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train: 모델 학습 방법 탐색 #13

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nestiank opened this issue May 20, 2022 · 1 comment
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train: 모델 학습 방법 탐색 #13

nestiank opened this issue May 20, 2022 · 1 comment
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modeling Training and testing the AI model
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@nestiank
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nestiank commented May 20, 2022

담당자: 김주영

학습을 제외한 모델 성능 개선은 #25 를 통해서 진행함

데이터셋 마련은 #35 를 통해서 진행함

V100 GPU 서버에는 메모리 이슈와 디스크 용량 이슈가 있다.
Federated learning 등을 고려한다.

  • 서버의 한계를 고려하여 성능을 향상시킬 수 있는 모델 학습 방법을 탐색하기

Decided by #20

@nestiank nestiank added the development Initial development of a core feature label May 20, 2022
@nestiank nestiank added this to the First Step milestone May 20, 2022
@nestiank nestiank added this to To do in 내일의집 via automation May 20, 2022
@nestiank nestiank self-assigned this May 20, 2022
@nestiank nestiank added modeling Training and testing the AI model and removed development Initial development of a core feature labels May 20, 2022
@nestiank nestiank moved this from To do to In progress in 내일의집 May 20, 2022
@nestiank nestiank moved this from In progress: long-term to To do in 내일의집 May 20, 2022
@nestiank nestiank moved this from To do to To do: modeling in 내일의집 May 24, 2022
@nestiank nestiank modified the milestones: First Step, Second Step May 24, 2022
@nestiank nestiank moved this from To do: modeling to In progress: long-term in 내일의집 May 25, 2022
@nestiank nestiank moved this from In progress: long-term to To do in 내일의집 May 25, 2022
@nestiank
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데이터셋을 구축하는 #35 의 결과가 좋지 못했고, 남은 프로젝트 기간과, 모델의 긴 학습 시간을 고려하면, 공개 데이터셋을 가공하고 학습에 사용하는 것이 현실적으로 불가능하게 되었으므로, 학습은 하지 않기로 결정했습니다.

내일의집 automation moved this from To do to Done May 30, 2022
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