readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft_rs4
    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_rs4
  
  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: 0.1088
  - F1: 0.9076
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2994        | 1.0   | 101  | 0.0977          | 0.8416 |
  | 0.0639        | 2.0   | 202  | 0.0846          | 0.8689 |
  | 0.0318        | 3.0   | 303  | 0.0781          | 0.8879 |
  | 0.0173        | 4.0   | 404  | 0.0770          | 0.8934 |
  | 0.0099        | 5.0   | 505  | 0.0905          | 0.9021 |
  | 0.005         | 6.0   | 606  | 0.0963          | 0.9020 |
  | 0.0031        | 7.0   | 707  | 0.1024          | 0.9095 |
  | 0.002         | 8.0   | 808  | 0.1063          | 0.9057 |
  | 0.0017        | 9.0   | 909  | 0.1072          | 0.9076 |
  | 0.0014        | 10.0  | 1010 | 0.1103          | 0.9089 |
  | 0.0013        | 11.0  | 1111 | 0.1093          | 0.9087 |
  | 0.0008        | 12.0  | 1212 | 0.1088          | 0.9076 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  