metadata
language: eu
license: cc-by-nc-4.0
tags:
- basque
- roberta
Roberta-eus Euscrawl large cased
This is a RoBERTa model for Basque model presented in Does corpus quality really matter for low-resource languages?. There are several models for Basque using the RoBERTa architecture, using different corpora:
- roberta-eus-euscrawl-base-cased: Basque RoBERTa model trained on Euscrawl, a corpus created using tailored crawling from Basque sites. EusCrawl contains 12,528k documents and 423M tokens.
- roberta-eus-euscrawl-large-cased: RoBERTa large trained on EusCrawl.
- roberta-eus-mC4-base-cased: Basque RoBERTa model trained on the Basque portion of mc4 dataset.
- roberta-eus-CC100-base-cased: Basque RoBERTa model trained on Basque portion of cc100 dataset.
The models have been tested on five different downstream tasks for Basque: Topic classification, Sentiment analysis, Stance detection, Named Entity Recognition (NER), and Question Answering (refer to the paper for more details). See summary of results below:
| Model | Topic class. | Sentiment | Stance det. | NER | QA | Average |
|---|---|---|---|---|---|---|
| roberta-eus-euscrawl-base-cased | 76.2 | 77.7 | 57.4 | 86.8 | 34.6 | 66.5 |
| roberta-eus-euscrawl-large-cased | 77.6 | 78.8 | 62.9 | 87.2 | 38.3 | 69.0 |
| roberta-eus-mC4-base-cased | 75.3 | 80.4 | 59.1 | 86.0 | 35.2 | 67.2 |
| roberta-eus-CC100-base-cased | 76.2 | 78.8 | 63.4 | 85.2 | 35.8 | 67.9 |
If you use any of these models, please cite the following paper:
@misc{artetxe2022euscrawl,
title={Does corpus quality really matter for low-resource languages?},
author={Mikel Artetxe, Itziar Aldabe, Rodrigo Agerri,
Olatz Perez-de-Viñaspre, Aitor Soroa},
year={2022},
eprint={2203.08111},
archivePrefix={arXiv},
primaryClass={cs.CL}
}