apausa/extractiveQA

Fine-tuning RoBERTa for extractive question-answering using the Stanford Question Answering Dataset (SQuAD) and preprocessing with sliding windows, achieving 85.71% Exact Match and 92.18% F1 score.

14
/ 100
Experimental
No License No Package No Dependents
Maintenance 6 / 25
Adoption 1 / 25
Maturity 7 / 25
Community 0 / 25

How are scores calculated?

Stars

1

Forks

Language

Jupyter Notebook

License

Last pushed

Dec 12, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/apausa/extractiveQA"

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