The birth of Romanian BERT




Stefan Dumitrescu, Andrei-Marius Avram, Sampo Pyysalo

Trevor Cohn, Yulan He, Yang Liu

Empirical Methods in Natural Language Processing

2020

Annual Meeting of the Association for Computational Linguistics

Findings of the Association for Computational Linguistics: EMNLP 2020

4324

4328

978-1-952148-90-3

DOIhttps://doi.org/10.18653/v1/2020.findings-emnlp.387

https://www.aclweb.org/anthology/2020.findings-emnlp.387/

https://arxiv.org/abs/2009.08712



Large-scale pretrained language models have
become ubiquitous in Natural Language Processing. However, most of these
models are available either in high-resource languages, in particular
English, or as multilingual models that compromise performance on
individual languages for coverage. This paper introduces Romanian BERT,
the first purely Romanian transformer-based language model, pretrained
on a large text corpus. We discuss corpus com-position and cleaning, the
model training process, as well as an extensive evaluation of the model
on various Romanian datasets. We opensource not only the model itself,
but also a repository that contains information on how to obtain the
corpus, fine-tune and use this model in production (with practical
examples), and how to fully replicate the evaluation process.

Last updated on 2024-26-11 at 23:23