readme: ---
  tags:
  - fill-mask
  - generated_from_trainer
  model-index:
  - name: ClinicalTrialBioBert
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  # ClinicalTrialBioBERT
  
  This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on [Clinical Trial Texts Dataset](domenicrosati/clinical_trial_texts).
  
  ## Model description
  
  A Clinical Trial Language Model.
  
  ## Intended uses & limitations
  
  Use when you need domain knowledge from the clinical trial domain.
  
  ## Training and evaluation data
  
  Trained on 500k steps of [Clinical Trial Texts Dataset](domenicrosati/clinical_trial_texts)
  
  Perplexity of BioBERT:
  Perplexity of ClinicalTrialBioBERT:
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 128
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - training_steps: 500000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  10k step training loss: 0.92
  500k step training loss: 0.50
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.7.1
  - Tokenizers 0.12.1
  