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An AI-powered web app that analyzes financial news headlines and classifies them as Positive, Negative, or Neutral using the FinBERT model — a finance-specific version of BERT by Hugging Face. The app helps investors, analysts, and finance professionals quickly gauge market sentiment from news or social media headlines.

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💹 Financial News Sentiment Analyzer App

Financial News Sentiment Analyzer App is a user-friendly web application that analyzes financial headlines and returns sentiment probabilities (Positive / Negative / Neutral) using FinBERT (ProsusAI/finbert).

🌐 Live App: 👉 Click here to use the app


🚀 Overview

This project started as a prototype (Gradio) and was converted to a polished Streamlit web app for better interactivity and shareability. It provides quick sentiment insights for financial headlines — great for analysts, journalists, researchers, and investors.

Key features

  • 🔍 Instant sentiment detection for financial headlines
  • 🤖 FinBERT-based model trained/tuned for finance text
  • 📊 Probability visualization for each sentiment class
  • 💬 Clean, responsive UI built with Streamlit
  • ☁️ Easy to run in Colab, CoreLab, Streamlit Cloud, or a server

🧠 Model

This app uses ProsusAI/finbert from Hugging Face — a specialized BERT model for financial sentiment classification (Positive / Negative / Neutral).


🧰 Tech Stack

  • Framework: Streamlit
  • Model: Hugging Face Transformers (FinBERT)
  • Libraries: transformers, torch, scipy, pandas
  • Runs on: Colab / CoreLab / Local / Streamlit Cloud

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An AI-powered web app that analyzes financial news headlines and classifies them as Positive, Negative, or Neutral using the FinBERT model — a finance-specific version of BERT by Hugging Face. The app helps investors, analysts, and finance professionals quickly gauge market sentiment from news or social media headlines.

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