Hugging Face's logo

egis-group
/
router_mini_lm_l12

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results
Model card Files Community
Totole commited on
Commit
2f1e6a0
·
verified ·
1 Parent(s): 0905fdf

Add SetFit model

Browse files
Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +471 -0
  3. config.json +26 -0
  4. config_sentence_transformers.json +10 -0
  5. config_setfit.json +7 -0
  6. model.safetensors +3 -0
  7. model_head.pkl +3 -0
  8. modules.json +20 -0
  9. sentence_bert_config.json +4 -0
  10. special_tokens_map.json +37 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +64 -0
  13. vocab.txt +0 -0
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "word_embedding_dimension": 384,
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 +1,471 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: setfit
3
+ tags:
4
+ - setfit
5
+ - sentence-transformers
6
+ - text-classification
7
+ - generated_from_setfit_trainer
8
+ base_model: sentence-transformers/all-MiniLM-L12-v2
9
+ metrics:
10
+ - accuracy
11
+ widget:
12
+ - text: Quel est le principal litige dans les projets de construction, et quel droit
13
+ de la partie accusee
14
+ - text: Clarifier quels sont les facteurs déterminants dans le choix d'un emplacement
15
+ pour un nouveau magasin
16
+ - text: Compare ces deux documents
17
+ - text: Can you explain the process of wind energy generation and discuss its environmental
18
+ impacts compared to those of hydroelectric power?
19
+ - text: Could you restate the advantages of using project management software that
20
+ were mentioned earlier? Provide a linkedin post about it
21
+ pipeline_tag: text-classification
22
+ inference: true
23
+ model-index:
24
+ - name: SetFit with sentence-transformers/all-MiniLM-L12-v2
25
+ results:
26
+ - task:
27
+ type: text-classification
28
+ name: Text Classification
29
+ dataset:
30
+ name: Unknown
31
+ type: unknown
32
+ split: test
33
+ metrics:
34
+ - type: accuracy
35
+ value: 0.9333333333333333
36
+ name: Accuracy
37
+ ---
38
+
39
+ # SetFit with sentence-transformers/all-MiniLM-L12-v2
40
+
41
+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) 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.
42
+
43
+ The model has been trained using an efficient few-shot learning technique that involves:
44
+
45
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
46
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
47
+
48
+ ## Model Details
49
+
50
+ ### Model Description
51
+ - **Model Type:** SetFit
52
+ - **Sentence Transformer body:** [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2)
53
+ - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
54
+ - **Maximum Sequence Length:** 128 tokens
55
+ - **Number of Classes:** 5 classes
56
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
57
+ <!-- - **Language:** Unknown -->
58
+ <!-- - **License:** Unknown -->
59
+
60
+ ### Model Sources
61
+
62
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
63
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
64
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
65
+
66
+ ### Model Labels
67
+ | Label | Examples |
68
+ |:-----------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
69
+ | sub_queries | <ul><li>'Could you break down the main factors I should consider when researching market prices and how to effectively communicate our needs to the supplier during negotiations?'</li><li>'Comment faire pousser une plante et le mesurer ?'</li><li>"Quel est le meilleur matériau pour l'isolation phonique et thermique?"</li></ul> |
70
+ | simple_questions | <ul><li>'What are the key strategies for maintaining efficient communication in a remote work environment?'</li><li>'Could you summarize the ways a person can help in adapting to climate change ?'</li><li>'What are the current trends in construction?'</li></ul> |
71
+ | exchange | <ul><li>'Could you please restate your last explanation using simpler terms?'</li><li>'Could you restate the impact of augmented reality on design practices?'</li><li>'Pourriez-vous me donner un résumé des principaux points abordés dans notre conversation précédente ?'</li></ul> |
72
+ | compare | <ul><li>'How do the conclusions differ?'</li><li>'Contrast the main arguments presented in each paper'</li><li>'Quelles sont les principales différences dans les programmes éducatifs décrits dans ces documents ?'</li></ul> |
73
+ | summary | <ul><li>'Que dois-je retenir de ce doc ?'</li><li>'What are the key assertions made within the text'</li><li>'What are the most important argument stated in the document?'</li></ul> |
74
+
75
+ ## Evaluation
76
+
77
+ ### Metrics
78
+ | Label | Accuracy |
79
+ |:--------|:---------|
80
+ | **all** | 0.9333 |
81
+
82
+ ## Uses
83
+
84
+ ### Direct Use for Inference
85
+
86
+ First install the SetFit library:
87
+
88
+ ```bash
89
+ pip install setfit
90
+ ```
91
+
92
+ Then you can load this model and run inference.
