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BDA594-fake-news-classification

Text Classification
Transformers
PyTorch
Safetensors
Enawené-Nawé
xlm-roberta
Inference Endpoints
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metadata
tags:
  - text-classification
language:
  - unk
datasets:
  - Kaludi/BDA594-fake-news-classification

Fake News Classification

This is a Fake News Classifier model that has been trained by Kaludi to determine the authenticity of news articles. It classifies articles into two categories: Real and Fake. By analyzing the content and context of a given article, this model can accurately determine whether the news is genuine or fabricated.

Gradio

This model supports a Gradio Web UI to run the BDA594-fake-news-classification model: Open In HF Spaces

Validation Metrics

  • Loss: 0.064
  • Accuracy: 0.992
  • Precision: 0.985
  • Recall: 1.000
  • AUC: 0.992
  • F1: 0.992