The effect of transfer learning on Turkish text classification Transfer öǧrenmenin Türkçe metin siniflandirma üzerindeki etkisi

ŞAHİN G., DİRİ B.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Türkiye, 9 - 11 Haziran 2021 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu53274.2021.9477910
  • Basıldığı Şehir: Virtual, Istanbul
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: text classification, deep learning, transfer learning, transformers, bert
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.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.