Push model using huggingface_hub.

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 768,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -0,0 +1,241 @@
+---
+base_model: mini1013/master_domain
+library_name: setfit
+metrics:
+- metric
+pipeline_tag: text-classification
+tags:
+- setfit
+- sentence-transformers
+- text-classification
+- generated_from_setfit_trainer
+widget:
+- text: 여성 가방 숄더백 미니 크로스백 퀼팅백 체인백 토트백 미니백 여자 핸드백 구름백 클러치백 직장인 백팩 프리아_카멜 더블유팝
+- text: 국내 잔스포츠 백팩 슈퍼브레이크 4QUT 블랙 학생 여성 가벼운 가방 캠핑 여행 당일  가원
+- text: 국내생산 코튼 양줄면주머니 미니&에코 주머니 7종 학원 학교 만들기수업 양줄주머니_14cmX28cm(J14) 명성패키지
+- text: 웨빙 플라워 스트랩 레디백 길이조절 가방끈 어깨끈 리폼 3-플라워가방끈-흰색 이백프로
+- text: 엔비조네/가방끈/가방끈리폼/가죽끈/크로스끈/숄더끈/스트랩 AOR오링25mm_블랙오플_폭11mm *35cm 니켈 엔비조네
+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: metric
+      value: 0.7867699642431466
+      name: Metric
+---
+
+# 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:** 10 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                                                                                                                                                                                                                             |
+|:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 3.0   | <ul><li>'[현대백화점][루이까또즈] MOONMOON(문문) 여성호보백 HR3SO02BL  (주)현대백화점'</li><li>'소프트레더 파스텔 보부상 빅숄더백 휘뚜루마뚜루가방 토드백 블랙_one size 아이디어코리아 주식회사'</li><li>'DRAGON DIFFUSION 드래곤디퓨전 폼폼 더블 점프백 여성 버킷백 8838 드래곤백 다크브라운 (DARK BROWN) 시계1위워치짱'</li></ul> |
+| 7.0   | <ul><li>'디어 4colors_H70301010 (W)퍼플와인 '</li><li>'[마이클코어스][정상가 1080000원] 에밀리아 라지 레더 사첼 35H0GU5S7T2171  신세계몰'</li><li>'칼린 소프트M 10colors _H71307020 (Y)라임네온_one size (주)칼린홍대점'</li></ul>                                                |
+| 1.0   | <ul><li>'마젤란9901 메신저백 크로스백 학생 여행용 가방 백팩 1_MA-9901-BlackPurple(+LK) 더블유팝'</li><li>'마젤란9901 메신저백 크로스백 학생 여행용 가방 백팩 1_MA-9901-D.Gray(+LK) 더블유팝'</li><li>'마젤란9901 메신저백 크로스백 학생 여행용 가방 백팩 1_MA-9901-Black(+LK) 더블유팝'</li></ul>            |
+| 9.0   | <ul><li>'룰루레몬 에브리웨어 벨트 백 Fleece WHTO/GOLD White Opal/Gold - O/S 오늘의원픽'</li><li>'[리본즈] LEMAIRE 남성 숄더백 37408558 블랙_ONE SIZE/단일상품 마리오아울렛몰'</li><li>'[코치][공식] 홀 벨트 백 CU103 WYE [00001] 없음 현대백화점'</li></ul>                               |
+| 0.0   | <ul><li>'가죽가방끈 천연소가죽 가죽 스트랩 32Color 블랙12mm페이던트골드 대성메디칼'</li><li>'[최초가 228,000원][잘모이] 밍크 듀에 퍼 스트랩 LTZ-5205 168688 와인���카이블루 주식회사 미르에셋'</li><li>'[조이그라이슨](강남점) 첼시 스트랩 LW4SX6880_55 GOLD 신세계백화점'</li></ul>                                |
+| 5.0   | <ul><li>'[소마치] 트래블 여권 지갑 파우치 핸드폰 미니 크로스백 카키_체인105cm(키160전후) 주식회사 소마치'</li><li>'비비안웨스트우드 코튼 숄더백 EDGWARE (3컬러) chacoal(당일발송) KHY INTERNATIONAL'</li><li>'남여 공용 미니 메신저백 귀여운 크로스백 학생 미니백 여행 보조 가방 여행용 보조백 아이보리 구공구코리아'</li></ul>         |
+| 2.0   | <ul><li>'메종미네드 MAISON MINED TWO POCKET BACKPACK S OC오피스'</li><li>'백팩01K1280ZSK외1종 블랙 롯데백화점1관'</li><li>'ANC CLASSIC BACKPACK_BLACK BLACK 주식회사 데일리컴퍼니'</li></ul>                                                                       |
+| 4.0   | <ul><li>'[스타벅스]텀블러 가방 컵홀더 데일리 캔버스 에코백 지퍼형_베이지 씨에스 인더스트리'</li><li>'마리떼 FRANCOIS GIRBAUD CLASSIC LOGO ECO BAG natural OS 다함'</li><li>'마크 곤잘레스 Print Eco Bag - 블랙 568032 BLACK_FREE 라임e커머스'</li></ul>                                   |
+| 8.0   | <ul><li>'국내생산 코튼 양줄면주머니 미니&에코 주머니 7종 학원 학교 만들기수업 양줄주머니_20cmX25cm(J20) 명성패키지'</li><li>'조리개 타입 반투명 파우치 보관 신발주머니 주머니 끈주머니 끈파우치 신주머니 여행용 중형(25X35) 정바른 길정'</li><li>'국내생산 코튼 화이트&블랙주머니 학원 학교 주머니만들기 W15_화이트 명성패키지'</li></ul>              |
+| 6.0   | <ul><li>'메종 마르지엘라 타비 스니커즈 S37WS0578 P4291 T1003 EU41(260-265) 보광컴퍼니'</li><li>'[롯데백화점]루이까또즈 클러치백 MO2DL03MDABL  롯데백화점_'</li><li>'깔끔한 여성용 데일리 핸드 스트랩 클러치 가방 남자클러치백  로우마켓'</li></ul>                                                     |
+
+## Evaluation
+
+### Metrics
+| Label   | Metric |
+|:--------|:-------|
+| **all** | 0.7868 |
+
+## 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_ac9")
+# Run inference
+preds = model("웨빙 플라워 스트랩 레디백 길이조절 가방끈 어깨끈 리폼 3-플라워가방끈-흰색 이백프로")
+```
+
+<!--
+### 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   | 3   | 9.6146 | 30  |
+
+| Label | Training Sample Count |
+|:------|:----------------------|
