Financial Sentiment Analysis
NLP platform with BERT-MPNet achieving 81% accuracy on 4,846 expert-annotated financial sentences
Technology Stack
ROI
Market intelligence automation
Accuracy
81.16% accuracy (BERT-MPNet)
Key Performance Indicators
Business Impact Summary
| Return on Investment | Market intelligence automation |
| Model Accuracy | 81.16% accuracy (BERT-MPNet) |
| F1-Score | 81.31% |
| XGBoost Accuracy | 74.41% |
| Inference Speed | Real-time |
Overview
Production-ready financial sentiment analysis platform with Transformer models (BERT-MPNet, MiniLM) and Traditional ML (XGBoost, Random Forest, SVM, Logistic Regression). Real-time sentiment classification with confidence scores across 4,846 expert-annotated financial news sentences.
Live Demo
Live Demo
Interactive Streamlit application
Financial Sentiment Analysis Demo
Click below to load the interactive demo
This is a live, interactive demo deployed on Streamlit Cloud. You can:
- •Upload your own data for predictions
- •Explore model performance metrics
- •View interactive visualizations
- •Understand model predictions with explainability
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