Adversarial Attack

This project implements a machine learning model capable of handling adversarial attacks, focusing particularly on a question-answering system that can withstand deceptive inputs designed to confuse or manipulate AI predictions.

Booklet : Adversarial Attack on Text Classification

🚀 Installation Instructions

Setting Up Your Development Environment

1. Create a Virtual Environment

   • For Windows:

     python.exe -m pip install --upgrade pip
     python -m venv myenv
     myenv\Scripts\activate
     

   • For Linux/Mac:

     python -m pip install --upgrade pip
     python -m venv myenv
     source myenv/bin/activate
     

2. Install Required Python Packages

   Run the following command to install all necessary dependencies listed in the requirements.txt file:

   pip install -r requirements.txt
   python -m pip install -e .

📦 Data Preparation

Before training the model, you need to download and prepare the required datasets:

cd utils
python dataloader.py

🏋️‍♂️ Training the Model

You can train the model by specifying the number of epochs in the model.py file. By default, the number of epochs is set to 1. To start training, execute the following commands:

cd model
python model.py