readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft_rs1
    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_rs1
  
  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: 0.0789
  - F1: 0.9267
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2742        | 1.0   | 101  | 0.0959          | 0.8413 |
  | 0.0698        | 2.0   | 202  | 0.0635          | 0.8923 |
  | 0.0335        | 3.0   | 303  | 0.0630          | 0.9013 |
  | 0.0171        | 4.0   | 404  | 0.0635          | 0.9133 |
  | 0.0096        | 5.0   | 505  | 0.0671          | 0.9171 |
  | 0.0058        | 6.0   | 606  | 0.0701          | 0.9210 |
  | 0.0037        | 7.0   | 707  | 0.0762          | 0.9231 |
  | 0.0034        | 8.0   | 808  | 0.0771          | 0.9168 |
  | 0.0021        | 9.0   | 909  | 0.0751          | 0.9268 |
  | 0.0013        | 10.0  | 1010 | 0.0770          | 0.9277 |
  | 0.0011        | 11.0  | 1111 | 0.0784          | 0.9259 |
  | 0.0008        | 12.0  | 1212 | 0.0789          | 0.9267 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  