+| 0.0   | 50                    |
+| 1.0   | 17                    |
+| 2.0   | 50                    |
+| 3.0   | 50                    |
+| 4.0   | 50                    |
+| 5.0   | 50                    |
+| 6.0   | 50                    |
+| 7.0   | 50                    |
+| 8.0   | 50                    |
+| 9.0   | 50                    |
+
+### Training Hyperparameters
+- batch_size: (512, 512)
+- num_epochs: (20, 20)
+- max_steps: -1
+- sampling_strategy: oversampling
+- num_iterations: 40
+- body_learning_rate: (2e-05, 2e-05)
+- head_learning_rate: 2e-05
+- loss: CosineSimilarityLoss
+- distance_metric: cosine_distance
+- margin: 0.25
+- end_to_end: False
+- use_amp: False
+- warmup_proportion: 0.1
+- seed: 42
+- eval_max_steps: -1
+- load_best_model_at_end: False
+
+### Training Results
+| Epoch   | Step | Training Loss | Validation Loss |
+|:-------:|:----:|:-------------:|:---------------:|
+| 0.0137  | 1    | 0.4278        | -               |
+| 0.6849  | 50   | 0.3052        | -               |
+| 1.3699  | 100  | 0.1524        | -               |
+| 2.0548  | 150  | 0.0583        | -               |
+| 2.7397  | 200  | 0.0292        | -               |
+| 3.4247  | 250  | 0.0197        | -               |
+| 4.1096  | 300  | 0.0061        | -               |
+| 4.7945  | 350  | 0.0022        | -               |
+| 5.4795  | 400  | 0.0033        | -               |
+| 6.1644  | 450  | 0.0003        | -               |
+| 6.8493  | 500  | 0.0002        | -               |
+| 7.5342  | 550  | 0.0001        | -               |
+| 8.2192  | 600  | 0.0001        | -               |
+| 8.9041  | 650  | 0.0001        | -               |
+| 9.5890  | 700  | 0.0001        | -               |
+| 10.2740 | 750  | 0.0001        | -               |
+| 10.9589 | 800  | 0.0001        | -               |
+| 11.6438 | 850  | 0.0001        | -               |
+| 12.3288 | 900  | 0.0001        | -               |
+| 13.0137 | 950  | 0.0001        | -               |
+| 13.6986 | 1000 | 0.0001        | -               |
+| 14.3836 | 1050 | 0.0001        | -               |
+| 15.0685 | 1100 | 0.0001        | -               |
+| 15.7534 | 1150 | 0.0001        | -               |
+| 16.4384 | 1200 | 0.0001        | -               |
+| 17.1233 | 1250 | 0.0           | -               |
+| 17.8082 | 1300 | 0.0001        | -               |
+| 18.4932 | 1350 | 0.0001        | -               |
+| 19.1781 | 1400 | 0.0001        | -               |
+| 19.8630 | 1450 | 0.0001        | -               |
+
+### Framework Versions
+- Python: 3.10.12
+- SetFit: 1.1.0.dev0
+- Sentence Transformers: 3.1.1
+- Transformers: 4.46.1
+- PyTorch: 2.4.0+cu121
+- Datasets: 2.20.0
+- Tokenizers: 0.20.0
+
+## 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}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

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+{
+  "_name_or_path": "mini1013/master_item_ac",
+  "architectures": [
+    "RobertaModel"
+  ],
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+  "bos_token_id": 0,
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+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "tokenizer_class": "BertTokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 32000
+}

config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "3.1.1",
+    "transformers": "4.46.1",
+    "pytorch": "2.4.0+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

config_setfit.json

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+  "normalize_embeddings": false
+}

model.safetensors

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model_head.pkl

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modules.json

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+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

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+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

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+}

tokenizer_config.json

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+}