A machine learning project for detecting fake news using BERT (Bidirectional Encoder Representations from Transformers). TruthTrace analyzes news headlines and text to classify them as real or fake news with high accuracy.
TruthTrace leverages state-of-the-art natural language processing techniques to combat misinformation by automatically identifying fake news articles. The project uses BERT-base-uncased for fine-tuning on a labeled dataset of real and fake news articles.
- BERT-based Classification: Uses pre-trained BERT model fine-tuned for fake news detection
- High Accuracy: Trained on a large dataset of real and fake news articles
- Easy to Use: Simple Python interface for classifying news headlines
- Preprocessing Pipeline: Complete data preprocessing and tokenization workflow
- Model Training: Custom training scripts for fine-tuning BERT
- Python 3.7+
- pip or conda package manager
- Clone the repository:
git clone https://github.com/SameepK/TruthTrace.git
cd TruthTrace