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---
base_model: mini1013/master_domain
library_name: setfit
metrics:
- accuracy
pipeline_tag: text-classification
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: 폴미첼 프리즈 앤 샤인 슈퍼 스프레이 250ml x 3개 단일상품 (#M)11st>헤어케어>헤어스프레이>헤어스프레이 11st > 뷰티
> 헤어케어 > 헤어스프레이
- text: 댕기머리 뉴골드 새치머리용 한방 칼라 크림 염색약 염색제 5호 4개 Coupang > 뷰티 > 헤어 > 염색/파마 > 염색/헤어컬러
> 한방염색제(새치);(#M)쿠팡 홈>뷰티>헤어>염색/파마>염색/헤어컬러>한방염색제(새치) Coupang > 뷰티 > 헤어 > 염색/파마 >
염색/헤어컬러 > 한방염색제(새치)
- text: 갸스비 스타일링 왁스 익사이팅 하드 80g MinSellAmount (#M)바디/헤어>헤어스타일링>헤어왁스 Gmarket > 뷰티 >
바디/헤어 > 헤어스타일링 > 헤어왁스
- text: 이지엔 쉐이킹 푸딩 헤어칼라 6.61(멋내기용-스모키 애쉬블러썸) (#M)홈>헤어케어>염색약>멋내기 염색 Naverstore > 화장품/미용
> 헤어스타일링 > 염색약
- text: '[웰라] 아이미 앱솔루트 셋 300ml LotteOn > 뷰티 > 헤어/바디 > 헤어스타일링 > 헤어스프레이 LotteOn > 뷰티
> 헤어/바디 > 헤어스타일링 > 헤어스프레이'
inference: true
model-index:
- name: SetFit with mini1013/master_domain
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: Unknown
type: unknown
split: test
metrics:
- type: accuracy
value: 0.8061538461538461
name: Accuracy
---
# SetFit with mini1013/master_domain
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.
The model has been trained using an efficient few-shot learning technique that involves:
1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
2. Training a classification head with features from the fine-tuned Sentence Transformer.
## Model Details
### Model Description
- **Model Type:** SetFit
- **Sentence Transformer body:** [mini1013/master_domain](https://huggingface.co/mini1013/master_domain)
- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
- **Maximum Sequence Length:** 512 tokens
- **Number of Classes:** 7 classes
<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
### Model Labels
| Label | Examples |
|:------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 6 | <ul><li>'이희 마블 에센스 헤어 팩트 블랙 본품14g / 흑채 상세페이지 참조 (#M)쿠팡 홈>뷰티>헤어>염색/파마>헤어메이크업>흑채/증모제 Coupang > 뷰티 > 헤어 > 염색/파마 > 헤어메이크업 > 흑채/증모제'</li><li>'[TS]리뉴얼 흑채23g/식물성펄프사용,순간증모제,대머리커버 검정 (#M)GSSHOP>뷰티>헤어케어>탈모케어 GSSHOP > 뷰티 > 헤어케어 > 탈모케어'</li><li>'이희 마블 에센스 헤어 팩트 다크브라운 본품1+리필2 (#M)홈>화장품/미용>헤어케어>탈모케어 Naverstore > 화장품/미용 > 헤어케어 > 탈모케어'</li></ul> |
| 2 | <ul><li>'아모스 아미노 매직 셋팅 펌 / 노멀 / 다운펌 / 스트레이트 매직약 1제노멀 2제 크림타입 (#M)홈>화장품/미용>헤어스타일링>파마약>스트레이트 Naverstore > 화장품/미용 > 헤어스타일링 > 파마약 > 스트레이트'</li><li>'아모스 아미노 매직셋팅펌 노멀 400ml+크림 500ml (#M)11st>헤어케어>파마약>파마약 11st > 뷰티 > 헤어케어 > 파마약 > 파마약'</li><li>'[눙크] 듀이트리 굿 릴랙스 애프터 수딩 패치 15g ssg > 뷰티 > 스킨케어 > 마스크/팩 > 아이패치 ssg > 뷰티 > 스킨케어 > 마스크/팩 > 아이패치'</li></ul> |
