datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
indonluThe IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia.fixed_indonlu
Dataset Card for IndoNLU
Dataset Summary
The IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia (Indonesian language).
There are 12 datasets in IndoNLU benchmark for Indonesian natural language understanding.
EmoT: An emotion classification dataset collected from the social media platform Twitter. The dataset consists of around 4000 Indonesian colloquial language… See the full description on the dataset page: https://huggingface.co/datasets/will702/fixed_indonlu.indonlu_nergritThis NER dataset is taken from the Grit-ID repository, and the labels are spans in IOB chunking representation.
The dataset consists of three kinds of named entity tags, PERSON (name of person), PLACE (name of location), and
ORGANIZATION (name of organization).indonlu-eval-gpt4o-vs-sealionv3-round1
Local vs Global: Testing GPT-4o-mini and SEA-LIONv3 on Bahasa Indonesia
A benchmark dataset comparing GPT-4o-mini and SEA-LIONv3 on 50 Indonesian-specific questions.This is Round 1 of the INDONLU Eval series, which was built to test LLM performance on culturally grounded, linguistically diverse Southeast Asian prompts.
Overview
We tested 50 prompts across four core categories to assess how well large language models can handle local Indonesian context:
Language –… See the full description on the dataset page: https://huggingface.co/datasets/Chemin-AI/indonlu-eval-gpt4o-vs-sealionv3-round1.indonlu-wreteindonluThe IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia.indonlu-eval-sealionv3-vs-sahabataiv1-round2
Benchmarking Bahasa Indonesia LLMs: SEA-LIONv3 vs SahabatAI-v1
Following our first benchmarking round, this dataset compares SEA-LIONv3 and SahabatAI-v1 on 50 carefully crafted Indonesian-language tasks. Both models are regionally fine-tuned for Southeast Asian content and evaluated on linguistic fluency, domain-specific accuracy, geographic knowledge, and cultural reasoning.
This is Round 2 of SUPA AI's INDONLU Eval series, which aims to benchmark LLMs for Southeast Asia in… See the full description on the dataset page: https://huggingface.co/datasets/Chemin-AI/indonlu-eval-sealionv3-vs-sahabataiv1-round2.indo-nlu-entailmen
Dataset Card for "indo-nlu-entailmen"
More Information needed
emotion_analysis_indonlu_benchmarkIndoNLU-migrateindonluThe IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia.indonluThe IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia.