---
license: unknown
language: 
- vie
pretty_name: Uit Vion
task_categories: 
- topic-modeling
tags: 
- topic-modeling
---

UIT-ViON (Vietnamese Online Newspaper) is a dataset collected from well-known online newspapers in Vietnamese.
The UIT-ViON is an open-domain, large-scale, and high-quality dataset consisting of 260,000 textual data
points annotated with 13 different categories for evaluating Vietnamese short text classification.
The dataset is split into training, validation, and test sets, each containing 208000, 26000,
and 26000 pieces of text, respectively.


## Languages

vie

## Supported Tasks

Topic Modeling

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/uit_vion", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("uit_vion", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("uit_vion"))
# 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/kh4nh12/UIT-ViON-Dataset](https://github.com/kh4nh12/UIT-ViON-Dataset)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

Unknown (unknown)

## Citation

If you are using the **Uit Vion** dataloader in your work, please cite the following:
```
@inproceedings{fujita2021empirical,
  title={An Empirical Investigation of Online News Classification on an Open-Domain, Large-Scale and High-Quality Dataset in Vietnamese},
  author={Fujita, H and Perez-Meana, H},
  booktitle={New Trends in Intelligent Software Methodologies, Tools and Techniques: Proceedings of the 20th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques (SoMeT_21)},
  volume={337},
  pages={367},
  year={2021},
  organization={IOS Press}
}


@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}
}

```