readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - clinc_oos
  model-index:
  - name: bert-base-uncased-fine-tuned-on-clinc_oos-dataset
    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. -->
  
  # bert-base-uncased-fine-tuned-on-clinc_oos-dataset
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the clinc_oos dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2811
  - Accuracy Score: 0.9239
  - F1 Score: 0.9213
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | F1 Score |
  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:--------:|
  | 4.4271        | 1.0   | 239  | 3.5773          | 0.6116         | 0.5732   |
  | 3.0415        | 2.0   | 478  | 2.4076          | 0.8390         | 0.8241   |
  | 2.1182        | 3.0   | 717  | 1.7324          | 0.8994         | 0.8934   |
  | 1.5897        | 4.0   | 956  | 1.3863          | 0.9210         | 0.9171   |
  | 1.3458        | 5.0   | 1195 | 1.2811          | 0.9239         | 0.9213   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  