Fine-tuning a Named Entity Recognition (NER) model to extract key entities like products, prices, and locations from Amharic Telegram messages.
# EthioMart NER Project
## Overview
This repository contains the code and resources for fine-tuning a Named Entity Recognition (NER) model to extract key entities like products, prices, and locations from Amharic Telegram messages. The project involves data preprocessing, model training, and evaluation, with the fine-tuning process conducted using Google Colab.
## Directory Structure
├── notebooks/ # Contains Jupyter notebooks for demo and model training │
├── scripts/ # Python scripts for preprocessing │
├── scraping.py # Script for scraping data from Telegram channels │
├── requirements.txt # List of required Python packages
├── README.md # Project documentation
└── .gitignore # Files to ignore in the Git repo
## Setup Instructions
### 1. Clone the repository
```bash
git clone
github.com
cd ethiomart
```
### 2. Install dependencies
Ensure that you have Python 3.7 or higher installed. Install the required packages by running:
```bash
pip install -r requirements.txt
```
### 3. Directory Details
notebooks/: This directory contains Jupyter notebooks demonstrating preprocessing and the fine-tuning process.
preprocessing.ipynb: Demonstrates the dataset preprocessing using the preprocessing.py script.
fine_tuning.ipynb: This notebook handles fine-tuning the NER model. It includes data loading, tokenization, model training, and evaluation. This notebook was run on Google Colab to take advantage of GPU resources for faster training.
scripts/: Contains Python scripts for scraping and preprocessing tasks.
scraping.py: A Python script for scraping messages from multiple Ethiopian Telegram e-commerce channels. It fetches text, images, and metadata (e.g., timestamps, sender info) in real-time and stores them for preprocessing.
preprocessing.py: A Python script for cleaning, tokenizing, and preparing raw text data for NER model training, as well as combining datasets.
requirements.txt: A list of all the Python libraries and version …