BERTabaporu: Assessing a Genre-specific Language Model for Portuguese NLP
Pablo da Costa, Matheus Camasmie Pavan, Wesley dos Santos, Samuel da 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.
Topics & Concepts
Computer scienceNatural language processingTransformerLanguage modelArtificial intelligencePortugueseEncoderLinguisticsEngineeringVoltageElectrical engineeringOperating systemPhilosophyTopic ModelingNatural Language Processing TechniquesSentiment Analysis and Opinion Mining