Hugging Face's logo

victomoe
/
setfit-intent-classifier-3

Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Model card Files
xet
Community
victomoe commited on
Commit
0af5018
·
verified ·
1 Parent(s): 0420580

Push model using huggingface_hub.

Browse files
Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +345 -0
  3. config.json +24 -0
  4. config_sentence_transformers.json +10 -0
  5. config_setfit.json +13 -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 +59 -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 +1,345 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: setfit
3
+ tags:
4
+ - setfit
5
+ - sentence-transformers
6
+ - text-classification
7
+ - generated_from_setfit_trainer
8
+ metrics:
9
+ - accuracy
10
+ widget:
11
+ - text: Can you set an alarm?
12
+ - text: Bring me one floor higher
13
+ - text: I’d like to go to floor 2.
14
+ - text: Okay, go ahead.
15
+ - text: I’d like to go down two floors
16
+ pipeline_tag: text-classification
17
+ inference: true
18
+ base_model: sentence-transformers/paraphrase-mpnet-base-v2
19
+ ---
20
+
21
+ # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
22
+
23
+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-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.
24
+
25
+ The model has been trained using an efficient few-shot learning technique that involves:
26
+
27
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
28
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
29
+
30
+ ## Model Details
31
+
32
+ ### Model Description
33
+ - **Model Type:** SetFit
34
+ - **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
35
+ - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
36
+ - **Maximum Sequence Length:** 512 tokens
37
+ - **Number of Classes:** 8 classes
38
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
39
+ <!-- - **Language:** Unknown -->
40
+ <!-- - **License:** Unknown -->
41
+
42
+ ### Model Sources
43
+
44
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
45
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
46
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
47
+
48
+ ### Model Labels
49
+ | Label | Examples |
50
+ |:------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------|
51
+ | RequestMoveToFloor | <ul><li>'Please go to the 3rd floor.'</li><li>'Can you take me to floor 5?'</li><li>'I need to go to the 8th floor.'</li></ul> |
52
+ | RequestMoveUp | <ul><li>'Go one floor up'</li><li>'Take me up two floors'</li><li>'Go up three floors, please'</li></ul> |
53
+ | RequestMoveDown | <ul><li>'Move me down one level'</li><li>'Can you take me down two floors?'</li><li>'Go down three levels'</li></ul> |
54
+ | Confirm | <ul><li>"Yes, that's right."</li><li>'Sure.'</li><li>'Exactly.'</li></ul> |
55
+ | RequestEmployeeLocation | <ul><li>'Where is Erik Velldal’s office?'</li><li>'Which floor is Andreas Austeng on?'</li><li>'Can you tell me where Birthe Soppe’s office is?'</li></ul> |
56
+ | CurrentFloor | <ul><li>'Which floor are we on?'</li><li>'What floor is this?'</li><li>'Are we on the 5th floor?'</li></ul> |
57
+ | Stop | <ul><li>'Stop the elevator.'</li><li>"Wait, don't go to that floor."</li><li>'No, not that floor.'</li></ul> |
58
+ | OutOfCoverage | <ul><li>"What's the capital of France?"</li><li>'How many floors does this building have?'</li><li>'Can you make a phone call for me?'</li></ul> |
59
+
60
+ ## Uses
61
+
62
+ ### Direct Use for Inference
63
+
64
+ First install the SetFit library:
65
+
66
+ ```bash
67
+ pip install setfit
68
+ ```
69
+
70
+ Then you can load this model and run inference.
71
+
72
+ ```python
73
+ from setfit import SetFitModel
74
+
75
+ # Download from the 🤗 Hub
76
+ model = SetFitModel.from_pretrained("victomoe/setfit-intent-classifier-3")
77
+ # Run inference
78
+ preds = model("Okay, go ahead.")
