DistilBERT English Fake News Classifier
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"
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