Joshuaatanu/GloVeModel

This repository contains the code and resources for training a GloVe (Global Vectors for Word Representation) model on Igala, a low-resource language. The project includes scripts for preprocessing the text data, training the GloVe model, evaluating the resulting word embeddings, and visualizing the embeddings using techniques such as t-SNE. # GloVe Model for Igala Language ## Overview This repository contains the code and resources for training a GloVe (Global Vectors for Word Representation) model on Igala, a low-resource language. The project includes scripts for preprocessing the text data, training the GloVe model, evaluating the resulting word embeddings, and visualizing the embeddings using techniques such as t-SNE. ## Features - **Data Preprocessing**: Tools for cleaning and tokenizing Igala text data. - **GloVe Model Training**: Implementation of a GloVe model using PyTorch. - **Evaluation**: Scripts to evaluate word embeddings using cosine similarity, intrinsic evaluation methods, and extrinsic tasks. - **Visualization**: Interactive visualization of word embeddings using t-SNE and Plotly. ## Getting Started ### Prerequisites Before running the code, ensure you have the following dependencies installed: - Python 3.x - PyTorch - NumPy - Matplotlib - Scikit-learn - Plotly - Pandas - GPU You can install these dependencies using pip: ```bash pip install torch numpy matplotlib scikit-learn plotly pandas