79
+ ```
80
+
81
+ <!--
82
+ ### Downstream Use
83
+
84
+ *List how someone could finetune this model on their own dataset.*
85
+ -->
86
+
87
+ <!--
88
+ ### Out-of-Scope Use
89
+
90
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
91
+ -->
92
+
93
+ <!--
94
+ ## Bias, Risks and Limitations
95
+
96
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
97
+ -->
98
+
99
+ <!--
100
+ ### Recommendations
101
+
102
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
103
+ -->
104
+
105
+ ## Training Details
106
+
107
+ ### Training Set Metrics
108
+ | Training set | Min | Median | Max |
109
+ |:-------------|:----|:-------|:----|
110
+ | Word count | 1 | 5.2118 | 9 |
111
+
112
+ | Label | Training Sample Count |
113
+ |:------------------------|:----------------------|
114
+ | Confirm | 22 |
115
+ | CurrentFloor | 21 |
116
+ | OutOfCoverage | 22 |
117
+ | RequestEmployeeLocation | 22 |
118
+ | RequestMoveDown | 20 |
119
+ | RequestMoveToFloor | 23 |
120
+ | RequestMoveUp | 20 |
121
+ | Stop | 20 |
122
+
123
+ ### Training Hyperparameters
124
+ - batch_size: (32, 32)
125
+ - num_epochs: (10, 10)
126
+ - max_steps: -1
127
+ - sampling_strategy: oversampling
128
+ - body_learning_rate: (2e-05, 1e-05)
129
+ - head_learning_rate: 0.01
130
+ - loss: CosineSimilarityLoss
131
+ - distance_metric: cosine_distance
132
+ - margin: 0.25
133
+ - end_to_end: False
134
+ - use_amp: False
135
+ - warmup_proportion: 0.1
136
+ - l2_weight: 0.01
137
+ - seed: 42
138
+ - eval_max_steps: -1
139
+ - load_best_model_at_end: False
140
+
141
+ ### Training Results
142
+ | Epoch | Step | Training Loss | Validation Loss |
143
+ |:------:|:----:|:-------------:|:---------------:|
144
+ | 0.0013 | 1 | 0.195 | - |
145
+ | 0.0633 | 50 | 0.1877 | - |
146
+ | 0.1266 | 100 | 0.1592 | - |
147
+ | 0.1899 | 150 | 0.1141 | - |
148
+ | 0.2532 | 200 | 0.0603 | - |
149
+ | 0.3165 | 250 | 0.0283 | - |
150
+ | 0.3797 | 300 | 0.0104 | - |
151
+ | 0.4430 | 350 | 0.0043 | - |
152
+ | 0.5063 | 400 | 0.0027 | - |
153
+ | 0.5696 | 450 | 0.0021 | - |
154
+ | 0.6329 | 500 | 0.0017 | - |
155
+ | 0.6962 | 550 | 0.0015 | - |
156
+ | 0.7595 | 600 | 0.0011 | - |
157
+ | 0.8228 | 650 | 0.001 | - |
158
+ | 0.8861 | 700 | 0.0011 | - |
159
+ | 0.9494 | 750 | 0.0008 | - |
160
+ | 1.0127 | 800 | 0.0007 | - |
161
+ | 1.0759 | 850 | 0.0006 | - |
162
+ | 1.1392 | 900 | 0.0006 | - |
163
+ | 1.2025 | 950 | 0.0005 | - |
164
+ | 1.2658 | 1000 | 0.0005 | - |
165
+ | 1.3291 | 1050 | 0.0005 | - |
166
+ | 1.3924 | 1100 | 0.0004 | - |
167
+ | 1.4557 | 1150 | 0.0004 | - |
168
+ | 1.5190 | 1200 | 0.0004 | - |
169
+ | 1.5823 | 1250 | 0.0004 | - |
170
+ | 1.6456 | 1300 | 0.0004 | - |
171
+ | 1.7089 | 1350 | 0.0003 | - |
172
+ | 1.7722 | 1400 | 0.0003 | - |
173
+ | 1.8354 | 1450 | 0.0003 | - |
174
+ | 1.8987 | 1500 | 0.0003 | - |
175
+ | 1.9620 | 1550 | 0.0003 | - |
176
