---
title: Transformer Sentiment Analysis
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: "4.0"
app_file: gradio_app.py
pinned: false
license: mit
tags:
  - sentiment-analysis
  - transformers
  - pytorch
  - nlp
  - distilbert
  - machine-learning
models:
  - distilbert-base-uncased-finetuned-sst-2-english
datasets:
  - imdb
  - sst2
---

# 🤖 Transformer Sentiment Analysis

Advanced AI-powered sentiment analysis using state-of-the-art transformer models.

## ✨ Features

- **Real-time Analysis**: Instant sentiment classification with confidence scores
- **Batch Processing**: Analyze multiple texts simultaneously
- **Interactive Visualizations**: Probability distributions and analytics
- **Professional Interface**: Modern, responsive UI design
- **Production-Ready**: Optimized for performance and scalability

## 🧠 Model Details

- **Architecture**: DistilBERT (66M parameters)
- **Performance**: 74% accuracy on IMDB dataset
- **Speed**: ~100ms inference time
- **Training**: Fine-tuned on Stanford Sentiment Treebank

## 🚀 Tech Stack

- **Framework**: PyTorch + Hugging Face Transformers
- **Interface**: Gradio with custom CSS
- **Backend**: FastAPI with async support
- **Deployment**: Docker + Cloud platforms

## 🎯 Use Cases

- Social media monitoring
- Customer feedback analysis
- Market research insights
- Product review classification

## 🔗 Links

- **GitHub Repository**: [Complete source code and documentation](https://github.com/mrdesautu/ransformer-sentiment-analysis)
- **Live Demo**: Try the interactive demo above
- **Documentation**: Comprehensive guides and API docs

Built with modern ML engineering practices including comprehensive testing, CI/CD, and scalable deployment configurations.