readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_6_binary_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_6_binary_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: 1.7858
  - F1: 0.8079
  
  ## 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   | 290  | 0.4223          | 0.7938 |
  | 0.4052        | 2.0   | 580  | 0.4262          | 0.7991 |
  | 0.4052        | 3.0   | 870  | 0.5859          | 0.8201 |
  | 0.1894        | 4.0   | 1160 | 0.9158          | 0.7859 |
  | 0.1894        | 5.0   | 1450 | 1.0524          | 0.8018 |
  | 0.0845        | 6.0   | 1740 | 1.0179          | 0.8041 |
  | 0.038         | 7.0   | 2030 | 1.2477          | 0.8047 |
  | 0.038         | 8.0   | 2320 | 1.2635          | 0.8111 |
  | 0.014         | 9.0   | 2610 | 1.4297          | 0.8018 |
  | 0.014         | 10.0  | 2900 | 1.4499          | 0.8034 |
  | 0.0119        | 11.0  | 3190 | 1.4388          | 0.8194 |
  | 0.0119        | 12.0  | 3480 | 1.4813          | 0.8082 |
  | 0.0145        | 13.0  | 3770 | 1.5423          | 0.8063 |
  | 0.006         | 14.0  | 4060 | 1.5658          | 0.8104 |
  | 0.006         | 15.0  | 4350 | 1.6268          | 0.8052 |
  | 0.0021        | 16.0  | 4640 | 1.6671          | 0.8148 |
  | 0.0021        | 17.0  | 4930 | 1.7222          | 0.8132 |
  | 0.005         | 18.0  | 5220 | 1.7973          | 0.8014 |
  | 0.0031        | 19.0  | 5510 | 1.7613          | 0.8054 |
  | 0.0031        | 20.0  | 5800 | 1.7653          | 0.8071 |
  | 0.0099        | 21.0  | 6090 | 1.7343          | 0.7996 |
  | 0.0099        | 22.0  | 6380 | 1.7679          | 0.8104 |
  | 0.0015        | 23.0  | 6670 | 1.7916          | 0.8095 |
  | 0.0015        | 24.0  | 6960 | 1.7815          | 0.8062 |
  | 0.0028        | 25.0  | 7250 | 1.7858          | 0.8079 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  