readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: clinical-finetuned-data10
    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-data10
  
  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: 0.5795
  - Accuracy: 0.8
  - Precision: 0.8507
  - Recall: 0.8507
  - F1: 0.8507
  
  ## 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: 1e-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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.4903        | 1.0   | 50   | 0.5799          | 0.65     | 0.8810    | 0.5522 | 0.6789 |
  | 0.4553        | 2.0   | 100  | 0.5528          | 0.71     | 0.8958    | 0.6418 | 0.7478 |
  | 0.3538        | 3.0   | 150  | 0.5463          | 0.76     | 0.8644    | 0.7612 | 0.8095 |
  | 0.2954        | 4.0   | 200  | 0.5511          | 0.78     | 0.8462    | 0.8209 | 0.8333 |
  | 0.2644        | 5.0   | 250  | 0.5869          | 0.79     | 0.8485    | 0.8358 | 0.8421 |
  | 0.2108        | 6.0   | 300  | 0.5418          | 0.79     | 0.8594    | 0.8209 | 0.8397 |
  | 0.1881        | 7.0   | 350  | 0.5622          | 0.81     | 0.8636    | 0.8507 | 0.8571 |
  | 0.1602        | 8.0   | 400  | 0.5796          | 0.8      | 0.8507    | 0.8507 | 0.8507 |
  | 0.1617        | 9.0   | 450  | 0.5795          | 0.8      | 0.8507    | 0.8507 | 0.8507 |
  | 0.1561        | 10.0  | 500  | 0.5795          | 0.8      | 0.8507    | 0.8507 | 0.8507 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  