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mini1013
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master_cate_bt_top10_test

Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results
Model card Files Community
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Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +541 -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
@@ -0,0 +1,541 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 센카 퍼펙트 휩 클렌징 폼 리뉴얼 120g × 10개 (#M)쿠팡 홈>싱글라이프>샤워/세안>클렌징>폼/젤/비누 Coupang > 뷰티
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+ > 클렌징/필링 > 클렌징 폼
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+ - text: 프로필링 소프트젤 100ml 피부 세안제 클렌징 필링 (#M)홈>화장품/미용>클렌징>스크럽/필링 Naverstore > 화장품/미용
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+ > 클렌징 > 스크럽/필링
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+ - text: 센카 퍼펙트 휩 페이셜 워시 대용량 클렌징 폼 150g × 3개 (#M)쿠팡 홈>싱글라이프>샤워/세안>클렌징>폼/젤/비누 Coupang
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+ > 뷰티 > 클렌징/필링 > 클렌징 폼
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+ - text: 센카 퍼펙트휩 2개+아크네케어 2개 센카 퍼펙트휩 2개+아크네케어 2개 LotteOn > 뷰티 > 남성화장품 > 클렌징 LotteOn
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+ > 뷰티 > 남성화장품 > 클렌징
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+ - text: '[20% ]한스킨 모공앰플체험딜 2500원 91% 外 비비크림/컨실러/클렌징오일/선크림/기초 전품목 32.블랙헤드 클렌징 티슈_블랙헤드
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+ 클렌징 티슈 100매 [GH990850] 쇼킹딜 홈>뷰티>선케어/메이크업>페이스메이크업;11st>뷰티>선케어/메이크업>페이스메이크업;11st>메이크업>페이스메이크업>BB크림;11st
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+ > 뷰티 > 메이크업 > 페이스메이크업 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 페이스메이크업'
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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: 0.9232323232323232
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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:** 7 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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+ | 6 | <ul><li>'남자클렌징폼 알로에성분 수분밸런스 세면도구 미셀라 클클 워터 미셀라워터100ml (#M)위메프 > 뷰티 > 이미용소품/기기 > 클렌징소품 > 브러쉬/진동클렌저 위메프 > 뷰티 > 이미용소품/기기 > 클렌징소품 > 브러쉬/진동클렌저'</li><li>'차앤박 CNP 에이클린 퓨리파잉 포밍 클렌저 145mL LotteOn > 뷰티 > 남성화장품 > 남성화장품세트 LotteOn > 뷰티 > 남성화장품 > 남성화장품세트'</li><li>'[클린앤드클리어] 딥 액��� 블랙헤드 데일리 클렌저 100gx2 CC딥액션블랙헤드클렌저100gx2 (#M)뷰티>화장품/향수>스킨케어>로션/에멀전 CJmall > 뷰티 > 화장품/향수 > 스킨케어 > 에센스/세럼/오일'</li></ul> |
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+ | 2 | <ul><li>'(키엘) 미드나잇 리커버리 보태니컬 클렌징 오일 - 모든 피부용 --85ml/2.8oz ssg > 뷰티 > 스킨케어 > 스킨/토너/미스트 > 스킨/토너 LOREAL > Ssg > 키엘 > Branded > 키엘'</li><li>'마녀공장 퓨어 클렌징 오일 141238 200ml x 3개 (#M)11st>바디케어>바디미스트>바디미스트 11st > 뷰티 > 바디케어 > 바디미스트'</li><li>'[정품 세럼쿠션 & 비타민 크림 샘플 증정] 인텐시브 세럼 파운데이션 세트 쿨 아이보리 ssg > 뷰티 > 메이크업 > 립메이크업;ssg > 뷰티 > 메이크업 > 베이스메이크업;ssg > 뷰티 > 스킨케어 > 스킨/토너;ssg > 뷰티 > 메이크업 > 베이스메이크업 > 파운데이션;SSG.COM/메이크업/베이스메이크업/리퀴드파운데이션;ssg > 뷰티 > 메이크업 > 아이메이크업 > 아이섀도우;ssg > 뷰티 > 명품화장품 > 메이크업 ssg > 뷰티 > 메이크업 > 아이메이크업'</li></ul> |
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+ | 5 | <ul><li>'[라끄베르] 딥 앤 모이스트 클렌징 티슈 05_클렌징 티슈 80매 홈>5월 행사;홈>6월 행사!;홈>전체상품;(#M)홈>라끄베르 Naverstore > 화장품/미용 > 클렌징 > 클렌징티슈'</li><li>'토니모리 프로클린 소프트 클렌징 티슈 1+1 (#M)홈>화장품/미용>클렌징>클렌징티슈 Naverstore > 화장품/미용 > 클렌징 > 클렌징티슈'</li><li>'[소미Pick! 코스알엑스] 원스텝 스킨패드 3종 / NEW 더 비타민C 세럼 外 포어리스 패드 11st>뷰티>스킨케어>스킨/로션;11st>스킨케어>스킨/토너>스킨/토너;11st Hour Event > 패션/뷰티 > 뷰티 > 스킨케어 > 스킨/로션 11st Hour Event > 패션/뷰티 > 뷰티 > 스킨케어 > 스킨/로션'</li></ul> |
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+ | 0 | <ul><li>'[일리윤] 프레쉬 모이스춰 립앤아이리무버 100ml 3개 단일상품 (#M)위메프 > 뷰티 > 네일케어 > 네일리무버 > 네일리무버 위메프 > 뷰티 > 네일케어 > 네일리무버 > 네일리무버'</li><li>'키스미 히로인메이크 스피디 마스카라 리무버 6.마스카라 리무버(K407A) (#M)화장품/향수>색조메이크업>마스카라 Gmarket > 뷰티 > 화장품/향수 > 색조메이크업 > 마스카라'</li><li>'랑콤 비파실 200ml ssg > 뷰티 > 스킨케어 > 스킨/토너 ssg > 뷰티 > 스킨케어 > 스킨/토너'</li></ul> |
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+ | 4 | <ul><li>'라떼 다 토일레테 250ml 화이트_Free (#M)뷰티>헤어/바디/미용기기>바디케어>바디로션/크림 CJmall > 뷰티 > 화장품/향수 > 향수/홈프래그런스 > 디퓨저/방향제'</li><li>'마몽드 트리플 멀티 클렌징 크림 190ml (#M)GSSHOP>뷰티>스킨케어>스킨케어세트 GSSHOP > 뷰티 > 스킨케어 > 스킨케어세트'</li><li>'마몽드 트리플 멀티 클렌징 크림 190ml MinSellAmount (#M)화장품/향수>클렌징/필링>클렌징크림 Gmarket > 뷰티 > 화장품/향수 > 클렌징/필링 > 클렌징크림'</li></ul> |
