readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft
    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. -->
  
  # stbl_clinical_bert_ft
  
  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: 0.1789
  - F1: 0.8523
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2786        | 1.0   | 95   | 0.1083          | 0.8090 |
  | 0.0654        | 2.0   | 190  | 0.1005          | 0.8475 |
  | 0.0299        | 3.0   | 285  | 0.1207          | 0.8481 |
  | 0.0146        | 4.0   | 380  | 0.1432          | 0.8454 |
  | 0.0088        | 5.0   | 475  | 0.1362          | 0.8475 |
  | 0.0056        | 6.0   | 570  | 0.1527          | 0.8518 |
  | 0.0037        | 7.0   | 665  | 0.1617          | 0.8519 |
  | 0.0022        | 8.0   | 760  | 0.1726          | 0.8495 |
  | 0.0018        | 9.0   | 855  | 0.1743          | 0.8527 |
  | 0.0014        | 10.0  | 950  | 0.1750          | 0.8463 |
  | 0.0014        | 11.0  | 1045 | 0.1775          | 0.8522 |
  | 0.001         | 12.0  | 1140 | 0.1789          | 0.8523 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  