https://github.com/vlada-pv/bert-predict-text-rating

BERT-based model for text classification tasks.
https://github.com/vlada-pv/bert-predict-text-rating

bert bert-embeddings neural-networks pytorch text-classification text-rating

Last synced: about 5 hours ago
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BERT-based model for text classification tasks.

• Host: GitHub
• URL: https://github.com/vlada-pv/bert-predict-text-rating
• Owner: vlada-pv
• Created: 2024-08-16T21:33:02.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-08-16T21:41:49.000Z (about 1 month ago)
• Last Synced: 2024-09-26T20:04:10.550Z (about 5 hours ago)
• Topics: bert, bert-embeddings, neural-networks, pytorch, text-classification, text-rating
• Language: Jupyter Notebook
• Homepage:
• Size: 53.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Text Classification with BERT

This project demonstrates the application of a BERT-based model for text classification tasks. The project is implemented using **PyTorch** and involves various stages of data preprocessing, model training, and evaluation.

## Project Overview

The project is focused on building and evaluating a text classification model using a dataset from Kaggle. The key steps involved in this project include:

**1) Data Loading and Preprocessing:**

Data is loaded from CSV files provided in the Kaggle dataset.

Text data is tokenized, cleaned, and prepared for model input using tools like NLTK and custom preprocessing functions.

**2) Model Implementation:**

A BERT-based model is implemented using the PyTorch framework.

The model architecture is designed to handle classification tasks, with appropriate layers and configurations for text data.

**3) Training and Evaluation:**

The dataset is split into training and validation sets using scikit-learn.

The model is trained and optimized using various hyperparameters, and its performance is evaluated using metrics such as accuracy.

**4) Results:**

The trained model is tested on unseen data, and results are reported in terms of accuracy and other relevant metrics.

## Getting Started

**Prerequisites:**

* Python 3.x

* PyTorch

* scikit-learn

* NLTK

* Matplotlib