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master_cate_bt3_test_flat_top_cate

Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files
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Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +926 -0
  3. config.json +29 -0
  4. config_sentence_transformers.json +10 -0
  5. config_setfit.json +4 -0
  6. model.safetensors +3 -0
  7. model_head.pkl +3 -0
  8. modules.json +14 -0
  9. sentence_bert_config.json +4 -0
  10. special_tokens_map.json +51 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +66 -0
  13. vocab.txt +0 -0
1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 768,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
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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: 아이깨끗해 핸드워시 490ml용기+450ml리필 2개 29.리필 200ml 5개(순) 홈>전체상품;홈>인기상품;(#M)홈>▶판매 BEST
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+ Naverstore > 화장품/미용 > 바디케어 > 핸드케어
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+ - text: 몰튼브라운 바디워시 300ml 21종 4. 네온 앰버 (#M)홈>화장품/미용>바디케어>바디클렌저 Naverstore > 화장품/미용
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+ > 바디케어 > 바디클렌저
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+ - text: Biotherm Homme Day Control Antiperspirant Roll-On Multicolor, 2.53oz, 1 pack
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+ 비오템 옴/8837866 LotteOn > 뷰티 > 바디케어 > 데오드란트 LotteOn > 뷰티 > 바디케어 > 데오드란트
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+ - text: 에스테소피 스크럽 솔트 솝 진저 1kg (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티 > 바디케어 > 바디스크럽
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+ - text: LUSH BUBBLE BAR Creamy Candy 러쉬 입욕제 버블 바 크리미 캔디 100g 2팩 (#M)홈>화장품/미용>바디케어>입욕제
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+ Naverstore > 화장품/미용 > 바디케어 > 입욕제
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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: 0.8482412060301507
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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 코드 데오도란트 스틱 남성용 무알코올 2.6온스 / 75g LotteOn > 뷰티 > 향수 > 남성향수 LotteOn > 뷰티 > 향수 > 남성향수'</li><li>'니베아 데오드란트 스틱/ 롤온/ 스프레이 X 2개 17.(스프레이 200) 드라이임팩트(M)_05.(롤온 50) 펄앤뷰티 (#M)바디/헤어>바디케어>데오드란트 Gmarket > 뷰티 > 바디/헤어 > 바디케어 > 데오드란트'</li><li>'펄 앤 뷰티 데오드란트 스프레이 48h 200ml 4개 (#M)11st>바디케어>데오드란트>데오드란트 11st > 뷰티 > 바디케어 > 데오드란트 > 데오드란트'</li></ul> |
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+ | 10 | <ul><li>'[백화점] 아브라카다브라 버블 스틱 60g - 버블 바/입욕제 LotteOn > 뷰티 > 헤어/바디 > 입욕제 > 솔트/파우더 LotteOn > 뷰티 > 헤어/바디 > 입욕제 > 솔트/파우더'</li><li>'영국 러쉬 사쿠라 배쓰밤 입욕제 Sakura bath bomb 200g 3개 (#M)쿠팡 홈>생활용품>헤어/바디/세안>샤워/입욕용품>입욕제>버블바스 Coupang > 뷰티 > 바디 > 샤워/입욕용품 > 입욕제 > 버블바스'</li><li>'바스참 사해소금 버블바스 레몬 1kg/거품입욕제/스푼포함 01-바스참버블바스-라벤더1kg LotteOn > 뷰티 > 헤어/바디 > 입욕제 > 버블바스 LotteOn > 뷰티 > 헤어/바디 > 입욕제'</li></ul> |
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+ | 4 | <ul><li>'(공식) 더마비 바디로션/기획/멀티오일/크림/워시 1+1 B8.(세라엠디) 바디오일 200ml×2개_S1.튜브견본(랜덤) (#M)화장품/향수>선케어>선크림 Gmarket > 뷰티 > 화장품/향수 > 선케어 > 선크림'</li><li>'벨레다 아니카 마사지 오일 100ml LotteOn > 뷰티 > 스킨케어 > 오일 LotteOn > 뷰티 > 스킨케어 > 오일'</li><li>'쏠레이 브룰런트 쉬머링 바디 오일 100ML (#M)DepartmentSsg > TOM FORD > FRAGRANCE > BODY LOREAL > DepartmentSsg > 아틀리에 코롱 > Generic > 향수'</li></ul> |
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+ | 13 | <ul><li>'[LG생활건강] 세이프솝 카카오 핸드워시 500ml X2개 리틀라이언 리틀라이언 500ml x 2 LotteOn > 뷰티 > 핸드케어 > 손소독제 LotteOn > 뷰티 > 헤어/바디 > 핸드케어 > 손소독제'</li><li>'아이깨끗해 대용량 용기 490ml x 4개 2.순 용기 490ml x 4개 ssg > 뷰티 > 헤어/바디 > 바디케어 > 핸드케어 ssg > 뷰티 > 헤어/바디 > 바디케어 > 핸드케어'</li><li>'[살림백서] 헤어바디 BEST 모음전 샴푸/워시/바디로션/핸드크림/핸드워시 외 오푼티아 라이스앤허브 탈모 아크네 01. 1+1 살림백서 핸드워시 손세정제 500ml_02) 레몬 향 (#M)헤어케어>샴푸>일반샴푸 11st Hour Event > 패션/뷰티 > 뷰티 > 헤어 > 샴푸/린스/기능성'</li></ul> |
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+ | 7 | <ul><li>'파츌리 리비에라 100ml + BEST 4ml X 4종 증정 일렉트릭 블루 LotteOn > 뷰티 > 명품화장품 > 향수/디퓨저 > 공용향수 LotteOn > 뷰티 > 향수 > 남녀공용향수'</li><li>'센티드 바디 파우더 15g DepartmentLotteOn > 뷰티 > 향수 > 여성용 > 51ml~100ml DepartmentLotteOn > 뷰티 > 향수 > 여성용 > 31ml~50ml'</li><li>'존슨즈 베이비 파우더 오리지날향 400g × 3개 쿠팡 홈>출산/유아동>욕실용품/스킨케어>기저귀크림/파우더>기저귀파우더;(#M)쿠팡 홈>출산/유아동>기저귀>기저귀크림/파우더>기저귀파우더 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디파우더'</li></ul> |
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+ | 14 | <ul><li>'[카밀] 핸드크림 본품 2개+미니 1개+케이스 증정(행사기간: 6/17~6/27일 결제건) 맨_프레쉬 (#M)11st>바디케어>핸드크림>핸드크림 11st > 뷰티 > 바디케어 > 핸드크림'</li><li>'카밀 핸드 앤 네일 우레아 핸드크림 75ml x 2개 (#M)GSSHOP>뷰티>바디케어>핸드케어 GSSHOP > 뷰티 > 바디케어 > 핸드케어'</li><li>'[카밀 오늘특가!] 핸드 앤 네일 크림 클래식 100ml 카밀 인텐시브 100ml (강력보습) (#M)홈>전체상품 Naverstore > 화장품/미용 > 바디케어 > 핸드케어'</li></ul> |
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+ | 1 | <ul><li>'JO MALONE LONDON Peony and Blush Suede body cream 조말론 바디 크림 피오니 앤 블러쉬 스웨이드 50ml 50ml × 1개 (#M)쿠팡 홈>뷰티>바디>바디로션/크림>바디크림 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디크림'</li><li>'프리메라 망고버터 바디로션 380ml 380ml × 2개 (#M)쿠팡 홈>뷰티>바디>바디로션/크림>바디로션 Coupang > 뷰티 > 바디 > 바디로션/크림 > 바디로션'</li><li>'[해외직구/홍콩직배송] 홍콩 제니베이커리 버터 쿠키 640g(L) ssg > 뷰티 > 스킨케어 > 스킨/토너 ssg > 뷰티 > 스킨케어 > 스킨/토너'</li></ul> |
