readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_7_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_7_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: 1.6855
  - F1: 0.8169
  
  ## 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  | 0.4412          | 0.7939 |
  | 0.4021        | 2.0   | 576  | 0.4104          | 0.8116 |
  | 0.4021        | 3.0   | 864  | 0.6152          | 0.8059 |
  | 0.1893        | 4.0   | 1152 | 0.8887          | 0.8135 |
  | 0.1893        | 5.0   | 1440 | 1.0395          | 0.7930 |
  | 0.08          | 6.0   | 1728 | 1.1491          | 0.7992 |
  | 0.0296        | 7.0   | 2016 | 1.2957          | 0.8028 |
  | 0.0296        | 8.0   | 2304 | 1.3748          | 0.8067 |
  | 0.0168        | 9.0   | 2592 | 1.3284          | 0.8077 |
  | 0.0168        | 10.0  | 2880 | 1.3705          | 0.8100 |
  | 0.0151        | 11.0  | 3168 | 1.4993          | 0.8015 |
  | 0.0151        | 12.0  | 3456 | 1.4156          | 0.8152 |
  | 0.0072        | 13.0  | 3744 | 1.4199          | 0.8108 |
  | 0.0105        | 14.0  | 4032 | 1.4797          | 0.8086 |
  | 0.0105        | 15.0  | 4320 | 1.4374          | 0.8244 |
  | 0.0101        | 16.0  | 4608 | 1.5125          | 0.8142 |
  | 0.0101        | 17.0  | 4896 | 1.5709          | 0.8131 |
  | 0.0105        | 18.0  | 5184 | 1.6013          | 0.8146 |
  | 0.0105        | 19.0  | 5472 | 1.5923          | 0.8150 |
  | 0.0039        | 20.0  | 5760 | 1.6233          | 0.8179 |
  | 0.0009        | 21.0  | 6048 | 1.5644          | 0.8203 |
  | 0.0009        | 22.0  | 6336 | 1.6229          | 0.8218 |
  | 0.001         | 23.0  | 6624 | 1.6706          | 0.8157 |
  | 0.001         | 24.0  | 6912 | 1.6754          | 0.8166 |
  | 0.0013        | 25.0  | 7200 | 1.6855          | 0.8169 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  