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SMS Spam Detection using DistilBERT

Model Description

This model is fine-tuned using DistilBERT for SMS spam classification.

Dataset

SMS Spam Collection Dataset

Labels

  • 0: Ham (Normal message)
  • 1: Spam

Model Architecture

DistilBERT transformer model fine-tuned for binary text classification.

Training

The model was trained using Google Colab with T4 GPU.

Evaluation Metrics

The model was evaluated using:

  • Accuracy
  • Precision
  • Recall
  • F1-Score

Intended Use

This model can classify SMS messages as spam or normal text.

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Model size
67M params
Tensor type
F32
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