Shawn1993/cnn-text-classification-pytorch

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1043 stars · 270 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of Kim's CNN architecture for sentence classification, reproducing results from the paper 'Convolutional Neural Networks for Sentence Classification'. It trains CNN text classifiers on datasets like MR and SST via a command-line interface.

Use cases

• train a CNN text classifier in pytorch
• reproduce Kim's sentence classification paper results
• classify sentences into sentiment categories
• learn how CNN text classification works
• benchmark text classification on MR and SST datasets

When to choose

• you want a faithful PyTorch reproduction of Kim's CNN sentence classification model
• you need a simple, dependency-light text classification baseline
• you want to experiment with CNN hyperparameters for text classification

When to avoid

• you need transformer-based or state-of-the-art text classification
• you want a production-ready text classification service
• you need multi-label or long-document classification

Facets

library · maturity active

machine-learning nlp deep-learning deep-learning machine-learning python cli pytorch cnn text-classification sentence-classification research-reproduction natural-language-processing gpu

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