readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: CR_roBERTa_5E
    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. -->
  
  # CR_roBERTa_5E
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3728
  - Accuracy: 0.9333
  
  ## 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: 1e-05
  - train_batch_size: 16
  - 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 | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6307        | 0.33  | 50   | 0.4608          | 0.66     |
  | 0.3468        | 0.66  | 100  | 0.3195          | 0.8933   |
  | 0.2359        | 0.99  | 150  | 0.2952          | 0.9      |
  | 0.1786        | 1.32  | 200  | 0.2839          | 0.92     |
  | 0.2581        | 1.66  | 250  | 0.2955          | 0.9267   |
  | 0.231         | 1.99  | 300  | 0.2864          | 0.9133   |
  | 0.1262        | 2.32  | 350  | 0.4320          | 0.8933   |
  | 0.1935        | 2.65  | 400  | 0.2874          | 0.9133   |
  | 0.1646        | 2.98  | 450  | 0.3581          | 0.9133   |
  | 0.1151        | 3.31  | 500  | 0.3666          | 0.92     |
  | 0.1184        | 3.64  | 550  | 0.3496          | 0.9267   |
  | 0.1089        | 3.97  | 600  | 0.3655          | 0.9267   |
  | 0.0969        | 4.3   | 650  | 0.3607          | 0.9267   |
  | 0.0988        | 4.64  | 700  | 0.3707          | 0.9333   |
  | 0.0597        | 4.97  | 750  | 0.3728          | 0.9333   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.13.0
  - Datasets 2.3.2
  - Tokenizers 0.13.1
  