BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP
Pablo Botton Costa, Matheus Camasmie Pavan, Wesley Ramos Santos, Samuel Caetano Silva, Ivandré Paraboni
Abstract
Transformer-based language models such as Bidirectional Encoder Representations from Transformers (BERT) are now mainstream in the NLP field, but extensions to languages other than English, to new domains and/or to more specific text genres are still in demand. In this paper we introduced BERTabaporu, a BERT language model that has been pre-trained on Twitter data in the Brazilian Portuguese language. The model is shown to outperform the best-known general-purpose model for this language in three Twitter-related NLP tasks, making a potentially useful resource for Portuguese NLP in general.- Anthology ID:
- 2023.ranlp-1.24
- Volume:
- Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
- Month:
- September
- Year:
- 2023
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd., Shoumen, Bulgaria
- Note:
- Pages:
- 217–223
- Language:
- URL:
- https://aclanthology.org/2023.ranlp-1.24
- DOI:
- Cite (ACL):
- Pablo Botton Costa, Matheus Camasmie Pavan, Wesley Ramos Santos, Samuel Caetano Silva, and Ivandré Paraboni. 2023. BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 217–223, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
- Cite (Informal):
- BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP (Costa et al., RANLP 2023)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2023.ranlp-1.24.pdf