readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_3_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_3_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: 2.0585
  - F1: 0.7952
  
  ## 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  | 0.5738          | 0.7709 |
  | 0.5512        | 2.0   | 578  | 0.5828          | 0.7733 |
  | 0.5512        | 3.0   | 867  | 0.7217          | 0.7830 |
  | 0.2304        | 4.0   | 1156 | 1.0389          | 0.7867 |
  | 0.2304        | 5.0   | 1445 | 1.0992          | 0.7915 |
  | 0.0951        | 6.0   | 1734 | 1.3528          | 0.7806 |
  | 0.0388        | 7.0   | 2023 | 1.4223          | 0.7879 |
  | 0.0388        | 8.0   | 2312 | 1.5588          | 0.7830 |
  | 0.0172        | 9.0   | 2601 | 1.5913          | 0.7976 |
  | 0.0172        | 10.0  | 2890 | 1.7464          | 0.7842 |
  | 0.0143        | 11.0  | 3179 | 1.7395          | 0.7927 |
  | 0.0143        | 12.0  | 3468 | 1.7523          | 0.7939 |
  | 0.0108        | 13.0  | 3757 | 1.8059          | 0.7952 |
  | 0.0099        | 14.0  | 4046 | 1.9056          | 0.7855 |
  | 0.0099        | 15.0  | 4335 | 1.8550          | 0.7903 |
  | 0.0076        | 16.0  | 4624 | 1.8718          | 0.7988 |
  | 0.0076        | 17.0  | 4913 | 1.9325          | 0.7976 |
  | 0.0033        | 18.0  | 5202 | 1.9504          | 0.7952 |
  | 0.0033        | 19.0  | 5491 | 1.9841          | 0.7879 |
  | 0.003         | 20.0  | 5780 | 1.9843          | 0.7952 |
  | 0.0001        | 21.0  | 6069 | 2.0110          | 0.7927 |
  | 0.0001        | 22.0  | 6358 | 2.0049          | 0.7939 |
  | 0.0028        | 23.0  | 6647 | 2.0638          | 0.7915 |
  | 0.0028        | 24.0  | 6936 | 2.0612          | 0.7903 |
  | 0.0011        | 25.0  | 7225 | 2.0585          | 0.7952 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  