readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: Bio_ClinicalBERT_fold_9_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_9_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: 1.6976
  - F1: 0.8065
  
  ## 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  | 0.4002          | 0.7826 |
  | 0.4094        | 2.0   | 582  | 0.3968          | 0.8212 |
  | 0.4094        | 3.0   | 873  | 0.6130          | 0.7984 |
  | 0.1977        | 4.0   | 1164 | 0.5853          | 0.8227 |
  | 0.1977        | 5.0   | 1455 | 0.9401          | 0.8143 |
  | 0.0837        | 6.0   | 1746 | 1.1764          | 0.8059 |
  | 0.0274        | 7.0   | 2037 | 1.1515          | 0.8112 |
  | 0.0274        | 8.0   | 2328 | 1.2614          | 0.8065 |
  | 0.0113        | 9.0   | 2619 | 1.3404          | 0.8002 |
  | 0.0113        | 10.0  | 2910 | 1.3926          | 0.8088 |
  | 0.0125        | 11.0  | 3201 | 1.4539          | 0.8010 |
  | 0.0125        | 12.0  | 3492 | 1.5460          | 0.7998 |
  | 0.0101        | 13.0  | 3783 | 1.5920          | 0.8060 |
  | 0.0107        | 14.0  | 4074 | 1.5631          | 0.8059 |
  | 0.0107        | 15.0  | 4365 | 1.6323          | 0.8020 |
  | 0.0127        | 16.0  | 4656 | 1.6183          | 0.8008 |
  | 0.0127        | 17.0  | 4947 | 1.6351          | 0.8033 |
  | 0.0068        | 18.0  | 5238 | 1.5608          | 0.8121 |
  | 0.0047        | 19.0  | 5529 | 1.6339          | 0.8141 |
  | 0.0047        | 20.0  | 5820 | 1.6039          | 0.8091 |
  | 0.0029        | 21.0  | 6111 | 1.5676          | 0.8085 |
  | 0.0029        | 22.0  | 6402 | 1.6489          | 0.8139 |
  | 0.0036        | 23.0  | 6693 | 1.6824          | 0.8087 |
  | 0.0036        | 24.0  | 6984 | 1.6773          | 0.8106 |
  | 0.0008        | 25.0  | 7275 | 1.6976          | 0.8065 |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  