readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: stbl_clinical_bert_ft_rs9
    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_rs9
  
  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: 0.0866
  - F1: 0.9109
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.2712        | 1.0   | 101  | 0.0879          | 0.8420 |
  | 0.0666        | 2.0   | 202  | 0.0776          | 0.8726 |
  | 0.031         | 3.0   | 303  | 0.0630          | 0.8923 |
  | 0.015         | 4.0   | 404  | 0.0821          | 0.8958 |
  | 0.0087        | 5.0   | 505  | 0.0736          | 0.9084 |
  | 0.0061        | 6.0   | 606  | 0.0738          | 0.9083 |
  | 0.0037        | 7.0   | 707  | 0.0838          | 0.9157 |
  | 0.0027        | 8.0   | 808  | 0.0827          | 0.9088 |
  | 0.0017        | 9.0   | 909  | 0.0850          | 0.9135 |
  | 0.0014        | 10.0  | 1010 | 0.0871          | 0.9090 |
  | 0.001         | 11.0  | 1111 | 0.0868          | 0.9094 |
  | 0.001         | 12.0  | 1212 | 0.0866          | 0.9109 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  