93
+
94
+ ```python
95
+ from setfit import SetFitModel
96
+
97
+ # Download from the 🤗 Hub
98
+ model = SetFitModel.from_pretrained("egis-group/router_mini_lm_l12")
99
+ # Run inference
100
+ preds = model("Compare ces deux documents")
101
+ ```
102
+
103
+ <!--
104
+ ### Downstream Use
105
+
106
+ *List how someone could finetune this model on their own dataset.*
107
+ -->
108
+
109
+ <!--
110
+ ### Out-of-Scope Use
111
+
112
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
113
+ -->
114
+
115
+ <!--
116
+ ## Bias, Risks and Limitations
117
+
118
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
119
+ -->
120
+
121
+ <!--
122
+ ### Recommendations
123
+
124
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
125
+ -->
126
+
127
+ ## Training Details
128
+
129
+ ### Training Set Metrics
130
+ | Training set | Min | Median | Max |
131
+ |:-------------|:----|:--------|:----|
132
+ | Word count | 4 | 13.4389 | 48 |
133
+
134
+ | Label | Training Sample Count |
135
+ |:---------|:----------------------|
136
+ | negative | 0 |
137
+ | positive | 0 |
138
+
139
+ ### Training Hyperparameters
140
+ - batch_size: (16, 16)
141
+ - num_epochs: (4, 4)
142
+ - max_steps: -1
143
+ - sampling_strategy: oversampling
144
+ - body_learning_rate: (2e-05, 1e-05)
145
+ - head_learning_rate: 0.01
146
+ - loss: CosineSimilarityLoss
147
+ - distance_metric: cosine_distance
148
+ - margin: 0.25
149
+ - end_to_end: False
150
+ - use_amp: False
151
+ - warmup_proportion: 0.1
152
+ - seed: 42
153
+ - eval_max_steps: -1
154
+ - load_best_model_at_end: True
155
+
156
+ ### Training Results
157
+ | Epoch | Step | Training Loss | Validation Loss |
158
+ |:-------:|:---------:|:-------------:|:---------------:|
159
+ | 0.0003 | 1 | 0.4073 | - |
160
+ | 0.0151 | 50 | 0.3054 | - |
161
+ | 0.0303 | 100 | 0.2066 | - |
162
+ | 0.0454 | 150 | 0.2664 | - |
163
+ | 0.0606 | 200 | 0.2463 | - |
164
+ | 0.0757 | 250 | 0.214 | - |
165
+ | 0.0909 | 300 | 0.1892 | - |
166
+ | 0.1060 | 350 | 0.1402 | - |
167
+ | 0.1212 | 400 | 0.1804 | - |
168
+ | 0.1363 | 450 | 0.0571 | - |
169
+ | 0.1515 | 500 | 0.0979 | - |
170
+ | 0.1666 | 550 | 0.1775 | - |
171
+ | 0.1818 | 600 | 0.0377 | - |
172
+ | 0.1969 | 650 | 0.0398 | - |
173
+ | 0.2121 | 700 | 0.0423 | - |
174
