readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: clinical_bert_ft
    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. -->
  
  # clinical_bert_ft
  
  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: 0.2439
  - F1: 0.8252
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.5938        | 1.0   | 95   | 0.2480          | 0.7084 |
  | 0.1567        | 2.0   | 190  | 0.2035          | 0.7855 |
  | 0.083         | 3.0   | 285  | 0.2002          | 0.8026 |
  | 0.0482        | 4.0   | 380  | 0.2046          | 0.8118 |
  | 0.0269        | 5.0   | 475  | 0.2230          | 0.8143 |
  | 0.0185        | 6.0   | 570  | 0.2178          | 0.8175 |
  | 0.0123        | 7.0   | 665  | 0.2269          | 0.8253 |
  | 0.0093        | 8.0   | 760  | 0.2421          | 0.8227 |
  | 0.0072        | 9.0   | 855  | 0.2446          | 0.8267 |
  | 0.006         | 10.0  | 950  | 0.2439          | 0.8252 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  