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+ ---
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+ base_model: mini1013/master_domain
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+ library_name: setfit
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+ metrics:
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+ - accuracy
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+ pipeline_tag: text-classification
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+ tags:
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+ - setfit
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+ - sentence-transformers
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+ - text-classification
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+ - generated_from_setfit_trainer
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+ widget:
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+ - text: 크리넥스 NEW 버블버블 핸드워시 에코그린 허브향 500ml / 250ml 손세정제 / 손소독제 안심+ 손소독제겔 카카오 55ml 그린2개+알로에2개
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+ (#M)바디케어>핸드워시>거품형핸드워시 AD > 11st > 뷰티 > 바디케어 > 핸드워시
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+ - text: 도브 스위트 코코넛 밀크 바디워시 1L 3개묶음 LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 바디워시 LotteOn > 뷰티
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+ > 헤어/바디 > 바디케어 > 바디워시
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+ - text: 니베아 데오드란트 롤온 엑스트라 브라이트 50ml 임박 몸냄새 땀 냄새 억제 바디 향수 데오도란트 추천 (#M)11st>바디케어>데오드란트>데오드란트
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+ 11st > 뷰티 > 바디케어 > 데오드란트
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+ - text: '[2021최신상/GS단독구성] 플루 바디스크럽 샤인에디션 매니아구성 (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티
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+ > 바디케어 > 바디스크럽'
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+ - text: 러쉬 [러쉬]오늘을 사랑해(섹스 밤+피치 배쓰 밤) (#M)11st>바디케어>바디워시>가루형입욕제 11st > 뷰티 > 바디케어 >
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+ 바디워시 > 가루형입욕제
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+ inference: true
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+ model-index:
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+ - name: SetFit with mini1013/master_domain
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: Unknown
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+ type: unknown
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.9065326633165829
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+ name: Accuracy
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+ ---
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+
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+ # SetFit with mini1013/master_domain
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+
