readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_2_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_2_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: 1.9317
  - F1: 0.7921
  
  ## 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  | 0.4221          | 0.7856 |
  | 0.4062        | 2.0   | 580  | 0.5184          | 0.7949 |
  | 0.4062        | 3.0   | 870  | 0.6854          | 0.7840 |
  | 0.1775        | 4.0   | 1160 | 0.9834          | 0.7840 |
  | 0.1775        | 5.0   | 1450 | 1.3223          | 0.7804 |
  | 0.0697        | 6.0   | 1740 | 1.2896          | 0.7923 |
  | 0.0265        | 7.0   | 2030 | 1.4620          | 0.7914 |
  | 0.0265        | 8.0   | 2320 | 1.5554          | 0.7835 |
  | 0.0102        | 9.0   | 2610 | 1.7009          | 0.7880 |
  | 0.0102        | 10.0  | 2900 | 1.6163          | 0.7923 |
  | 0.015         | 11.0  | 3190 | 1.6851          | 0.7841 |
  | 0.015         | 12.0  | 3480 | 1.7493          | 0.7901 |
  | 0.0141        | 13.0  | 3770 | 1.8819          | 0.7827 |
  | 0.0133        | 14.0  | 4060 | 1.7535          | 0.7939 |
  | 0.0133        | 15.0  | 4350 | 1.6613          | 0.7966 |
  | 0.0067        | 16.0  | 4640 | 1.6807          | 0.7999 |
  | 0.0067        | 17.0  | 4930 | 1.6703          | 0.7978 |
  | 0.0053        | 18.0  | 5220 | 1.7309          | 0.8013 |
  | 0.0037        | 19.0  | 5510 | 1.8058          | 0.7942 |
  | 0.0037        | 20.0  | 5800 | 1.8233          | 0.7916 |
  | 0.0023        | 21.0  | 6090 | 1.8206          | 0.7913 |
  | 0.0023        | 22.0  | 6380 | 1.8466          | 0.7949 |
  | 0.0012        | 23.0  | 6670 | 1.8531          | 0.7985 |
  | 0.0012        | 24.0  | 6960 | 1.9211          | 0.7944 |
  | 0.0001        | 25.0  | 7250 | 1.9317          | 0.7921 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  