anaol216/amharic-ecommerce-ner-vendor-scorecard

Fine-tuned Amharic NER system for extracting product, price, and location data from Telegram e-commerce channels, with a vendor scoring engine for micro-lending insights. # 🛍️ Amharic E-Commerce NER & Vendor Scorecard This project builds a Named Entity Recognition (NER) system to extract product, price, and location data from Amharic Telegram-based e-commerce posts. It also includes a vendor scoring system to support micro-lending decisions for small businesses. --- ## 📌 Key Features - 🔎 Extracts entities like `Product`, `Price`, `Location`, `Delivery Fee`, and `Contact Info` - 🤖 Fine-tunes multilingual models (XLM-Roberta, AfroXLMR, etc.) for Amharic NER - 📊 Scores vendors based on posting activity, views, and product prices - 🧠 Uses SHAP and LIME for model explainability --- ## 📁 Folder Structure amharic-ecommerce-ner/ ├── data/ # Raw, cleaned, and labeled Telegram data ├── scripts/ # Python scripts for scraping, training, scoring ├── notebooks/ # Jupyter/Colab notebooks ├── models/ # Fine-tuned NER models ├── tests/ # Pytest unit tests ├── reports/ # Project reports (PDF) ├── .vscode/ # VS Code settings ├── .github/workflows/ # GitHub Actions CI --- ## 🚀 How to Run ```bash # Create virtual environment python -m venv venv source venv/bin/activate # or venv\Scripts\activate on Windows # Install dependencies pip install -r requirements.txt # Run tests pytest tests/