readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_10_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_10_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: 2.0706
  - F1: 0.7748
  
  ## 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   | 290  | 0.6097          | 0.7290 |
  | 0.555         | 2.0   | 580  | 0.6106          | 0.7649 |
  | 0.555         | 3.0   | 870  | 0.6608          | 0.7847 |
  | 0.2449        | 4.0   | 1160 | 0.8894          | 0.7809 |
  | 0.2449        | 5.0   | 1450 | 1.1049          | 0.7760 |
  | 0.1055        | 6.0   | 1740 | 1.2951          | 0.7884 |
  | 0.0338        | 7.0   | 2030 | 1.4809          | 0.7760 |
  | 0.0338        | 8.0   | 2320 | 1.4751          | 0.7698 |
  | 0.0225        | 9.0   | 2610 | 1.6648          | 0.7809 |
  | 0.0225        | 10.0  | 2900 | 1.7174          | 0.7772 |
  | 0.006         | 11.0  | 3190 | 1.7872          | 0.7735 |
  | 0.006         | 12.0  | 3480 | 1.7803          | 0.7748 |
  | 0.0161        | 13.0  | 3770 | 1.9302          | 0.7735 |
  | 0.0005        | 14.0  | 4060 | 1.9853          | 0.7748 |
  | 0.0005        | 15.0  | 4350 | 2.0043          | 0.7735 |
  | 0.0062        | 16.0  | 4640 | 1.9969          | 0.7760 |
  | 0.0062        | 17.0  | 4930 | 2.0173          | 0.7760 |
  | 0.0068        | 18.0  | 5220 | 1.9891          | 0.7785 |
  | 0.0034        | 19.0  | 5510 | 1.9951          | 0.7797 |
  | 0.0034        | 20.0  | 5800 | 2.0283          | 0.7748 |
  | 0.0049        | 21.0  | 6090 | 1.9985          | 0.7834 |
  | 0.0049        | 22.0  | 6380 | 2.0131          | 0.7760 |
  | 0.0011        | 23.0  | 6670 | 2.0526          | 0.7748 |
  | 0.0011        | 24.0  | 6960 | 2.0662          | 0.7748 |
  | 0.001         | 25.0  | 7250 | 2.0706          | 0.7748 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  