amitprgx commited on
Commit
1411061
1 Parent(s): ab73f33

Add SetFit model

Browse files
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 +1,449 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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/paraphrase-mpnet-base-v2
9
+ metrics:
10
+ - accuracy
11
+ widget:
12
+ - text: BI 8U-Q10-AP6X2-V1131 SENSOR QUICK DISCO
13
+ - text: 48-08-0551 FOLDING MITRE SAW STAND
14
+ - text: JAS-LEB04-M3 COMPACT SPEED CONTROLLER
15
+ - text: LWFS37C2R1025HS2/E37.5 RAIL
16
+ - text: '300108'
17
+ pipeline_tag: text-classification
18
+ inference: false
19
+ model-index:
20
+ - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
21
+ results:
22
+ - task:
23
+ type: text-classification
24
+ name: Text Classification
25
+ dataset:
26
+ name: Unknown
27
+ type: unknown
28
+ split: test
29
+ metrics:
30
+ - type: accuracy
31
+ value: 0.3217244143582435
32
+ name: Accuracy
33
+ ---
34
+
35
+ # SetFit with sentence-transformers/paraphrase-mpnet-base-v2
36
+
37
+ 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 OneVsRestClassifier instance is used for classification.
38
+
39
+ The model has been trained using an efficient few-shot learning technique that involves:
40
+
41
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
42
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
43
+
44
+ ## Model Details
45
+
46
+ ### Model Description
47
+ - **Model Type:** SetFit
48
+ - **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
49
+ - **Classification head:** a OneVsRestClassifier instance
50
+ - **Maximum Sequence Length:** 512 tokens
51
+ <!-- - **Number of Classes:** Unknown -->
52
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
53
+ <!-- - **Language:** Unknown -->
54
+ <!-- - **License:** Unknown -->
55
+
56
+ ### Model Sources
57
+
58
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
59
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
60
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
61
+
62
+ ## Evaluation
63
+
64
+ ### Metrics
65
+ | Label | Accuracy |
66
+ |:--------|:---------|
67
+ | **all** | 0.3217 |
68
+
69
+ ## Uses
70
+
71
+ ### Direct Use for Inference
72
+
73
+ First install the SetFit library:
74
+
75
+ ```bash
76
+ pip install setfit
77
+ ```
78
+
79
+ Then you can load this model and run inference.
80
+
81
+ ```python
82
+ from setfit import SetFitModel
83
+
84
+ # Download from the 🤗 Hub
85
+ model = SetFitModel.from_pretrained("amitprgx/setfit-categorization")
86
+ # Run inference
87
+ preds = model("300108")
88
+ ```
89
+
90
+ <!--
91
+ ### Downstream Use
92
+
93
+ *List how someone could finetune this model on their own dataset.*
94
+ -->
95
+
96
+ <!--
97
+ ### Out-of-Scope Use
98
+
99
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
