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metadata
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

roberta-base-finetuned-sms-spam-detection

This model is a fine-tuned version of 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