Skip to content

Latest commit

 

History

History
37 lines (24 loc) · 998 Bytes

ReadMe.md

File metadata and controls

37 lines (24 loc) · 998 Bytes

Text Classification Model

This repository contains a text classification model that uses the Hugging Face library and the Amazon review dataset to identify whether a review is helpful or not.

Getting Started

Prerequisites

  • Python 3.8 or higher
  • Hugging Face library
  • Pytorch
  • pandas
  • numpy
  • Transformers
  • sklearn

Installation

Clone this repository and install the required libraries on the requirements.txt file:

git clone https://github.com/dom-inic/huggingface-text-classifier.git cd huggingface-text-classifier pip install -r requirements.txt

Download distilbert-base-uncased model install git lfs cd distilbert-base-uncased git lfs pull

Training the model

you can train the model using code available on the ipynb file as well as evaluate the preformance of the model.

Dataset

The Amazon review dataset used to train the model contains a combination of helpful and not helpful reviews. The dataset is preprocessed and can be found in the data folder.