+ | 2.0253 | 1600 | 0.0003 | - |
177
+ | 2.0886 | 1650 | 0.0003 | - |
178
+ | 2.1519 | 1700 | 0.0003 | - |
179
+ | 2.2152 | 1750 | 0.0003 | - |
180
+ | 2.2785 | 1800 | 0.0003 | - |
181
+ | 2.3418 | 1850 | 0.0002 | - |
182
+ | 2.4051 | 1900 | 0.0002 | - |
183
+ | 2.4684 | 1950 | 0.0002 | - |
184
+ | 2.5316 | 2000 | 0.0002 | - |
185
+ | 2.5949 | 2050 | 0.0002 | - |
186
+ | 2.6582 | 2100 | 0.0002 | - |
187
+ | 2.7215 | 2150 | 0.0002 | - |
188
+ | 2.7848 | 2200 | 0.0002 | - |
189
+ | 2.8481 | 2250 | 0.0002 | - |
190
+ | 2.9114 | 2300 | 0.0002 | - |
191
+ | 2.9747 | 2350 | 0.0002 | - |
192
+ | 3.0380 | 2400 | 0.0002 | - |
193
+ | 3.1013 | 2450 | 0.0009 | - |
194
+ | 3.1646 | 2500 | 0.0003 | - |
195
+ | 3.2278 | 2550 | 0.0002 | - |
196
+ | 3.2911 | 2600 | 0.0002 | - |
197
+ | 3.3544 | 2650 | 0.0002 | - |
198
+ | 3.4177 | 2700 | 0.0002 | - |
199
+ | 3.4810 | 2750 | 0.0002 | - |
200
+ | 3.5443 | 2800 | 0.0002 | - |
201
+ | 3.6076 | 2850 | 0.0002 | - |
202
+ | 3.6709 | 2900 | 0.0002 | - |
203
+ | 3.7342 | 2950 | 0.0002 | - |
204
+ | 3.7975 | 3000 | 0.0002 | - |
205
+ | 3.8608 | 3050 | 0.0002 | - |
206
+ | 3.9241 | 3100 | 0.0001 | - |
207
+ | 3.9873 | 3150 | 0.0002 | - |
208
+ | 4.0506 | 3200 | 0.0001 | - |
209
+ | 4.1139 | 3250 | 0.0001 | - |
210
+ | 4.1772 | 3300 | 0.0001 | - |
211
+ | 4.2405 | 3350 | 0.0001 | - |
212
+ | 4.3038 | 3400 | 0.0001 | - |
213
+ | 4.3671 | 3450 | 0.0001 | - |
214
+ | 4.4304 | 3500 | 0.0005 | - |
215
+ | 4.4937 | 3550 | 0.0001 | - |
216
+ | 4.5570 | 3600 | 0.0001 | - |
217
+ | 4.6203 | 3650 | 0.0001 | - |
218
+ | 4.6835 | 3700 | 0.0001 | - |
219
+ | 4.7468 | 3750 | 0.0001 | - |
220
+ | 4.8101 | 3800 | 0.0001 | - |
221
+ | 4.8734 | 3850 | 0.0001 | - |
222
+ | 4.9367 | 3900 | 0.0001 | - |
223
+ | 5.0 | 3950 | 0.0001 | - |
224
+ | 5.0633 | 4000 | 0.0001 | - |
225
+ | 5.1266 | 4050 | 0.0001 | - |
226
+ | 5.1899 | 4100 | 0.0001 | - |
227
+ | 5.2532 | 4150 | 0.0001 | - |
228
+ | 5.3165 | 4200 | 0.0001 | - |
229
+ | 5.3797 | 4250 | 0.0001 | - |
230
+ | 5.4430 | 4300 | 0.0001 | - |
231
+ | 5.5063 | 4350 | 0.0001 | - |
232
+ | 5.5696 | 4400 | 0.0001 | - |
233
+ | 5.6329 | 4450 | 0.0001 | - |
234
+ | 5.6962 | 4500 | 0.0001 | - |
235
+ | 5.7595 | 4550 | 0.0001 | - |
236
+ | 5.8228 | 4600 | 0.0001 | - |
237
+ | 5.8861 | 4650 | 0.0001 | - |
238
+ | 5.9494 | 4700 | 0.0001 | - |
239
+ | 6.0127 | 4750 | 0.0001 | - |
240
+ | 6.0759 | 4800 | 0.0001 | - |
241
+ | 6.1392 | 4850 | 0.0001 | - |
242
+ | 6.2025 | 4900 | 0.0001 | - |
243
+ | 6.2658 | 4950 | 0.0001 | - |
244
+ | 6.3291 | 5000 | 0.0001 | - |
245
+ | 6.3924 | 5050 | 0.0001 | - |
246
+ | 6.4557 | 5100 | 0.0001 | - |
247
+ | 6.5190 | 5150 | 0.0001 | - |
248
+ | 6.5823 | 5200 | 0.0001 | - |
249
+ | 6.6456 | 5250 | 0.0001 | - |
250
+ | 6.7089 | 5300 | 0.0001 | - |
251
+ | 6.7722 | 5350 | 0.0001 | - |
252
+ | 6.8354 | 5400 | 0.0001 | - |
253
+ | 6.8987 | 5450 | 0.0001 | - |
