lgalke/text-clf-baselines

WideMLP for Text Classification

39
/ 100
Emerging

This project helps researchers and developers evaluate text classification models more efficiently. It takes datasets for text classification (like news articles or reviews) and provides code to benchmark different model architectures, including a Bag-of-Words Wide MLP, against established methods like graph neural networks and Transformer models. The primary users are machine learning researchers or NLP engineers who need to compare model performance.

No commits in the last 6 months.

Use this if you are a researcher or developer comparing text classification models and want to quickly set up baselines and experiments for your datasets.

Not ideal if you need a plug-and-play solution for a business application, or if you are not comfortable working with research code and setting up dependencies.

natural-language-processing machine-learning-research text-analytics model-benchmarking data-science
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

29

Forks

5

Language

Python

License

MIT

Last pushed

Aug 10, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/lgalke/text-clf-baselines"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.