readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: ft_clinical_bert_diabetes
    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. -->
  
  # ft_clinical_bert_diabetes
  
  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: 0.1020
  - Accuracy: 0.9632
  - F1: 0.9578
  
  ## 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: 3e-05
  - train_batch_size: 5
  - eval_batch_size: 5
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.1641        | 1.0   | 1064 | 0.1604          | 0.9526   | 0.9462 |
  | 0.1088        | 2.0   | 2128 | 0.0878          | 0.9623   | 0.9573 |
  | 0.0956        | 3.0   | 3192 | 0.0963          | 0.9632   | 0.9578 |
  | 0.0858        | 4.0   | 4256 | 0.1020          | 0.9632   | 0.9578 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  