MEL: Legal Spanish Language Model

David Betancur Sánchez; Nuria Aldama García; Álvaro Barbero Jiménez; Marta Guerrero Nieto; Patricia Marsà Morales; Nicolás Serrano Salas; Carlos García Hernán; Pablo Haya Coll; Elena Montiel Ponsoda; Pablo Calleja Ibáñez

arXiv · 2501.16011

MEL: Legal Spanish Language Model

David Betancur Sánchez·Nuria Aldama García·Álvaro Barbero Jiménez·Marta Guerrero Nieto·Patricia Marsà Morales·Nicolás Serrano Salas·Carlos García Hernán·Pablo Haya Coll·Elena Montiel Ponsoda·Pablo Calleja Ibáñez

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Abstract

Legal texts, characterized by complex and specialized terminology, present a significant challenge for Language Models. Adding an underrepresented language, such as Spanish, to the mix makes it even more challenging. While pre-trained models like XLM-RoBERTa have shown capabilities in handling multilingual corpora, their performance on domain specific documents remains underexplored. This paper presents the development and evaluation of MEL, a legal language model based on XLM-RoBERTa-large, fine-tuned on legal documents such as BOE (Bolet\'in Oficial del Estado, the Spanish oficial report of laws) and congress texts. We detail the data collection, processing, training, and evaluation processes. Evaluation benchmarks show a significant improvement over baseline models in understanding the legal Spanish language. We also present case studies demonstrating the model's application to new legal texts, highlighting its potential to perform top results over different NLP tasks.

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David Betancur Sánchez, Nuria Aldama García, Álvaro Barbero Jiménez, Marta Guerrero Nieto, Patricia Marsà Morales, Nicolás Serrano Salas, Carlos García Hernán, Pablo Haya Coll, Elena Montiel Ponsoda, Pablo Calleja Ibáñez. 2025-01-27. MEL: Legal Spanish Language Model. https://arxiv.org/abs/2501.16011

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