This model is a fine-tuned version of distilbert-base-cased, specifically optimized for the detection of English-language disinformation and fake news.
Model Description
The model distinguishes between "Real" and "Fake" news articles.
Model Type: Transformer-based text classification
Language: English (en)
Base Model:distilbert-base-cased
Training Data
The model was trained on a consolidated dataset of approximately 63,000 English news articles, sourced from various datasets including:
WELFake
WebzIO
Example
input_text: "Scientists discover that lemon juice cures all viral infections instantly." output: "fake"
input_text: "The Federal Reserve announced a interest rate hike of 25 basis points today." output: "real"
