071        | 19.0  | 5529 | 1.9909          | 0.7849 |
  | 0.0071        | 20.0  | 5820 | 2.0568          | 0.7798 |
  | 0.0029        | 21.0  | 6111 | 2.0508          | 0.7759 |
  | 0.0029        | 22.0  | 6402 | 2.0267          | 0.7823 |
  | 0.0047        | 23.0  | 6693 | 2.0534          | 0.7785 |
  | 0.0047        | 24.0  | 6984 | 2.0336          | 0.7849 |
  | 0.0014        | 25.0  | 7275 | 2.0233          | 0.7849 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  