Hugging Face's logo

mini1013
/
master_cate_bt_top8_test

Text Classification
setfit
Safetensors
sentence-transformers
roberta
generated_from_setfit_trainer
Eval Results
Model card Files Community
mini1013 commited on
Commit
6432d6e
•
1 Parent(s): ab60d71

Push model using huggingface_hub.

Browse files
Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +442 -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
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "word_embedding_dimension": 768,
3
+ "pooling_mode_cls_token": false,
4
+ "pooling_mode_mean_tokens": true,
5
+ "pooling_mode_max_tokens": false,
6
+ "pooling_mode_mean_sqrt_len_tokens": false,
7
+ "pooling_mode_weightedmean_tokens": false,
8
+ "pooling_mode_lasttoken": false,
9
+ "include_prompt": true
10
+ }
README.md ADDED
@@ -0,0 +1,442 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: mini1013/master_domain
3
+ library_name: setfit
4
+ metrics:
5
+ - accuracy
6
+ pipeline_tag: text-classification
7
+ tags:
8
+ - setfit
9
+ - sentence-transformers
10
+ - text-classification
11
+ - generated_from_setfit_trainer
12
+ widget:
13
+ - text: 엔프라니 옴므 선블록 썬크림 남성용 선크림 (#M)화장품/미용>남성화장품>선크림 Naverstore > 화장품/미용 > 남성화장품
14
+ > 선크림
15
+ - text: (시세이도)(시세이도)(특별한정) 파란자차 50ml 세트(+파란자차 정품 용량) NEW 파란자차 (정품) (#M)화장품/향수>선케어>선크림
16
+ Gmarket > 뷰티 > 화장품/향수 > 선케어 > 선크림
17
+ - text: 에스쁘아 워터스플래쉬 선크림 SPF50+ PA+++ 60ml × 5개 (#M)쿠팡 홈>뷰티>스킨케어>선케어/태닝>선케어>선블록/선크림/선로션
18
+ Coupang > 뷰티 > 스킨케어 > 선케어/태닝 > 선케어 > 선블록/선크림/선로션
19
+ - text: 이니스프리 인텐시브 롱래스팅 선스크린50ml 50ml × 6개 LotteOn > 뷰티 > 남성화장품 > 스킨 LotteOn > 뷰티
20
+ > 남성화장품 > 스킨
21
+ - text: 에스트라 리제덤 RX 듀얼 선크림 +BB 50ml 병원전용제품 (#M)SSG.COM/메이크업/베이스메이크업/BB/CC크림 ssg
22
+ > 뷰티 > 메이크업 > 베이스메이크업 > BB/CC크림
23
+ inference: true
24
+ model-index:
25
+ - name: SetFit with mini1013/master_domain
26
+ results:
27
+ - task:
28
+ type: text-classification
29
+ name: Text Classification
30
+ dataset:
31
+ name: Unknown
32
+ type: unknown
33
+ split: test
34
+ metrics:
35
+ - type: accuracy
36
+ value: 0.4902962206332993
37
+ name: Accuracy
38
+ ---
39
+
40
+ # SetFit with mini1013/master_domain
41
+
42
+ 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.
