Spanish Language Models.
Year: 2021
Type: preprint
Abstract: This paper presents the Spanish RoBERTa-base and RoBERTa-large models, as well as the corresponding performance evaluations. Both models were 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 from 2009 to 2019. We extended the current evaluation datasets with an extractive Question Answering dataset and our models outperform the existing Spanish models across tasks and settings.
Source: arXiv (Cornell University)
Institution: Barcelona Supercomputing Center
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3180918883