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text-summarization-S2S-Model

Overview

A Seq2Seq model with Attention that reads a food review and generates a short summary.

Side notes

The model is pretty bad, it was only trained on a 100 summaries so it can't make a really good summary.

Sample test:

Test Loss: nan

Sample predictions:

Example 1
Pred: first okay party especially rather oils lemonlime pot pot fat work approved transfer deliberately company remember loved wholesome home method
True: flavor

Example 2
Pred: first okay party especially starving doesnt sits whenever taffy year expensive hour five tea agree regularly method visits abdominal sensitive
True: stomach

Prerequisites

Before you begin, ensure you have the following installed:

  • pandas
  • numpy
  • python-dotenv
  • nltk
  • torch
  • scikit-learn
  • beautifulsoup4

Configuration

Configuration options can be set via environment variables or a config file:

Environment Variables

REVIEWS_DATA={Path_to_review_data}

Development Setup

git clone https://github.com/Troppy2/text-summarization.git
cd [project_name]
pip install python-dotenv numpy pandas nltk torch scikit-learn beautifulsoup4