Meet XLM-RLnews-8: Not Just Another Sentiment Analysis Model

Elisa Di Nuovo, Emmanuel Cartier, Bertrand De Longueville

Abstract: Although automatic sentiment analysis has been widely studied in the past decade, multilingualism remains an issue impairing real-life applications. This paper describes the development and evaluation of XLM-RLnews-8, a model based on XLM-RoBERTa-Large, domain-adapted using a novel dataset of multilingual news articles and fine-tuned for the tripartite sentiment analysis task. In addition, it provides a quantitative analysis of the Unified Multilingual Sentiment Analysis Benchmark, the dataset used for the fine-tuning and the in-domain evaluation. The model is also out-of-domain evaluated, on the IMDb dataset and a new multilingual news headlines silver dataset, and its performance is compared with current State-of-the-Art multilingual models. Models, notebooks and datasets developed for this publication are available at https://github.com/ElisaDiNuovo/XLM-RLnews-8/.

External IDs:doi:10.1007/978-3-031-70242-6_3