readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft_rs7
    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. -->
  
  # stbl_clinical_bert_ft_rs7
  
  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: 0.0848
  - F1: 0.9208
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2755        | 1.0   | 101  | 0.0986          | 0.8484 |
  | 0.0655        | 2.0   | 202  | 0.0780          | 0.8873 |
  | 0.0299        | 3.0   | 303  | 0.0622          | 0.9047 |
  | 0.0145        | 4.0   | 404  | 0.0675          | 0.9110 |
  | 0.0097        | 5.0   | 505  | 0.0706          | 0.9141 |
  | 0.0057        | 6.0   | 606  | 0.0753          | 0.9174 |
  | 0.0032        | 7.0   | 707  | 0.0755          | 0.9182 |
  | 0.0024        | 8.0   | 808  | 0.0835          | 0.9219 |
  | 0.0014        | 9.0   | 909  | 0.0838          | 0.9197 |
  | 0.0013        | 10.0  | 1010 | 0.0838          | 0.9204 |
  | 0.0009        | 11.0  | 1111 | 0.0850          | 0.9183 |
  | 0.0009        | 12.0  | 1212 | 0.0848          | 0.9208 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  