ScholarGate
Msaidizi
Machine learningDeep learning / NLP / CV

Transformer yenye usimamizi-nusu

Kujifunza kwa usimamizi-nusu kwa kutumia usanifu wa Transformer hutumia kiasi kikubwa cha data isiyo na lebo pamoja na seti ndogo yenye lebo ili kufunza miundo yenye nguvu ya mfuatano. Muundo mkuu — unaoonyeshwa na BERT — kwanza huandaa Transformer kwenye data isiyo na lebo kwa kutumia malengo ya kujisimamia kama vile utabiri wa tokeni iliyofichwa, kisha huiboresha kwa kazi yenye lebo. Mbinu hii ya hatua mbili hupunguza sana data yenye lebo inayohitajika ili kufikia utendaji mzuri.

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Vyanzo

  1. Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT 2019, 4171–4186. DOI: 10.18653/v1/N19-1423
  2. Zoph, B., Ghiasi, G., Lin, T.-Y., Cui, Y., Liu, H., Cubuk, E. D., & Le, Q. V. (2020). Rethinking Pre-training and Self-training. Advances in Neural Information Processing Systems (NeurIPS), 33, 3833–3845. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Semi-supervised Learning with Transformer Architectures. ScholarGate. https://scholargate.app/sw/deep-learning/semi-supervised-transformer

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Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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Imerejelewa na

ScholarGateSemi-supervised Transformer (Semi-supervised Learning with Transformer Architectures). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/semi-supervised-transformer · Seti ya data: https://doi.org/10.5281/zenodo.20539026