hw-llama-2-7B-nsmc

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llama2-7b모델 미세튜닝

네이버 영화 리뷰텍스트(NSMC)데이터셋을 프롬포트에 포함하여 모델에 입력하면 "긍정" 또는 "부정" 이라고 예측하는 텍스트 생성하는 것이 목표

실험내용: train dataset의 2000개 샘플,valid dataset의 1000개 샘플을 미세튜닝에 사용

• 일반적으로 1900스텝에서는 정확도 accuracy가 80후반대(약 85%)가 도출, 2000스텝이상부터 90%에 근접한 수치를 보였다.
• seq length=256 gradient accumulation steps=2로 설정하면 매우 낮은 정확도(accuracy)가 도출되기때문에 그 이상의 seq length와 accumulation steps가 필요하다는 사실 확인.

##Accuracy 정확도 분석 ###valid_dataset(test dataset 1000개에 대한 정확도)

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***정확도:0.902

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Framework versions

• PEFT 0.7.1