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metadata
language:
  - es
license: apache-2.0
tags:
  - national library of spain
  - spanish
  - bne
  - capitel
  - ner
datasets:
  - bne
  - capitel
metrics:
  - f1
inference:
  parameters:
    aggregation_strategy: first

Spanish RoBERTa-large trained on BNE finetuned for CAPITEL Named Entity Recognition (NER) dataset.

RoBERTa-large-bne is a transformer-based masked language model for the Spanish language. It is based on the RoBERTa large model and has been pre-trained using the largest Spanish corpus known to date, with a total of 570GB of clean and deduplicated text processed for this work, compiled from the web crawlings performed by the National Library of Spain (Biblioteca Nacional de España) from 2009 to 2019.

Original pre-trained model can be found here: https://huggingface.co/BSC-TeMU/roberta-large-bne

Dataset

The dataset used is the one from the CAPITEL competition at IberLEF 2020 (sub-task 1).

Evaluation and results

F1 Score: 0.8998

For evaluation details visit our GitHub repository.

Citing

Check out our paper for all the details: https://arxiv.org/abs/2107.07253

@article{gutierrezfandino2022,
    author = {Asier Gutiérrez-Fandiño and Jordi Armengol-Estapé and Marc Pàmies and Joan Llop-Palao and Joaquin Silveira-Ocampo and Casimiro Pio Carrino and Carme Armentano-Oller and Carlos Rodriguez-Penagos and Aitor Gonzalez-Agirre and Marta Villegas},
    title = {MarIA: Spanish Language Models},
    journal = {Procesamiento del Lenguaje Natural},
    volume = {68},
    number = {0},
    year = {2022},
    issn = {1989-7553},
    url = {http://journal.sepln.org/sepln/ojs/ojs/index.php/pln/article/view/6405},
    pages = {39--60}
}

Funding

This work was partially funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL, and the Future of Computing Center, a Barcelona Supercomputing Center and IBM initiative (2020).

Disclaimer

The models published in this repository are intended for a generalist purpose and are available to third parties. These models may have bias and/or any other undesirable distortions.

When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of artificial intelligence.

In no event shall the owner of the models (SEDIA – State Secretariat for digitalization and artificial intelligence) nor the creator (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.

Los modelos publicados en este repositorio tienen una finalidad generalista y están a disposición de terceros. Estos modelos pueden tener sesgos y/u otro tipo de distorsiones indeseables.

Cuando terceros desplieguen o proporcionen sistemas y/o servicios a otras partes usando alguno de estos modelos (o utilizando sistemas basados en estos modelos) o se conviertan en usuarios de los modelos, deben tener en cuenta que es su responsabilidad mitigar los riesgos derivados de su uso y, en todo caso, cumplir con la normativa aplicable, incluyendo la normativa en materia de uso de inteligencia artificial.

En ningún caso el propietario de los modelos (SEDIA – Secretaría de Estado de Digitalización e Inteligencia Artificial) ni el creador (BSC – Barcelona Supercomputing Center) serán responsables de los resultados derivados del uso que hagan terceros de estos modelos.