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Exploring Transformers in Emotion Recognition: a comparison of BERT, DistillBERT, RoBERTa, XLNet and ELECTRA

2021/04/05 by Cortiz, Diogo · 1 citation
#Computation and Language (cs.CL) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.2104.02041

Abstract

This paper investigates how Natural Language Understanding (NLU) could be applied in Emotion Recognition, a specific task in affective computing. We finetuned different transformers language models (BERT, DistilBERT, RoBERTa, XLNet, and ELECTRA) using a fine-grained emotion dataset and evaluating them in terms of performance (f1-score) and time to complete.

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