readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_4_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_4_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: 1.7349
  - F1: 0.8052
  
  ## 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  | 0.5378          | 0.7818 |
  | 0.5561        | 2.0   | 578  | 0.4835          | 0.8002 |
  | 0.5561        | 3.0   | 867  | 0.6401          | 0.7978 |
  | 0.2473        | 4.0   | 1156 | 0.8665          | 0.7842 |
  | 0.2473        | 5.0   | 1445 | 0.9942          | 0.7965 |
  | 0.1002        | 6.0   | 1734 | 1.1535          | 0.8015 |
  | 0.0428        | 7.0   | 2023 | 1.2619          | 0.8027 |
  | 0.0428        | 8.0   | 2312 | 1.4386          | 0.7990 |
  | 0.017         | 9.0   | 2601 | 1.4864          | 0.8039 |
  | 0.017         | 10.0  | 2890 | 1.4817          | 0.8015 |
  | 0.0145        | 11.0  | 3179 | 1.5205          | 0.8052 |
  | 0.0145        | 12.0  | 3468 | 1.6825          | 0.7842 |
  | 0.0115        | 13.0  | 3757 | 1.6670          | 0.7990 |
  | 0.0083        | 14.0  | 4046 | 1.7283          | 0.7904 |
  | 0.0083        | 15.0  | 4335 | 1.6552          | 0.8039 |
  | 0.0071        | 16.0  | 4624 | 1.6760          | 0.8076 |
  | 0.0071        | 17.0  | 4913 | 1.6973          | 0.7891 |
  | 0.0109        | 18.0  | 5202 | 1.6050          | 0.8027 |
  | 0.0109        | 19.0  | 5491 | 1.6379          | 0.8126 |
  | 0.0037        | 20.0  | 5780 | 1.6936          | 0.8039 |
  | 0.0013        | 21.0  | 6069 | 1.7187          | 0.8027 |
  | 0.0013        | 22.0  | 6358 | 1.7839          | 0.7965 |
  | 0.0015        | 23.0  | 6647 | 1.7551          | 0.8015 |
  | 0.0015        | 24.0  | 6936 | 1.7312          | 0.8064 |
  | 0.001         | 25.0  | 7225 | 1.7349          | 0.8052 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  