| 5 | <ul><li>'(2개)꽃을든남자 케라틴 실크프로테인 헤어젤 500ml MinSellAmount (#M)바디/헤어>헤어스타일링>헤어젤 Gmarket > 뷰티 > 바디/헤어 > 헤어스타일링 > 헤어젤'</li><li>'아베다 맨 퓨어 포먼스 그루밍 클레이 75ml (#M)11st>헤어케어>샴푸>일반 11st > 뷰티 > 헤어케어 > 샴푸 > 일반'</li><li>'아베다 - 맨 퓨어 포맨스 리퀴드 포마드 200ml/6.7oz ssg > 뷰티 > 헤어/바디 > 헤어케어 > 헤어앰플 ssg > 뷰티 > 헤어/바디 > 헤어케어 > 헤어앰플'</li></ul> |
| 0 | <ul><li>'로레알 뉴앙셀 보태닉 헤어 매니큐어 150g 왁싱 코팅 내츄럴브라운다크 (#M)11st>헤어케어>염색약>크림염색약 11st > 뷰티 > 헤어케어 > 염색약 > 크림염색약'</li><li>'사이오스 NEW 올레오 크림 프리미엄 헤어 컬러 1B 크리스탈베이지 3개 LotteOn > 뷰티 > 헤어/바디 > 헤어케어 > 트리트먼트/헤어팩 LotteOn > 뷰티 > 헤어/바디 > 헤어케어 > 트리트먼트/헤어팩'</li><li>'로레알파리 매직 리터치 75 ml1433989 10 브라운 x 5개143398910 LotteOn > 뷰티 > 헤어/바디 > 헤어스타일링 > 염색/매니큐어 LotteOn > 뷰티 > 헤어/바디 > 헤어스타일링 > 염색/매니큐어'</li></ul> |
| 4 | <ul><li>'핫템 미장센 스타일케어 헤어스프레이 300ml - O 화이트플로럴 (#M)SSG.COM/스킨케어/클렌징/클렌징오일 ssg > 뷰티 > 스킨케어 > 클렌징 > 클렌징오일'</li><li>'비레디 에어리 헤어 스프레이 LotteOn > 뷰티 > 헤어/바디 > 헤어스타일링 > 컬크림 LotteOn > 뷰티 > 헤어/바디 > 헤어스타일링 > 컬크림'</li><li>'[밀본] 밀본 니제르 홀드핏 베일 180g (#M)홈>헤어 스타일링 Naverstore > 화장품/미용 > 헤어스타일링 > 헤어스프레이'</li></ul> |
| 1 | <ul><li>'컬링 에센스 150ml 1+1 (#M)뷰티>헤어/바디/미용기기>헤어케어>에센스/앰플/오일 CJmall > 뷰티 > 헤어/바디/미용기기 > 헤어케어 > 트리트먼트/팩/마스크'</li><li>'미쟝센 스테이지 컬링에센스 2X 150ml 1개 01_미쟝센 스테이지 컬링에센스 2X 150ml 1개 위메프 > 생활·주방·반려동물 > 바디/헤어 > 샴푸/린스/헤어케어 > 트리트먼트;위메프 > 뷰티 > 바디/헤어 > 헤어염색/파마/왁스 > 염색약;위메프 > 생활·주방·반려동물 > 바디/헤어 > 샴푸/린스/헤어케어 > 샴푸/린스;위메프 > 생활·주방·반려동물 > 바디/헤어 > 바디케어/워시/제모;(#M)위메프 > 생활·주방용품 > 바디/헤어 > 샴푸/린스/헤어케어 > 트리트먼트 위메프 > 뷰티 > 바디/헤어 > 바디케어/워시/제모 > 바디워시/스크럽'</li><li>'[현대백화점][VDL] 스킨프로 미스트 아쿠아 밤 브이디엘 스킨프로 미스트 아쿠아 밤 (#M)홈>화장품/미용>베이스메이크업>베이스메이크업세트 Naverstore > 화장품/미용 > 베이스메이크업 > 베이스메이크업세트'</li></ul> |
| 3 | <ul><li>'리르 퀵 헤어 커버 쿠션 빈모 새치커버 [0006]헤어쿠션_브라운 (#M)11st>헤어케어>탈모/두피관리제>클리닉용품 기타 11st > 뷰티 > 헤어케어 > 탈모/두피관리제'</li><li>'[12월기획]비레디 헤어라인 커버스틱 다크브라운 (#M)GSSHOP>뷰티>스킨케어>스킨케어세트 GSSHOP > 뷰티 > 스킨케어 > 뷰티 합포장'</li><li>'마몽드 팡팡 헤어 섀도우 - 3.5g/택1 3호 레디쉬 브라운 화장품/향수>립케어/블러셔>블러셔/볼터치;(#M)화장품/향수>색조메이크업>블러셔 Gmarket > 뷰티 > 화장품/향수 > 색조메이크업 > 블러셔'</li></ul> |
## Evaluation
### Metrics
| Label | Accuracy |
|:--------|:---------|
| **all** | 0.8062 |
## Uses
### Direct Use for Inference
First install the SetFit library:
```bash
pip install setfit
```
Then you can load this model and run inference.
