readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_8_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_8_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: 1.5821
  - F1: 0.8265
  
  ## 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  | 0.3933          | 0.8222 |
  | 0.4092        | 2.0   | 580  | 0.4431          | 0.8237 |
  | 0.4092        | 3.0   | 870  | 0.6243          | 0.8292 |
  | 0.1845        | 4.0   | 1160 | 0.6526          | 0.8300 |
  | 0.1845        | 5.0   | 1450 | 0.9229          | 0.8203 |
  | 0.0671        | 6.0   | 1740 | 0.9436          | 0.8279 |
  | 0.0303        | 7.0   | 2030 | 1.1281          | 0.8260 |
  | 0.0303        | 8.0   | 2320 | 1.1676          | 0.8327 |
  | 0.0105        | 9.0   | 2610 | 1.2557          | 0.8291 |
  | 0.0105        | 10.0  | 2900 | 1.3556          | 0.8326 |
  | 0.0102        | 11.0  | 3190 | 1.3160          | 0.8413 |
  | 0.0102        | 12.0  | 3480 | 1.3199          | 0.8344 |
  | 0.0068        | 13.0  | 3770 | 1.3827          | 0.8314 |
  | 0.0049        | 14.0  | 4060 | 1.5265          | 0.8197 |
  | 0.0049        | 15.0  | 4350 | 1.5481          | 0.8215 |
  | 0.0069        | 16.0  | 4640 | 1.3824          | 0.8292 |
  | 0.0069        | 17.0  | 4930 | 1.4398          | 0.8305 |
  | 0.0073        | 18.0  | 5220 | 1.5004          | 0.8255 |
  | 0.0033        | 19.0  | 5510 | 1.5322          | 0.8253 |
  | 0.0033        | 20.0  | 5800 | 1.5239          | 0.8237 |
  | 0.0025        | 21.0  | 6090 | 1.5299          | 0.8286 |
  | 0.0025        | 22.0  | 6380 | 1.5788          | 0.8271 |
  | 0.0005        | 23.0  | 6670 | 1.5903          | 0.8298 |
  | 0.0005        | 24.0  | 6960 | 1.5893          | 0.8232 |
  | 0.0026        | 25.0  | 7250 | 1.5821          | 0.8265 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  