100
+ -->
101
+
102
+ <!--
103
+ ## Bias, Risks and Limitations
104
+
105
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
106
+ -->
107
+
108
+ <!--
109
+ ### Recommendations
110
+
111
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
112
+ -->
113
+
114
+ ## Training Details
115
+
116
+ ### Training Set Metrics
117
+ | Training set | Min | Median | Max |
118
+ |:-------------|:----|:-------|:----|
119
+ | Word count | 1 | 4.7197 | 10 |
120
+
121
+ ### Training Hyperparameters
122
+ - batch_size: (8, 8)
123
+ - num_epochs: (10, 10)
124
+ - max_steps: -1
125
+ - sampling_strategy: oversampling
126
+ - num_iterations: 20
127
+ - body_learning_rate: (2e-05, 2e-05)
128
+ - head_learning_rate: 2e-05
129
+ - loss: CosineSimilarityLoss
130
+ - distance_metric: cosine_distance
131
+ - margin: 0.25
132
+ - end_to_end: False
133
+ - use_amp: False
134
+ - warmup_proportion: 0.1
135
+ - seed: 42
136
+ - eval_max_steps: -1
137
+ - load_best_model_at_end: False
138
+
139
+ ### Training Results
140
+ | Epoch | Step | Training Loss | Validation Loss |
141
+ |:------:|:-----:|:-------------:|:---------------:|
142
+ | 0.0008 | 1 | 0.1444 | - |
143
+ | 0.0379 | 50 | 0.1563 | - |
144
+ | 0.0758 | 100 | 0.2163 | - |
145
+ | 0.1136 | 150 | 0.3125 | - |
146
+ | 0.1515 | 200 | 0.2152 | - |
147
+ | 0.1894 | 250 | 0.2731 | - |
148
+ | 0.2273 | 300 | 0.2788 | - |
149
+ | 0.2652 | 350 | 0.2315 | - |
150
+ | 0.3030 | 400 | 0.1847 | - |
151
+ | 0.3409 | 450 | 0.1253 | - |
152
+ | 0.3788 | 500 | 0.1363 | - |
153
+ | 0.4167 | 550 | 0.1816 | - |
154
+ | 0.4545 | 600 | 0.1957 | - |
155
+ | 0.4924 | 650 | 0.1931 | - |
156
+ | 0.5303 | 700 | 0.1392 | - |
157
+ | 0.5682 | 750 | 0.0613 | - |
158
+ | 0.6061 | 800 | 0.0403 | - |
159
+ | 0.6439 | 850 | 0.0796 | - |
160
+ | 0.6818 | 900 | 0.0661 | - |
161
+ | 0.7197 | 950 | 0.1207 | - |
162
+ | 0.7576 | 1000 | 0.0795 | - |
163
+ | 0.7955 | 1050 | 0.0439 | - |
164
+ | 0.8333 | 1100 | 0.0744 | - |
165
+ | 0.8712 | 1150 | 0.0972 | - |
166
+ | 0.9091 | 1200 | 0.0512 | - |
167
+ | 0.9470 | 1250 | 0.0335 | - |
168
+ | 0.9848 | 1300 | 0.0092 | - |
169
+ | 1.0227 | 1350 | 0.0489 | - |
170
+ | 1.0606 | 1400 | 0.0176 | - |
171
+ | 1.0985 | 1450 | 0.0302 | - |
172
+ | 1.1364 | 1500 | 0.0811 | - |
173
+ | 1.1742 | 1550 | 0.0181 | - |
174
+ | 1.2121 | 1600 | 0.0354 | - |
175
+ | 1.25 | 1650 | 0.0183 | - |
176
+ | 1.2879 | 1700 | 0.0167 | - |
177
+ | 1.3258 | 1750 | 0.006 | - |
178
+ | 1.3636 | 1800 | 0.0294 | - |
179
+ | 1.4015 | 1850 | 0.0342 | - |
180
+ | 1.4394 | 1900 | 0.005 | - |
181
+ | 1.4773 | 1950 | 0.0044 | - |
182
+ | 1.5152 | 2000 | 0.0069 | - |
183
+ | 1.5530 | 2050 | 0.0051 | - |
184
+ | 1.5909 | 2100 | 0.0375 | - |
185
+ | 1.6288 | 2150 | 0.0123 | - |
186