+ | 0.2272 | 750 | 0.0036 | - |
175
+ | 0.2424 | 800 | 0.0079 | - |
176
+ | 0.2575 | 850 | 0.0049 | - |
177
+ | 0.2726 | 900 | 0.0018 | - |
178
+ | 0.2878 | 950 | 0.0018 | - |
179
+ | 0.3029 | 1000 | 0.0032 | - |
180
+ | 0.3181 | 1050 | 0.0019 | - |
181
+ | 0.3332 | 1100 | 0.0008 | - |
182
+ | 0.3484 | 1150 | 0.0006 | - |
183
+ | 0.3635 | 1200 | 0.0006 | - |
184
+ | 0.3787 | 1250 | 0.0011 | - |
185
+ | 0.3938 | 1300 | 0.0005 | - |
186
+ | 0.4090 | 1350 | 0.001 | - |
187
+ | 0.4241 | 1400 | 0.0009 | - |
188
+ | 0.4393 | 1450 | 0.0004 | - |
189
+ | 0.4544 | 1500 | 0.0003 | - |
190
+ | 0.4696 | 1550 | 0.0003 | - |
191
+ | 0.4847 | 1600 | 0.0006 | - |
192
+ | 0.4998 | 1650 | 0.0003 | - |
193
+ | 0.5150 | 1700 | 0.0002 | - |
194
+ | 0.5301 | 1750 | 0.0002 | - |
195
+ | 0.5453 | 1800 | 0.0005 | - |
196
+ | 0.5604 | 1850 | 0.0003 | - |
197
+ | 0.5756 | 1900 | 0.0002 | - |
198
+ | 0.5907 | 1950 | 0.0002 | - |
199
+ | 0.6059 | 2000 | 0.0001 | - |
200
+ | 0.6210 | 2050 | 0.0002 | - |
201
+ | 0.6362 | 2100 | 0.0002 | - |
202
+ | 0.6513 | 2150 | 0.0001 | - |
203
+ | 0.6665 | 2200 | 0.0002 | - |
204
+ | 0.6816 | 2250 | 0.0002 | - |
205
+ | 0.6968 | 2300 | 0.0002 | - |
206
+ | 0.7119 | 2350 | 0.0002 | - |
207
+ | 0.7271 | 2400 | 0.0002 | - |
208
+ | 0.7422 | 2450 | 0.0002 | - |
209
+ | 0.7573 | 2500 | 0.0001 | - |
210
+ | 0.7725 | 2550 | 0.0001 | - |
211
+ | 0.7876 | 2600 | 0.0002 | - |
212
+ | 0.8028 | 2650 | 0.0001 | - |
213
+ | 0.8179 | 2700 | 0.0002 | - |
214
+ | 0.8331 | 2750 | 0.0007 | - |
215
+ | 0.8482 | 2800 | 0.0001 | - |
216
+ | 0.8634 | 2850 | 0.0001 | - |
217
+ | 0.8785 | 2900 | 0.0001 | - |
218
+ | 0.8937 | 2950 | 0.0001 | - |
219
+ | 0.9088 | 3000 | 0.0001 | - |
220
+ | 0.9240 | 3050 | 0.0002 | - |
221
+ | 0.9391 | 3100 | 0.0001 | - |
222
+ | 0.9543 | 3150 | 0.0001 | - |
223
+ | 0.9694 | 3200 | 0.0001 | - |
224
+ | 0.9846 | 3250 | 0.0001 | - |
225
+ | 0.9997 | 3300 | 0.0002 | - |
226
+ | 1.0 | 3301 | - | 0.0001 |
227
+ | 1.0148 | 3350 | 0.0003 | - |
228
+ | 1.0300 | 3400 | 0.0002 | - |
229
+ | 1.0451 | 3450 | 0.0001 | - |
230
+ | 1.0603 | 3500 | 0.0001 | - |
231
+ | 1.0754 | 3550 | 0.0001 | - |
232
+ | 1.0906 | 3600 | 0.0001 | - |
233
+ | 1.1057 | 3650 | 0.0001 | - |
234
+ | 1.1209 | 3700 | 0.0002 | - |
235
+ | 1.1360 | 3750 | 0.0001 | - |
236
