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| title: Advanced Sentiment Analyzer | |
| emoji: π | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 4.44.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # π Advanced Sentiment Analyzer | |
| **Multi-Model AI System for Superior Sentiment Analysis** | |
| This space demonstrates an advanced sentiment analysis system that uses multiple AI models working together to provide more accurate predictions than any single model alone. | |
| ## π€ How It Works | |
| The system employs up to 4 different transformer models: | |
| - **YelpReviewsAnalyzer**: Custom fine-tuned model (78.5% accuracy) | |
| - **DistilBERT**: General-purpose sentiment analysis | |
| - **Twitter-RoBERTa**: Optimized for social media text | |
| - **FinBERT**: Specialized for financial sentiment | |
| These models work together using a **consensus algorithm** that: | |
| 1. Runs all models in parallel | |
| 2. Collects individual predictions | |
| 3. Builds consensus through weighted voting | |
| 4. Provides agreement scores for reliability assessment | |
| ## π― Features | |
| - **Multi-Model Consensus**: Higher accuracy through model ensemble | |
| - **Real-time Analysis**: Fast sentiment prediction | |
| - **Confidence Scoring**: Know how certain the prediction is | |
| - **Agreement Assessment**: Understand model consensus level | |
| - **Production Ready**: Built for real-world applications | |
| ## π Performance | |
| - **Individual Model Accuracy**: 72-78% | |
| - **Consensus Accuracy**: ~85%+ through ensemble voting | |
| - **Processing Speed**: < 2 seconds for multi-model analysis | |
| ## π Links | |
| - **GitHub Repository**: [Sentiment-Analyzer](https://github.com/fitsblb/Sentiment-Analyzer) | |
| - **Original Model**: [YelpReviewsAnalyzer](https://huggingface.co/fitsblb/YelpReviewsAnalyzer) | |
| - **Paper/Research**: Complete methodology in GitHub repo | |
| --- | |
| *Built with β€οΈ using Hugging Face Transformers, PyTorch, and Gradio* | |