readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: clinical-finetuned-data2
    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-finetuned-data2
  
  This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4949
  - F1: 0.7800
  
  ## 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.66          | 1.0   | 50   | 0.6269          | 0.6659 |
  | 0.5476        | 2.0   | 100  | 0.5311          | 0.7615 |
  | 0.3766        | 3.0   | 150  | 0.4457          | 0.7970 |
  | 0.2785        | 4.0   | 200  | 0.5251          | 0.7615 |
  | 0.2274        | 5.0   | 250  | 0.4949          | 0.7800 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  