+ | 1.1512 | 3800 | 0.0001 | - |
237
+ | 1.1663 | 3850 | 0.0001 | - |
238
+ | 1.1815 | 3900 | 0.0001 | - |
239
+ | 1.1966 | 3950 | 0.001 | - |
240
+ | 1.2118 | 4000 | 0.0001 | - |
241
+ | 1.2269 | 4050 | 0.0001 | - |
242
+ | 1.2420 | 4100 | 0.0001 | - |
243
+ | 1.2572 | 4150 | 0.0001 | - |
244
+ | 1.2723 | 4200 | 0.0001 | - |
245
+ | 1.2875 | 4250 | 0.0001 | - |
246
+ | 1.3026 | 4300 | 0.0001 | - |
247
+ | 1.3178 | 4350 | 0.0 | - |
248
+ | 1.3329 | 4400 | 0.0001 | - |
249
+ | 1.3481 | 4450 | 0.0001 | - |
250
+ | 1.3632 | 4500 | 0.0001 | - |
251
+ | 1.3784 | 4550 | 0.0001 | - |
252
+ | 1.3935 | 4600 | 0.0001 | - |
253
+ | 1.4087 | 4650 | 0.0001 | - |
254
+ | 1.4238 | 4700 | 0.0001 | - |
255
+ | 1.4390 | 4750 | 0.0001 | - |
256
+ | 1.4541 | 4800 | 0.0 | - |
257
+ | 1.4693 | 4850 | 0.0 | - |
258
+ | 1.4844 | 4900 | 0.0001 | - |
259
+ | 1.4995 | 4950 | 0.0001 | - |
260
+ | 1.5147 | 5000 | 0.0001 | - |
261
+ | 1.5298 | 5050 | 0.0001 | - |
262
+ | 1.5450 | 5100 | 0.0 | - |
263
+ | 1.5601 | 5150 | 0.0001 | - |
264
+ | 1.5753 | 5200 | 0.0 | - |
265
+ | 1.5904 | 5250 | 0.0 | - |
266
+ | 1.6056 | 5300 | 0.0001 | - |
267
+ | 1.6207 | 5350 | 0.0 | - |
268
+ | 1.6359 | 5400 | 0.0001 | - |
269
+ | 1.6510 | 5450 | 0.0 | - |
270
+ | 1.6662 | 5500 | 0.0001 | - |
271
+ | 1.6813 | 5550 | 0.0001 | - |
272
+ | 1.6965 | 5600 | 0.0 | - |
273
+ | 1.7116 | 5650 | 0.0 | - |
274
+ | 1.7267 | 5700 | 0.0 | - |
275
+ | 1.7419 | 5750 | 0.0001 | - |
276
+ | 1.7570 | 5800 | 0.0001 | - |
277
+ | 1.7722 | 5850 | 0.0 | - |
278
+ | 1.7873 | 5900 | 0.0 | - |
279
+ | 1.8025 | 5950 | 0.0001 | - |
280
+ | 1.8176 | 6000 | 0.0002 | - |
281
+ | 1.8328 | 6050 | 0.0 | - |
282
+ | 1.8479 | 6100 | 0.0001 | - |
283
+ | 1.8631 | 6150 | 0.0001 | - |
284
+ | 1.8782 | 6200 | 0.0001 | - |
285
+ | 1.8934 | 6250 | 0.0 | - |
286
+ | 1.9085 | 6300 | 0.0001 | - |
287
+ | 1.9237 | 6350 | 0.0 | - |
288
+ | 1.9388 | 6400 | 0.0001 | - |
289
+ | 1.9540 | 6450 | 0.0001 | - |
290
+ | 1.9691 | 6500 | 0.0 | - |
291
+ | 1.9842 | 6550 | 0.0 | - |
292
+ | 1.9994 | 6600 | 0.0 | - |
293
+ | 2.0 | 6602 | - | 0.0 |
294
+ | 2.0145 | 6650 | 0.0 | - |
295
+ | 2.0297 | 6700 | 0.0 | - |
296
+ | 2.0448 | 6750 | 0.0 | - |
297
+ | 2.0600 | 6800 | 0.0 | - |
298
+ | 2.0751 | 6850 | 0.0 | - |
299
+ | 2.0903 | 6900 | 0.0001 | - |
300
+ | 2.1054 | 6950 | 0.0 | - |
301
+ | 2.1206 | 7000 | 0.0 | - |
302
+ | 2.1357 | 7050 | 0.0 | - |
303
+ | 2.1509 | 7100 | 0.0001 | - |
304
+ | 2.1660 | 7150 | 0.0 | - |
305
+ | 2.1812 | 7200 | 0.0 | - |
306
+ | 2.1963 | 7250 | 0.0 | - |
307
+ | 2.2115 | 7300 | 0.0 | - |
308
+ | 2.2266 | 7350 | 0.0001 | - |
309
+ | 2.2417 | 7400 | 0.0 | - |
310
+ | 2.2569 | 7450 | 0.0 | - |
311
+ | 2.2720 | 7500 | 0.0001 | - |
312
+ | 2.2872 | 7550 | 0.0001 | - |
313
+ | 2.3023 | 7600 | 0.0 | - |
314
+ | 2.3175 | 7650 | 0.0 | - |
315
+ | 2.3326 | 7700 | 0.0 | - |
316
+ | 2.3478 | 7750 | 0.0 | - |
317
+ | 2.3629 | 7800 | 0.0 | - |
318
+ | 2.3781 | 7850 | 0.0 | - |
319
+ | 2.3932 | 7900 | 0.0 | - |
320
+ | 2.4084 | 7950 | 0.0 | - |
321
+ | 2.4235 | 8000 | 0.0 | - |
322
+ | 2.4387 | 8050 | 0.0 | - |
323
+ | 2.4538 | 8100 | 0.0001 | - |
324
+ | 2.4689 | 8150 | 0.0 | - |
325
+ | 2.4841 | 8200 | 0.0001 | - |
326
+ | 2.4992 | 8250 | 0.0 | - |
327
+ | 2.5144 | 8300 | 0.0 | - |
328
+ | 2.5295 | 8350 | 0.0001 | - |
329
+ | 2.5447 | 8400 | 0.0 | - |
330
+ | 2.5598 | 8450 | 0.0 | - |
331
+ | 2.5750 | 8500 | 0.0 | - |
332
+ | 2.5901 | 8550 | 0.0001 | - |
333
+ | 2.6053 | 8600 | 0.0001 | - |
334
+ | 2.6204 | 8650 | 0.0 | - |
335
+ | 2.6356 | 8700 | 0.0 | - |
336
+ | 2.6507 | 8750 | 0.0 | - |
337
+ | 2.6659 | 8800 | 0.0 | - |
338
+ | 2.6810 | 8850 | 0.0 | - |
339
+ | 2.6962 | 8900 | 0.0 | - |
340
+ | 2.7113 | 8950 | 0.0 | - |
341
+ | 2.7264 | 9000 | 0.0 | - |
342
+ | 2.7416 | 9050 | 0.0001 | - |
343
+ | 2.7567 | 9100 | 0.0001 | - |
344
+ | 2.7719 | 9150 | 0.0 | - |
345
+ | 2.7870 | 9200 | 0.0001 | - |
346
+ | 2.8022 | 9250 | 0.0 | - |
347
+ | 2.8173 | 9300 | 0.0 | - |
348
+ | 2.8325 | 9350 | 0.0 | - |
349
+ | 2.8476 | 9400 | 0.0 | - |
350
+ | 2.8628 | 9450 | 0.0 | - |
351
+ | 2.8779 | 9500 | 0.0 | - |
352
+ | 2.8931 | 9550 | 0.0 | - |
353
+ | 2.9082 | 9600 | 0.0 | - |
354
+ | 2.9234 | 9650 | 0.0 | - |
355
+ | 2.9385 | 9700 | 0.0 | - |
356
+ | 2.9537 | 9750 | 0.0 | - |
357
+ | 2.9688 | 9800 | 0.0 | - |
358
+ | 2.9839 | 9850 | 0.0 | - |
359
+ | 2.9991 | 9900 | 0.0 | - |
360
+ | 3.0 | 9903 | - | 0.0 |
361
+ | 3.0142 | 9950 | 0.0 | - |
362
+ | 3.0294 | 10000 | 0.0 | - |
363
+ | 3.0445 | 10050 | 0.0 | - |
364
+ | 3.0597 | 10100 | 0.0 | - |
365
+ | 3.0748 | 10150 | 0.0 | - |
366
+ | 3.0900 | 10200 | 0.0 | - |
367
+ | 3.1051 | 10250 | 0.0001 | - |
368
+ | 3.1203 | 10300 | 0.0001 | - |
369
+ | 3.1354 | 10350 | 0.0 | - |
370
+ | 3.1506 | 10400 | 0.0 | - |
371
+ | 3.1657 | 10450 | 0.0 | - |
372
+ | 3.1809 | 10500 | 0.0 | - |
373
+ | 3.1960 | 10550 | 0.0 | - |
374
+ | 3.2111 | 10600 | 0.0 | - |
375
+ | 3.2263 | 10650 | 0.0 | - |
376
+ | 3.2414 | 10700 | 0.0 | - |
377
+ | 3.2566 | 10750 | 0.0 | - |
378
+ | 3.2717 | 10800 | 0.0 | - |
379
+ | 3.2869 | 10850 | 0.0 | - |
380
+ | 3.3020 | 10900 | 0.0 | - |
381
+ | 3.3172 | 10950 | 0.0 | - |
382
+ | 3.3323 | 11000 | 0.0 | - |
383
+ | 3.3475 | 11050 | 0.0 | - |
384
+ | 3.3626 | 11100 | 0.0 | - |
385
+ | 3.3778 | 11150 | 0.0 | - |
386
+ | 3.3929 | 11200 | 0.0 | - |
387
+ | 3.4081 | 11250 | 0.0001 | - |
388
+ | 3.4232 | 11300 | 0.0 | - |
389
+ | 3.4384 | 11350 | 0.0 | - |
390
+ | 3.4535 | 11400 | 0.0 | - |
391
+ | 3.4686 | 11450 | 0.0 | - |
392
+ | 3.4838 | 11500 | 0.0 | - |
393
+ | 3.4989 | 11550 | 0.0 | - |
394
+ | 3.5141 | 11600 | 0.0 | - |
395
+ | 3.5292 | 11650 | 0.0 | - |
396
+ | 3.5444 | 11700 | 0.0 | - |
397
+ | 3.5595 | 11750 | 0.0 | - |
398
+ | 3.5747 | 11800 | 0.0 | - |
399
+ | 3.5898 | 11850 | 0.0 | - |
400
+ | 3.6050 | 11900 | 0.0 | - |
401
+ | 3.6201 | 11950 | 0.0 | - |
402
+ | 3.6353 | 12000 | 0.0 | - |
403
+ | 3.6504 | 12050 | 0.0 | - |
404
+ | 3.6656 | 12100 | 0.0001 | - |
405
+ | 3.6807 | 12150 | 0.0 | - |
406
+ | 3.6958 | 12200 | 0.0 | - |
407
+ | 3.7110 | 12250 | 0.0 | - |
408
+ | 3.7261 | 12300 | 0.0 | - |
409
+ | 3.7413 | 12350 | 0.0 | - |
410
+ | 3.7564 | 12400 | 0.0 | - |
411
+ | 3.7716 | 12450 | 0.0 | - |
412
+ | 3.7867 | 12500 | 0.0 | - |
413
+ | 3.8019 | 12550 | 0.0 | - |
414
+ | 3.8170 | 12600 | 0.0 | - |
415
+ | 3.8322 | 12650 | 0.0 | - |
416
+ | 3.8473 | 12700 | 0.0 | - |
417
+ | 3.8625 | 12750 | 0.0 | - |
418
+ | 3.8776 | 12800 | 0.0 | - |
419
+ | 3.8928 | 12850 | 0.0 | - |
420
+ | 3.9079 | 12900 | 0.0 | - |
421
+ | 3.9231 | 12950 | 0.0 | - |
422
+ | 3.9382 | 13000 | 0.0 | - |
423
+ | 3.9533 | 13050 | 0.0 | - |
424
+ | 3.9685 | 13100 | 0.0 | - |
425
+ | 3.9836 | 13150 | 0.0 | - |
426
+ | 3.9988 | 13200 | 0.0 | - |
427
+ | **4.0** | **13204** | **-** | **0.0** |
428
+
429
+ * The bold row denotes the saved checkpoint.