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+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [mini1013/master_domain](https://huggingface.co/mini1013/master_domain) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
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+
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+ The model has been trained using an efficient few-shot learning technique that involves:
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+
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+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** SetFit
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+ - **Sentence Transformer body:** [mini1013/master_domain](https://huggingface.co/mini1013/master_domain)
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+ - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
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+ - **Maximum Sequence Length:** 512 tokens
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+ - **Number of Classes:** 15 classes
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+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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+ <!-- - **Language:** Unknown -->
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+ <!-- - **License:** Unknown -->
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+
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+ ### Model Sources
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+
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+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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+
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+ ### Model Labels
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+ | Label | Examples |
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+ |:------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | 0 | <ul><li>'조르지오 아르마니 아쿠아 디 지오 옴므 데오도란트 스틱 75 ml (#M)홈>화장품/미용>바디케어>데오드란트 Naverstore > 화장품/미용 > 바디케어 > 데오드란트'</li><li>'POLO GREEN ORIGINAL 랄프 로렌 60 Oz 170 G 남성용 데오도란트 스프레이 NEW Sealed LotteOn > 뷰티 > 향수 > 남성향수 LotteOn > 뷰티 > 향수 > 남성향수'</li><li>'조르지오 아르마니 코드 데오도란트 스틱 남성용 무알코올 2.6온스 / 75g LotteOn > 뷰티 > 향수 > 남성향수 LotteOn > 뷰티 > 향수 > 남성향수'</li></ul> |
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+ | 8 | <ul><li>'[산타마리아노벨라] 사포네 알라 만돌라 (세안비누) DepartmentSsg > 명품화장품 > 스킨케어 > 클렌징 DepartmentSsg > 명품화장품 > 스킨케어 > 클렌징'</li><li>'[백화점]록시땅 체리 블라썸 솝 50g (#M)GSSHOP>뷰티>명품화장품>현대백화점 GSSHOP > 뷰티 > 명품화장품 > 현대백화점 > 바디/헤어케어'</li><li>'LG 디오리진 비타시드 클렌징 비누 90gx12 (#M)쿠팡 홈>미세먼지용품>씻을 때>성인클렌저>비누 Coupang > 뷰티 > 바디 > 핸드/풋/데오 > 핸드케어 > 비누'</li></ul> |
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+ | 4 | <ul><li>'[스킨케어 4종 키트 제공] 페이보드 아로마 듀오 (향수 & 테라피 오일) 테싯 & 진저 플라이트 (#M)홈>NEW Naverstore > 화장품/미용 > 향수 > 향수세트'</li><li>'뉴트로지나 바디 오일 라이트 세서미 포뮬러 250ml × 1개 (#M)쿠팡 홈>생활용품>헤어/바디/세안>바디로션/크림>바디오일 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디오일'</li><li>'쟈도르 드라이 실키 바디 앤 헤어 오일 ssg > 뷰티 > 향수 > 여성향수 ssg > 뷰티 > 향수 > 여성향수'</li></ul> |
