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 +1,253 @@
+---
+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: 네스프레소 버츄오 캡슐 머그 멜로지오 1Box (10캡슐) 아이스 라떼 03. 알티시오 제이유
+- text: 맥심 티오피 스위트 아메리카노 200ml  (주)디에이치솔루션
+- text: 굿라이프365 스피아민트 삼각티백 50개입 익모초 삼각티백 50개입 주식회사 굿라이프365
+- text: 칠성사이다 제로 ECO 무라벨 300ml 20pet [음료] 커피음료_맥심티오피심플리스무스로스티라떼360mlx20개 옐로우로켓
+- text: 동서식품 kanu 미니 마일드 로스트 아메리카노 0.9g 카누디카페인 0.9g 100+20(120개입) 강유팩토리
+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: 0.6535632816801699
+      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:** 12 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                                                                                                                                                                                                                     |
+|:------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 10.0  | <ul><li>'라인바싸 탄산수 레몬 500ml 20개 자몽 500ml 20개 에이치앤제이원'</li><li>'라인바싸 탄산수 파인애플 500ml 20입 1박스 (추가)+ 플레인 1박스 동아오츠카주식회사'</li><li>'코카콜라 씨그램 레몬 350mlx24페트 탄산수모음 15_트레비 라임 355mlx24CAN 주식회사대성에프앤비'</li></ul>                         |
+| 8.0   | <ul><li>'맥심 아이스 커피믹스 110T +커피믹스 스틱 2T 콤부차_다농원 콤부차 세븐베리 20T+보틀 주식회사 경일종합식품 케이마트몰'</li><li>'[카누]카누 디카페인 미니 0.9g x 120개입 - 1개 HN 다크 로스트 0.9g 100+텀블러(사은품) 하나엔피그먼트'</li><li>'프렌치카페 카페믹스 스테비아 디카페인 10.3g x 100개입  대은상사'</li></ul> |
+| 1.0   | <ul><li>'매일유업 매일우유 매일두유 99.9 190ml 12개 12개 테켄종합상사'</li><li>'매일유업 마이너피겨스 유기농 오트밀크 1L  주식회사 지룩'</li><li>'아몬드 브리즈 뉴트리플러스 프로틴 190ml 48개  스타일바이맘'</li></ul>                                                                       |
+| 6.0   | <ul><li>'이제부터 무가당 무설탕 생강진액 생강차 생강즙 생강청 1L ★이벤트★ 3+1(생강청)-박스없음_소비자가 태후자연식품영농조합법인'</li><li>'티젠 콤부차 파인애플 5g x 30개입 샤인머스켓(30개입) 엠비알글로벌'</li><li>'[오설록](신세계 본점)세작 80 g(잎차)  주식회사 에스에스지닷컴'</li></ul>                               |
+| 5.0   | <ul><li>'파낙스 참다음 매실 원액 1.5L/6배희석 로쏘 레몬음료 베이스 1L (주) 이카루스'</li><li>'동원 덴마크 푸르티 포도 주스 120mL x 24개  블라썸플라워'</li><li>'썬업 과���야채샐러드 그린 200ml x 24팩 과일야채 샐러드 레드 200ml x 24팩 하니컴퍼니'</li></ul>                                         |
+| 9.0   | <ul><li>'허쉬 코코아 가루 분말 226g W-00652_허쉬코코아파우더226g(파손) 월푸드'</li><li>'기라델리 프리미엄 핫코코아믹스 초콜렛 907g X 1박스(4개)  고고커피'</li><li>'Nestle Hot Cocoa 핫 코코아 믹스 30개 0.28온스 207799 무설탕 무지방_2개들이 팩 더블스토어'</li></ul>                            |
+| 4.0   | <ul><li>'코카콜라 태양의 식후비법 W차 500ml  (주)디에이치솔루션'</li><li>'광동 힘찬하루 헛개차 1.5L 1개 대패트_게토레이 레몬 1.5L 12개 대영상사'</li><li>'웰그린 스위츠 복숭아 녹차 음료 340ml 티트라 레몬그린티 제로 500mlX24PET 브론스코리아(주)'</li></ul>                                          |
+| 0.0   | <ul><li>'레드불 에너지 드링크 355ml (6개) 카페인 타우린 비타민 알프스 워터 대량 구매  노건'</li><li>'청정원 홍초 석류 1.5L 홍초 블루베리 1.5L (주) 이카루스'</li><li>'청정원 홍초 자몽 900ml 아이스티_티오 아이스티 레몬맛40T 주식회사 경일종합식품 케이마트몰'</li></ul>                                       |
+| 7.0   | <ul><li>'동서 티오 아이스티 복숭아 70T +커피믹스 스틱 2T 콤부차_다농원 콤부차 리치 20T+보틀 주식회사 경일종합식품 케이마트몰'</li><li>'립톤 아이스티 복숭아 770g 레몬 770g_자몽 아이스티 키트(2개입) 유니레버코리아 (주)'</li><li>'술픽 하이트진로 토닉워터 600ml 대용량  술벙커 주식회사 농업회사법인 이천지점'</li></ul>            |
+| 11.0  | <ul><li>'포모나 블루베리스무디 2kg 블루베리농축액  (주)제이제이푸드시스템'</li><li>'베오베 오곡 파우더 1kg 라떼 곡물 미숫가루 분말 티에이치커피  티에이치커피'</li><li>'타코 복숭아 아이스티 /선택 08.블루베리라떼870g 주식회사 커피바바'</li></ul>                                                            |
+| 3.0   | <ul><li>'[매니저배송] MPRO 장&면역+피부 (5개입)  (주)에치와이'</li><li>'요플레 닥터캡슐 베리믹스 130mLx4개/1000배/냉장무배  대명유통'</li><li>'매일바이오 알로에 120g 12개_냉장  매일유업 주식회사'</li></ul>                                                                         |
+| 2.0   | <ul><li>'화인바이오 지리산 물하나 2L X 6개  글로벌웨이브'</li><li>'하이트 천연광천수 미네랄 석수 무라벨 500ml 20pet ◇ 석수 무라벨 500ml 20pet 주식회사 부산종합유통'</li><li>'아이시스8.0 300ml x 1BOX(20PET) 생수 아이시스8.0 200ml(40p) (주)하나유통'</li></ul>                            |
+
+## Evaluation
+
+### Metrics
+| Label   | Metric |
+|:--------|:-------|
+| **all** | 0.6536 |
+
+## 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_fd14")
+# Run inference
+preds = model("맥심 티오피 스위트 아메리카노 200ml  (주)디에이치솔루션")
+```
+
+<!--
+### 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   | 4   | 9.805  | 20  |
+
+| Label | Training Sample Count |
+|:------|:----------------------|
+| 0.0   | 50                    |
+| 1.0   | 50                    |
+| 2.0   | 50                    |
+| 3.0   | 50                    |
+| 4.0   | 50                    |
+| 5.0   | 50                    |
+| 6.0   | 50                    |
+| 7.0   | 50                    |
+| 8.0   | 50                    |
+| 9.0   | 50                    |
+| 10.0  | 50                    |
+| 11.0  | 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 |
+|:-------:|:----:|:-------------:|:---------------:|
+| 0.0106  | 1    | 0.3763        | -               |
+| 0.5319  | 50   | 0.3216        | -               |
+| 1.0638  | 100  | 0.1166        | -               |
+| 1.5957  | 150  | 0.0863        | -               |
+| 2.1277  | 200  | 0.0548        | -               |
+| 2.6596  | 250  | 0.0559        | -               |
+| 3.1915  | 300  | 0.0323        | -               |
+| 3.7234  | 350  | 0.0301        | -               |
+| 4.2553  | 400  | 0.0191        | -               |
+| 4.7872  | 450  | 0.0127        | -               |
+| 5.3191  | 500  | 0.0059        | -               |
+| 5.8511  | 550  | 0.0003        | -               |
+| 6.3830  | 600  | 0.0002        | -               |
+| 6.9149  | 650  | 0.0001        | -               |
+| 7.4468  | 700  | 0.0001        | -               |
+| 7.9787  | 750  | 0.0001        | -               |
+| 8.5106  | 800  | 0.0001        | -               |
+| 9.0426  | 850  | 0.0001        | -               |
+| 9.5745  | 900  | 0.0001        | -               |
+| 10.1064 | 950  | 0.0001        | -               |
+| 10.6383 | 1000 | 0.0001        | -               |
+| 11.1702 | 1050 | 0.0001        | -               |
+| 11.7021 | 1100 | 0.0001        | -               |
+| 12.2340 | 1150 | 0.0001        | -               |
+| 12.7660 | 1200 | 0.0001        | -               |
+| 13.2979 | 1250 | 0.0           | -               |
+| 13.8298 | 1300 | 0.0001        | -               |
+| 14.3617 | 1350 | 0.0001        | -               |
+| 14.8936 | 1400 | 0.0001        | -               |
+| 15.4255 | 1450 | 0.0           | -               |
+| 15.9574 | 1500 | 0.0           | -               |
+| 16.4894 | 1550 | 0.0           | -               |
+| 17.0213 | 1600 | 0.0           | -               |
+| 17.5532 | 1650 | 0.0           | -               |
+| 18.0851 | 1700 | 0.0           | -               |
+| 18.6170 | 1750 | 0.0           | -               |
+| 19.1489 | 1800 | 0.0           | -               |
+| 19.6809 | 1850 | 0.0           | -               |
+
+### 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

@@ -0,0 +1,29 @@
+{
+  "_name_or_path": "mini1013/master_item_fd",
+  "architectures": [
+    "RobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "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

@@ -0,0 +1,10 @@
+{
+  "__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

@@ -0,0 +1,4 @@
+{
+  "labels": null,
+  "normalize_embeddings": false
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f4587bed81fd0fd02cee91393cbc0d4451fee74a425cabda93fb99c70c5d6632
+size 442494816

model_head.pkl

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+oid sha256:145382b268b54384d5c425cb5c70809198e257ac6a1311907a437ed3ee1728e6
+size 74727

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "eos_token": "[SEP]",
+  "mask_token": "[MASK]",
+  "max_length": 512,
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}