readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_10_binary_v1
    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. -->
  
  # Bio_ClinicalBERT_fold_10_binary_v1
  
  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: 1.5504
  - F1: 0.8243
  
  ## 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: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | No log        | 1.0   | 288  | 0.3803          | 0.8103 |
  | 0.4005        | 2.0   | 576  | 0.4769          | 0.8070 |
  | 0.4005        | 3.0   | 864  | 0.5258          | 0.7955 |
  | 0.1889        | 4.0   | 1152 | 0.7423          | 0.8153 |
  | 0.1889        | 5.0   | 1440 | 1.1246          | 0.8012 |
  | 0.0703        | 6.0   | 1728 | 1.1325          | 0.8039 |
  | 0.0246        | 7.0   | 2016 | 1.2192          | 0.8196 |
  | 0.0246        | 8.0   | 2304 | 1.3645          | 0.8050 |
  | 0.0192        | 9.0   | 2592 | 1.4029          | 0.8087 |
  | 0.0192        | 10.0  | 2880 | 1.3714          | 0.8117 |
  | 0.0107        | 11.0  | 3168 | 1.4673          | 0.8092 |
  | 0.0107        | 12.0  | 3456 | 1.3941          | 0.8199 |
  | 0.0084        | 13.0  | 3744 | 1.4350          | 0.8126 |
  | 0.0083        | 14.0  | 4032 | 1.4428          | 0.8162 |
  | 0.0083        | 15.0  | 4320 | 1.2892          | 0.8263 |
  | 0.0119        | 16.0  | 4608 | 1.4238          | 0.8222 |
  | 0.0119        | 17.0  | 4896 | 1.4961          | 0.8174 |
  | 0.0046        | 18.0  | 5184 | 1.5010          | 0.8107 |
  | 0.0046        | 19.0  | 5472 | 1.4876          | 0.8215 |
  | 0.0036        | 20.0  | 5760 | 1.5080          | 0.8180 |
  | 0.0031        | 21.0  | 6048 | 1.5317          | 0.8261 |
  | 0.0031        | 22.0  | 6336 | 1.5103          | 0.8215 |
  | 0.0005        | 23.0  | 6624 | 1.5255          | 0.8197 |
  | 0.0005        | 24.0  | 6912 | 1.5578          | 0.8257 |
  | 0.0001        | 25.0  | 7200 | 1.5504          | 0.8243 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  