readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_2_ternary_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_2_ternary_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: 1.8186
  - F1: 0.8038
  
  ## 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   | 294  | 0.5629          | 0.7645 |
  | 0.5579        | 2.0   | 588  | 0.5078          | 0.8078 |
  | 0.5579        | 3.0   | 882  | 0.6622          | 0.7754 |
  | 0.2341        | 4.0   | 1176 | 0.8584          | 0.7943 |
  | 0.2341        | 5.0   | 1470 | 1.1953          | 0.7821 |
  | 0.0942        | 6.0   | 1764 | 1.3193          | 0.7876 |
  | 0.0338        | 7.0   | 2058 | 1.3324          | 0.7903 |
  | 0.0338        | 8.0   | 2352 | 1.5043          | 0.7930 |
  | 0.0202        | 9.0   | 2646 | 1.5255          | 0.7889 |
  | 0.0202        | 10.0  | 2940 | 1.5382          | 0.7916 |
  | 0.0119        | 11.0  | 3234 | 1.6377          | 0.7903 |
  | 0.0051        | 12.0  | 3528 | 1.7349          | 0.7835 |
  | 0.0051        | 13.0  | 3822 | 1.7297          | 0.7835 |
  | 0.0082        | 14.0  | 4116 | 1.7817          | 0.7808 |
  | 0.0082        | 15.0  | 4410 | 1.7105          | 0.7970 |
  | 0.0054        | 16.0  | 4704 | 1.7325          | 0.7984 |
  | 0.0054        | 17.0  | 4998 | 1.7919          | 0.7943 |
  | 0.0049        | 18.0  | 5292 | 1.8850          | 0.7876 |
  | 0.0045        | 19.0  | 5586 | 1.8237          | 0.7916 |
  | 0.0045        | 20.0  | 5880 | 1.8760          | 0.7970 |
  | 0.0024        | 21.0  | 6174 | 1.8544          | 0.7984 |
  | 0.0024        | 22.0  | 6468 | 1.7852          | 0.8011 |
  | 0.0005        | 23.0  | 6762 | 1.7795          | 0.8065 |
  | 0.0031        | 24.0  | 7056 | 1.7978          | 0.7997 |
  | 0.0031        | 25.0  | 7350 | 1.8186          | 0.8038 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  