readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_8_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_8_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: 1.8248
  - F1: 0.8010
  
  ## 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  | 0.5418          | 0.7899 |
  | 0.5486        | 2.0   | 578  | 0.6456          | 0.7727 |
  | 0.5486        | 3.0   | 867  | 0.6705          | 0.8010 |
  | 0.223         | 4.0   | 1156 | 0.8590          | 0.7998 |
  | 0.223         | 5.0   | 1445 | 1.1503          | 0.7973 |
  | 0.0936        | 6.0   | 1734 | 1.2678          | 0.7985 |
  | 0.035         | 7.0   | 2023 | 1.3791          | 0.7973 |
  | 0.035         | 8.0   | 2312 | 1.4720          | 0.7899 |
  | 0.0249        | 9.0   | 2601 | 1.4755          | 0.7973 |
  | 0.0249        | 10.0  | 2890 | 1.5383          | 0.7936 |
  | 0.0177        | 11.0  | 3179 | 1.5926          | 0.8022 |
  | 0.0177        | 12.0  | 3468 | 1.6685          | 0.8010 |
  | 0.0124        | 13.0  | 3757 | 1.7205          | 0.7912 |
  | 0.0047        | 14.0  | 4046 | 1.6311          | 0.7973 |
  | 0.0047        | 15.0  | 4335 | 1.8000          | 0.7924 |
  | 0.0051        | 16.0  | 4624 | 1.7546          | 0.7924 |
  | 0.0051        | 17.0  | 4913 | 1.7800          | 0.7998 |
  | 0.0018        | 18.0  | 5202 | 1.8507          | 0.7948 |
  | 0.0018        | 19.0  | 5491 | 1.8112          | 0.7912 |
  | 0.0052        | 20.0  | 5780 | 1.8149          | 0.7985 |
  | 0.0026        | 21.0  | 6069 | 1.7938          | 0.7973 |
  | 0.0026        | 22.0  | 6358 | 1.8643          | 0.8034 |
  | 0.0013        | 23.0  | 6647 | 1.8311          | 0.7936 |
  | 0.0013        | 24.0  | 6936 | 1.8298          | 0.7961 |
  | 0.0031        | 25.0  | 7225 | 1.8248          | 0.8010 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  