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Machine learningDeep learning / NLP / CV

Ujifunzaji wa Kuimarisha Uliosafishwa (Fine-Tuned Reinforcement Learning)

Ujifunzaji wa Kuimarisha Uliosafishwa hubadilisha sera au mfumo uliopatiwa mafunzo ya awali ili kuendana na kazi mpya au lengo la kitabia kwa kutumia ishara za uimarishaji — ikiwemo maoni ya binadamu — badala ya kutoa mafunzo upya kuanzia mwanzo. Umejulikana sana kupitia RLHF, na ni mbinu kuu inayotumika kuoanisha mifumo mikuu ya lugha na kurekebisha mawakala wa RL ya kina kwa mazingira maalum kwa kutumia data ndogo ya ziada.

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Ujifunzaji wa Kuimarisha Uliosafishwa (Fine-Tuned Reinforcement Learning)
Uainishaji wa BERT Uliob…Transformer IliyoboreshwaJifunze kwa Kuimarisha (…Ujifunzaji wa Uimarishaj…Kujifunza kwa Kuhamisha…Jifunze za Lugha Nyingi

Vyanzo

  1. Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., Schulman, J., Hilton, J., Kelton, F., Miller, L., Simens, M., Askell, A., Welinder, P., Christiano, P., Leike, J., & Lowe, R. (2022). Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, 35, 27730–27744. link ↗
  2. Christiano, P., Leike, J., Brown, T. B., Martic, M., Legg, S., & Amodei, D. (2017). Deep reinforcement learning from human preferences. Advances in Neural Information Processing Systems, 30. link ↗

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Fine-Tuned Reinforcement Learning (Policy Adaptation via Fine-Tuning). ScholarGate. https://scholargate.app/sw/deep-learning/fine-tuned-reinforcement-learning

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Imerejelewa na

Jifunze za Lugha NyingiKujifunza kwa Kuhamisha kwa Kutumia Kujifunza kwa Uimarishaji

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ScholarGate — Fine-Tuned Reinforcement Learning (Fine-Tuned Reinforcement Learning (Policy Adaptation via Fine-Tuning)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/fine-tuned-reinforcement-learning · Seti ya data: https://doi.org/10.5281/zenodo.20539026