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+ | 1 | <ul><li>'클라란스 컴포트 스크럽 - 너리싱 오일 스크럽50ml/1.7oz (#M)홈>스트로베리넷>향수|디퓨저>향수|디퓨저 전체보기 HMALL > 뷰티 > 스킨케어 > 스크럽/필링'</li><li>'닥터지 레드 블레미쉬 수딩 크림 토너 폼 에멀전 필링 젤 03.브라이트닝 필링 젤 120g (#M)11st>스킨케어>앰플>앰플 11st > 뷰티 > 스킨케어 > 앰플'</li><li>'데쌍브르 올인원 각질 트러블 흔적 시카 미백 아하 바하 스피큘 해초 약초 니들필링50g 30데이즈(필링크림30g+앰플30ea) (#M)화장품/미용>클렌징>스크럽/필링 Naverstore > 화장품/미용 > 클렌징 > 스크럽/필링'</li></ul> |
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+ | 3 | <ul><li>'산타마리아노벨라 아쿠아 디 로즈 미셀라 워터 200ml 투명_F (#M)화장품/미용>클렌징>클렌징워터 Naverstore > 화장품/미용 > 클렌징 > 클렌징워터'</li><li>'[쿠폰+T11%] 라네즈 퍼펙트리뉴 유스 레티놀 프로 꿀잠 잠옷 증정!/1밤1레티놀/라네즈레티놀 35. 라네즈 워터뱅크 아이젤 25ml_선택완료 쇼킹딜 홈>뷰티>스킨케어>스킨/로션;11st>스킨케어>스킨/토너>스킨/토너;쇼킹딜 홈>뷰티>선케어/메이크업>선블록;11st>뷰티>선케어/메이크업>선블록;11st > 뷰티 > 스킨케어 > 스킨/토너;(#M)11st>뷰티>스킨케어>스킨/로션 11st Hour Event > 패션/뷰티 > 뷰티 > 스킨케어 > 스킨/로션'</li><li>'[클린앤클리어] 미셀라 워터 100ml x2 (#M)GSSHOP>뷰티>클렌징>클렌징폼 GSSHOP > 뷰티 > 클렌징 > 클렌징폼'</li></ul> |
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+
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+ ## 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** | 0.9232 |
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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
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+ 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_bt_top10_test")
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+ # Run inference
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+ preds = model("프로필링 소프트젤 100ml 피부 세안제 클렌징 필링 (#M)홈>화장품/미용>클렌징>스크럽/필링 Naverstore > 화장품/미용 > 클렌징 > 스크럽/필링")
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+ ```
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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 | 21.9571 | 61 |
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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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+
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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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+ | 0.0018 | 1 | 0.4528 | - |
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+ | 0.0914 | 50 | 0.4525 | - |
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+ | 0.1828 | 100 | 0.4612 | - |
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+ | 0.2742 | 150 | 0.4424 | - |
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+ | 0.3656 | 200 | 0.4291 | - |
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176
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177
+ | 0.6399 | 350 | 0.2943 | - |
178
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179
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180
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181
+ | 1.0055 | 550 | 0.253 | - |
182
+ | 1.0969 | 600 | 0.2367 | - |
183
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184
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185
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186
+ | 1.4625 | 800 | 0.1786 | - |
187
+ | 1.5539 | 850 | 0.1609 | - |
188
+ | 1.6453 | 900 | 0.1472 | - |
189
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190
+ | 1.8282 | 1000 | 0.1213 | - |
191
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192
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193
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194
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195
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196
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197
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198
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199
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200
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201
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+ | 3.5649 | 1950 | 0.0002 | - |
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+ | 3.8391 | 2100 | 0.0001 | - |
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224
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225
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226
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227
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228
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229
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230
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231
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232
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234
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235
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236
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237
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+ | 6.3071 | 3450 | 0.0006 | - |
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241
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242
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243
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244
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245
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246
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247
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248
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249
+ | 7.2212 | 3950 | 0.0001 | - |
250
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256
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259
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275
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+ | 11.5174 | 6300 | 0.0 | - |
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+ | 11.8830 | 6500 | 0.0 | - |
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+ | 12.3400 | 6750 | 0.0001 | - |
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+ | 12.6143 | 6900 | 0.0 | - |
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+ | 12.7057 | 6950 | 0.0003 | - |
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+ | 12.7971 | 7000 | 0.0001 | - |
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+ | 12.8885 | 7050 | 0.0004 | - |
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+ | 12.9799 | 7100 | 0.0018 | - |
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+ | 13.0713 | 7150 | 0.0002 | - |
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+ | 13.1627 | 7200 | 0.0 | - |
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+ | 13.2541 | 7250 | 0.0001 | - |
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+ | 13.3455 | 7300 | 0.0 | - |
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+ | 13.4369 | 7350 | 0.0 | - |
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+ | 13.5283 | 7400 | 0.0001 | - |
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+ | 13.6197 | 7450 | 0.0 | - |
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+ | 13.7112 | 7500 | 0.0 | - |
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+ | 13.8026 | 7550 | 0.0 | - |
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+ | 13.8940 | 7600 | 0.0 | - |
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+ | 13.9854 | 7650 | 0.0 | - |
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+ | 14.0768 | 7700 | 0.0 | - |
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+ | 14.1682 | 7750 | 0.0 | - |
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+ | 14.3510 | 7850 | 0.0 | - |
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+ | 14.4424 | 7900 | 0.0 | - |
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+ | 14.5338 | 7950 | 0.0 | - |
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+ | 14.6252 | 8000 | 0.0 | - |
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+ | 16.3620 | 8950 | 0.0 | - |
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+ | 16.4534 | 9000 | 0.0 | - |
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+ | 16.5448 | 9050 | 0.0 | - |
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+ | 16.7276 | 9150 | 0.0 | - |
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+ | 16.8190 | 9200 | 0.0 | - |
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+ | 16.9104 | 9250 | 0.0 | - |
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+ | 17.0018 | 9300 | 0.0 | - |