43
+
44
+ The model has been trained using an efficient few-shot learning technique that involves:
45
+
46
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
47
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
48
+
49
+ ## Model Details
50
+
51
+ ### Model Description
52
+ - **Model Type:** SetFit
53
+ - **Sentence Transformer body:** [mini1013/master_domain](https://huggingface.co/mini1013/master_domain)
54
+ - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
55
+ - **Maximum Sequence Length:** 512 tokens
56
+ - **Number of Classes:** 5 classes
57
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
58
+ <!-- - **Language:** Unknown -->
59
+ <!-- - **License:** Unknown -->
60
+
61
+ ### Model Sources
62
+
63
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
64
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
65
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
66
+
67
+ ### Model Labels
68
+ | Label | Examples |
69
+ |:------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
70
+ | 2 | <ul><li>'이니스프리 노세범 선쿠션 SPF50+ PA++++ 14g × 2개 (#M)위메프 > 뷰티 > 메이크업 > 베이스 메이크업 > 파우더/팩트 위메프 > 뷰티 > 메이크업 > 베이스 메이크업 > 파우더/팩트'</li><li>'스킨 세팅 톤업 선 쿠션(리필포함) + 추가구성품 톤업 선 쿠션 LotteOn > 백화점 > 뷰티 > 상단 배너 (Mobile) LotteOn > 뷰티 > 메이크업 > 베이스메이크업 > 쿠션/팩트'</li><li>'이니스프��� 노세범 선쿠션 리필 14g 1 +1 (#M)쿠팡 홈>뷰티>스킨케어>선케어/태닝>선케어>선스틱 Coupang > 뷰티 > 로드샵 > 스킨케어 > 선케어/태닝'</li></ul> |
71
+ | 1 | <ul><li>'SUNDANCE 썬댄스 햇빛 차단+태닝 선스프레이 LSF 50, 200ml ssg > 뷰티 > 스킨케어 > 선케어 > 선스프레이 ssg > 뷰티 > 스킨케어 > 선케어 > 선스프레이'</li><li>'리더스 여름자외선 썬버디 올 오버 선 스프레이 180ml MinSellAmount (#M)화장품/향수>선케어>선스프레이 Gmarket > 뷰티 > 화장품/향수 > 선케어 > 선스프레이'</li><li>'온더바디 헬로키티 에코 썬 스프레이 120ml+120ml 기획세트 (#M)홈>화장품/미용>선케어>선케어세트 Naverstore > 화장품/미용 > 선케어 > 선케어세트'</li></ul> |
72
+ | 0 | <ul><li>'[피지오겔] [정가 85,000원] 레드 수딩 AI 에어리 썬스틱 1+1 특별기획 롯데홈쇼핑 > 뷰티 > 남성화장품 LotteOn > 뷰티 > 남성화장품 > 선크림'</li><li>'[빌리프][2106] 해피 보 이지워시 선스틱 18g 세트(타임스퀘어점패션관) (#M)11st>선케어>선밤>선밤 11st > 뷰티 > 선케어 > 선밤 > 선밤'</li><li>'피지오겔 레드 수딩 AI 에어리 썬스틱 7g 1+1(2개) (#M)홈>스킨케어>선케어 HMALL > 뷰티 > 스킨케어 > 선케어'</li></ul> |
73
+ | 4 | <ul><li>'오스트레일리안골드 헴프네이션 오리지널 탠 익스텐더 바디로션 535ml (#M)SSG.COM/스킨케어/선케어/태닝 ssg > 뷰티 > 스킨케어 > 선케어 > 태닝'</li><li>'수딩앤모이스처 알로에베라92%수딩젤300ml (#M)홈>화장품/미용>바디케어>바디로션 Naverstore > 화장품/미용 > 바디케어 > 바디로션'</li><li>'세인트 트로페즈 셀프 탠 익스프레스 어드밴스드 브론징 무스 200ml (#M)SSG.COM/스킨케어/선케어/태닝 ssg > 뷰티 > 스킨케어 > 선케어 > 태닝'</li></ul> |
74
+ | 3 | <ul><li>'[맥퀸뉴욕] 1+ 1 UV 데일리 모이스처(수분) 선크림 1+1 UV 데일리 모이스처 선크림 (#M)SSG.COM/메이크업/립메이크업/립글로스 ssg > 뷰티 > 메이크업 > 아이메이크업 > 아이라이너'</li><li>'[공식] 더마비 10주년 바디로션/기획세트/멀티오일/프레쉬/크림/워시 1+1 S11.(애브리데이) 대용량 선블록 200ml×2개_S1.튜브견본(랜덤) 쇼킹딜 홈;쇼킹딜 홈>뷰티>바디/향수>바디케어;11st>뷰티>바디/향수>바디케어;11st>바디케어>바디로션>바디로션;11st > 뷰티 > 바디케어 > 바디로션 11st Hour Event > 패션/뷰티 > 뷰티 > 바디/향수 > 바디케어'</li><li>'[20%찜+T11%+묶음+당일 ] 롬앤 11번가 런칭! 모든 취향 취급 중! 밀크 그로서리 외 BEST 1+1 옵션31. 제로 선 클린 단품_01 프레쉬 쇼킹딜 홈>뷰티>선케어/메이크업>립/치크메이크업;11st>메이크업>립메이크업>립틴트;11st>뷰티>선케어/메이크업>립/치크메이크업;11st>뷰티>선케어/메이크업>아이메이크업;11st>메이크업>아이메이크업>마스카라;11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 립/치크메이크업 11st Hour Event > 패션/뷰티 > 뷰티 > 선케어/메이크업 > 아이메이크업'</li></ul> |
75
+
76
+ ## Evaluation
77
+
78
+ ### Metrics
79
+ | Label | Accuracy |
80
+ |:--------|:---------|
81
+ | **all** | 0.4903 |
82
+
83
+ ## Uses
84
+
85
+ ### Direct Use for Inference
86
+
87
+ First install the SetFit library:
88
+
89
+ ```bash
90
+ pip install setfit
91
+ ```
92
+
93
+ Then you can load this model and run inference.
