Fine-tune-Vision-Language-Model

This repository contains the implementation of the Vision-and-Language Transformer (ViLT) model fine-tuned for Visual Question Answering (VQA) tasks. The project is structured to be easy to set up and use, providing a streamlined approach for experimenting with different configurations and datasets.

Installation

1. Clone the Repository

git clone https://your-repository-url.git
cd vilt-vqa

2. Install Dependencies

pip install -r requirements.txt

3. Download Data Ensure that your data files are in the data/ directory as specified in settings.py.

Usage

Training the Model

To train the model, run:

python train.py

This script will train the model using the configurations specified in config/settings.py.

Making Predictions

To perform inference with a pre-trained model, run:

python infer.py --image_path 'path/to/image.jpg' --question 'What is in the picture?'

This will load the trained model and output the top predictions for the specified image and question.

Configuration

Edit config/settings.py to modify paths, model parameters, and other settings like device configuration for GPU acceleration.