readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: ClinicalTextV4
    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. -->
  
  # ClinicalTextV4
  
  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: 0.5609
  - Accuracy: 0.8658
  - Precision: 0.8371
  - Recall: 0.8939
  - F1: 0.8646
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.4824        | 1.0   | 600  | 0.3630          | 0.8458   | 0.825     | 0.8609 | 0.8426 |
  | 0.3314        | 2.0   | 1200 | 0.3583          | 0.8558   | 0.8252    | 0.8870 | 0.8550 |
  | 0.2673        | 3.0   | 1800 | 0.3437          | 0.8583   | 0.8189    | 0.9043 | 0.8595 |
  | 0.2255        | 4.0   | 2400 | 0.3678          | 0.8675   | 0.8302    | 0.9096 | 0.8680 |
  | 0.1883        | 5.0   | 3000 | 0.4002          | 0.8642   | 0.8259    | 0.9078 | 0.8650 |
  | 0.1562        | 6.0   | 3600 | 0.4695          | 0.8633   | 0.8352    | 0.8904 | 0.8620 |
  | 0.1372        | 7.0   | 4200 | 0.4940          | 0.8658   | 0.8371    | 0.8939 | 0.8646 |
  | 0.1269        | 8.0   | 4800 | 0.5376          | 0.865    | 0.8402    | 0.8870 | 0.8629 |
  | 0.1097        | 9.0   | 5400 | 0.5539          | 0.8633   | 0.8397    | 0.8835 | 0.8610 |
  | 0.0997        | 10.0  | 6000 | 0.5609          | 0.8658   | 0.8371    | 0.8939 | 0.8646 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  