430
+ ### Framework Versions
431
+ - Python: 3.10.12
432
+ - SetFit: 1.0.3
433
+ - Sentence Transformers: 3.0.1
434
+ - Transformers: 4.39.0
435
+ - PyTorch: 2.3.0+cu121
436
+ - Datasets: 2.19.2
437
+ - Tokenizers: 0.15.2
438
+
439
+ ## Citation
440
+
441
+ ### BibTeX
442
+ ```bibtex
443
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
444
+ doi = {10.48550/ARXIV.2209.11055},
445
+ url = {https://arxiv.org/abs/2209.11055},
446
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
447
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
448
+ title = {Efficient Few-Shot Learning Without Prompts},
449
+ publisher = {arXiv},
450
+ year = {2022},
451
+ copyright = {Creative Commons Attribution 4.0 International}
452
+ }
453
+ ```
454
+
455
+ <!--
456
+ ## Glossary
457
+
458
+ *Clearly define terms in order to be accessible across audiences.*
459
+ -->
460
+
461
+ <!--
462
+ ## Model Card Authors
463
+
464
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
465
+ -->
466
+
467
+ <!--
468
+ ## Model Card Contact
469
+
470
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
471
+ -->
config.json ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "checkpoints/step_13204",
3
+ "architectures": [
4
+ "BertModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "gradient_checkpointing": false,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 384,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 1536,
14
+ "layer_norm_eps": 1e-12,
15
+ "max_position_embeddings": 512,
16
+ "model_type": "bert",
17
+ "num_attention_heads": 12,
18
+ "num_hidden_layers": 12,
19
+ "pad_token_id": 0,
20
+ "position_embedding_type": "absolute",
21
+ "torch_dtype": "float32",
22
+ "transformers_version": "4.39.0",
23
+ "type_vocab_size": 2,
24
+ "use_cache": true,
25
+ "vocab_size": 30522
26
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.0.1",
4
+ "transformers": "4.39.0",
5
+ "pytorch": "2.3.0+cu121"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": null
10
+ }
config_setfit.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "normalize_embeddings": false,
3
+ "labels": [
4
+ "negative",
5
+ "positive"
6
+ ]
7
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:40e4cc7db0adcc18ad2ffb99b2b10140583b345bcfc9069ad9dbaac3ab83b733
3
+ size 133462128
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:878280bcf58d6869d7a31c866e31de59e398374d8008422dae0b780102ab3a97
3
+ size 16559
modules.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ {
15
+ "idx": 2,
16
+ "name": "2",
17
+ "path": "2_Normalize",
18
+ "type": "sentence_transformers.models.Normalize"
19
+ }
20
+ ]
sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 128,
3
+ "do_lower_case": false
4
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cls_token": {
3
+ "content": "[CLS]",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "mask_token": {
10
+ "content": "[MASK]",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "pad_token": {
17
+ "content": "[PAD]",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "sep_token": {
24
+ "content": "[SEP]",
25
+ "lstrip": false,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "unk_token": {
31
+ "content": "[UNK]",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ }
37
+ }
tokenizer.json ADDED
The diff for this file is too large to render. See raw diff
 
tokenizer_config.json ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "[PAD]",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "100": {
12
+ "content": "[UNK]",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "101": {
20
+ "content": "[CLS]",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "102": {
28
+ "content": "[SEP]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "103": {
36
+ "content": "[MASK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "clean_up_tokenization_spaces": true,
45
+ "cls_token": "[CLS]",
46
+ "do_basic_tokenize": true,
47
+ "do_lower_case": true,
48
+ "mask_token": "[MASK]",
49
+ "max_length": 128,
50
+ "model_max_length": 128,
51
+ "never_split": null,
52
+ "pad_to_multiple_of": null,
53
+ "pad_token": "[PAD]",
54
+ "pad_token_type_id": 0,
55
+ "padding_side": "right",
56
+ "sep_token": "[SEP]",
57
+ "stride": 0,
58
+ "strip_accents": null,
59
+ "tokenize_chinese_chars": true,
60
+ "tokenizer_class": "BertTokenizer",
61
+ "truncation_side": "right",
62
+ "truncation_strategy": "longest_first",
63
+ "unk_token": "[UNK]"
64
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff