readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: Bio_ClinicalBERT-SurgicalCardiothoracic
    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-SurgicalCardiothoracic
  
  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: 0.8426
  
  ## 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: 1
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | No log        | 1.0   | 13144 | 0.9092          |
  | No log        | 2.0   | 26288 | 0.8575          |
  | No log        | 3.0   | 39432 | 0.8417          |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.8.0
  - Datasets 2.2.2
  - Tokenizers 0.11.6
  