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--- |
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language: |
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- om |
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- am |
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- rw |
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- rn |
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- ha |
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- ig |
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- pcm |
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- so |
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- sw |
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- ti |
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- yo |
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- multilingual |
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license: "Apache License 2.0" |
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task_categories: |
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- sequence-modeling |
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task_ids: |
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- language-modeling |
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--- |
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# Dataset Card for AfriBERTa's Corpus |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Loading Dataset](#loading-dataset) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Additional Information](#additional-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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### Dataset Summary |
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This is the corpus on which AfriBERTa was trained on. |
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The dataset is mostly from the BBC news website, but some languages also have data from Common Crawl. |
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- **Homepage:** https://github.com/keleog/afriberta |
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- **Models:** |
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- https://huggingface.co/castorini/afriberta_small |
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- https://huggingface.co/castorini/afriberta_base |
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- https://huggingface.co/castorini/afriberta_large |
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- **Paper:** https://aclanthology.org/2021.mrl-1.11/ |
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- **Point of Contact:** kelechi.ogueji@uwaterloo.ca |
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### Supported Tasks and Leaderboards |
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The AfriBERTa corpus was mostly intended to pre-train language models. |
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### Languages |
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``` |
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afaanoromoo |
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amharic |
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gahuza |
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hausa |
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igbo |
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pidgin |
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somali |
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swahili |
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tigrinya |
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yoruba |
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``` |
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### Loading Dataset |
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An example to load the train split of the Somali corpus: |
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``` |
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dataset = load_dataset("castorini/afriberta-corpus", "somali", split="train") |
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``` |
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An example to load the test split of the Pidgin corpus: |
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``` |
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dataset = load_dataset("castorini/afriberta-corpus", "pidgin", split="test") |
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``` |
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## Dataset Structure |
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### Data Instances |
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Each data point is a line of text. |
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An example from the `igbo` dataset: |
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``` |
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{"id": "6", "text": "Ngwá ọrụ na-echebe ma na-ebuli gị na kọmputa."} |
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``` |
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### Data Fields |
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The data fields are: |
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- id: id of the example |
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- text: content as a string |
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### Data Splits |
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Each language has a train and test split, with varying sizes. |
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## Considerations for Using the Data |
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### Discussion of Biases |
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Since majority of the data is obtained from the BBC's news website, models trained on this dataset are likely going to |
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be biased towards the news domain. |
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Also, since some of the data is obtained from Common Crawl, care should be taken (especially for text generation models) since personal and sensitive information might be present. |
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## Additional Information |
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### Citation Information |
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``` |
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@inproceedings{ogueji-etal-2021-small, |
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title = "Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages", |
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author = "Ogueji, Kelechi and |
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Zhu, Yuxin and |
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Lin, Jimmy", |
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booktitle = "Proceedings of the 1st Workshop on Multilingual Representation Learning", |
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month = nov, |
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year = "2021", |
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address = "Punta Cana, Dominican Republic", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2021.mrl-1.11", |
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pages = "116--126", |
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} |
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``` |
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### Contributions |
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Thanks to [Kelechi Ogueji](https://github.com/keleog) for adding this dataset. |
