README.md

metadata

title: Emotion Detection App
emoji: 😊
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 4.27.0
app_file: app.py
pinned: false

😊 Emotion Detection from Text using BERT

Welcome to the Emotion Detection Web App! This application uses a fine-tuned BERT model to detect human emotions from short pieces of text.

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🚀 Demo

👉 Try the live app: Click here to open the web app

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🔍 Description

This project leverages the nateraw/bert-base-uncased-emotion model from Hugging Face Transformers to classify input text into one of six emotions:

• 😢 Sadness
• 😀 Joy
• 💖 Love
• 😡 Anger
• 😱 Fear
• 😲 Surprise

It uses:

• Hugging Face Transformers for model and tokenizer
• PyTorch for deep learning inference
• Gradio to build an interactive web interface

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🧠 Model Used

• Model Name: nateraw/bert-base-uncased-emotion
• Base Architecture: BERT (uncased)
• Dataset: GoEmotions subset

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📦 Dependencies

Dependencies are defined in requirements.txt:

• transformers
• torch
• gradio

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📈 Use Cases

• Social media sentiment analysis
• Customer feedback classification
• Chatbot emotion understanding
• Mental health applications

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👨‍💻 Author

• Sujith Kumar
• Hugging Face: @sujith13082003

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📝 License

This project is for educational and research purposes. Refer to individual library licenses for commercial use.