readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - sms_spam
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-finetuned-sms-spam-detection
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: sms_spam
        type: sms_spam
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.998
  ---
  
  <!-- 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. -->
  
  # roberta-base-finetuned-sms-spam-detection
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the sms_spam dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0133
  - Accuracy: 0.998
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.0363        | 1.0   | 250  | 0.0156          | 0.996    |
  | 0.0147        | 2.0   | 500  | 0.0133          | 0.998    |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  