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+ | 13 | <ul><li>'[광희 PICK] 닥터그루트 제이몬스터즈 +베스트제품 모음전 09_카카오 핸드워시 세트_라이언 2개 쇼킹딜 홈>뷰티>헤어>샴푸/린스/기능성;11st>뷰티>헤어>샴푸/린스/기능성;11st>헤어케어>샴푸>기능성;11st Hour Event > 유아동 11st Hour Event > 패션/뷰티 > 뷰티 > 헤어 > 샴푸/린스/기능성'</li><li>'핸드워시 백은향 300ml 300~500ml(g) LotteOn > 뷰티 > 클렌징 > 클렌징폼 LotteOn > 뷰티 > 럭셔리 스킨케어 > 클렌징 > 클렌징폼'</li><li>'라이온 아이깨끗해 대용량 용기 490ml x 5개 3.청포도 용기 490ml x 5개 (#M)바디/헤어>헤어케어>샴푸/린스 Gmarket > 뷰티 > 바디/헤어 > 헤어케어 > 샴푸/린스'</li></ul> |
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+ | 10 | <ul><li>'[러쉬/디왈리]랑골리 드림즈 130g - 배쓰 밤/입욕제182576 L41461175 L2 단일상품182576 L41461175 L2 (#M)위메프 > 생활·주방용품 > 바디/헤어 > 바디케어/워시/제모 > 입욕제 위메프 > 뷰티 > 바디/헤어 > 바디케어/워시/제모 > 입욕제'</li><li>'[러쉬] 베스트 배쓰 밤 - 입욕제 03.트와일라잇 (#M)11st>바디케어>바디워시>아로마입욕제 11st > 뷰티 > 바디케어 > 바디워시 > 아로마입욕제'</li><li>'러쉬 버블 바 - 입욕제/거품목욕/버블 05. 퍼피 러브 (#M)11st>바디케어>바디워시>가루형입욕제 11st > 뷰티 > 바디케어 > 바디워시 > 가루형입욕제'</li></ul> |
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+ | 14 | <ul><li>'버츠비 로즈마리 핸드 크림 28.3g 듀오 MinSellAmount (#M)화장품/향수>색조메이크업>립틴트 Gmarket > 뷰티 > 화장품/향수 > 색조메이크업 > 립틴트'</li><li>'[공식] 카밀 핸드크림 2개 허벌_클래식100ml LotteOn > 뷰티 > 핸드케어 > 핸드크림 LotteOn > 뷰티 > 헤어/바디 > 핸드케어 > 핸드크림'</li><li>'탬버린즈 퍼퓸핸드 듀오 세트(FEY9+000) LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 바디케어용품 LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 바디케어용품'</li></ul> |
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+ | 1 | <ul><li>'(4PACK)Aveeno Active Naturals 스트레스 릴리프 모이스쳐라이징 아비노바디로션 라벤더 카모마일 12 fl oz (354 ml) One Size × 4팩 Coupang > 뷰티 > 스킨케어 > 로션;(#M)쿠팡 홈>뷰티>스킨케어>로션 Coupang > 뷰티 > 스킨케어 > 로션'</li><li>'일리윤 세라마이드 아토 로션 350ml x 2개 (#M)위메프 > 뷰티 > 스킨케어 > 로션/에멀젼 > 로션/에멀젼 위메프 > 뷰티 > 스킨케어 > 로션/에멀젼 > 로션/에멀젼'</li><li>'[10% 즉시할인] 닥터브로너스 오가닉 코코넛 밤 60g ssg > 뷰티 > 스킨케어 > 클렌징 ssg > 뷰티 > 스킨케어 > 클렌징 > 클렌징폼/젤'</li></ul> |
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+ | 3 | <ul><li>'온더바디 때 필링 500ml MI LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 바디스크럽 LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 바디스크럽'</li><li>'라끄베르 아무때나 때필링 500ml (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티 > 바디케어 > 바디스크럽'</li><li>'[1+1] 플루 오리지널 바디스크럽 200g 화이트머스크 200g_로즈마리허브 200g (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티 > 바디케어 > 바디스크럽'</li></ul> |
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+ | 11 | <ul><li>'아르코왁싱 롤온 카트리지 키트 (#M)홈>아르코왁싱 Naverstore > 화장품/미용 > 바디케어 > 제모제'</li><li>'알롱 셀프 제모 비즈왁스 리필형 200g 2개 세트(왁스100g ) (#M)화장품/미용>바디케어>제모제 Naverstore > 바디케어 > 제모용품'</li><li>'아트박스/스무스 왁스 호�� No.1 천연제모제 겟잇뷰티 제모제 스무스왁스 350 LotteOn > 뷰티 > 뷰티기기/소품 > 면도기/제모기 > 제모기 LotteOn > 뷰티 > 뷰티기기/소품 > 면도기/제모기 > 제모기'</li></ul> |
