--- license: apache-2.0 language: - en base_model: - answerdotai/ModernBERT-base pipeline_tag: text-classification metrics: - accuracy --- # ModernBERT-FakeNewsClassifier ## Model Description **ModernBERT-FakeNewsClassifier** is a fine-tuned version of [ModernBERT](https://huggingface.co/answerdotai/ModernBERT-base), optimized for the binary classification task of detecting fake news. This model processes news articles, including their titles, text content, subject, and publication date, to classify them as either **real (1)** or **fake (0)**. The model is fine-tuned on a dataset containing over 30,000 labeled examples, achieving high accuracy and robustness. ### Key Features: - **Base Model**: ModernBERT, designed for long-context processing (up to 8,192 tokens). - **Task**: Binary classification for fake news detection. - **Architecture Highlights**: - Rotary Positional Embeddings (RoPE) for long-context support. - Local-global alternating attention for memory efficiency. - Flash Attention for optimized inference speed. ## Dataset The dataset used for fine-tuning comprises over 30,000 examples, with the following features: - **Title**: The headline of the news article. - **Text**: The main body of the article. - **Subject**: The category or topic of the article (e.g., Politics, Health). - **Date**: The publication date of the article. - **Label**: Binary labels indicating whether the article is fake (`0`) or real (`1`). ## Notebook: Training and Fine-Tuning The repository includes the code.ipynb file, which provides: - Step-by-step instructions for preprocessing the dataset. - Fine-tuning the ModernBERT model for binary classification. - Code for evaluating the model using metrics such as accuracy, F1-score, and AUC-ROC. - You can directly open and run the notebook to replicate or customize the training process. ## Citation If you use this model in your research or applications, please cite: ``` @misc{ModernBERT-FakeNewsClassifier, author = {Daksh Rathi}, title = {ModernBERT-FakeNewsClassifier: A Transformer-Based Model for Fake News Detection}, year = {2024}, url = {https://huggingface.co/dakshrathi/ModernBERT-base-FakeNewsClassifier}, }