---
language: 
- ind
pretty_name: Indo4B
task_categories: 
- self-supervised-pretraining
tags: 
- self-supervised-pretraining
---

Indo4B is a large-scale Indonesian self-supervised pre-training corpus
consists of around 3.6B words, with around 250M sentences. The corpus
covers both formal and colloquial Indonesian sentences compiled from 
12 sources, of which two cover Indonesian colloquial language, eight
cover formal Indonesian language, and the rest have a mixed style of
both colloquial and formal.


## Languages

ind

## Supported Tasks

Self Supervised Pretraining

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/indo4b", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("indo4b", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("indo4b"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://github.com/IndoNLP/indonlu](https://github.com/IndoNLP/indonlu)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

CC0

## Citation

If you are using the **Indo4B** dataloader in your work, please cite the following:
```
@inproceedings{wilie-etal-2020-indonlu,
        title = "{I}ndo{NLU}: Benchmark and Resources for Evaluating {I}ndonesian 
            Natural Language Understanding",
        author = "Wilie, Bryan  and
          Vincentio, Karissa  and
          Winata, Genta Indra  and
          Cahyawijaya, Samuel  and
          Li, Xiaohong  and
          Lim, Zhi Yuan  and
          Soleman, Sidik  and
          Mahendra, Rahmad  and
          Fung, Pascale  and
          Bahar, Syafri  and
          Purwarianti, Ayu",
        booktitle = "Proceedings of the 1st Conference of the Asia-Pacific Chapter of the 
                Association for Computational Linguistics and the 10th International Joint 
                Conference on Natural Language Processing",
        month = dec,
        year = "2020",
        address = "Suzhou, China",
        publisher = "Association for Computational Linguistics",
        url = "https://aclanthology.org/2020.aacl-main.85",
        pages = "843--857",
        abstract = "Although Indonesian is known to be the fourth most frequently used language 
            over the internet, the research progress on this language in natural language processing (NLP) 
            is slow-moving due to a lack of available resources. In response, we introduce the first-ever vast 
            resource for training, evaluation, and benchmarking on Indonesian natural language understanding 
            (IndoNLU) tasks. IndoNLU includes twelve tasks, ranging from single sentence classification to 
            pair-sentences sequence labeling with different levels of complexity. The datasets for the tasks 
            lie in different domains and styles to ensure task diversity. We also provide a set of Indonesian 
            pre-trained models (IndoBERT) trained from a large and clean Indonesian dataset (Indo4B) collected 
            from publicly available sources such as social media texts, blogs, news, and websites. 
            We release baseline models for all twelve tasks, as well as the framework for benchmark evaluation, 
            thus enabling everyone to benchmark their system performances.",
    }


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```