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:
Validation Metrics
- Loss: 0.064
- Accuracy: 0.992
- Precision: 0.985
- Recall: 1.000
- AUC: 0.992
- F1: 0.992