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Roberta Fake News
R
Roberta Fake News
Developed by ghanashyamvtatti
A fake news detection model trained based on the RoBERTa architecture, which determines the authenticity of news by analyzing its textual content.
Downloads 26
Release Time : 3/2/2022
Model Overview
This model uses the RoBERTa architecture and is specifically designed for fake news detection. By analyzing linguistic features and content consistency in news texts, the model can effectively distinguish between real news and misinformation.
Model Features
Powerful Text Understanding Based on RoBERTa
Leverages the deep text comprehension capabilities of the RoBERTa pre-trained model to effectively capture features of misinformation in news.
Hyperparameter Optimized
Optimized through 10 rounds of hyperparameter search to ensure peak model performance.
High-Quality Training Data
Trained using real and fake news datasets from Kaggle, ensuring reliable data quality.
Model Capabilities
Text classification
Fake news detection
Natural language understanding
Use Cases
News Media
News Authenticity Verification
Automatically detects misinformation in news articles.
Helps editors quickly identify suspicious news content.
Social Media
Misinformation Filtering
Automatically flags potential fake news on social media platforms.
Reduces the spread of misinformation.
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