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+ | 12 | <ul><li>'메디필 스케일링 모이스처 풋 크림 130g _G (#M)11st>바디케어>풋케어>풋크림 11st > 뷰티 > 바디케어 > 풋케어 > 풋크림'</li><li>'(1+1) 더샘 디어 마이 풋 스크럽 클렌저 100ml MinSellAmount (#M)바디/헤어>핸드케어/풋케어>발각질제거제 Gmarket > 뷰티 > 바디/헤어 > 핸드케어/풋케어 > 발각질제거제'</li><li>'라벨영 쇼킹솝풋버전 발꼬락비누 5+2 쇼킹솝풋버전/7개 (#M)쿠팡 홈>생활용품>헤어/바디/세안>핸드/풋/데오>핸드케어세트 Coupang > 뷰티 > 바디 > 핸드/풋/데오 > 핸드케어세트'</li></ul> |
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+ | 7 | <ul><li>'존슨즈 베이비 파우더 오리지날향 200g × 5개 (#M)쿠팡 홈>출산/유아동>기저귀>기저귀크림/파우더>기저귀파우더 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디파우더'</li><li>'BTM 존슨즈베이비베드타임파우더400g 오일 바디관리 바디바스 바디케어용품 바디오일 바스파우더 바디크림 1 (#M)쿠팡 홈>생활용품>헤어/바디/세안>바디로션/크림>바디오일 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디오일'</li><li>'더샘 어반 딜라이트 바디 파우더 (로즈) 50g MinSellAmount (#M)바디/헤어>바디케어>바디로션 Gmarket > 뷰티 > 바디/헤어 > 바디케어 > 바디로션'</li></ul> |
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+ | 9 | <ul><li>'쿤달 샴푸/트리트먼트/바디워시/디퓨저 모음전!! 45.쿤달 여성청결제 300ml 1+1_베르가못 (#M)헤어케어>샴푸>일반샴푸 AD > traverse > 11st > 뷰티 > 헤어케어 > 샴푸 > 일반샴푸'</li><li>'[포엘리에] 캡슐 와이클렌저+이너퍼퓸 9종 택1 와이클렌저+이너퍼퓸(오드봉봉) (#M)쿠팡 홈>생활용품>생리대/성인기저귀>여성청결제 Coupang > 뷰티 > 바디 > 제모/슬리밍/청결제 > 청결제 > 여성청결제'</li><li>'오리지널 10개입X2박스 (#M)뷰티>헤어/바디/미용기기>샤워/입욕용품>청결제 CJmall > 뷰티 > 헤어/바디/미용기기 > 샤워/입욕용품 > 청결제'</li></ul> |
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+ | 2 | <ul><li>'딥퍼랑스 만다린로즈 무드퍼퓸 헤어/바디/룸스프레이 300ml 만다린로즈 무드퍼퓸 300ml (#M)홈>화장품/미용>헤어케어>헤어미스트 Naverstore > 화장품/미용 > 헤어케어 > 헤어미스트'</li><li>'바디판타지 향기 바디미스트 236ml 1+1 웨딩데이/피치애프리콧 (#M)11st>바디케어>바디미스트>바디미스트 11st > 뷰티 > 바디케어 > 바디미스트 > 바디미스트'</li><li>'더프트앤도프트 스톡홀름로즈 바디미스트 100ml 더프트앤도프트 스톡홀름로즈 헤어&바디미스트 100ml 홈>바디케어>미스트/오일>바디미스트;(#M)홈>바디케어>바디미스트>퍼퓸바디미스트 OLIVEYOUNG > 바디케어 > 바디미스트 > 퍼퓸바디미스트'</li></ul> |
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+ | 5 | <ul><li>'[1+1] 부케가르니 나드 리프레쉬 퍼퓸드 샴푸 1,000ml 화이트머스크 향 바디워시 프레쉬라벤더 향 1개_바디워시 프레쉬라벤더 향 1개 (#M)화장품/미용>헤어케어>샴푸 AD > traverse > Naverstore > 화장품/미용 > 헤어케어 > 샴푸 > 일반샴푸'</li><li>'(대용량 500ml ) 우르오스 올인원 스킨 워시 바디클렌저 우르오스 올인원 바디클렌저 500ml (#M)홈>전체상품 Naverstore > 화장품/미용 > 바디케어 > 바디클렌저'</li><li>'[닥터브로너스]그린티 퓨어 캐스틸솝 950ml+거품용기 단품 (#M)11st>클렌징/필링>클렌징크림>클렌징크림 11st > 뷰티 > 클렌징/필링 > 클렌징크림 > 클렌징크림'</li></ul> |
84
+ | 6 | <ul><li>'쇼킹소주스킨 310ml / 2개 (#M)위메프 > 뷰티 > 스킨케어 > 스킨/토너 > 스킨/토너 위메프 > 뷰티 > 스킨케어 > 스킨/토너 > 스킨/토너'</li><li>'록시땅 [기프트]에르베 & 라벤더 핸드 트리오 단일상품 (#M)뷰티>명품화장품>핸드/풋/덴탈케어>핸드케어 CJmall > 뷰티 > 화장품/향수 > 향수/홈프래그런스 > 기획세트'</li><li>'1+1 바디브 약산성 샴푸 1000ml 대용량 비듬 천연 유래 세정성분 청소년 사춘기 초등학생 머리 퍼퓸 향기좋은 지성 정수리 냄새 베이베리오차드향 07. 트리트먼트 엘딘디파르바향_09. 바디워시 인디즈도즌향 (#M)화장품/미용>헤어케어>샴푸 AD > Naverstore > 화장품/미용 > 헤어케어 > 샴푸 > 약산성샴푸'</li></ul> |
85
+
86
+ ## Evaluation
87
+
88
+ ### Metrics
89
+ | Label | Accuracy |
90
+ |:--------|:---------|
91
+ | **all** | 0.9065 |
92
+
93
+ ## Uses
94
+
95
+ ### Direct Use for Inference
96
+
97
+ First install the SetFit library:
98
+
99
+ ```bash
100
+ pip install setfit
101
+ ```
102
+
103
+ Then you can load this model and run inference.
