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Machine learningDeep learning / NLP / CV

Transfer Learning med BERT-baseret Klassifikation

Transfer Learning med BERT-baseret Klassifikation tilpasser en stor transformer-sprogmodel, der er forhåndstrænet på massive tekstkorpora, til en specifik klassifikationsopgave ved at finjustere dens vægte på mærkede eksempler. De forhåndstrænede repræsentationer koder rig syntaktisk og semantisk viden, hvilket muliggør høj nøjagtighed, selv når det mærkede datasæt er lille.

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Kilder

  1. Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of NAACL-HLT 2019, 4171–4186. Association for Computational Linguistics. DOI: 10.18653/v1/N19-1423
  2. Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. DOI: 10.1109/TKDE.2009.191

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ScholarGate. (2026, June 3). Transfer Learning with BERT-based Text Classification. ScholarGate. https://scholargate.app/da/deep-learning/transfer-learning-with-bert-based-classification

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ScholarGateTransfer Learning with BERT-based Classification (Transfer Learning with BERT-based Text Classification). Hentet 2026-06-15 fra https://scholargate.app/da/deep-learning/transfer-learning-with-bert-based-classification · Datasæt: https://doi.org/10.5281/zenodo.20539026