254
+ | 6.9620 | 5500 | 0.0001 | - |
255
+ | 7.0253 | 5550 | 0.0001 | - |
256
+ | 7.0886 | 5600 | 0.0001 | - |
257
+ | 7.1519 | 5650 | 0.0001 | - |
258
+ | 7.2152 | 5700 | 0.0001 | - |
259
+ | 7.2785 | 5750 | 0.0001 | - |
260
+ | 7.3418 | 5800 | 0.0001 | - |
261
+ | 7.4051 | 5850 | 0.0001 | - |
262
+ | 7.4684 | 5900 | 0.0001 | - |
263
+ | 7.5316 | 5950 | 0.0001 | - |
264
+ | 7.5949 | 6000 | 0.0001 | - |
265
+ | 7.6582 | 6050 | 0.0001 | - |
266
+ | 7.7215 | 6100 | 0.0001 | - |
267
+ | 7.7848 | 6150 | 0.0001 | - |
268
+ | 7.8481 | 6200 | 0.0001 | - |
269
+ | 7.9114 | 6250 | 0.0001 | - |
270
+ | 7.9747 | 6300 | 0.0001 | - |
271
+ | 8.0380 | 6350 | 0.0001 | - |
272
+ | 8.1013 | 6400 | 0.0001 | - |
273
+ | 8.1646 | 6450 | 0.0001 | - |
274
+ | 8.2278 | 6500 | 0.0001 | - |
275
+ | 8.2911 | 6550 | 0.0001 | - |
276
+ | 8.3544 | 6600 | 0.0001 | - |
277
+ | 8.4177 | 6650 | 0.0001 | - |
278
+ | 8.4810 | 6700 | 0.0001 | - |
279
+ | 8.5443 | 6750 | 0.0001 | - |
280
+ | 8.6076 | 6800 | 0.0001 | - |
281
+ | 8.6709 | 6850 | 0.0001 | - |
282
+ | 8.7342 | 6900 | 0.0001 | - |
283
+ | 8.7975 | 6950 | 0.0001 | - |
284
+ | 8.8608 | 7000 | 0.0001 | - |
285
+ | 8.9241 | 7050 | 0.0001 | - |
286
+ | 8.9873 | 7100 | 0.0001 | - |
287
+ | 9.0506 | 7150 | 0.0001 | - |
288
+ | 9.1139 | 7200 | 0.0001 | - |
289
+ | 9.1772 | 7250 | 0.0001 | - |
290
+ | 9.2405 | 7300 | 0.0001 | - |
291
+ | 9.3038 | 7350 | 0.0001 | - |
292
+ | 9.3671 | 7400 | 0.0001 | - |
293
+ | 9.4304 | 7450 | 0.0001 | - |
294
+ | 9.4937 | 7500 | 0.0001 | - |
295
+ | 9.5570 | 7550 | 0.0001 | - |
296
+ | 9.6203 | 7600 | 0.0001 | - |
297
+ | 9.6835 | 7650 | 0.0001 | - |
298
+ | 9.7468 | 7700 | 0.0001 | - |
299
+ | 9.8101 | 7750 | 0.0001 | - |
300
+ | 9.8734 | 7800 | 0.0001 | - |
301
+ | 9.9367 | 7850 | 0.0001 | - |
302
+ | 10.0 | 7900 | 0.0001 | - |
303
+
304
+ ### Framework Versions
305
+ - Python: 3.10.8
306
+ - SetFit: 1.1.0
307
+ - Sentence Transformers: 3.1.1
308
+ - Transformers: 4.38.2
309
+ - PyTorch: 2.1.2
310
+ - Datasets: 2.17.1
311
+ - Tokenizers: 0.15.0
312
+
313
+ ## Citation
314
+
315
+ ### BibTeX
316
+ ```bibtex
317
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
318
+ doi = {10.48550/ARXIV.2209.11055},
319
+ url = {https://arxiv.org/abs/2209.11055},
320
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
321
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
322
+ title = {Efficient Few-Shot Learning Without Prompts},
323
+ publisher = {arXiv},
324
+ year = {2022},
325
+ copyright = {Creative Commons Attribution 4.0 International}
326
+ }
327
+ ```
328
+
329
+ <!--
330
+ ## Glossary
331
+
332
+ *Clearly define terms in order to be accessible across audiences.*
333
+ -->
334
+
335
+ <!--
336
+ ## Model Card Authors
337
+
338
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
339
+ -->
340
+
341
+ <!--
342
+ ## Model Card Contact
343
+
