  This paper presents RigoBERTa, a State-of-the-Art Language Model for Spanish.
RigoBERTa is trained over a well-curated corpus formed up from different
subcorpora with key features. It follows the DeBERTa architecture, which has
several advantages over other architectures of similar size as BERT or RoBERTa.
RigoBERTa performance is assessed over 13 NLU tasks in comparison with other
available Spanish language models, namely, MarIA, BERTIN and BETO. RigoBERTa
outperformed the three models in 10 out of the 13 tasks, achieving new
"State-of-the-Art" results.
