# AfriBERTa's Corpus

## Summary
* [Introduction](#introduction)
* [Dataset Structure](#dataset_structure)
* [Reference](#reference)
* [License](#license)
* [Citation](#citation)

## Introduction

This is the corpus on which AfriBERTa was trained on. The dataset is mostly from the BBC news website, but some languages also have data from Common Crawl.

* Homepage: [Afriberta](https://github.com/keleog/afriberta)
* Models:
* [Afriberta Small](https://huggingface.co/castorini/afriberta_small)
* [Afriberta Base](https://huggingface.co/castorini/afriberta_base)
* [Afriberta Large](https://huggingface.co/castorini/afriberta_large)
* Paper: [Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages](https://aclanthology.org/2021.mrl-1.11/)
* Point of Contact: [e-mail]

## Dataset Structure
### Data Instances
Each data point is a line of text. An example from the igbo dataset:

{
    "id": "6", 
    "text": "Ngwá ọrụ na-echebe ma na-ebuli gị na kọmputa."
}

### Data Fields
The data fields are:

* `id`: id of the example
* `text`: content as a string

## Reference

We would like to acknowledge Ogueji, Kelechi et al. for creating and maintaining the AfriBERTa's Corpus dataset as a valuable resource for the computer vision and machine learning research community. For more information about the AfriBERTa's Corpus dataset and its creator, please visit [the AfriBERTa's Corpus website](https://github.com/keleog/afriberta).

## License

The dataset has been released under the Apache License 2.0.

## Citation

@inproceedings{ogueji-etal-2021-small,
    title = "Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages",
    author = "Ogueji, Kelechi  and
      Zhu, Yuxin  and
      Lin, Jimmy",
    booktitle = "Proceedings of the 1st Workshop on Multilingual Representation Learning",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.mrl-1.11",
    pages = "116--126",
}