My Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow

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Text Data & NLP nlp data deep-learning lstm tensorflow2
Overview

Easy Data Augmentation Implementation

This repository contains my Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow

I have reimplemented the 4 Data Augmentation Techniques Described in the Paper and tested it on the Stanford Sentiment Treebank v2 (SST2) dataset acquired from here

p.s. I have also discussed and gone through the paper here

FAQs-

Q- How can I run this?

A - Just open the .ipynb file, click on the "open in colab" button located at the start of the notebook, set runtime to GPU (for speedy training) and run all cells (everything else is already handled)

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