Machine learningDeep learning / NLP / CV

Polu-nadgledana BERT-bazirana klasifikacija

Semi-supervised BERT-based klasifikacija doteruje (fine-tunes) prethodno obučeni BERT enkoder na malom skupu označenih tekstualnih primera, istovremeno koristeći mnogo veći skup neoznačenog teksta — putem obuke konzistencije, pseudo-označavanja ili augmentacije podataka — da bi se proizveli visokokvalitetni klasifikatori čak i kada je ručna anotacija oskudna.

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Izvori

  1. Xie, Q., Dai, Z., Hovy, E., Luong, T., & Le, Q. (2020). Unsupervised Data Augmentation for Consistency Training. Advances in Neural Information Processing Systems (NeurIPS), 33, 27780–27792. link
  2. Chen, J., Yang, Z., & Yang, D. (2020). MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), 2147–2157. DOI: 10.18653/v1/2020.acl-main.194

Kako citirati ovu stranicu

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

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Citirana u

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