RobBERT: a Dutch RoBERTa-based Language Model

Pieter Delobelle, Thomas Winters, Bettina Berendt


Abstract
Pre-trained language models have been dominating the field of natural language processing in recent years, and have led to significant performance gains for various complex natural language tasks. One of the most prominent pre-trained language models is BERT, which was released as an English as well as a multilingual version. Although multilingual BERT performs well on many tasks, recent studies show that BERT models trained on a single language significantly outperform the multilingual version. Training a Dutch BERT model thus has a lot of potential for a wide range of Dutch NLP tasks. While previous approaches have used earlier implementations of BERT to train a Dutch version of BERT, we used RoBERTa, a robustly optimized BERT approach, to train a Dutch language model called RobBERT. We measured its performance on various tasks as well as the importance of the fine-tuning dataset size. We also evaluated the importance of language-specific tokenizers and the model’s fairness. We found that RobBERT improves state-of-the-art results for various tasks, and especially significantly outperforms other models when dealing with smaller datasets. These results indicate that it is a powerful pre-trained model for a large variety of Dutch language tasks. The pre-trained and fine-tuned models are publicly available to support further downstream Dutch NLP applications.
Anthology ID:
2020.findings-emnlp.292
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Editors:
Trevor Cohn, Yulan He, Yang Liu
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3255–3265
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.292
DOI:
10.18653/v1/2020.findings-emnlp.292
Bibkey:
Cite (ACL):
Pieter Delobelle, Thomas Winters, and Bettina Berendt. 2020. RobBERT: a Dutch RoBERTa-based Language Model. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 3255–3265, Online. Association for Computational Linguistics.
Cite (Informal):
RobBERT: a Dutch RoBERTa-based Language Model (Delobelle et al., Findings 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/landing_page/2020.findings-emnlp.292.pdf
Code
 iPieter/RobBERT
Data
CoNLL 2002DBRD