readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_7_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_7_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: 1.9612
  - F1: 0.7939
  
  ## 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   | 291  | 0.5762          | 0.7593 |
  | 0.5434        | 2.0   | 582  | 0.5577          | 0.7939 |
  | 0.5434        | 3.0   | 873  | 0.6501          | 0.7951 |
  | 0.2198        | 4.0   | 1164 | 0.8661          | 0.7939 |
  | 0.2198        | 5.0   | 1455 | 1.1493          | 0.7900 |
  | 0.0953        | 6.0   | 1746 | 1.1999          | 0.7977 |
  | 0.0375        | 7.0   | 2037 | 1.4623          | 0.7759 |
  | 0.0375        | 8.0   | 2328 | 1.4526          | 0.7900 |
  | 0.0246        | 9.0   | 2619 | 1.6915          | 0.7734 |
  | 0.0246        | 10.0  | 2910 | 1.6097          | 0.7913 |
  | 0.0113        | 11.0  | 3201 | 1.7091          | 0.8015 |
  | 0.0113        | 12.0  | 3492 | 1.7252          | 0.7990 |
  | 0.0103        | 13.0  | 3783 | 1.7305          | 0.8015 |
  | 0.0079        | 14.0  | 4074 | 1.7932          | 0.8003 |
  | 0.0079        | 15.0  | 4365 | 1.7800          | 0.8028 |
  | 0.0071        | 16.0  | 4656 | 1.7000          | 0.7977 |
  | 0.0071        | 17.0  | 4947 | 1.8342          | 0.8003 |
  | 0.0077        | 18.0  | 5238 | 1.8517          | 0.7990 |
  | 0.0044        | 19.0  | 5529 | 1.8633          | 0.7964 |
  | 0.0044        | 20.0  | 5820 | 1.8813          | 0.7926 |
  | 0.0028        | 21.0  | 6111 | 1.8914          | 0.7964 |
  | 0.0028        | 22.0  | 6402 | 1.9412          | 0.7926 |
  | 0.0043        | 23.0  | 6693 | 1.9760          | 0.7939 |
  | 0.0043        | 24.0  | 6984 | 1.9509          | 0.7977 |
  | 0.0002        | 25.0  | 7275 | 1.9612          | 0.7939 |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  