Samri-A/Amharic-E-commerce-Data-Extractor

# Amharic E-commerce Data Extractor ## Overview The Amharic E-commerce Data Extractor is a project designed to scrape and preprocess e-commerce data from Amharic Telegram channels. This tool aims to facilitate the extraction of relevant product information and make it available for further analysis and research. ## Table of Contents - Features - Installation - Usage - Fine-Tuning Amharic Models for NER - Project Structure - Contributing - License ## Features - Scrapes e-commerce data from Amharic Telegram channels. - Preprocesses the extracted data into a structured format. - Supports output in CoNLL format for labeled data. - Includes Jupyter Notebooks for easy experimentation and modification. ## Installation To get started with the Amharic E-commerce Data Extractor, follow these steps: 1. Clone the repository: ```bash git clone github.com ``` 2. Navigate to the project directory: ```bash cd Amharic-E-commerce-Data-Extractor ``` 3. Install the required dependencies: Make sure you have Python installed, then run: ```bash pip install -r requirements.txt ``` ## Usage To use the data extractor, you can run the provided scripts in the `scripts` folder. For example: ```bash python scripts/extract_data.py ``` Make sure to modify any parameters as necessary to suit your specific needs. ## Fine-Tuning Amharic Models for NER The project includes scripts and Jupyter Notebooks for fine-tuning Amharic models specifically for Named Entity Recognition (NER) tasks. Fine-tuning allows you to adapt pre-trained models to better recognize entities relevant to your specific dataset. ### Steps for Fine-Tuning: 1. **Prepare Your Dataset**: Ensure your dataset is in CoNLL format or another compatible format for NER tasks. 2. **Run the Fine-Tuning Script**: Use the provided scripts in the `scripts` folder to initiate fine-tuning. For example: ```bash python scripts/fine_tune_ner.py --data_path your_data_file.CoNLL ``` 3. **Eval …