Assessing the Efficiency of Transformer Models with Varying Sizes for Text Classification: A Study of Rule-Based Annotation with DistilBERT and Other Transformers

This study presents a comparative analysis of transformer models for text classification, utilizing a hybrid approach that integrates rule-based regular expressions with fine-tuned neural network models. Initially, regular expressions are employed to annotate sentences in a cost-effective manner, pr...

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Detalhes bibliográficos

Principais autores:	Arafet Sbei, Khaoula ElBedoui, Walid Barhoumi
Formato:	Artigo
Idioma:	Inglês
Publicado em:	World Scientific Publishing 2025-08-01
coleção:	Vietnam Journal of Computer Science
Assuntos:	Data annotation rule-based methods transformers hybrid labeling text classification
Acesso em linha:	https://www.worldscientific.com/doi/10.1142/S2196888824500209
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