  In this paper, we compare automated metrical pattern identification systems
available for Spanish against extensive experiments done by fine-tuning
language models trained on the same task. Despite being initially conceived as
a model suitable for semantic tasks, our results suggest that BERT-based models
retain enough structural information to perform reasonably well for Spanish
scansion.