```python
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("mini1013/master_cate_bt_top12_test")
# Run inference
preds = model("폴미첼 프리즈 앤 샤인 슈퍼 스프레이 250ml x 3개 단일상품 (#M)11st>헤어케어>헤어스프레이>헤어스프레이 11st > 뷰티 > 헤어케어 > 헤어스프레이")
```
<!--
### Downstream Use
*List how someone could finetune this model on their own dataset.*
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Set Metrics
| Training set | Min | Median | Max |
|:-------------|:----|:--------|:----|
| Word count | 11 | 21.3486 | 60 |
| Label | Training Sample Count |
|:------|:----------------------|
| 0 | 50 |
| 1 | 50 |
| 2 | 50 |
| 3 | 50 |
| 4 | 50 |
| 5 | 50 |
| 6 | 50 |
### Training Hyperparameters
- batch_size: (64, 64)
- num_epochs: (30, 30)
- max_steps: -1
- sampling_strategy: oversampling
- num_iterations: 100
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- l2_weight: 0.01
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: False
### Training Results
| Epoch | Step | Training Loss | Validation Loss |
|:-------:|:-----:|:-------------:|:---------------:|
| 0.0018 | 1 | 0.4121 | - |
| 0.0914 | 50 | 0.4364 | - |
| 0.1828 | 100 | 0.4222 | - |
| 0.2742 | 150 | 0.395 | - |
| 0.3656 | 200 | 0.3538 | - |
| 0.4570 | 250 | 0.3385 | - |
| 0.5484 | 300 | 0.3178 | - |
| 0.6399 | 350 | 0.2704 | - |
| 0.7313 | 400 | 0.2307 | - |
| 0.8227 | 450 | 0.1968 | - |
| 0.9141 | 500 | 0.1908 | - |
| 1.0055 | 550 | 0.1629 | - |
| 1.0969 | 600 | 0.1568 | - |
| 1.1883 | 650 | 0.1495 | - |
| 1.2797 | 700 | 0.1378 | - |
| 1.3711 | 750 | 0.1215 | - |
| 1.4625 | 800 | 0.0961 | - |
| 1.5539 | 850 | 0.0704 | - |
| 1.6453 | 900 | 0.0564 | - |
| 1.7367 | 950 | 0.0565 | - |
| 1.8282 | 1000 | 0.0549 | - |
| 1.9196 | 1050 | 0.0489 | - |
| 2.0110 | 1100 | 0.0484 | - |
| 2.1024 | 1150 | 0.0471 | - |
| 2.1938 | 1200 | 0.042 | - |
| 2.2852 | 1250 | 0.0456 | - |
| 2.3766 | 1300 | 0.0329 | - |
| 2.4680 | 1350 | 0.0308 | - |
| 2.5594 | 1400 | 0.0262 | - |
| 2.6508 | 1450 | 0.0317 | - |
| 2.7422 | 1500 | 0.0267 | - |
| 2.8336 | 1550 | 0.0248 | - |
| 2.9250 | 1600 | 0.0175 | - |
| 3.0165 | 1650 | 0.0113 | - |
| 3.1079 | 1700 | 0.0111 | - |
| 3.1993 | 1750 | 0.0096 | - |
| 3.2907 | 1800 | 0.0054 | - |
| 3.3821 | 1850 | 0.004 | - |
| 3.4735 | 1900 | 0.0035 | - |
| 3.5649 | 1950 | 0.0015 | - |
| 3.6563 | 2000 | 0.0013 | - |
| 3.7477 | 2050 | 0.0015 | - |
| 3.8391 | 2100 | 0.0009 | - |
| 3.9305 | 2150 | 0.0009 | - |
| 4.0219 | 2200 | 0.0007 | - |
| 4.1133 | 2250 | 0.0007 | - |
| 4.2048 | 2300 | 0.0006 | - |
| 4.2962 | 2350 | 0.0011 | - |
