The Effect of Transfer Learning on Turkish Text Classification

Abstract

Text classification is one of the most important issues in natural language processing. In this study, texts belonging to different problems were classified using classical machine learning and deep learning methods. Additionally, transformer-based classifiers using transfer learning were also used, and the effects of transfer learning on classification success were examined. As a result of the experiments, it was seen that higher performance was obtained from the transfer learning based Bert classifier compared to other methods. With the study, transfer learning effect in Turkish text classification was examined in detail.