94
+
95
+ ```python
96
+ from setfit import SetFitModel
97
+
98
+ # Download from the 🤗 Hub
99
+ model = SetFitModel.from_pretrained("mini1013/master_cate_bt_top8_test")
100
+ # Run inference
101
+ preds = model("엔���라니 옴므 선블록 썬크림 남성용 선크림 (#M)화장품/미용>남성화장품>선크림 Naverstore > 화장품/미용 > 남성화장품 > 선크림")
102
+ ```
103
+
104
+ <!--
105
+ ### Downstream Use
106
+
107
+ *List how someone could finetune this model on their own dataset.*
108
+ -->
109
+
110
+ <!--
111
+ ### Out-of-Scope Use
112
+
113
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
114
+ -->
115
+
116
+ <!--
117
+ ## Bias, Risks and Limitations
118
+
119
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
120
+ -->
121
+
122
+ <!--
123
+ ### Recommendations
124
+
125
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
126
+ -->
127
+
128
+ ## Training Details
129
+
130
+ ### Training Set Metrics
131
+ | Training set | Min | Median | Max |
132
+ |:-------------|:----|:-------|:----|
133
+ | Word count | 11 | 21.656 | 72 |
134
+
135
+ | Label | Training Sample Count |
136
+ |:------|:----------------------|
137
+ | 0 | 50 |
138
+ | 1 | 50 |
139
+ | 2 | 50 |
140
+ | 3 | 50 |
141
+ | 4 | 50 |
142
+
143
+ ### Training Hyperparameters
144
+ - batch_size: (64, 64)
145
+ - num_epochs: (30, 30)
146
+ - max_steps: -1
147
+ - sampling_strategy: oversampling
148
+ - num_iterations: 100
149
+ - body_learning_rate: (2e-05, 1e-05)
150
+ - head_learning_rate: 0.01
151
+ - loss: CosineSimilarityLoss
152
+ - distance_metric: cosine_distance
153
+ - margin: 0.25
154
+ - end_to_end: False
155
+ - use_amp: False
156
+ - warmup_proportion: 0.1
157
+ - l2_weight: 0.01
158
+ - seed: 42
159
+ - eval_max_steps: -1
160
+ - load_best_model_at_end: False
161
+
162
+ ### Training Results
163
+ | Epoch | Step | Training Loss | Validation Loss |
164
+ |:-------:|:-----:|:-------------:|:---------------:|
165
+ | 0.0026 | 1 | 0.4513 | - |
166
+ | 0.1279 | 50 | 0.4435 | - |
167
+ | 0.2558 | 100 | 0.4063 | - |
168
+ | 0.3836 | 150 | 0.3413 | - |
169
+ | 0.5115 | 200 | 0.2997 | - |
170
+ | 0.6394 | 250 | 0.2434 | - |
171
+ | 0.7673 | 300 | 0.1724 | - |
172
+ | 0.8951 | 350 | 0.1334 | - |
173
+ | 1.0230 | 400 | 0.1078 | - |
174
+ | 1.1509 | 450 | 0.0997 | - |
175
+ | 1.2788 | 500 | 0.0937 | - |
176
+ | 1.4066 | 550 | 0.0933 | - |
177
+ | 1.5345 | 600 | 0.0909 | - |
178
+ | 1.6624 | 650 | 0.0897 | - |
179
+ | 1.7903 | 700 | 0.0842 | - |
180
+ | 1.9182 | 750 | 0.0741 | - |
181
+ | 2.0460 | 800 | 0.0764 | - |
182
+ | 2.1739 | 850 | 0.0745 | - |
183
+ | 2.3018 | 900 | 0.0733 | - |
184
+ | 2.4297 | 950 | 0.0748 | - |
185
+ | 2.5575 | 1000 | 0.0718 | - |
186
+ | 2.6854 | 1050 | 0.0568 | - |
187
+ | 2.8133 | 1100 | 0.0415 | - |
188
+ | 2.9412 | 1150 | 0.0256 | - |
189
+ | 3.0691 | 1200 | 0.0233 | - |
190
+ | 3.1969 | 1250 | 0.0128 | - |
191
+ | 3.3248 | 1300 | 0.0088 | - |
192
+ | 3.4527 | 1350 | 0.0066 | - |
193
+ | 3.5806 | 1400 | 0.0058 | - |
194
+ | 3.7084 | 1450 | 0.006 | - |
195
+ | 3.8363 | 1500 | 0.0058 | - |
196
+ | 3.9642 | 1550 | 0.0039 | - |
197
+ | 4.0921 | 1600 | 0.0043 | - |
198
+ | 4.2199 | 1650 | 0.0033 | - |
199
+ | 4.3478 | 1700 | 0.0059 | - |
200
+ | 4.4757 | 1750 | 0.0065 | - |
201
+ | 4.6036 | 1800 | 0.0061 | - |
202
+ | 4.7315 | 1850 | 0.0052 | - |
203
+ | 4.8593 | 1900 | 0.0054 | - |
204
+ | 4.9872 | 1950 | 0.0043 | - |
205
+ | 5.1151 | 2000 | 0.0064 | - |
206
+ | 5.2430 | 2050 | 0.0042 | - |
207
+ | 5.3708 | 2100 | 0.0046 | - |
208
+ | 5.4987 | 2150 | 0.0038 | - |
209
+ | 5.6266 | 2200 | 0.0031 | - |
210
+ | 5.7545 | 2250 | 0.0021 | - |
211
+ | 5.8824 | 2300 | 0.0006 | - |
212
+ | 6.0102 | 2350 | 0.0003 | - |
213
+ | 6.1381 | 2400 | 0.0001 | - |
214
+ | 6.2660 | 2450 | 0.0002 | - |
215
+ | 6.3939 | 2500 | 0.0 | - |
216
+ | 6.5217 | 2550 | 0.0 | - |
217
+ | 6.6496 | 2600 | 0.0001 | - |
218
+ | 6.7775 | 2650 | 0.0 | - |
219
+ | 6.9054 | 2700 | 0.0 | - |
220
+ | 7.0332 | 2750 | 0.0 | - |
221
+ | 7.1611 | 2800 | 0.0 | - |
222
+ | 7.2890 | 2850 | 0.0 | - |
223
+ | 7.4169 | 2900 | 0.0 | - |
224
+ | 7.5448 | 2950 | 0.0 | - |
225
+ | 7.6726 | 3000 | 0.0 | - |
226
+ | 7.8005 | 3050 | 0.0 | - |
227
+ | 7.9284 | 3100 | 0.0 | - |
228
+ | 8.0563 | 3150 | 0.0 | - |
229
+ | 8.1841 | 3200 | 0.0 | - |
230
+ | 8.3120 | 3250 | 0.0 | - |
231
+ | 8.4399 | 3300 | 0.0 | - |
232
+ | 8.5678 | 3350 | 0.0 | - |
233
+ | 8.6957 | 3400 | 0.0 | - |
234
+ | 8.8235 | 3450 | 0.0 | - |
235
+ | 8.9514 | 3500 | 0.0 | - |
236
+ | 9.0793 | 3550 | 0.0 | - |
237
+ | 9.2072 | 3600 | 0.0 | - |
238
+ | 9.3350 | 3650 | 0.0 | - |
239
+ | 9.4629 | 3700 | 0.0 | - |
240
+ | 9.5908 | 3750 | 0.0 | - |
241
+ | 9.7187 | 3800 | 0.0 | - |
242
+ | 9.8465 | 3850 | 0.0 | - |
243
+ | 9.9744 | 3900 | 0.0 | - |
244
+ | 10.1023 | 3950 | 0.0 | - |
245
+ | 10.2302 | 4000 | 0.0 | - |
246
+ | 10.3581 | 4050 | 0.0 | - |
247
+ | 10.4859 | 4100 | 0.0 | - |
248
+ | 10.6138 | 4150 | 0.0 | - |
249
+ | 10.7417 | 4200 | 0.0 | - |
250
+ | 10.8696 | 4250 | 0.0 | - |
251
+ | 10.9974 | 4300 | 0.0 | - |
252
+ | 11.1253 | 4350 | 0.0 | - |
253
+ | 11.2532 | 4400 | 0.0 | - |
254
+ | 11.3811 | 4450 | 0.0 | - |
255
+ | 11.5090 | 4500 | 0.0 | - |
256
+ | 11.6368 | 4550 | 0.0 | - |
257
+ | 11.7647 | 4600 | 0.0 | - |
258
+ | 11.8926 | 4650 | 0.0 | - |
259
+ | 12.0205 | 4700 | 0.0 | - |
260
+ | 12.1483 | 4750 | 0.0 | - |
261
+ | 12.2762 | 4800 | 0.0 | - |
262
+ | 12.4041 | 4850 | 0.0 | - |
263
+ | 12.5320 | 4900 | 0.0 | - |
264
+ | 12.6598 | 4950 | 0.0 | - |
265
+ | 12.7877 | 5000 | 0.0 | - |
266
+ | 12.9156 | 5050 | 0.0 | - |
267
+ | 13.0435 | 5100 | 0.0 | - |
268
+ | 13.1714 | 5150 | 0.0 | - |
269
+ | 13.2992 | 5200 | 0.0 | - |
270
+ | 13.4271 | 5250 | 0.0 | - |
271
+ | 13.5550 | 5300 | 0.0 | - |
272
+ | 13.6829 | 5350 | 0.0 | - |
273
+ | 13.8107 | 5400 | 0.0 | - |
274
+ | 13.9386 | 5450 | 0.0 | - |
275
+ | 14.0665 | 5500 | 0.0 | - |
276
+ | 14.1944 | 5550 | 0.0 | - |
277
+ | 14.3223 | 5600 | 0.0 | - |
278
+ | 14.4501 | 5650 | 0.0 | - |
279
+ | 14.5780 | 5700 | 0.0 | - |
280
+ | 14.7059 | 5750 | 0.0 | - |
281
+ | 14.8338 | 5800 | 0.0 | - |
282
+ | 14.9616 | 5850 | 0.0 | - |
283
+ | 15.0895 | 5900 | 0.0 | - |
284
+ | 15.2174 | 5950 | 0.0 | - |
285
+ | 15.3453 | 6000 | 0.0 | - |
286
+ | 15.4731 | 6050 | 0.0 | - |
287
+ | 15.6010 | 6100 | 0.0 | - |
288
+ | 15.7289 | 6150 | 0.0 | - |
289
+ | 15.8568 | 6200 | 0.0 | - |
290
+ | 15.9847 | 6250 | 0.0 | - |
291
+ | 16.1125 | 6300 | 0.0 | - |
292
+ | 16.2404 | 6350 | 0.0 | - |
293
+ | 16.3683 | 6400 | 0.0 | - |
294
+ | 16.4962 | 6450 | 0.0 | - |
295
+ | 16.6240 | 6500 | 0.0 | - |
296
+ | 16.7519 | 6550 | 0.0 | - |
297
+ | 16.8798 | 6600 | 0.0 | - |
298
+ | 17.0077 | 6650 | 0.0 | - |
299
+ | 17.1355 | 6700 | 0.0 | - |
300
+ | 17.2634 | 6750 | 0.0 | - |
301
+ | 17.3913 | 6800 | 0.0 | - |
302
+ | 17.5192 | 6850 | 0.0 | - |
303
+ | 17.6471 | 6900 | 0.0 | - |
304
+ | 17.7749 | 6950 | 0.0 | - |
305
+ | 17.9028 | 7000 | 0.0 | - |
306
+ | 18.0307 | 7050 | 0.0 | - |
307
+ | 18.1586 | 7100 | 0.0 | - |
308
+ | 18.2864 | 7150 | 0.0 | - |
309
+ | 18.4143 | 7200 | 0.0 | - |
310
+ | 18.5422 | 7250 | 0.0 | - |
311
+ | 18.6701 | 7300 | 0.0 | - |
312
+ | 18.7980 | 7350 | 0.0 | - |
313
+ | 18.9258 | 7400 | 0.0 | - |
314
+ | 19.0537 | 7450 | 0.0 | - |
315
+ | 19.1816 | 7500 | 0.0 | - |
316
+ | 19.3095 | 7550 | 0.0 | - |
317
+ | 19.4373 | 7600 | 0.0 | - |
318
+ | 19.5652 | 7650 | 0.0 | - |
319
+ | 19.6931 | 7700 | 0.0 | - |
320
+ | 19.8210 | 7750 | 0.0 | - |
321
+ | 19.9488 | 7800 | 0.0 | - |
322
+ | 20.0767 | 7850 | 0.0 | - |
323
+ | 20.2046 | 7900 | 0.0 | - |
324
+ | 20.3325 | 7950 | 0.0 | - |
325
+ | 20.4604 | 8000 | 0.0 | - |
326
+ | 20.5882 | 8050 | 0.0 | - |
327
+ | 20.7161 | 8100 | 0.0 | - |
328
+ | 20.8440 | 8150 | 0.0 | - |
329
+ | 20.9719 | 8200 | 0.0 | - |
330
+ | 21.0997 | 8250 | 0.0 | - |
331
+ | 21.2276 | 8300 | 0.0 | - |
332
+ | 21.3555 | 8350 | 0.0 | - |
333
+ | 21.4834 | 8400 | 0.0 | - |
334
+ | 21.6113 | 8450 | 0.0 | - |
335
+ | 21.7391 | 8500 | 0.0 | - |
336
+ | 21.8670 | 8550 | 0.0 | - |
337
+ | 21.9949 | 8600 | 0.0 | - |
338
+ | 22.1228 | 8650 | 0.0 | - |
339
+ | 22.2506 | 8700 | 0.0 | - |
340
+ | 22.3785 | 8750 | 0.0 | - |
341
+ | 22.5064 | 8800 | 0.0 | - |
342
+ | 22.6343 | 8850 | 0.0 | - |
343
+ | 22.7621 | 8900 | 0.0 | - |
344
+ | 22.8900 | 8950 | 0.0 | - |
345
+ | 23.0179 | 9000 | 0.0 | - |
346
+ | 23.1458 | 9050 | 0.0 | - |
347
+ | 23.2737 | 9100 | 0.0 | - |
348
+ | 23.4015 | 9150 | 0.0 | - |
349
+ | 23.5294 | 9200 | 0.0 | - |
350
+ | 23.6573 | 9250 | 0.0 | - |
351
+ | 23.7852 | 9300 | 0.0 | - |
352
+ | 23.9130 | 9350 | 0.0 | - |
353
+ | 24.0409 | 9400 | 0.0 | - |
354
+ | 24.1688 | 9450 | 0.0 | - |
355
+ | 24.2967 | 9500 | 0.0 | - |
356
+ | 24.4246 | 9550 | 0.0 | - |
357
+ | 24.5524 | 9600 | 0.0 | - |
358
+ | 24.6803 | 9650 | 0.0 | - |
359
+ | 24.8082 | 9700 | 0.0 | - |
360
+ | 24.9361 | 9750 | 0.0 | - |
361
+ | 25.0639 | 9800 | 0.0 | - |
362
+ | 25.1918 | 9850 | 0.0 | - |
363
+ | 25.3197 | 9900 | 0.0 | - |
364
+ | 25.4476 | 9950 | 0.0 | - |
365
+ | 25.5754 | 10000 | 0.0 | - |
366
+ | 25.7033 | 10050 | 0.0 | - |
367
+ | 25.8312 | 10100 | 0.0 | - |
368
+ | 25.9591 | 10150 | 0.0 | - |
369
+ | 26.0870 | 10200 | 0.0 | - |
370
+ | 26.2148 | 10250 | 0.0 | - |
371
+ | 26.3427 | 10300 | 0.0 | - |
372
+ | 26.4706 | 10350 | 0.0 | - |
373
+ | 26.5985 | 10400 | 0.0 | - |
374
+ | 26.7263 | 10450 | 0.0 | - |
375
+ | 26.8542 | 10500 | 0.0 | - |
376
+ | 26.9821 | 10550 | 0.0 | - |
377
+ | 27.1100 | 10600 | 0.0 | - |
378
+ | 27.2379 | 10650 | 0.0 | - |
379
+ | 27.3657 | 10700 | 0.0 | - |
380
+ | 27.4936 | 10750 | 0.0 | - |
381
+ | 27.6215 | 10800 | 0.0 | - |
382
+ | 27.7494 | 10850 | 0.0 | - |
383
+ | 27.8772 | 10900 | 0.0 | - |
384
+ | 28.0051 | 10950 | 0.0 | - |
385
+ | 28.1330 | 11000 | 0.0 | - |
386
+ | 28.2609 | 11050 | 0.0 | - |
387
+ | 28.3887 | 11100 | 0.0 | - |
388
+ | 28.5166 | 11150 | 0.0 | - |
389
+ | 28.6445 | 11200 | 0.0 | - |
390
+ | 28.7724 | 11250 | 0.0 | - |
391
+ | 28.9003 | 11300 | 0.0 | - |
392
+ | 29.0281 | 11350 | 0.0 | - |
393
+ | 29.1560 | 11400 | 0.0 | - |
394
+ | 29.2839 | 11450 | 0.0 | - |
395
+ | 29.4118 | 11500 | 0.0 | - |
396
+ | 29.5396 | 11550 | 0.0 | - |
397
+ | 29.6675 | 11600 | 0.0 | - |
398
+ | 29.7954 | 11650 | 0.0 | - |
399
+ | 29.9233 | 11700 | 0.0 | - |
400
+
401
+ ### Framework Versions
402
+ - Python: 3.10.12
403
+ - SetFit: 1.1.0
404
+ - Sentence Transformers: 3.3.1
405
+ - Transformers: 4.44.2
406
+ - PyTorch: 2.2.0a0+81ea7a4
407
+ - Datasets: 3.2.0
408
+ - Tokenizers: 0.19.1
409
+
410
+ ## Citation
411
+
412
+ ### BibTeX
413
+ ```bibtex
414
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
415
+ doi = {10.48550/ARXIV.2209.11055},
416
+ url = {https://arxiv.org/abs/2209.11055},
417
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
418
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
419
+ title = {Efficient Few-Shot Learning Without Prompts},
420
+ publisher = {arXiv},
421
+ year = {2022},
422
+ copyright = {Creative Commons Attribution 4.0 International}
423
+ }
424
+ ```
425
+
426
+ <!--
427
+ ## Glossary
428
+
429
+ *Clearly define terms in order to be accessible across audiences.*
430
+ -->
431
+
432
+ <!--
433
+ ## Model Card Authors
434
+
435
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
436
+ -->
437
+
438
+ <!--
439
+ ## Model Card Contact
440
+
441
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
442
+ -->
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 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca5767db6afd938df9ba4ffd09c97cd091e981f7273e4774a1725051ca2b2407
3
+ size 442494816
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c03844eb5a62a80eb88636b18968ac39e2789406356ddce2d0afba8cc833364
3
+ size 31647
modules.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "idx": 0,
4
+ "name": "0",
5
+ "path": "",
6
+ "type": "sentence_transformers.models.Transformer"
7
+ },
8
+ {
9
+ "idx": 1,
10
+ "name": "1",
11
+ "path": "1_Pooling",
12
+ "type": "sentence_transformers.models.Pooling"
13
+ }
14
+ ]
sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 512,
3
+ "do_lower_case": false
4
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "[CLS]",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "cls_token": {
10
+ "content": "[CLS]",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "eos_token": {
17
+ "content": "[SEP]",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "mask_token": {
24
+ "content": "[MASK]",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "pad_token": {
31
+ "content": "[PAD]",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ },
37
+ "sep_token": {
38
+ "content": "[SEP]",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false
43
+ },
44
+ "unk_token": {
45
+ "content": "[UNK]",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false
50
+ }
51
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[CLS]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "[PAD]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "[SEP]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
28
+ "content": "[UNK]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "4": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "bos_token": "[CLS]",
45
+ "clean_up_tokenization_spaces": false,
46
+ "cls_token": "[CLS]",
47
+ "do_basic_tokenize": true,
48
+ "do_lower_case": false,
49
+ "eos_token": "[SEP]",
50
+ "mask_token": "[MASK]",
51
+ "max_length": 512,
52
+ "model_max_length": 512,
53
+ "never_split": null,
54
+ "pad_to_multiple_of": null,
55
+ "pad_token": "[PAD]",
56
+ "pad_token_type_id": 0,
57
+ "padding_side": "right",
58
+ "sep_token": "[SEP]",
59
+ "stride": 0,
60
+ "strip_accents": null,
61
+ "tokenize_chinese_chars": true,
62
+ "tokenizer_class": "BertTokenizer",
63
+ "truncation_side": "right",
64
+ "truncation_strategy": "longest_first",
65
+ "unk_token": "[UNK]"
66
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff