README.txt

NLP Project: Sentiment Analysis on Rotten Tomatoes Dataset

Contributors

• Jden Goh
• Jovan Foo
• Shao Jie
• Qi Wei

Overview

This repository explores sentiment analysis on the Rotten Tomatoes dataset using various neural network models (Simple RNN, CNN, BiLSTM, BiGRU, and an Ensemble model). Each model is trained and evaluated to determine the best-performing architecture for sentiment classification.

Dataset

• The dataset used is the Rotten Tomatoes dataset, which can be loaded using the datasets library.
• The dataset is split into training, validation, and test sets.

Setting up the Environemnt

Please download and unzip this folder.

Create Virtual Environment

    python3 -m venv venv

Activate your Virtual Environment

• On Windows:

    venv\Scripts\activate

• On macOS and Linux:

    source venv/bin/activate

Install Dependencies

The required dependencies can be installed using the requirements.txt file provided.

    pip install -r requirements.txt

Project Structure and Usage

• Train Models: Each model (Simple RNN, CNN, BiLSTM, BiGRU, Ensemble, etc) can be trained by running the corresponding cells in the notebook

• Evaluate Models: After training, each model is evaluated, and test accuracies printed and saved