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+ | 17.0932 | 9350 | 0.0 | - |
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+ | 17.1846 | 9400 | 0.0 | - |
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+ | 17.2761 | 9450 | 0.0 | - |
360
+ | 17.3675 | 9500 | 0.0 | - |
361
+ | 17.4589 | 9550 | 0.0002 | - |
362
+ | 17.5503 | 9600 | 0.0011 | - |
363
+ | 17.6417 | 9650 | 0.0003 | - |
364
+ | 17.7331 | 9700 | 0.0 | - |
365
+ | 17.8245 | 9750 | 0.0001 | - |
366
+ | 17.9159 | 9800 | 0.0001 | - |
367
+ | 18.0073 | 9850 | 0.0002 | - |
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+ | 18.0987 | 9900 | 0.0003 | - |
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+ | 18.1901 | 9950 | 0.0 | - |
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+ | 18.2815 | 10000 | 0.0 | - |
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+ | 18.3729 | 10050 | 0.0 | - |
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+ | 18.4644 | 10100 | 0.0 | - |
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+ | 18.5558 | 10150 | 0.0002 | - |
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+ | 18.6472 | 10200 | 0.0002 | - |
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+ | 18.7386 | 10250 | 0.0 | - |
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+ | 18.8300 | 10300 | 0.0004 | - |
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+ | 19.0128 | 10400 | 0.0 | - |
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384
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+ | 19.6527 | 10750 | 0.0002 | - |
386
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388
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390
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392
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398
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399
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400
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401
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402
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403
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404
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405
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406
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407
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408
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409
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410
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411
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412
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413
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414
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415
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416
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417
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419
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420
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421
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422
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+ | 23.7660 | 13000 | 0.0 | - |
431
+ | 23.8574 | 13050 | 0.0 | - |
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433
+ | 24.0402 | 13150 | 0.0 | - |
434
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435
+ | 24.2230 | 13250 | 0.0 | - |
436
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437
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438
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439
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440
+ | 24.6801 | 13500 | 0.0001 | - |
441
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442
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443
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447
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448
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449
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450
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451
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452
