Machine learningDeep learning / NLP / CV

Polunadgledana klasifikacija zasnovana na RoBERTa modelu

Polunadgledana klasifikacija zasnovana na RoBERTa modelu kombinuje veliki unapred trenirani jezički model RoBERTa sa malim obeleženim skupom podataka i većim skupom neobeleženog teksta. Generisanjem pseudo-oznaka ili nametanjem konzistentnosti na neobeleženim primerima, metoda izvlači nadzorni signal iz neanotiranih podataka, dajući jače klasifikatore kada su anotacije stvarne istine retke.

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Izvori

  1. Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach. arXiv preprint arXiv:1907.11692. link
  2. Xie, Q., Dai, Z., Hovy, E., Luong, M.-T., & Le, Q. V. (2020). Unsupervised Data Augmentation for Consistency Training. Advances in Neural Information Processing Systems (NeurIPS), 33, 11904–11915. link

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Semi-supervised RoBERTa-based Text Classification. ScholarGate. https://scholargate.app/sr/deep-learning/semi-supervised-roberta-based-classification

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Citirana u

ScholarGateSemi-supervised RoBERTa-based Classification (Semi-supervised RoBERTa-based Text Classification). Preuzeto 2026-06-15 sa https://scholargate.app/sr/deep-learning/semi-supervised-roberta-based-classification · Skup podataka: https://doi.org/10.5281/zenodo.20539026