readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: results
    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. -->
  
  # results
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4578
  - Precision: 0.0060
  - Recall: 0.0286
  - F1: 0.0099
  - Accuracy: 0.4288
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 8    | 1.6449          | 0.0       | 0.0    | 0.0    | 0.3860   |
  | No log        | 2.0   | 16   | 1.5439          | 0.0014    | 0.0071 | 0.0023 | 0.4025   |
  | No log        | 3.0   | 24   | 1.4986          | 0.0068    | 0.0286 | 0.0110 | 0.4176   |
  | No log        | 4.0   | 32   | 1.4603          | 0.0033    | 0.0143 | 0.0054 | 0.4285   |
  | No log        | 5.0   | 40   | 1.4578          | 0.0060    | 0.0286 | 0.0099 | 0.4288   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  