readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: ClinicalBioBERT
    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. -->
  
  # ClinicalBioBERT
  
  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: 0.9404
  - Accuracy: 0.77
  - Precision: 0.8333
  - Recall: 0.8209
  - F1: 0.8271
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.693         | 1.0   | 50   | 0.6142          | 0.61     | 0.8182    | 0.5373 | 0.6486 |
  | 0.5547        | 2.0   | 100  | 0.5753          | 0.66     | 0.8367    | 0.6119 | 0.7069 |
  | 0.3912        | 3.0   | 150  | 0.5167          | 0.8      | 0.8406    | 0.8657 | 0.8529 |
  | 0.2618        | 4.0   | 200  | 0.6664          | 0.8      | 0.8133    | 0.9104 | 0.8592 |
  | 0.1648        | 5.0   | 250  | 0.5954          | 0.79     | 0.8594    | 0.8209 | 0.8397 |
  | 0.1446        | 6.0   | 300  | 0.6131          | 0.81     | 0.8871    | 0.8209 | 0.8527 |
  | 0.0841        | 7.0   | 350  | 0.8966          | 0.79     | 0.8194    | 0.8806 | 0.8489 |
  | 0.0708        | 8.0   | 400  | 0.9366          | 0.78     | 0.8169    | 0.8657 | 0.8406 |
  | 0.049         | 9.0   | 450  | 0.9523          | 0.78     | 0.8358    | 0.8358 | 0.8358 |
  | 0.0516        | 10.0  | 500  | 0.9404          | 0.77     | 0.8333    | 0.8209 | 0.8271 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  