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MarIA: Modelos del Lenguaje en Español

  • Autores: Aitor González Agirre, Marta Villegas Montserrat Árbol académico, Asier Gutiérrez Fandiño, Jordi Armengol Estapé, Marc Pàmies, Joan Llop Palao, Joaquín Silveira Ocampo, Casimiro Pio Carrino, Carme Armentano i Oller, Carlos Rodríguez Penagos
  • Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 68, 2022, págs. 39-60
  • Idioma: español
  • Títulos paralelos:
    • MarIA:: Spanish Language Models
  • Enlaces
  • Resumen
    • español

      En este artículo se presenta MarIA, una familia de modelos del lenguaje en español y sus correspondientes recursos que se hacen públicos para la industria y la comunidad científica. Actualmente, MarIA incluye los modelos del lenguaje en español RoBERTa-base, RoBERTa-large, GPT2 y GPT2-large, que pueden considerarse como los modelos más grandes y mejores para español. Los modelos han sido preentrenados utilizando un corpus masivo de 570 GB de textos limpios y deduplicados, que comprende un total de 135 mil millones de palabras extraídas del Archivo Web del Español construido por la Biblioteca Nacional de España entre los años 2009 y 2019. Evaluamos el rendimiento de los modelos con nueve conjuntos de datos existentes y con un nuevo conjunto de datos de pregunta-respuesta extractivo creado ex novo. El conjunto de modelos de MarIA supera, en la práctica totalidad, el rendimiento de los modelos existentes en español en las diferentes tareas y configuraciones presentadas.

    • English

      This work presents MarIA, a family of Spanish language models and associated resources made available to the industry and the research community. Currently, MarIA includes RoBERTa-base, RoBERTa-large, GPT2 and GPT2-large Spanish language models, which can arguably be presented as the largest and most proficient language models in Spanish. The models were pretrained using a massive corpus of 570GB of clean and deduplicated texts with 135 billion words extracted from the Spanish Web Archive crawled by the National Library of Spain between 2009 and 2019. We assessed the performance of the models with nine existing evaluation datasets and with a novel extractive Question Answering dataset created ex novo. Overall, MarIA models outperform the existing Spanish models across a variety of NLU tasks and training settings.

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