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453
+ | 25.8684 | 14150 | 0.0 | - |
454
+ | 25.9598 | 14200 | 0.0 | - |
455
+ | 26.0512 | 14250 | 0.0 | - |
456
+ | 26.1426 | 14300 | 0.0 | - |
457
+ | 26.2340 | 14350 | 0.0 | - |
458
+ | 26.3254 | 14400 | 0.0 | - |
459
+ | 26.4168 | 14450 | 0.0 | - |
460
+ | 26.5082 | 14500 | 0.0 | - |
461
+ | 26.5996 | 14550 | 0.0 | - |
462
+ | 26.6910 | 14600 | 0.0 | - |
463
+ | 26.7824 | 14650 | 0.0 | - |
464
+ | 26.8739 | 14700 | 0.0 | - |
465
+ | 26.9653 | 14750 | 0.0 | - |
466
+ | 27.0567 | 14800 | 0.0 | - |
467
+ | 27.1481 | 14850 | 0.0 | - |
468
+ | 27.2395 | 14900 | 0.0 | - |
469
+ | 27.3309 | 14950 | 0.0 | - |
470
+ | 27.4223 | 15000 | 0.0 | - |
471
+ | 27.5137 | 15050 | 0.0 | - |
472
+ | 27.6051 | 15100 | 0.0 | - |
473
+ | 27.6965 | 15150 | 0.0 | - |
474
+ | 27.7879 | 15200 | 0.0 | - |
475
+ | 27.8793 | 15250 | 0.0 | - |
476
+ | 27.9707 | 15300 | 0.0 | - |
477
+ | 28.0622 | 15350 | 0.0 | - |
478
+ | 28.1536 | 15400 | 0.0 | - |
479
+ | 28.2450 | 15450 | 0.0 | - |
480
+ | 28.3364 | 15500 | 0.0 | - |
481
+ | 28.4278 | 15550 | 0.0 | - |
482
+ | 28.5192 | 15600 | 0.0 | - |
483
+ | 28.6106 | 15650 | 0.0 | - |
484
+ | 28.7020 | 15700 | 0.0 | - |
485
+ | 28.7934 | 15750 | 0.0 | - |
486
+ | 28.8848 | 15800 | 0.0 | - |
487
+ | 28.9762 | 15850 | 0.0 | - |
488
+ | 29.0676 | 15900 | 0.0 | - |
489
+ | 29.1590 | 15950 | 0.0 | - |
490
+ | 29.2505 | 16000 | 0.0 | - |
491
+ | 29.3419 | 16050 | 0.0 | - |
492
+ | 29.4333 | 16100 | 0.0 | - |
493
+ | 29.5247 | 16150 | 0.0 | - |
494
+ | 29.6161 | 16200 | 0.0 | - |
495
+ | 29.7075 | 16250 | 0.0 | - |
496
+ | 29.7989 | 16300 | 0.0 | - |
497
+ | 29.8903 | 16350 | 0.0 | - |
498
+ | 29.9817 | 16400 | 0.0 | - |
499
+
500
+ ### Framework Versions
501
+ - Python: 3.10.12
502
+ - SetFit: 1.1.0
503
+ - Sentence Transformers: 3.3.1
504
+ - Transformers: 4.44.2
505
+ - PyTorch: 2.2.0a0+81ea7a4
506
+ - Datasets: 3.2.0
507
+ - Tokenizers: 0.19.1
508
+
509
+ ## Citation
510
+
511
+ ### BibTeX
512
+ ```bibtex
513
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
514
+ doi = {10.48550/ARXIV.2209.11055},
515
+ url = {https://arxiv.org/abs/2209.11055},
516
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
517
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
518
+ title = {Efficient Few-Shot Learning Without Prompts},
519
+ publisher = {arXiv},
520
+ year = {2022},
521
+ copyright = {Creative Commons Attribution 4.0 International}
522
+ }
523
+ ```
524
+
525
+ <!--
526
+ ## Glossary
527
+
528
+ *Clearly define terms in order to be accessible across audiences.*
529
+ -->
530
+
531
+ <!--
532
+ ## Model Card Authors
533
+
534
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
535
+ -->
536
+
537
+ <!--
538
+ ## Model Card Contact
539
+
540
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
541
+ -->
config.json ADDED
@@ -0,0 +1,29 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "mini1013/master_item_bt_test_flat_top",
3
+ "architectures": [
4
+ "RobertaModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "classifier_dropout": null,
9
+ "eos_token_id": 2,
10
+ "gradient_checkpointing": false,
11
+ "hidden_act": "gelu",
12
+ "hidden_dropout_prob": 0.1,
13
+ "hidden_size": 768,
14
+ "initializer_range": 0.02,
15
+ "intermediate_size": 3072,
16
+ "layer_norm_eps": 1e-05,
17
+ "max_position_embeddings": 514,
18
+ "model_type": "roberta",
19
+ "num_attention_heads": 12,
20
+ "num_hidden_layers": 12,
21
+ "pad_token_id": 1,
22
+ "position_embedding_type": "absolute",
23
+ "tokenizer_class": "BertTokenizer",
24
+ "torch_dtype": "float32",
25
+ "transformers_version": "4.44.2",
26
+ "type_vocab_size": 1,
27
+ "use_cache": true,
28
+ "vocab_size": 32000
29
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.3.1",
4
+ "transformers": "4.44.2",
5
+ "pytorch": "2.2.0a0+81ea7a4"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": "cosine"
10
+ }
config_setfit.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "labels": null,
3
+ "normalize_embeddings": false
4
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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