Hate Speech Detection

This project is a Hate Speech Detection model that classifies text into three categories:

• Hate Speech
• Offensive Language
• Neither

It uses machine learning techniques to identify harmful comments online.

Model Performance

• Accuracy: 89%
• F1-Scores:
  • Hate Speech: 30%
  • Offensive Language: 94%
  • Neither: 84%

Files Included

• 'app.py': Streamlit app for real-time predictions.
• 'hate_speech_model.pkl': The trained model.
• 'vectorizer.pkl': Text vectorizer for data processing.
• 'requirements.txt': List of dependencies.

How to Run Locally

1. Clone the repository.
2. Install dependencies:

   pip install -r requirements.txt

3. Run the app:

   streamlit run app.py

4. Open your browser at http://localhost:8501.

How to Use

1. Enter a comment in the input box.
2. Click “Classify” to see the result (Hate Speech, Offensive Language, or Neither).

Technologies Used

• Python
• Streamlit for building the web app.
• scikit-learn for machine learning.
• joblib for saving/loading models.

Future Improvements

• Upgrade the model with more advanced techniques (e.g., BERT, GPT).
• Add multilingual support.
• Improve text preprocessing.