anshy047/fake-news-detector-transformer

🧠 Fake News Detection using Transformer

This model is a fine-tuned DistilBERT model designed to classify news articles as FAKE or REAL.

🚀 Model Overview

• —Base Model: distilbert-base-uncased
• —Task: Text Classification
• —Labels: FAKE, REAL
• —Architecture: Transformer-based (DistilBERT)

📊 Performance

• —Accuracy: ~98%
• —F1 Score: ~0.98

📂 Dataset

Trained on a combined dataset including:

• —Fake news datasets
• —Real news datasets
• —Cleaned and preprocessed text corpus

🧠 How It Works

The model analyzes:

• —Semantic meaning of text
• —Contextual relationships
• —Writing patterns

⚡ Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="your-username/your-model")

classifier("Breaking news: Scientists discover new planet")