PeLLE: Encoder-based language models for Brazilian Portuguese based on open data

• URL: http://arxiv.org/abs/2402.19204v1
• Date: Thu, 29 Feb 2024 14:34:03 GMT
• Title: PeLLE: Encoder-based language models for Brazilian Portuguese based on open data
• Authors: Guilherme Lamartine de Mello and Marcelo Finger and and Felipe Serras and Miguel de Mello Carpi and Marcos Menon Jose and Pedro Henrique Domingues and Paulo Cavalim
• Abstract summary: We present PeLLE, a family of large language models based on the RoBERTa architecture, for Brazilian Portuguese, trained on curated, open data from the Carolina corpus. We evaluate PeLLE models against a set of existing multilingual and PT-BR refined pretrained Transformer-based LLM encoders, contrasting performance of large versus smaller-but-curated pretrained models in several downstream tasks.
• Score: 0.40485107444088947
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper we present PeLLE, a family of large language models based on the RoBERTa architecture, for Brazilian Portuguese, trained on curated, open data from the Carolina corpus. Aiming at reproducible results, we describe details of the pretraining of the models. We also evaluate PeLLE models against a set of existing multilingual and PT-BR refined pretrained Transformer-based LLM encoders, contrasting performance of large versus smaller-but-curated pretrained models in several downstream tasks. We conclude that several tasks perform better with larger models, but some tasks benefit from smaller-but-curated data in its pretraining.

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