PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese

TL;DR

This paper introduces PORTULAN ExtraGLUE, a comprehensive benchmark with datasets and models for Portuguese language processing, aiming to facilitate future research and development in neural NLP for Portuguese.

Contribution

It provides the first Portuguese-specific benchmark and baseline models, created by translating English datasets and fine-tuning neural models with low-rank adaptation.

Findings

Datasets cover multiple language tasks for Portuguese.

Fine-tuned models serve as baselines for future research.

Resources are available for both European and Brazilian Portuguese.

Abstract

Leveraging research on the neural modelling of Portuguese, we contribute a collection of datasets for an array of language processing tasks and a corresponding collection of fine-tuned neural language models on these downstream tasks. To align with mainstream benchmarks in the literature, originally developed in English, and to kick start their Portuguese counterparts, the datasets were machine-translated from English with a state-of-the-art translation engine. The resulting PORTULAN ExtraGLUE benchmark is a basis for research on Portuguese whose improvement can be pursued in future work. Similarly, the respective fine-tuned neural language models, developed with a low-rank adaptation approach, are made available as baselines that can stimulate future work on the neural processing of Portuguese. All datasets and models have been developed and are made available for two variants of Portuguese: European and Brazilian.