TrelBERT: A pre-trained encoder for Polish Twitter
Wojciech Szmyd, Alicja Kotyla, Michał Zobniów, Piotr Falkiewicz, Jakub Bartczuk, Artur Zygadło
Abstract
Pre-trained Transformer-based models have become immensely popular amongst NLP practitioners. We present TrelBERT – the first Polish language model suited for application in the social media domain. TrelBERT is based on an existing general-domain model and adapted to the language of social media by pre-training it further on a large collection of Twitter data. We demonstrate its usefulness by evaluating it in the downstream task of cyberbullying detection, in which it achieves state-of-the-art results, outperforming larger monolingual models trained on general-domain corpora, as well as multilingual in-domain models, by a large margin. We make the model publicly available. We also release a new dataset for the problem of harmful speech detection.- Anthology ID:
- 2023.bsnlp-1.3
- Volume:
- Proceedings of the 9th Workshop on Slavic Natural Language Processing 2023 (SlavicNLP 2023)
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Venue:
- BSNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 17–24
- Language:
- URL:
- https://aclanthology.org/2023.bsnlp-1.3
- DOI:
- Cite (ACL):
- Wojciech Szmyd, Alicja Kotyla, Michał Zobniów, Piotr Falkiewicz, Jakub Bartczuk, and Artur Zygadło. 2023. TrelBERT: A pre-trained encoder for Polish Twitter. In Proceedings of the 9th Workshop on Slavic Natural Language Processing 2023 (SlavicNLP 2023), pages 17–24, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- TrelBERT: A pre-trained encoder for Polish Twitter (Szmyd et al., BSNLP 2023)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/2023.bsnlp-1.3.pdf