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+ | 3 | <ul><li>'온더바디 때 필링 500ml (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티 > 바디케어 > 바디스크럽'</li><li>'플루 스크럽 인텐시브슬림핏 180g x10+50g x1+그린티수딩젤2 (#M)뷰티>화장품/향수>클렌징>기획세트 CJmall > 뷰티 > 헤어/바디/미용기기 > 샤워/입욕용품 > 스크럽'</li><li>'NEW 쟈도르 쉬머링 스크럽 150ML 쟈도르 쉬머링 스크럽 150ML (#M)신세계백화점/향수/여성향수 DepartmentSsg > 명품화장품 > 향수 > 여성향수'</li></ul> |
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+ | 6 | <ul><li>'2021 록시땅 멀티 라인 어드벤트 캘린더 1set (#M)홈>2021 어드벤트 캘린더 Naverstore > 화장품/미용 > 바디케어 > 바디케어세트'</li><li>'밀크바오밥 세라 헤어&바디 4종 선물세트 (화이트머스크) 단품없음 (#M)쿠팡 홈>뷰티>헤어>헤어세트 Coupang > 뷰티 > 헤어 > 헤어세트'</li><li>'록시땅 코쿤 드 세레니떼 릴랙싱 필로우 미스�� 100ml [00001] 코쿤 드 세레니떼 릴랙싱 필로우 미스트 (#M)11st>헤어케어>헤어왁스>헤어왁스 11st > 뷰티 > 헤어케어 > 헤어왁스'</li></ul> |
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+ | 11 | <ul><li>'라이콘 스트립 왁스 800g 12종 / lycon strip wax 800g 소야미 800g (#M)홈>호주왁싱>라이콘 Naverstore > 화장품/미용 > 바디케어 > 제모제'</li><li>'[MANSIM]무스타치 수염세럼 제모세럼 18ml (#M)홈>화장품/미용>남성화장품>에센스 Naverstore > 화장품/미용 > 남성화장품 > 에센스'</li><li>'모레모 클레이 제모크림 핑크(1개) + 클레이(1개) × 상세설명 참조 Coupang > 뷰티 > 바디 > 제모/슬리밍/청결제 > 제모/왁싱;(#M)쿠팡 홈>뷰티>바디>제모/슬리밍/청결제>제모/왁싱>제모제/제모크림 Coupang > 뷰티 > 바디 > 제모/슬리밍/청결제 > 제모/왁싱 > 제모제/제모크림'</li></ul> |
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+ | 12 | <ul><li>'딥 모이스쳐 풋크림 x2개 MinSellAmount (#M)바디/헤어>핸드케어/풋케어>풋크림 Gmarket > 뷰티 > 바디/헤어 > 핸드케어/풋케어 > 풋크림'</li><li>'티타니아 메탈샌드 더블 풋파일 랜덤 발송 1개 Coupang > 뷰티 > 바디 > 핸드/풋/데오 > 풋케어;(#M)쿠팡 홈>생활용품>헤어/바디/세안>핸드/풋/데오>풋케어>각질제거기 Coupang > 뷰티 > 바디 > 핸드/풋/데오 > 풋케어'</li><li>'푸드어홀릭 베이비파우더 풋크림 100g MinSellAmount (#M)바디/헤어>핸드케어/풋케어>풋크림 Gmarket > 뷰티 > 바디/헤어 > 핸드케어/풋케어 > 풋크림'</li></ul> |
80
+ | 9 | <ul><li>'[백화점]프리메라 [8월] 후리 앤 후리 소프트 폼 150ml 세트 (#M)GSSHOP>뷰티>명품화장품>현대백화점 GSSHOP > 뷰티 > 명품화장품 > 현대백화점 > 바디/헤어케어'</li><li>'포엘리에 이너퍼퓸 오드미엘 5ml × 1개 쿠팡 홈>생활용품>헤어/바디/세안>제모/슬리밍/청결제>청결제>여성청결제;Coupang > 뷰티 > 바디 > 제모/슬리밍/청결제 > 청결제;(#M)쿠팡 홈>생활용품>생리대/성인기저귀>여성청결제 Coupang > 뷰티 > 바디 > 제모/슬리밍/청결제 > 청결제 > 여성청결제'</li><li>'자스민 캔들 190g ssg > 뷰티 > 향수 > 캔들/디퓨저/아로마 ssg > 뷰티 > 향수 > 캔들/디퓨저/아로마'</li></ul> |
81
+ | 5 | <ul><li>'뉴스킨 리퀴드바디바 500mlX2개 MinSellAmount (#M)화장품/향수>팩/마스크>워시오프팩 Gmarket > 뷰티 > 화장품/향수 > 팩/마스크 > 워시오프팩'</li><li>'브로앤팁스 본사정품 수퍼클리어 바디워시 480ml (#M)화장품/향수>클렌징/필링>폼클렌징 Gmarket > 뷰티 > 화장품/향수 > 클렌징/필링 > 폼클렌징'</li><li>'닥터브로너스 페퍼민트 퓨어캐스틸솝 475ml + 펌프 세트 MinSellAmount (#M)화장품/향수>클렌징/필링>폼클렌징 Gmarket > 뷰티 > 화장품/향수 > 클렌징/필링 > 폼클렌징'</li></ul> |
82
+ | 8 | <ul><li>'페이스 솝 80g LotteOn > 뷰티 > 바디케어 > 목욕비누 LotteOn > 뷰티 > 헤어/바디 > 바디케어 > 목욕비누'</li><li>'[공식수입정품] 양키캔들 가든랜턴 캔들워머 가든랜턴 브론즈 ssg > 뷰티 > 향수 > 캔들/디퓨저/아로마 ssg > 뷰티 > 향수 > 캔들/디퓨저/아로마'</li><li>'두보레 백합 비누 (100G X 60EA) (#M)SSG.COM/스킨케어/클렌징/비누 ssg > 뷰티 > 스킨케어 > 클렌징 > 비누'</li></ul> |
83
+ | 2 | <ul><li>'비욘드 딥 모이스처 바디 미스트 200ml 사용기한 2024년 12월까지 (#M)홈>화장품/미용>바디케어>바디미스트 Naverstore > 화장품/미용 > 바디케어 > 바디미스트'</li><li>'[1+1] 바디판타지 바디미스트 236ml 트와일라잇(236ml)_트와일라잇(236ml) (#M)홈>화장품/미용>바디케어>바디미스트 Naverstore > 화장품/미용 > 바디케어 > 바디미스트'</li><li>'쿤달 퓨어 바디미스트 2구 세트 128ml 퍼퓸 화이트머스크 (#M)홈>화장품/미용>바디케어>바디미스트 Naverstore > 화장품/미용 > 바디케어 > 바디미스트'</li></ul> |
84
+
85
+ ## Evaluation
86
+
87
+ ### Metrics
88
+ | Label | Accuracy |
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+ |:--------|:---------|
90
+ | **all** | 0.8482 |
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+
92
+ ## Uses
93
+
94
+ ### Direct Use for Inference
95
+
96
+ First install the SetFit library:
97
+
98
+ ```bash
99
+ pip install setfit
100
+ ```
101
+
102
+ Then you can load this model and run inference.
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+
104
+ ```python
105
+ 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_bt3_test_flat_top_cate")
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+ # Run inference
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+ preds = model("에스테소피 스크럽 솔트 솝 진저 1kg (#M)11st>바디케어>바디스크럽>바디스크럽 11st > 뷰티 > 바디케어 > 바디스크럽")
111
+ ```
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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 | 11 | 21.6635 | 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 | 46 |
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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
182
+ | Epoch | Step | Training Loss | Validation Loss |
183
+ |:-------:|:-----:|:-------------:|:---------------:|
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+ | 0.0009 | 1 | 0.421 | - |
185
+ | 0.0429 | 50 | 0.4469 | - |
186
+ | 0.0858 | 100 | 0.4667 | - |
187
+ | 0.1286 | 150 | 0.4451 | - |
188
+ | 0.1715 | 200 | 0.4292 | - |
189
+ | 0.2144 | 250 | 0.4105 | - |
190
+ | 0.2573 | 300 | 0.4006 | - |
191
+ | 0.3002 | 350 | 0.3816 | - |
192
+ | 0.3431 | 400 | 0.3448 | - |
193
+ | 0.3859 | 450 | 0.3177 | - |
194
+ | 0.4288 | 500 | 0.2957 | - |
195
+ | 0.4717 | 550 | 0.2719 | - |
196
+ | 0.5146 | 600 | 0.2574 | - |
197
+ | 0.5575 | 650 | 0.2516 | - |
198
+ | 0.6003 | 700 | 0.2601 | - |
199
+ | 0.6432 | 750 | 0.2533 | - |
200
+ | 0.6861 | 800 | 0.2498 | - |
201
+ | 0.7290 | 850 | 0.2401 | - |
202
+ | 0.7719 | 900 | 0.2253 | - |
203
+ | 0.8148 | 950 | 0.2273 | - |
204
+ | 0.8576 | 1000 | 0.223 | - |
205
+ | 0.9005 | 1050 | 0.22 | - |
206
+ | 0.9434 | 1100 | 0.2089 | - |
207
+ | 0.9863 | 1150 | 0.2111 | - |
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+ | 1.0292 | 1200 | 0.2048 | - |
209
+ | 1.0720 | 1250 | 0.2072 | - |
210
+ | 1.1149 | 1300 | 0.1999 | - |
211
+ | 1.1578 | 1350 | 0.1977 | - |
212
+ | 1.2007 | 1400 | 0.1938 | - |
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+ | 1.2436 | 1450 | 0.1805 | - |
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+ | 1.2864 | 1500 | 0.1769 | - |
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+ | 1.3293 | 1550 | 0.1764 | - |
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+ | 1.3722 | 1600 | 0.1716 | - |
217
+ | 1.4151 | 1650 | 0.1635 | - |
218
+ | 1.4580 | 1700 | 0.1529 | - |
219
+ | 1.5009 | 1750 | 0.1563 | - |
220
+ | 1.5437 | 1800 | 0.148 | - |
221
+ | 1.5866 | 1850 | 0.1465 | - |
222
+ | 1.6295 | 1900 | 0.1393 | - |
223
+ | 1.6724 | 1950 | 0.1278 | - |
224
+ | 1.7153 | 2000 | 0.1262 | - |
225
+ | 1.7581 | 2050 | 0.12 | - |
226
+ | 1.8010 | 2100 | 0.1123 | - |
227
+ | 1.8439 | 2150 | 0.1051 | - |
228
+ | 1.8868 | 2200 | 0.0968 | - |
229
+ | 1.9297 | 2250 | 0.0902 | - |
230
+ | 1.9726 | 2300 | 0.0843 | - |
231
+ | 2.0154 | 2350 | 0.0784 | - |
232
+ | 2.0583 | 2400 | 0.0698 | - |
233
+ | 2.1012 | 2450 | 0.0671 | - |
234
+ | 2.1441 | 2500 | 0.0605 | - |
235
+ | 2.1870 | 2550 | 0.0601 | - |
236
+ | 2.2298 | 2600 | 0.0494 | - |
237
+ | 2.2727 | 2650 | 0.0484 | - |
238
+ | 2.3156 | 2700 | 0.0442 | - |
239
+ | 2.3585 | 2750 | 0.0376 | - |
240
+ | 2.4014 | 2800 | 0.0356 | - |
241
+ | 2.4443 | 2850 | 0.0308 | - |
242
+ | 2.4871 | 2900 | 0.0313 | - |
243
+ | 2.5300 | 2950 | 0.0321 | - |
244
+ | 2.5729 | 3000 | 0.0279 | - |
245
+ | 2.6158 | 3050 | 0.0293 | - |
246
+ | 2.6587 | 3100 | 0.0304 | - |
247
+ | 2.7015 | 3150 | 0.0211 | - |
248
+ | 2.7444 | 3200 | 0.0233 | - |
249
+ | 2.7873 | 3250 | 0.0204 | - |
250
+ | 2.8302 | 3300 | 0.0177 | - |
251
+ | 2.8731 | 3350 | 0.0181 | - |
252
+ | 2.9160 | 3400 | 0.0183 | - |
253
+ | 2.9588 | 3450 | 0.0145 | - |
254
+ | 3.0017 | 3500 | 0.0163 | - |
255
+ | 3.0446 | 3550 | 0.0145 | - |
256
+ | 3.0875 | 3600 | 0.0131 | - |
257
+ | 3.1304 | 3650 | 0.0113 | - |
258
+ | 3.1732 | 3700 | 0.0136 | - |
259
+ | 3.2161 | 3750 | 0.012 | - |
260
+ | 3.2590 | 3800 | 0.0109 | - |
261
+ | 3.3019 | 3850 | 0.011 | - |
262
+ | 3.3448 | 3900 | 0.0113 | - |
263
+ | 3.3877 | 3950 | 0.0105 | - |
264
+ | 3.4305 | 4000 | 0.0095 | - |
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+ | 3.4734 | 4050 | 0.008 | - |
266
+ | 3.5163 | 4100 | 0.0072 | - |
267
+ | 3.5592 | 4150 | 0.0077 | - |
268
+ | 3.6021 | 4200 | 0.0057 | - |
269
+ | 3.6449 | 4250 | 0.0056 | - |
270
+ | 3.6878 | 4300 | 0.0061 | - |
271
+ | 3.7307 | 4350 | 0.004 | - |
272
+ | 3.7736 | 4400 | 0.0049 | - |
273
+ | 3.8165 | 4450 | 0.0041 | - |
274
+ | 3.8593 | 4500 | 0.0028 | - |
275
+ | 3.9022 | 4550 | 0.002 | - |
276
+ | 3.9451 | 4600 | 0.0015 | - |
277
+ | 3.9880 | 4650 | 0.0012 | - |
278
+ | 4.0309 | 4700 | 0.0011 | - |
279
+ | 4.0738 | 4750 | 0.0021 | - |
280
+ | 4.1166 | 4800 | 0.0014 | - |
281
+ | 4.1595 | 4850 | 0.0006 | - |
282
+ | 4.2024 | 4900 | 0.0008 | - |
283
+ | 4.2453 | 4950 | 0.0006 | - |
284
+ | 4.2882 | 5000 | 0.0005 | - |
285
+ | 4.3310 | 5050 | 0.0003 | - |
286
+ | 4.3739 | 5100 | 0.0003 | - |
287
+ | 4.4168 | 5150 | 0.0002 | - |
288
+ | 4.4597 | 5200 | 0.0002 | - |
289
+ | 4.5026 | 5250 | 0.0002 | - |
290
+ | 4.5455 | 5300 | 0.0002 | - |
291
+ | 4.5883 | 5350 | 0.0002 | - |
292
+ | 4.6312 | 5400 | 0.0002 | - |
293
+ | 4.6741 | 5450 | 0.0003 | - |
294
+ | 4.7170 | 5500 | 0.0001 | - |
295
+ | 4.7599 | 5550 | 0.0001 | - |
296
+ | 4.8027 | 5600 | 0.0001 | - |
297
+ | 4.8456 | 5650 | 0.0001 | - |
298
+ | 4.8885 | 5700 | 0.0001 | - |
299
+ | 4.9314 | 5750 | 0.0001 | - |
300
+ | 4.9743 | 5800 | 0.0001 | - |
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+ | 5.0172 | 5850 | 0.0001 | - |
302
+ | 5.0600 | 5900 | 0.0001 | - |
303
+ | 5.1029 | 5950 | 0.0001 | - |
304
+ | 5.1458 | 6000 | 0.0001 | - |
305
+ | 5.1887 | 6050 | 0.0001 | - |
306
+ | 5.2316 | 6100 | 0.0001 | - |
307
+ | 5.2744 | 6150 | 0.0001 | - |
308
+ | 5.3173 | 6200 | 0.0002 | - |
309
+ | 5.3602 | 6250 | 0.0001 | - |
310
+ | 5.4031 | 6300 | 0.0001 | - |
311
+ | 5.4460 | 6350 | 0.0001 | - |
312
+ | 5.4889 | 6400 | 0.0 | - |
313
+ | 5.5317 | 6450 | 0.0 | - |
314
+ | 5.5746 | 6500 | 0.0001 | - |
315
+ | 5.6175 | 6550 | 0.0 | - |
316
+ | 5.6604 | 6600 | 0.0001 | - |
317
+ | 5.7033 | 6650 | 0.0 | - |
318
+ | 5.7461 | 6700 | 0.0001 | - |
319
+ | 5.7890 | 6750 | 0.0 | - |
320
+ | 5.8319 | 6800 | 0.0 | - |
321
+ | 5.8748 | 6850 | 0.0001 | - |
322
+ | 5.9177 | 6900 | 0.0 | - |
323
+ | 5.9605 | 6950 | 0.0001 | - |
324
+ | 6.0034 | 7000 | 0.0023 | - |
325
+ | 6.0463 | 7050 | 0.0094 | - |
326
+ | 6.0892 | 7100 | 0.0089 | - |
327
+ | 6.1321 | 7150 | 0.0075 | - |
328
+ | 6.1750 | 7200 | 0.0033 | - |
329
+ | 6.2178 | 7250 | 0.0026 | - |
330
+ | 6.2607 | 7300 | 0.0023 | - |
331
+ | 6.3036 | 7350 | 0.0034 | - |
332
+ | 6.3465 | 7400 | 0.0013 | - |
333
+ | 6.3894 | 7450 | 0.0008 | - |
334
+ | 6.4322 | 7500 | 0.0004 | - |
335
+ | 6.4751 | 7550 | 0.0002 | - |
336
+ | 6.5180 | 7600 | 0.0001 | - |
337
+ | 6.5609 | 7650 | 0.0001 | - |
338
+ | 6.6038 | 7700 | 0.0001 | - |
339
+ | 6.6467 | 7750 | 0.0002 | - |
340
+ | 6.6895 | 7800 | 0.0001 | - |
341
+ | 6.7324 | 7850 | 0.0002 | - |
342
+ | 6.7753 | 7900 | 0.0001 | - |
343
+ | 6.8182 | 7950 | 0.0 | - |
344
+ | 6.8611 | 8000 | 0.0021 | - |
345
+ | 6.9039 | 8050 | 0.0003 | - |
346
+ | 6.9468 | 8100 | 0.0011 | - |
347
+ | 6.9897 | 8150 | 0.0013 | - |
348
+ | 7.0326 | 8200 | 0.0001 | - |
349
+ | 7.0755 | 8250 | 0.0001 | - |
350
+ | 7.1184 | 8300 | 0.0 | - |
351
+ | 7.1612 | 8350 | 0.0001 | - |
352
+ | 7.2041 | 8400 | 0.0002 | - |
353
+ | 7.2470 | 8450 | 0.0015 | - |
354
+ | 7.2899 | 8500 | 0.0008 | - |
355
+ | 7.3328 | 8550 | 0.0001 | - |
356
+ | 7.3756 | 8600 | 0.0 | - |
357
+ | 7.4185 | 8650 | 0.0 | - |
358
+ | 7.4614 | 8700 | 0.0 | - |
359
+ | 7.5043 | 8750 | 0.0 | - |
360
+ | 7.5472 | 8800 | 0.0001 | - |
361
+ | 7.5901 | 8850 | 0.0 | - |
362
+ | 7.6329 | 8900 | 0.0001 | - |
363
+ | 7.6758 | 8950 | 0.0001 | - |
364
+ | 7.7187 | 9000 | 0.0 | - |
365
+ | 7.7616 | 9050 | 0.0001 | - |
366
+ | 7.8045 | 9100 | 0.0003 | - |
367
+ | 7.8473 | 9150 | 0.0002 | - |
368
+ | 7.8902 | 9200 | 0.0 | - |
369
+ | 7.9331 | 9250 | 0.0 | - |
370
+ | 7.9760 | 9300 | 0.0 | - |
371
+ | 8.0189 | 9350 | 0.0 | - |
372
+ | 8.0617 | 9400 | 0.0 | - |
373
+ | 8.1046 | 9450 | 0.0005 | - |
374
+ | 8.1475 | 9500 | 0.0092 | - |
375
+ | 8.1904 | 9550 | 0.009 | - |
376
+ | 8.2333 | 9600 | 0.0042 | - |
377
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+
885
+ ### Framework Versions
886
+ - Python: 3.10.12
887
+ - SetFit: 1.1.0
888
+ - Sentence Transformers: 3.3.1
889
+ - Transformers: 4.44.2
890
+ - PyTorch: 2.2.0a0+81ea7a4
891
+ - Datasets: 3.2.0
892
+ - Tokenizers: 0.19.1
893
+
894
+ ## Citation
895
+
896
+ ### BibTeX
897
+ ```bibtex
898
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
899
+ doi = {10.48550/ARXIV.2209.11055},
900
+ url = {https://arxiv.org/abs/2209.11055},
901
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
902
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
903
+ title = {Efficient Few-Shot Learning Without Prompts},
904
+ publisher = {arXiv},
905
+ year = {2022},
906
+ copyright = {Creative Commons Attribution 4.0 International}
907
+ }
908
+ ```
909
+
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+ <!--
911
+ ## Glossary
912
+
913
+ *Clearly define terms in order to be accessible across audiences.*
914
+ -->
915
+
916
+ <!--
917
+ ## Model Card Authors
918
+
919
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
920
+ -->
921
+
922
+ <!--
923
+ ## Model Card Contact
924
+
925
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
926
+ -->
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