readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_1_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_1_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: 1.7063
  - F1: 0.8114
  
  ## 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   | 288  | 0.4168          | 0.7949 |
  | 0.3981        | 2.0   | 576  | 0.4124          | 0.8137 |
  | 0.3981        | 3.0   | 864  | 0.6691          | 0.8002 |
  | 0.1779        | 4.0   | 1152 | 0.8402          | 0.8122 |
  | 0.1779        | 5.0   | 1440 | 0.9786          | 0.8007 |
  | 0.082         | 6.0   | 1728 | 1.0425          | 0.7981 |
  | 0.0332        | 7.0   | 2016 | 1.2070          | 0.8006 |
  | 0.0332        | 8.0   | 2304 | 1.3305          | 0.8028 |
  | 0.0149        | 9.0   | 2592 | 1.4515          | 0.8009 |
  | 0.0149        | 10.0  | 2880 | 1.3826          | 0.8160 |
  | 0.01          | 11.0  | 3168 | 1.5267          | 0.7963 |
  | 0.01          | 12.0  | 3456 | 1.5158          | 0.8112 |
  | 0.0084        | 13.0  | 3744 | 1.5919          | 0.7998 |
  | 0.0027        | 14.0  | 4032 | 1.6206          | 0.8060 |
  | 0.0027        | 15.0  | 4320 | 1.6861          | 0.8014 |
  | 0.0061        | 16.0  | 4608 | 1.6660          | 0.8001 |
  | 0.0061        | 17.0  | 4896 | 1.5061          | 0.8054 |
  | 0.0133        | 18.0  | 5184 | 1.5813          | 0.8025 |
  | 0.0133        | 19.0  | 5472 | 1.6314          | 0.7968 |
  | 0.0032        | 20.0  | 5760 | 1.6282          | 0.8117 |
  | 0.0007        | 21.0  | 6048 | 1.6378          | 0.8153 |
  | 0.0007        | 22.0  | 6336 | 1.6710          | 0.8033 |
  | 0.0018        | 23.0  | 6624 | 1.6999          | 0.8066 |
  | 0.0018        | 24.0  | 6912 | 1.7045          | 0.8109 |
  | 0.0001        | 25.0  | 7200 | 1.7063          | 0.8114 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  