readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_4_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_4_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: 1.4627
  - F1: 0.8342
  
  ## 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   | 289  | 0.3641          | 0.8394 |
  | 0.3953        | 2.0   | 578  | 0.3729          | 0.8294 |
  | 0.3953        | 3.0   | 867  | 0.6156          | 0.8126 |
  | 0.189         | 4.0   | 1156 | 0.7389          | 0.8326 |
  | 0.189         | 5.0   | 1445 | 0.8925          | 0.8322 |
  | 0.0783        | 6.0   | 1734 | 1.0909          | 0.8196 |
  | 0.0219        | 7.0   | 2023 | 1.1241          | 0.8346 |
  | 0.0219        | 8.0   | 2312 | 1.2684          | 0.8130 |
  | 0.0136        | 9.0   | 2601 | 1.2615          | 0.8202 |
  | 0.0136        | 10.0  | 2890 | 1.2477          | 0.8401 |
  | 0.0143        | 11.0  | 3179 | 1.3211          | 0.8254 |
  | 0.0143        | 12.0  | 3468 | 1.2627          | 0.8286 |
  | 0.0165        | 13.0  | 3757 | 1.3804          | 0.8264 |
  | 0.006         | 14.0  | 4046 | 1.3213          | 0.8414 |
  | 0.006         | 15.0  | 4335 | 1.3152          | 0.8427 |
  | 0.0117        | 16.0  | 4624 | 1.3373          | 0.8368 |
  | 0.0117        | 17.0  | 4913 | 1.3599          | 0.8406 |
  | 0.0021        | 18.0  | 5202 | 1.4072          | 0.8237 |
  | 0.0021        | 19.0  | 5491 | 1.3893          | 0.8336 |
  | 0.0045        | 20.0  | 5780 | 1.4331          | 0.8391 |
  | 0.0049        | 21.0  | 6069 | 1.4128          | 0.8370 |
  | 0.0049        | 22.0  | 6358 | 1.4660          | 0.8356 |
  | 0.0029        | 23.0  | 6647 | 1.4721          | 0.8388 |
  | 0.0029        | 24.0  | 6936 | 1.4636          | 0.8329 |
  | 0.0023        | 25.0  | 7225 | 1.4627          | 0.8342 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  