| 4.3876 | 2400 | 0.0004 | - |
| 4.4790 | 2450 | 0.0004 | - |
| 4.5704 | 2500 | 0.0002 | - |
| 4.6618 | 2550 | 0.0001 | - |
| 4.7532 | 2600 | 0.0001 | - |
| 4.8446 | 2650 | 0.0001 | - |
| 4.9360 | 2700 | 0.0001 | - |
| 5.0274 | 2750 | 0.0001 | - |
| 5.1188 | 2800 | 0.0001 | - |
| 5.2102 | 2850 | 0.0001 | - |
| 5.3016 | 2900 | 0.0001 | - |
| 5.3931 | 2950 | 0.0001 | - |
| 5.4845 | 3000 | 0.0001 | - |
| 5.5759 | 3050 | 0.0 | - |
| 5.6673 | 3100 | 0.0001 | - |
| 5.7587 | 3150 | 0.0 | - |
| 5.8501 | 3200 | 0.0 | - |
| 5.9415 | 3250 | 0.0 | - |
| 6.0329 | 3300 | 0.0 | - |
| 6.1243 | 3350 | 0.0 | - |
| 6.2157 | 3400 | 0.0 | - |
| 6.3071 | 3450 | 0.0 | - |
| 6.3985 | 3500 | 0.0 | - |
| 6.4899 | 3550 | 0.0 | - |
| 6.5814 | 3600 | 0.0 | - |
| 6.6728 | 3650 | 0.0 | - |
| 6.7642 | 3700 | 0.0 | - |
| 6.8556 | 3750 | 0.0 | - |
| 6.9470 | 3800 | 0.0 | - |
| 7.0384 | 3850 | 0.0001 | - |
| 7.1298 | 3900 | 0.0 | - |
| 7.2212 | 3950 | 0.0 | - |
| 7.3126 | 4000 | 0.0 | - |
| 7.4040 | 4050 | 0.0 | - |
| 7.4954 | 4100 | 0.0 | - |
| 7.5868 | 4150 | 0.0 | - |
| 7.6782 | 4200 | 0.0 | - |
| 7.7697 | 4250 | 0.0 | - |
| 7.8611 | 4300 | 0.0 | - |
| 7.9525 | 4350 | 0.0 | - |
| 8.0439 | 4400 | 0.0 | - |
| 8.1353 | 4450 | 0.0 | - |
| 8.2267 | 4500 | 0.0 | - |
| 8.3181 | 4550 | 0.0 | - |
| 8.4095 | 4600 | 0.0002 | - |
| 8.5009 | 4650 | 0.0 | - |
| 8.5923 | 4700 | 0.0 | - |
| 8.6837 | 4750 | 0.0 | - |
| 8.7751 | 4800 | 0.0 | - |
| 8.8665 | 4850 | 0.0 | - |
| 8.9580 | 4900 | 0.0 | - |
| 9.0494 | 4950 | 0.0 | - |
| 9.1408 | 5000 | 0.0 | - |
| 9.2322 | 5050 | 0.0 | - |
| 9.3236 | 5100 | 0.0 | - |
| 9.4150 | 5150 | 0.0 | - |
| 9.5064 | 5200 | 0.0 | - |
| 9.5978 | 5250 | 0.0 | - |
| 9.6892 | 5300 | 0.0 | - |
| 9.7806 | 5350 | 0.0 | - |
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| 12.2486 | 6700 | 0.0007 | - |
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| 12.4314 | 6800 | 0.0285 | - |
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| 12.6143 | 6900 | 0.0047 | - |
| 12.7057 | 6950 | 0.003 | - |
| 12.7971 | 7000 | 0.0047 | - |
| 12.8885 | 7050 | 0.0027 | - |
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| 29.9817 | 16400 | 0.0 | - |
### Framework Versions
- Python: 3.10.12
- SetFit: 1.1.0
- Sentence Transformers: 3.3.1
- Transformers: 4.44.2
- PyTorch: 2.2.0a0+81ea7a4
- Datasets: 3.2.0
- Tokenizers: 0.19.1
## Citation
### BibTeX
```bibtex
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}
```
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