몇 개의 토큰을 더 생성하면 다음과 같은 출력을 볼 수 있습니다. 노래를 만들기 시작하고 있지
만, 꽤 빠르게 의미 없는 말로 변합니다
inthetownofathyonemyheart
wastheyweretheareflections
onmeallthefrivolity;
ofmeandmeandmeandthe
therewasmyheartwas
ontheaoverthefrivolity;
‘
sweet
Jeremy
saw
Dublin
’의 경우
80
% 확률로 ‘
she
’를 예측합니다. 이어서 몇 개의 단어를
예측한 결과는 다음과 같습니다.
sweet jeremy saw dublin she of his on the frivolity; of a heart is the ground
조금 나아 보이는군요! 하지만 더 개선할 수 있을까요?
8.5
모델 구조 개선하기
모델을 향상할 수 있는 한 가지 방법은 여러 개의
LSTM
층과 다른 최적화 기법을 사용해 구조
를 개선하는 것입니다. 이와 같은 데이터셋에서는 정확도에 대한 명확한 벤치마크가 없습니다
(올바르거나 잘못된 것을 분류하는 작업이 아니고 타깃을 가진 회귀도 아닙니다). 따라서 모
델이 좋은지 나쁜지 판단하기 어려우며 정확도 결과는 매우 주관적일
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