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+
105
+ ```python
106
+ from setfit import SetFitModel
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+
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+ # Download from the 🤗 Hub
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+ model = SetFitModel.from_pretrained("mini1013/master_cate_bt_top4_test")
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+ # Run inference
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+ preds = model("러쉬 [러쉬]오늘을 사랑해(섹스 밤+피치 배쓰 밤) (#M)11st>바디케어>바디워시>가루형입욕제 11st > 뷰티 > 바디케어 > 바디워시 > 가루형입욕제")
112
+ ```
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+
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+ <!--
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+ ### Downstream Use
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+
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+ *List how someone could finetune this model on their own dataset.*
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+ -->
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+
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+ <!--
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+ ### Out-of-Scope Use
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+
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+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
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+ -->
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+
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+ <!--
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+ ## Bias, Risks and Limitations
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+
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+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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+ -->
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+
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+ <!--
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+ ### Recommendations
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+
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+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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+ -->
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+
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+ ## Training Details
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+
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+ ### Training Set Metrics
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+ | Training set | Min | Median | Max |
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+ |:-------------|:----|:--------|:----|
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+ | Word count | 12 | 21.7607 | 51 |
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+
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+ | Label | Training Sample Count |
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+ |:------|:----------------------|
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+ | 0 | 50 |
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+ | 1 | 50 |
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+ | 2 | 50 |
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+ | 3 | 50 |
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+ | 4 | 50 |
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+ | 5 | 50 |
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+ | 6 | 50 |
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+ | 7 | 48 |
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+ | 8 | 50 |
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+ | 9 | 50 |
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+ | 10 | 50 |
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+ | 11 | 50 |
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+ | 12 | 50 |
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+ | 13 | 50 |
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+ | 14 | 50 |
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+
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+ ### Training Hyperparameters
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+ - batch_size: (64, 64)
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+ - num_epochs: (30, 30)
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+ - max_steps: -1
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+ - sampling_strategy: oversampling
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+ - num_iterations: 100
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+ - body_learning_rate: (2e-05, 1e-05)
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+ - head_learning_rate: 0.01
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+ - loss: CosineSimilarityLoss
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+ - distance_metric: cosine_distance
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+ - margin: 0.25
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+ - end_to_end: False
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+ - use_amp: False
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+ - warmup_proportion: 0.1
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+ - l2_weight: 0.01
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+ - seed: 42
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+ - eval_max_steps: -1
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+ - load_best_model_at_end: False
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+
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+ ### Training Results
183
+ | Epoch | Step | Training Loss | Validation Loss |
184
+ |:-------:|:-----:|:-------------:|:---------------:|
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+ | 0.0009 | 1 | 0.4485 | - |
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+ | 0.0428 | 50 | 0.4501 | - |
187
+ | 0.0855 | 100 | 0.4537 | - |
188
+ | 0.1283 | 150 | 0.4456 | - |
189
+ | 0.1711 | 200 | 0.438 | - |
190
+ | 0.2139 | 250 | 0.4018 | - |
191
+ | 0.2566 | 300 | 0.3949 | - |
192
+ | 0.2994 | 350 | 0.3759 | - |
193
+ | 0.3422 | 400 | 0.3392 | - |
194
+ | 0.3849 | 450 | 0.3183 | - |
195
+ | 0.4277 | 500 | 0.2821 | - |
196
+ | 0.4705 | 550 | 0.2688 | - |
197
+ | 0.5133 | 600 | 0.2653 | - |
198
+ | 0.5560 | 650 | 0.2568 | - |
199
+ | 0.5988 | 700 | 0.2565 | - |
200
+ | 0.6416 | 750 | 0.2598 | - |
201
+ | 0.6843 | 800 | 0.2502 | - |
202
+ | 0.7271 | 850 | 0.2427 | - |
203
+ | 0.7699 | 900 | 0.2356 | - |
204
+ | 0.8127 | 950 | 0.2285 | - |
205
+ | 0.8554 | 1000 | 0.2192 | - |
206
+ | 0.8982 | 1050 | 0.2219 | - |
207
+ | 0.9410 | 1100 | 0.2181 | - |
208
+ | 0.9837 | 1150 | 0.2123 | - |
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+ | 1.0265 | 1200 | 0.2079 | - |
210
+ | 1.0693 | 1250 | 0.2067 | - |
211
+ | 1.1121 | 1300 | 0.1987 | - |
212
+ | 1.1548 | 1350 | 0.1957 | - |
213
+ | 1.1976 | 1400 | 0.1908 | - |
214
+ | 1.2404 | 1450 | 0.1883 | - |
215
+ | 1.2831 | 1500 | 0.1824 | - |
216
+ | 1.3259 | 1550 | 0.1821 | - |
217
+ | 1.3687 | 1600 | 0.1821 | - |
218
+ | 1.4115 | 1650 | 0.1686 | - |
219
+ | 1.4542 | 1700 | 0.1693 | - |
220
+ | 1.4970 | 1750 | 0.1611 | - |
221
+ | 1.5398 | 1800 | 0.1581 | - |
222
+ | 1.5825 | 1850 | 0.1416 | - |
223
+ | 1.6253 | 1900 | 0.1412 | - |
224
+ | 1.6681 | 1950 | 0.1257 | - |
225
+ | 1.7109 | 2000 | 0.13 | - |
226
+ | 1.7536 | 2050 | 0.1205 | - |
227
+ | 1.7964 | 2100 | 0.1182 | - |
228
+ | 1.8392 | 2150 | 0.111 | - |
229
+ | 1.8820 | 2200 | 0.1141 | - |
230
+ | 1.9247 | 2250 | 0.1022 | - |
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+ | 1.9675 | 2300 | 0.0919 | - |
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+ | 2.0103 | 2350 | 0.0834 | - |
233
+ | 2.0530 | 2400 | 0.0776 | - |
234
+ | 2.0958 | 2450 | 0.0701 | - |
235
+ | 2.1386 | 2500 | 0.0644 | - |
236
+ | 2.1814 | 2550 | 0.0552 | - |
237
+ | 2.2241 | 2600 | 0.0486 | - |
238
+ | 2.2669 | 2650 | 0.0433 | - |
239
+ | 2.3097 | 2700 | 0.0323 | - |
240
+ | 2.3524 | 2750 | 0.0279 | - |
241
+ | 2.3952 | 2800 | 0.0268 | - |
242
+ | 2.4380 | 2850 | 0.0247 | - |
243
+ | 2.4808 | 2900 | 0.0154 | - |
244
+ | 2.5235 | 2950 | 0.0126 | - |
245
+ | 2.5663 | 3000 | 0.0097 | - |
246
+ | 2.6091 | 3050 | 0.0099 | - |
247
+ | 2.6518 | 3100 | 0.0082 | - |
248
+ | 2.6946 | 3150 | 0.0078 | - |
249
+ | 2.7374 | 3200 | 0.0058 | - |
250
+ | 2.7802 | 3250 | 0.0048 | - |
251
+ | 2.8229 | 3300 | 0.0039 | - |
252
+ | 2.8657 | 3350 | 0.0032 | - |
253
+ | 2.9085 | 3400 | 0.0024 | - |
254
+ | 2.9512 | 3450 | 0.0021 | - |
255
+ | 2.9940 | 3500 | 0.0018 | - |
256
+ | 3.0368 | 3550 | 0.0014 | - |
257
+ | 3.0796 | 3600 | 0.001 | - |
258
+ | 3.1223 | 3650 | 0.0006 | - |
259
+ | 3.1651 | 3700 | 0.0007 | - |
260
+ | 3.2079 | 3750 | 0.0007 | - |
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+ | 3.2506 | 3800 | 0.0006 | - |
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+ | 3.2934 | 3850 | 0.0009 | - |
263
+ | 3.3362 | 3900 | 0.001 | - |
264
+ | 3.3790 | 3950 | 0.001 | - |
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+ | 3.4217 | 4000 | 0.0005 | - |
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+ | 3.4645 | 4050 | 0.0004 | - |
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+ | 3.5073 | 4100 | 0.0008 | - |
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+ | 3.5500 | 4150 | 0.0004 | - |
269
+ | 3.5928 | 4200 | 0.0022 | - |
270
+ | 3.6356 | 4250 | 0.0021 | - |
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+ | 3.6784 | 4300 | 0.0051 | - |
272
+ | 3.7211 | 4350 | 0.0037 | - |
273
+ | 3.7639 | 4400 | 0.0026 | - |
274
+ | 3.8067 | 4450 | 0.0021 | - |
275
+ | 3.8494 | 4500 | 0.0009 | - |
276
+ | 3.8922 | 4550 | 0.0004 | - |
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+ | 3.9350 | 4600 | 0.0002 | - |
278
+ | 3.9778 | 4650 | 0.0002 | - |
279
+ | 4.0205 | 4700 | 0.0001 | - |
280
+ | 4.0633 | 4750 | 0.0001 | - |
281
+ | 4.1061 | 4800 | 0.0001 | - |
282
+ | 4.1488 | 4850 | 0.0001 | - |
283
+ | 4.1916 | 4900 | 0.0001 | - |
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+ | 4.2344 | 4950 | 0.0001 | - |
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+ | 4.2772 | 5000 | 0.0001 | - |
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+ | 4.3199 | 5050 | 0.0001 | - |
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+ | 4.3627 | 5100 | 0.0001 | - |
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+ | 4.4055 | 5150 | 0.0001 | - |
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+ | 4.4482 | 5200 | 0.0001 | - |
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+ | 4.4910 | 5250 | 0.0001 | - |
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+ | 4.5338 | 5300 | 0.0001 | - |
292
+ | 4.5766 | 5350 | 0.0001 | - |
293
+ | 4.6193 | 5400 | 0.0001 | - |
294
+ | 4.6621 | 5450 | 0.0001 | - |
295
+ | 4.7049 | 5500 | 0.0001 | - |
296
+ | 4.7476 | 5550 | 0.0001 | - |
297
+ | 4.7904 | 5600 | 0.0001 | - |
298
+ | 4.8332 | 5650 | 0.0001 | - |
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+ | 4.8760 | 5700 | 0.0001 | - |
300
+ | 4.9187 | 5750 | 0.0001 | - |
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+ | 4.9615 | 5800 | 0.0002 | - |
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+ | 5.0043 | 5850 | 0.0001 | - |
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+ | 5.0470 | 5900 | 0.0001 | - |
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+ | 5.0898 | 5950 | 0.0001 | - |
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+ | 5.1326 | 6000 | 0.0001 | - |
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+ | 5.1754 | 6050 | 0.0001 | - |
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+ | 5.2181 | 6100 | 0.0001 | - |
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+ | 5.2609 | 6150 | 0.0 | - |
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+ | 5.3037 | 6200 | 0.0 | - |
310
+ | 5.3464 | 6250 | 0.0001 | - |
311
+ | 5.3892 | 6300 | 0.0003 | - |
312
+ | 5.4320 | 6350 | 0.0008 | - |
313
+ | 5.4748 | 6400 | 0.0016 | - |
314
+ | 5.5175 | 6450 | 0.0069 | - |
315
+ | 5.5603 | 6500 | 0.0152 | - |
316
+ | 5.6031 | 6550 | 0.0175 | - |
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+ | 5.6459 | 6600 | 0.0055 | - |
318
+ | 5.6886 | 6650 | 0.0041 | - |
319
+ | 5.7314 | 6700 | 0.0024 | - |
320
+ | 5.7742 | 6750 | 0.0025 | - |
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+ | 5.8169 | 6800 | 0.0015 | - |
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+ | 5.8597 | 6850 | 0.0016 | - |
323
+ | 5.9025 | 6900 | 0.0018 | - |
324
+ | 5.9453 | 6950 | 0.0007 | - |
325
+ | 5.9880 | 7000 | 0.0012 | - |
326
+ | 6.0308 | 7050 | 0.001 | - |
327
+ | 6.0736 | 7100 | 0.001 | - |
328
+ | 6.1163 | 7150 | 0.0003 | - |
329
+ | 6.1591 | 7200 | 0.0001 | - |
330
+ | 6.2019 | 7250 | 0.0003 | - |
331
+ | 6.2447 | 7300 | 0.0001 | - |
332
+ | 6.2874 | 7350 | 0.0001 | - |
333
+ | 6.3302 | 7400 | 0.0001 | - |
334
+ | 6.3730 | 7450 | 0.0045 | - |
335
+ | 6.4157 | 7500 | 0.0018 | - |
336
+ | 6.4585 | 7550 | 0.0005 | - |
337
+ | 6.5013 | 7600 | 0.0012 | - |
338
+ | 6.5441 | 7650 | 0.0005 | - |
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+ | 6.5868 | 7700 | 0.0002 | - |
340
+ | 6.6296 | 7750 | 0.0003 | - |
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+ | 6.6724 | 7800 | 0.0002 | - |
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+ | 6.7151 | 7850 | 0.0 | - |
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+ | 6.7579 | 7900 | 0.0 | - |
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+ | 6.8007 | 7950 | 0.0 | - |
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+ | 6.8435 | 8000 | 0.0 | - |
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+ | 6.8862 | 8050 | 0.0 | - |
347
+ | 6.9290 | 8100 | 0.0 | - |
348
+ | 6.9718 | 8150 | 0.0 | - |
349
+ | 7.0145 | 8200 | 0.0 | - |
350
+ | 7.0573 | 8250 | 0.0 | - |
351
+ | 7.1001 | 8300 | 0.0 | - |
352
+ | 7.1429 | 8350 | 0.0 | - |
353
+ | 7.1856 | 8400 | 0.0 | - |
354
+ | 7.2284 | 8450 | 0.0 | - |
355
+ | 7.2712 | 8500 | 0.0 | - |
356
+ | 7.3139 | 8550 | 0.0001 | - |
357
+ | 7.3567 | 8600 | 0.0 | - |
358
+ | 7.3995 | 8650 | 0.0 | - |
359
+ | 7.4423 | 8700 | 0.0 | - |
360
+ | 7.4850 | 8750 | 0.0 | - |
361
+ | 7.5278 | 8800 | 0.0 | - |
362
+ | 7.5706 | 8850 | 0.0 | - |
363
+ | 7.6133 | 8900 | 0.0 | - |
364
+ | 7.6561 | 8950 | 0.0 | - |
365
+ | 7.6989 | 9000 | 0.0 | - |
366
+ | 7.7417 | 9050 | 0.0 | - |
367
+ | 7.7844 | 9100 | 0.0 | - |
368
+ | 7.8272 | 9150 | 0.0 | - |
369
+ | 7.8700 | 9200 | 0.0 | - |
370
+ | 7.9127 | 9250 | 0.0 | - |
371
+ | 7.9555 | 9300 | 0.0 | - |
372
+ | 7.9983 | 9350 | 0.0 | - |
373
+ | 8.0411 | 9400 | 0.0 | - |
374
+ | 8.0838 | 9450 | 0.0013 | - |
375
+ | 8.1266 | 9500 | 0.0024 | - |
376
+ | 8.1694 | 9550 | 0.0043 | - |
377
+ | 8.2121 | 9600 | 0.0038 | - |
378
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+
888
+ ### Framework Versions
889
+ - Python: 3.10.12
890
+ - SetFit: 1.1.0
891
+ - Sentence Transformers: 3.3.1
892
+ - Transformers: 4.44.2
893
+ - PyTorch: 2.2.0a0+81ea7a4
894
+ - Datasets: 3.2.0
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+ - Tokenizers: 0.19.1
896
+
897
+ ## Citation
898
+
899
+ ### BibTeX
900
+ ```bibtex
901
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
902
+ doi = {10.48550/ARXIV.2209.11055},
903
+ url = {https://arxiv.org/abs/2209.11055},
904
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
905
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
906
+ title = {Efficient Few-Shot Learning Without Prompts},
907
+ publisher = {arXiv},
908
+ year = {2022},
909
+ copyright = {Creative Commons Attribution 4.0 International}
910
+ }
911
+ ```
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+
913
+ <!--
914
+ ## Glossary
915
+
916
+ *Clearly define terms in order to be accessible across audiences.*
917
+ -->
918
+
919
+ <!--
920
+ ## Model Card Authors
921
+
922
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
923
+ -->
924
+
925
+ <!--
926
+ ## Model Card Contact
927
+
928
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
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+ -->
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