readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft_rs10
    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_rs10
  
  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: 0.0846
  - F1: 0.9297
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2834        | 1.0   | 101  | 0.0930          | 0.8446 |
  | 0.0669        | 2.0   | 202  | 0.0732          | 0.8938 |
  | 0.033         | 3.0   | 303  | 0.0676          | 0.9119 |
  | 0.0168        | 4.0   | 404  | 0.0703          | 0.9219 |
  | 0.0084        | 5.0   | 505  | 0.0742          | 0.9245 |
  | 0.006         | 6.0   | 606  | 0.0772          | 0.9252 |
  | 0.0033        | 7.0   | 707  | 0.0844          | 0.9239 |
  | 0.0023        | 8.0   | 808  | 0.0855          | 0.9272 |
  | 0.0019        | 9.0   | 909  | 0.0843          | 0.9296 |
  | 0.0013        | 10.0  | 1010 | 0.0878          | 0.9262 |
  | 0.0012        | 11.0  | 1111 | 0.0857          | 0.9266 |
  | 0.0008        | 12.0  | 1212 | 0.0846          | 0.9297 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  