344
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
345
+ -->
config.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "sentence-transformers/paraphrase-mpnet-base-v2",
3
+ "architectures": [
4
+ "MPNetModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
8
+ "eos_token_id": 2,
9
+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 768,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 3072,
14
+ "layer_norm_eps": 1e-05,
15
+ "max_position_embeddings": 514,
16
+ "model_type": "mpnet",
17
+ "num_attention_heads": 12,
18
+ "num_hidden_layers": 12,
19
+ "pad_token_id": 1,
20
+ "relative_attention_num_buckets": 32,
21
+ "torch_dtype": "float32",
22
+ "transformers_version": "4.38.2",
23
+ "vocab_size": 30527
24
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.1.1",
4
+ "transformers": "4.38.2",
5
+ "pytorch": "2.1.2"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": null
10
+ }
config_setfit.json ADDED
@@ -0,0 +1,13 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "normalize_embeddings": false,
3
+ "labels": [
4
+ "Confirm",
5
+ "CurrentFloor",
6
+ "OutOfCoverage",
7
+ "RequestEmployeeLocation",
8
+ "RequestMoveDown",
9
+ "RequestMoveToFloor",
10
+ "RequestMoveUp",
11
+ "Stop"
12
+ ]
13
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6ead188d82449572432c606460a7a3656df1237c849758b3ff27942dc07e6f6b
3
+ size 437967672
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8985ae5c3b3995575e8b77a085fc6b19f05bb8e3bcce29a269998a4a92b06237
3
+ size 50775
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": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "cls_token": {
10
+ "content": "<s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "eos_token": {
17
+ "content": "</s>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "mask_token": {
24
+ "content": "<mask>",
25
+ "lstrip": true,
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": "</s>",
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 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<s>",
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": "</s>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "104": {
28
+ "content": "[UNK]",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "30526": {
36
+ "content": "<mask>",
37
+ "lstrip": true,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ }
43
+ },
44
+ "bos_token": "<s>",
45
+ "clean_up_tokenization_spaces": true,
46
+ "cls_token": "<s>",
47
+ "do_basic_tokenize": true,
48
+ "do_lower_case": true,
49
+ "eos_token": "</s>",
50
+ "mask_token": "<mask>",
51
+ "model_max_length": 512,
52
+ "never_split": null,
53
+ "pad_token": "<pad>",
54
+ "sep_token": "</s>",
55
+ "strip_accents": null,
56
+ "tokenize_chinese_chars": true,
57
+ "tokenizer_class": "MPNetTokenizer",
58
+ "unk_token": "[UNK]"
59
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff