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master_cate_bt6_test_flat_top_cate

Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results
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Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +734 -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: 백화점정품 샤넬 루쥬 알뤼르 잉크 6ml 140-AMOUREUX_. (#M)쿠팡 홈>뷰티>메이크업>립 메이크업>립스틱 Coupang
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+ > 뷰티 > 메이크업 > 립 메이크업 > 립스틱
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+ - text: 더페이스샵 모노큐브 아이섀도우 2g 매트_앙 버터 (#M)화장품/향수>색조메이크업>아이섀도 Gmarket > 뷰티 > 화장품/향수 >
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+ 색조메이크업 > 아이섀도
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+ - text: 3CE BLUR WATER TINT 블러 워터 틴트 FRE_SEPIA LOREAL > LotteOn > 입생로랑 > Generic >
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+ 틴트 LotteOn > 뷰티 > 메이크업 > 립메이크업 > 립틴트
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+ - text: 3CE 페이스 블러쉬 ROSE BEIGE 홈>전체상품;(#M)홈>FACE>치크 Naverstore > 화장품/미용 > 색조메이크업 >
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+ 블러셔
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+ - text: 섀도 듀오 4g 6호 라이커블 LotteOn > 뷰티 > 색조메이크업 > 아이메이크업 LotteOn > 뷰티 > 메이크업 > 아이메이크업
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+ > 아이섀도우
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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: 0.48148148148148145
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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:** 11 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>'[쿠폰10%+~25%묶음]에뛰드 타임어택 50% 반값 전품목 특가 (순정/수분가득콜라겐/섀도우팔레트/클렌징폼) 85.디어달링워터젤틴트_4호앵두레드_650011600 쇼킹딜 홈>뷰티>선케어/메이크업>아이메이크업;11st>메이크업>아이메이크업>아이섀도우;11st>뷰티>선케어/메이크업>아이메이크업;11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 아이메���크업 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 아이메이크업'</li><li>'네이처카인드 강력한 헤어커버 타투틴트 1개 (#M)쿠팡 홈>생활용품>헤어/바디/세안>염색/파마>염색/헤어컬러>일반염색제(새치) Coupang > 뷰티 > 헤어 > 염색/파마 > 염색/헤어컬러 > 일반염색제(새치)'</li><li>'조르지오 아르마니 엑스터 래커 500 빈티지 500 빈티지 (#M)홈>▶▶ 메이크업 Naverstore > 화장품/미용 > 색조메이크업 > 립글로스'</li></ul> |
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+ | 4 | <ul><li>'(할인UP)재생소재를 사용한 대표상품+최대38%혜택까지 카.(192-232)가을메이크업은이니스프리_스키니꼼꼼카라ZERO2브라운X2 화장품/향수>스킨/로션>스킨/토너;(#M)화장품/향수>스킨케어>스킨/토너 Gmarket > 뷰티 > 화장품/향수 > 스킨케어'</li><li>'썸츄어스 레벨 렝쓰 + 리프트 마스카라 DepartmentSsg > 명품화장품 > 메이크업 > 아이 메이크업 > 마스카라 DepartmentSsg > 명품화장품 > 메이크업 > 아이 메이크업 > 마스카라'</li><li>'더블니즈 팡팡 마스카라 (EM01012600)02 컬링팡 (#M)화장품/향수>색조메이크업>마스카라 Gmarket > 뷰티 > 화장품/향수 > 색조메이크업 > 마스카라'</li></ul> |
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+ | 8 | <ul><li>'맨즈 아이브로우 펜슬 흙갈색 (#M)11st>남성화장품>남성BB크림>남성BB크림 11st > 뷰티 > 남성화장품 > 남성BB크림'</li><li>'NEW 내추럴 브라우 쉐이퍼 에스프레소 LotteOn > 뷰티 > 네일 > 네일케어 > 큐티클케어 LotteOn > 뷰티 > 네일 > 네일케어 > 큐티클케어'</li><li>'[하프클럽/메이블린뉴욕]디파인 블렌드 아이브로우 펜슬 0.16g 라이트브라운/상세설명참조 LotteOn > 뷰티 > 클렌징 > 립아이리무버 LotteOn > 뷰티 > 클렌징 > 립아이리무버'</li></ul> |
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+ | 9 | <ul><li>'[~묶음20%] 에어리벨벳 물복딱복 출시기념 신상&베스트 모음 027.프로 아이 팔레트 미니_001모노무드_선택사항없음 11st>메이크업>립메이크업>립틴트;쇼킹딜 홈>뷰티>선케어/메이크업>립/치크메이크업;11st>뷰티>선케어/메이크업>립/치크메이크업;11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 립/치크메이크업 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 립/치크메이크업'</li><li>'[30%+T11%] 에이지투웨니스 샤이닝드롭팩트 케이스+리필3개+단독증정 외 NEW & BEST 모음/루나/포인트 앤 (위글위글)루나 데일리 크러쉬 아이섀도우 팔레트_2호 드라이로즈 쇼킹딜 홈>뷰티>선케어/메이크업>페이스메이크업;11st>뷰티>선케어/메이크업>페이스메이크업;11st>메이크업>페이스메이크업>쿠션팩트;11st > 뷰티 > 메이크업 > 페이스메이크업 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 페이스메이크업'</li><li>'[홀리카홀리카] 즉시10%+금액별쿠폰+T11% 개강맞이 ALL세일 /단독 /1+1/금액별 / 56.하드커버 컴플리트 컨실팔레트_없음 11st>메이크업>아이메이크업>아이섀도우;쇼킹딜 홈>뷰티>선케어/메이크업>아이메이크업;11st>뷰티>선케어/메이크업>아이메이크업;11st > 뷰티 > 메이크업 > 아이메이크업 > 아이섀도우 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 아이메이크업'</li></ul> |
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+ | 6 | <ul><li>'글로우 플레이 블러쉬 쏘 내추럴 SSG.COM>신세계백화점MAC>신규 컬렉션>글로우 플레이 블러쉬;(#M)SSG.COM>신세계백화점MAC>MAKE-UP ssg > 뷰티 > 메이크업 > 아이메이크업'</li><li>'[~48%+10%즉시]피카소 홀리데이 레디백 추첨 ! 단독세트/스파츌라&팔레트/아이미속눈썹/메이크업브러쉬 [피카소] 생기창조 108 블러셔_-_- 쇼킹딜 홈>뷰티>네일아트/미용기기>미용소품/피부관리;11st>뷰티>네일아트/미용기기>미용소품/피부관리;11st>��티소품>메이크업소품>메이크업소품;11st > 뷰티 > 뷰티소품 > 메이크업소품 11st Hour Event > 패션/뷰티 > 뷰티 > 네일아트/미용기기 > 미용소품/피부관리'</li><li>'[클렌징오일50ml] 글로우온 블러셔(리필+케이스) 세트 M335 소프트 핑크 LotteOn > 뷰티 > 명품화장품 > 메이크업 LotteOn > 뷰티 > 색조메이크업 > 블러셔'</li></ul> |
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+ | 1 | <ul><li>'소프트 터치 오토 립 라이너 3호 밀키 브라운 ssg > 뷰티 > 메이크업 > 립메이크업 > 립라이너 ssg > 뷰티 > 메이크업 > 립메이크업 > 립라이너'</li><li>'Maybelline New York Color Sensational Shaping Lip Liner Makeup Gone Griege 001 oz 104 GONE GRIEGE_One Size (#M)SSG.COM/메이크업/립메이크업/립스틱 ssg > 뷰티 > 메이크업 > 립메이크업 > 립스틱'</li><li>'로라 메르시에 롱웨어 립 라이너 - 프렌치 푸시아1.49g/0.05oz (#M)홈>스트로베리넷>향수|디퓨저>향수|디퓨저 전체보기 HMALL > 뷰티 > 메이크업 > 립메이크업'</li></ul> |
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+ | 3 | <ul><li>'루즈 언리미티드 마뜨 M BR771 ssg > 뷰티 > 스킨케어 > 클렌징;ssg > 뷰티 > 메이크업 > 치크메이크업;LOREAL > Ssg > 메이블린 > Generic > 아이브로우;ssg > 뷰티 > 스킨케어 > 클렌징 > 클렌징오일;ssg > 뷰티 > 명품화장품 > 메이크업 ssg > 뷰티 > 메이크업 > 치크메이크업 > 블러셔'</li><li>'[하프클럽/메이블린뉴욕]슈퍼 스테이 립 잉크 크레용 1.2g 50_오운유어엠파이어/상세설명참조 LotteOn > 뷰티 > 클렌징 > 립아이리무버 LotteOn > 뷰티 > 클렌징 > 립아이리무버'</li><li>'[단독] 퓨어 컬러 리바이탈라이징 크리스탈 밤 세트 (+파우치) 썬 크리스탈 LotteOn > 백화점 TAP > 명품화장품 > 메인 배너 (PC) LotteOn > 뷰티 > 럭셔리 스킨케어 > 에센스/세럼'</li></ul> |
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+ | 7 | <ul><li>'클라란스 워터프루프 펜슬 - 04 피그0.29g/0.01oz (#M)홈>스트로베리넷>향수|디퓨저>향수|디퓨저 전체보기 HMALL > 뷰티 > 메이크업 > 아이메이크업'</li><li>'플린 디파인 슬림 아이라이너 02 딥 브라운 × 2개 (#M)쿠팡 홈>뷰티>메이크업>아이 메이크업>아이라이너 Coupang > 뷰티 > 메이크업 > 아이 메이크업 > 아이라이너'</li><li>'[쿠폰30%+스토어10%]에뛰드 ~64% 21년 신제품 앵콜전(플레이컬러아이즈/그림자쉐딩/픽싱틴트/순정) 40.플레이 101 펜슬_8호_650003065 쇼킹딜 홈>뷰티>스킨케어>크림;쇼킹딜 홈>뷰티>스킨케어>스킨/로션;11st>스킨케어>스킨/토너>스킨/토너;11st>메이크업>아이메이크업>아이섀도우;쇼킹딜 홈>뷰티>선케어/메이크업>아이메이크업;11st>뷰티>선케어/메이크업>아이메이크업;11st > timedeal 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 아이메이크업'</li></ul> |
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+ | 10 | <ul><li>'시슬리 스띨로 루미에르 - 3 소프트 베이지2.5ml/0.08oz (#M)홈>스트로베리넷>향수|디퓨저>향수|디퓨저 전체보기 HMALL > 뷰티 > 메이크업 > 치크메이크업'</li><li>'포에버 꾸뛰르 루미나이저 06 코랄 글로우 (#M)홈>화장품/미용>베이스메이크업>파우더>팩트파우더 Naverstore > 화장품/미용 > 베이스메이크업 > 파우더 > 팩트파우더'</li><li>'헤라 페이스 디자이닝 브론저 10g 쉐이딩 팩트 LotteOn > 뷰티 > 메이크업 > 쉐딩/컨투어링 LotteOn > 뷰티 > 메이크업 > 쉐딩/컨투어링'</li></ul> |
79
+ | 2 | <ul><li>'다슈 맨즈 컬러 체인지 모이스처 립밤 3.9g (#M)화장품/미용>남성화장품>메이크업 Naverstore > 화장품/미용 > 남성화장품 > 메이크업'</li><li>'듀왑 립플럼퍼 오리지날 베놈 3.5ml 트와일라잇 베놈 홈>바디케어>립케어>립케어(스틱);(#M)홈>바디케어>립케어>스틱/밤타입 OLIVEYOUNG > 바디케어 > 립케어 > 스틱/밤타입'</li><li>'라네즈 립 트리트먼트 밤 (볼륨&보습) 라네즈 립 트리트먼트 밤 [볼륨&보습] 홈>바디케어>립케어>립케어(밤);(#M)홈>바디케어>립케어>스틱/밤타입 OLIVEYOUNG > 바디케어 > 립케어 > 스틱/밤타입'</li></ul> |
80
+ | 5 | <ul><li>'록시땅 홈 퍼퓸 디퓨저 키트 4가지 향기 중 택 1 수플레드리베르떼리바이탈라이징디퓨저리필 (#M)뷰티>명품화장품>향수/홈프래그런스>캔들 CJmall > 뷰티 > 명품화장품 > 향수/홈프래그런스 > 캔들'</li><li>'[해외직구/홍콩직배송] 어반디케이 네이키드 체리 ssg > 뷰티 > 메이크업 > 베이스메이크업 > 메이크업베이스 ssg > 뷰티 > 메이크업 > 베이스메이크업 > 메이크업베이스'</li><li>'밀크바오밥 헤어케어 3종세트 3호 1세트 쿠팡 홈>뷰티>헤어>헤어세트;Coupang > 뷰티 > 헤어 > 헤어세트;(#M)쿠팡 홈>뷰티>선물세트/키트>선물세트>헤어케어 Coupang > 뷰티 > 선물세트/키트 > 선물세트 > 헤어케어'</li></ul> |
81
+
82
+ ## Evaluation
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+
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+ ### Metrics
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+ | Label | Accuracy |
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+ |:--------|:---------|
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+ | **all** | 0.4815 |
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+
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+ ## Uses
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+
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+ ### Direct Use for Inference
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+
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+ First install the SetFit library:
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+
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+ ```bash
96
+ pip install setfit
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+ ```
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+
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+ Then you can load this model and run inference.
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+
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+ ```python
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+ 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_bt6_test_flat_top_cate")
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+ # Run inference
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+ preds = model("3CE 페이스 블러쉬 ROSE BEIGE 홈>전체상품;(#M)홈>FACE>치크 Naverstore > 화장품/미용 > 색조메이크업 > 블러셔")
108
+ ```
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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 | 10 | 24.2404 | 79 |
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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 | 50 |
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+ | 8 | 50 |
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+ | 9 | 50 |
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+ | 10 | 49 |
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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
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:-------:|:-----:|:-------------:|:---------------:|
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+ | 0.0012 | 1 | 0.4756 | - |
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+ | 0.0583 | 50 | 0.447 | - |
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+ | 0.1166 | 100 | 0.4629 | - |
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+ | 0.1748 | 150 | 0.4327 | - |
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+ | 0.2331 | 200 | 0.4182 | - |
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+ | 0.2914 | 250 | 0.3863 | - |
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+ | 0.3497 | 300 | 0.3492 | - |
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+ | 0.4079 | 350 | 0.3277 | - |
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+ | 0.4662 | 400 | 0.2987 | - |
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+ | 0.5245 | 450 | 0.2729 | - |
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+ | 0.5828 | 500 | 0.2637 | - |
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+ | 0.6410 | 550 | 0.2554 | - |
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+ | 0.6993 | 600 | 0.252 | - |
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+ | 0.7576 | 650 | 0.2419 | - |
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+ | 0.8159 | 700 | 0.2382 | - |
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+ | 0.8741 | 750 | 0.239 | - |
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+ | 0.9324 | 800 | 0.2294 | - |
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+ | 0.9907 | 850 | 0.2274 | - |
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+ | 1.0490 | 900 | 0.2237 | - |
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+ | 1.1072 | 950 | 0.2241 | - |
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+ | 1.1655 | 1000 | 0.2196 | - |
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+ | 1.2238 | 1050 | 0.2164 | - |
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+ | 1.2821 | 1100 | 0.2119 | - |
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+ | 1.3403 | 1150 | 0.2048 | - |
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+ | 1.3986 | 1200 | 0.2007 | - |
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+ | 1.4569 | 1250 | 0.1969 | - |
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+ | 1.5152 | 1300 | 0.1898 | - |
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+ | 1.5734 | 1350 | 0.1857 | - |
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+ | 1.6317 | 1400 | 0.1753 | - |
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+ | 1.6900 | 1450 | 0.1703 | - |
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+ | 1.7483 | 1500 | 0.1552 | - |
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+ | 1.8065 | 1550 | 0.1481 | - |
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+ | 1.8648 | 1600 | 0.1341 | - |
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+ | 1.9231 | 1650 | 0.1254 | - |
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+ | 1.9814 | 1700 | 0.1077 | - |
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+ | 2.0396 | 1750 | 0.0895 | - |
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+ | 2.0979 | 1800 | 0.0806 | - |
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+ | 2.1562 | 1850 | 0.0674 | - |
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+ | 2.2145 | 1900 | 0.0618 | - |
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+ | 2.2727 | 1950 | 0.056 | - |
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+ | 2.3310 | 2000 | 0.0549 | - |
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+ | 2.3893 | 2050 | 0.0492 | - |
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+ | 2.4476 | 2100 | 0.0438 | - |
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+ | 2.5058 | 2150 | 0.0394 | - |
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+ | 2.5641 | 2200 | 0.0395 | - |
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+ | 2.6224 | 2250 | 0.0358 | - |
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+ | 2.6807 | 2300 | 0.0373 | - |
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+ | 2.7389 | 2350 | 0.0303 | - |
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+ | 2.7972 | 2400 | 0.0321 | - |
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+ | 2.8555 | 2450 | 0.0267 | - |
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+ | 2.9138 | 2500 | 0.029 | - |
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+ | 2.9720 | 2550 | 0.0314 | - |
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+ | 3.0303 | 2600 | 0.031 | - |
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+ | 3.0886 | 2650 | 0.019 | - |
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+ | 3.1469 | 2700 | 0.02 | - |
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+ | 3.2051 | 2750 | 0.0223 | - |
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+ | 3.2634 | 2800 | 0.0206 | - |
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+ | 3.3217 | 2850 | 0.0173 | - |
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+ | 3.3800 | 2900 | 0.016 | - |
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+ | 3.4382 | 2950 | 0.0181 | - |
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+ | 3.4965 | 3000 | 0.0102 | - |
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+ | 3.5548 | 3050 | 0.0078 | - |
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+ | 3.6131 | 3100 | 0.0107 | - |
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+ | 3.6713 | 3150 | 0.0094 | - |
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+ | 3.7296 | 3200 | 0.0089 | - |
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+ | 3.7879 | 3250 | 0.0097 | - |
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+ | 3.8462 | 3300 | 0.0094 | - |
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+ | 3.9044 | 3350 | 0.0111 | - |
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+ | 3.9627 | 3400 | 0.0102 | - |
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+ | 4.0210 | 3450 | 0.0091 | - |
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+ | 4.0793 | 3500 | 0.0082 | - |
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+ | 4.1375 | 3550 | 0.0048 | - |
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+ | 4.1958 | 3600 | 0.0022 | - |
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+ | 4.2541 | 3650 | 0.0007 | - |
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+ | 4.3124 | 3700 | 0.0007 | - |
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+ | 4.3706 | 3750 | 0.0012 | - |
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+ | 4.4289 | 3800 | 0.0009 | - |
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+ | 4.4872 | 3850 | 0.0006 | - |
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+ | 4.5455 | 3900 | 0.0002 | - |
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+ | 4.6037 | 3950 | 0.0002 | - |
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+ | 4.6620 | 4000 | 0.0002 | - |
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+ | 4.7203 | 4050 | 0.0002 | - |
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+ | 4.7786 | 4100 | 0.0002 | - |
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+ | 4.8368 | 4150 | 0.0001 | - |
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+ | 4.8951 | 4200 | 0.0001 | - |
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+ | 4.9534 | 4250 | 0.0001 | - |
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+ | 5.0117 | 4300 | 0.0001 | - |
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+ | 5.0699 | 4350 | 0.0001 | - |
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+ | 5.1282 | 4400 | 0.0001 | - |
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+ | 5.1865 | 4450 | 0.0001 | - |
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+ | 5.2448 | 4500 | 0.0001 | - |
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+ | 5.3030 | 4550 | 0.001 | - |
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+ | 5.3613 | 4600 | 0.0003 | - |
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+ | 5.4196 | 4650 | 0.0005 | - |
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+ | 5.4779 | 4700 | 0.0014 | - |
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+ | 5.5361 | 4750 | 0.0005 | - |
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+ | 5.5944 | 4800 | 0.0016 | - |
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+ | 5.6527 | 4850 | 0.0007 | - |
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+ | 5.7110 | 4900 | 0.0003 | - |
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+ | 5.7692 | 4950 | 0.0001 | - |
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+ | 5.8275 | 5000 | 0.0005 | - |
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+ | 5.8858 | 5050 | 0.0004 | - |
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+ | 5.9441 | 5100 | 0.0003 | - |
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+ | 6.0023 | 5150 | 0.0011 | - |
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+ | 6.0606 | 5200 | 0.0001 | - |
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+ | 6.1189 | 5250 | 0.0001 | - |
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+ | 6.1772 | 5300 | 0.0001 | - |
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+ | 6.2354 | 5350 | 0.0001 | - |
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+ | 6.2937 | 5400 | 0.0002 | - |
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+ | 6.3520 | 5450 | 0.0004 | - |
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+ | 6.4103 | 5500 | 0.0009 | - |
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+ | 6.4685 | 5550 | 0.0002 | - |
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+ | 6.5268 | 5600 | 0.0001 | - |
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+ | 6.5851 | 5650 | 0.0 | - |
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+ | 6.6434 | 5700 | 0.0 | - |
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+ | 6.7016 | 5750 | 0.0 | - |
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+ | 6.7599 | 5800 | 0.0 | - |
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+ | 6.8182 | 5850 | 0.0001 | - |
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+ | 6.8765 | 5900 | 0.0006 | - |
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+ | 6.9347 | 5950 | 0.0008 | - |
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+ | 6.9930 | 6000 | 0.0013 | - |
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+ | 7.0513 | 6050 | 0.0015 | - |
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+ | 7.1096 | 6100 | 0.0007 | - |
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+ | 7.1678 | 6150 | 0.003 | - |
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+ | 7.2261 | 6200 | 0.0031 | - |
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+ | 7.2844 | 6250 | 0.0013 | - |
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+ | 7.3427 | 6300 | 0.0019 | - |
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+ | 7.4009 | 6350 | 0.0025 | - |
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+ | 7.4592 | 6400 | 0.0009 | - |
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+ | 7.5175 | 6450 | 0.0008 | - |
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+ | 7.6340 | 6550 | 0.0001 | - |
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+ | 7.6923 | 6600 | 0.0001 | - |
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+ | 7.7506 | 6650 | 0.0 | - |
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+ | 10.0233 | 8600 | 0.0 | - |
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+ | 10.1399 | 8700 | 0.0036 | - |
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+ | 10.8392 | 9300 | 0.0003 | - |
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+ | 11.0140 | 9450 | 0.0001 | - |
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+ | 11.1888 | 9600 | 0.0 | - |
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+ | 11.6550 | 10000 | 0.0014 | - |
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+ | 11.7133 | 10050 | 0.0006 | - |
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+ | 11.7716 | 10100 | 0.0003 | - |
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+ | 11.8881 | 10200 | 0.0 | - |
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+ | 12.2378 | 10500 | 0.002 | - |
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+ | 12.2960 | 10550 | 0.0005 | - |
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+ | 12.3543 | 10600 | 0.0002 | - |
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+ | 12.4126 | 10650 | 0.0 | - |
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+ | 12.4709 | 10700 | 0.0 | - |
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+ | 12.5291 | 10750 | 0.0 | - |
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+ | 12.5874 | 10800 | 0.0 | - |
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+ | 12.6457 | 10850 | 0.0002 | - |
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+ | 12.7040 | 10900 | 0.0 | - |
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+ | 12.7622 | 10950 | 0.0 | - |
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+ | 12.8205 | 11000 | 0.0 | - |
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+ | 12.8788 | 11050 | 0.0 | - |
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+ | 12.9371 | 11100 | 0.0 | - |
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+
693
+ ### Framework Versions
694
+ - Python: 3.10.12
695
+ - SetFit: 1.1.0
696
+ - Sentence Transformers: 3.3.1
697
+ - Transformers: 4.44.2
698
+ - PyTorch: 2.2.0a0+81ea7a4
699
+ - Datasets: 3.2.0
700
+ - Tokenizers: 0.19.1
701
+
702
+ ## Citation
703
+
704
+ ### BibTeX
705
+ ```bibtex
706
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
707
+ doi = {10.48550/ARXIV.2209.11055},
708
+ url = {https://arxiv.org/abs/2209.11055},
709
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
710
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
711
+ title = {Efficient Few-Shot Learning Without Prompts},
712
+ publisher = {arXiv},
713
+ year = {2022},
714
+ copyright = {Creative Commons Attribution 4.0 International}
715
+ }
716
+ ```
717
+
718
+ <!--
719
+ ## Glossary
720
+
721
+ *Clearly define terms in order to be accessible across audiences.*
722
+ -->
723
+
724
+ <!--
725
+ ## Model Card Authors
726
+
727
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
728
+ -->
729
+
730
+ <!--
731
+ ## Model Card Contact
732
+
733
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
734
+ -->
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+ "pad_token": {
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+ "content": "[PAD]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ "sep_token": {
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+ "single_word": false
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+ "unk_token": {
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+ "content": "[UNK]",
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+ "lstrip": false,
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+ "normalized": false,
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+ "rstrip": false,
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+ "single_word": false
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+ }
51
+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "added_tokens_decoder": {
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+ "0": {
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+ "special": true
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+ "2": {
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+ },
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+ "bos_token": "[CLS]",
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+ "clean_up_tokenization_spaces": false,
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+ "cls_token": "[CLS]",
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+ "do_basic_tokenize": true,
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+ "do_lower_case": false,
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+ "eos_token": "[SEP]",
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+ "mask_token": "[MASK]",
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+ "max_length": 512,
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+ "pad_to_multiple_of": null,
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+ "pad_token": "[PAD]",
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+ "pad_token_type_id": 0,
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+ "padding_side": "right",
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+ "sep_token": "[SEP]",
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+ "stride": 0,
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+ "strip_accents": null,
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+ "tokenize_chinese_chars": true,
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+ "tokenizer_class": "BertTokenizer",
63
+ "truncation_side": "right",
64
+ "truncation_strategy": "longest_first",
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+ "unk_token": "[UNK]"
66
+ }
vocab.txt ADDED
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