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IndoNLU

IndoNLP
gated / Overall score: 3.1

IndoNLU is a benchmark for Indonesian natural language understanding with twelve tasks, from emotion and sentiment classification to part-of-speech tagging, named-entity recognition, keyphrase extraction, textual entailment and extractive QA. The task data comes from social media, reviews, news and Wikipedia, some of it labeled by Indonesian linguists. It shipped with the Indo4B pretraining corpus and the IndoBERT models, from a collaboration including Institut Teknologi Bandung, Universitas Indonesia, Gojek and Prosa.AI.

Openness

2 medium confidence
2.0
license
mit(HF card: 'The licensing status of the IndoNLU benchmark datasets is under MIT License'
access
public(ungated)
dataset_card
present(per-task descriptions
answers
held-out(GitHub test-set labels are masked

The task data downloads freely under a permissive license, but the official test labels are masked and scored through a CodaLab competition. The Hugging Face card leaves its collection and annotation sections unfilled, so provenance comes from the paper.

Adoption

1 high confidence
1.0

Adoption is Hugging Face downloads of the repository. Users of the GitHub copies and of the CodaLab test sets are not counted.

Capability

4 medium confidence
4.0

IndoNLU is documented in a paper, shipped with the IndoBERT models, and many Indonesian classifiers are fine-tuned on its tasks. It covers only Indonesian and only understanding tasks, while SEA-HELM tests Indonesian alongside other Southeast Asian languages and adds generative, cultural and safety tasks.

Verified 2026-09-24