readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_9_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_9_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: 2.0189
  - F1: 0.7905
  
  ## 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   | 292  | 0.5758          | 0.7571 |
  | 0.5482        | 2.0   | 584  | 0.6282          | 0.7609 |
  | 0.5482        | 3.0   | 876  | 0.6823          | 0.7841 |
  | 0.2346        | 4.0   | 1168 | 0.9898          | 0.7776 |
  | 0.2346        | 5.0   | 1460 | 1.1397          | 0.7866 |
  | 0.1001        | 6.0   | 1752 | 1.3832          | 0.7751 |
  | 0.0447        | 7.0   | 2044 | 1.6002          | 0.7674 |
  | 0.0447        | 8.0   | 2336 | 1.7265          | 0.7584 |
  | 0.0171        | 9.0   | 2628 | 1.6650          | 0.7699 |
  | 0.0171        | 10.0  | 2920 | 1.7322          | 0.7661 |
  | 0.0156        | 11.0  | 3212 | 1.8071          | 0.7789 |
  | 0.012         | 12.0  | 3504 | 1.8322          | 0.7841 |
  | 0.012         | 13.0  | 3796 | 1.8948          | 0.7763 |
  | 0.01          | 14.0  | 4088 | 1.7667          | 0.7918 |
  | 0.01          | 15.0  | 4380 | 1.8538          | 0.7879 |
  | 0.0063        | 16.0  | 4672 | 1.9763          | 0.7776 |
  | 0.0063        | 17.0  | 4964 | 1.9970          | 0.7841 |
  | 0.0028        | 18.0  | 5256 | 1.9366          | 0.7931 |
  | 0.0003        | 19.0  | 5548 | 1.9709          | 0.7892 |
  | 0.0003        | 20.0  | 5840 | 1.9460          | 0.7879 |
  | 0.0044        | 21.0  | 6132 | 2.0280          | 0.7866 |
  | 0.0044        | 22.0  | 6424 | 1.9423          | 0.7918 |
  | 0.0013        | 23.0  | 6716 | 1.9618          | 0.7918 |
  | 0.004         | 24.0  | 7008 | 2.0241          | 0.7905 |
  | 0.004         | 25.0  | 7300 | 2.0189          | 0.7905 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  