readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_5_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_5_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: 1.6689
  - F1: 0.8148
  
  ## 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  | 0.4406          | 0.8072 |
  | 0.4043        | 2.0   | 576  | 0.4952          | 0.8059 |
  | 0.4043        | 3.0   | 864  | 0.4988          | 0.8222 |
  | 0.2025        | 4.0   | 1152 | 0.8866          | 0.7948 |
  | 0.2025        | 5.0   | 1440 | 0.9027          | 0.8176 |
  | 0.0865        | 6.0   | 1728 | 1.1263          | 0.8003 |
  | 0.035         | 7.0   | 2016 | 1.2498          | 0.7998 |
  | 0.035         | 8.0   | 2304 | 1.3188          | 0.8093 |
  | 0.0133        | 9.0   | 2592 | 1.4641          | 0.8021 |
  | 0.0133        | 10.0  | 2880 | 1.4972          | 0.8042 |
  | 0.0119        | 11.0  | 3168 | 1.5511          | 0.8057 |
  | 0.0119        | 12.0  | 3456 | 1.5184          | 0.8108 |
  | 0.0131        | 13.0  | 3744 | 1.5716          | 0.8017 |
  | 0.0067        | 14.0  | 4032 | 1.5305          | 0.8176 |
  | 0.0067        | 15.0  | 4320 | 1.4945          | 0.8227 |
  | 0.0113        | 16.0  | 4608 | 1.5241          | 0.8216 |
  | 0.0113        | 17.0  | 4896 | 1.5571          | 0.8182 |
  | 0.0072        | 18.0  | 5184 | 1.6044          | 0.8107 |
  | 0.0072        | 19.0  | 5472 | 1.6129          | 0.8156 |
  | 0.002         | 20.0  | 5760 | 1.6990          | 0.8126 |
  | 0.0036        | 21.0  | 6048 | 1.6867          | 0.8109 |
  | 0.0036        | 22.0  | 6336 | 1.7301          | 0.8100 |
  | 0.0021        | 23.0  | 6624 | 1.6595          | 0.8167 |
  | 0.0021        | 24.0  | 6912 | 1.6577          | 0.8132 |
  | 0.0029        | 25.0  | 7200 | 1.6689          | 0.8148 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  