+ | 1.6667 | 2200 | 0.0058 | - |
187
+ | 1.7045 | 2250 | 0.0086 | - |
188
+ | 1.7424 | 2300 | 0.0141 | - |
189
+ | 1.7803 | 2350 | 0.0014 | - |
190
+ | 1.8182 | 2400 | 0.0047 | - |
191
+ | 1.8561 | 2450 | 0.0018 | - |
192
+ | 1.8939 | 2500 | 0.0063 | - |
193
+ | 1.9318 | 2550 | 0.0018 | - |
194
+ | 1.9697 | 2600 | 0.0032 | - |
195
+ | 2.0076 | 2650 | 0.001 | - |
196
+ | 2.0455 | 2700 | 0.0165 | - |
197
+ | 2.0833 | 2750 | 0.0773 | - |
198
+ | 2.1212 | 2800 | 0.0014 | - |
199
+ | 2.1591 | 2850 | 0.0105 | - |
200
+ | 2.1970 | 2900 | 0.0013 | - |
201
+ | 2.2348 | 2950 | 0.0009 | - |
202
+ | 2.2727 | 3000 | 0.0034 | - |
203
+ | 2.3106 | 3050 | 0.0013 | - |
204
+ | 2.3485 | 3100 | 0.0065 | - |
205
+ | 2.3864 | 3150 | 0.0008 | - |
206
+ | 2.4242 | 3200 | 0.1143 | - |
207
+ | 2.4621 | 3250 | 0.0036 | - |
208
+ | 2.5 | 3300 | 0.0254 | - |
209
+ | 2.5379 | 3350 | 0.0023 | - |
210
+ | 2.5758 | 3400 | 0.004 | - |
211
+ | 2.6136 | 3450 | 0.0034 | - |
212
+ | 2.6515 | 3500 | 0.0019 | - |
213
+ | 2.6894 | 3550 | 0.001 | - |
214
+ | 2.7273 | 3600 | 0.1044 | - |
215
+ | 2.7652 | 3650 | 0.0005 | - |
216
+ | 2.8030 | 3700 | 0.0955 | - |
217
+ | 2.8409 | 3750 | 0.0011 | - |
218
+ | 2.8788 | 3800 | 0.0018 | - |
219
+ | 2.9167 | 3850 | 0.0017 | - |
220
+ | 2.9545 | 3900 | 0.0007 | - |
221
+ | 2.9924 | 3950 | 0.001 | - |
222
+ | 3.0303 | 4000 | 0.0009 | - |
223
+ | 3.0682 | 4050 | 0.001 | - |
224
+ | 3.1061 | 4100 | 0.0035 | - |
225
+ | 3.1439 | 4150 | 0.0009 | - |
226
+ | 3.1818 | 4200 | 0.0009 | - |
227
+ | 3.2197 | 4250 | 0.0005 | - |
228
+ | 3.2576 | 4300 | 0.0011 | - |
229
+ | 3.2955 | 4350 | 0.0007 | - |
230
+ | 3.3333 | 4400 | 0.0007 | - |
231
+ | 3.3712 | 4450 | 0.0003 | - |
232
+ | 3.4091 | 4500 | 0.0008 | - |
233
+ | 3.4470 | 4550 | 0.0007 | - |
234
+ | 3.4848 | 4600 | 0.0004 | - |
235
+ | 3.5227 | 4650 | 0.0011 | - |
236
+ | 3.5606 | 4700 | 0.0009 | - |
237
+ | 3.5985 | 4750 | 0.0004 | - |
238
+ | 3.6364 | 4800 | 0.0006 | - |
239
+ | 3.6742 | 4850 | 0.0012 | - |
240
+ | 3.7121 | 4900 | 0.0004 | - |
241
+ | 3.75 | 4950 | 0.0003 | - |
242
+ | 3.7879 | 5000 | 0.0005 | - |
243
+ | 3.8258 | 5050 | 0.0007 | - |
244
+ | 3.8636 | 5100 | 0.0012 | - |
245
+ | 3.9015 | 5150 | 0.0003 | - |
246
+ | 3.9394 | 5200 | 0.0009 | - |
247
+ | 3.9773 | 5250 | 0.0003 | - |
248
+ | 4.0152 | 5300 | 0.0003 | - |
249
+ | 4.0530 | 5350 | 0.0005 | - |
250
+ | 4.0909 | 5400 | 0.0004 | - |
251
+ | 4.1288 | 5450 | 0.0003 | - |
252
+ | 4.1667 | 5500 | 0.0003 | - |
253
+ | 4.2045 | 5550 | 0.0011 | - |
254
+ | 4.2424 | 5600 | 0.0002 | - |
255
+ | 4.2803 | 5650 | 0.0004 | - |
256
+ | 4.3182 | 5700 | 0.0009 | - |
257
+ | 4.3561 | 5750 | 0.0003 | - |
258
+ | 4.3939 | 5800 | 0.0002 | - |
259
+ | 4.4318 | 5850 | 0.0008 | - |
260
+ | 4.4697 | 5900 | 0.0003 | - |
261
+ | 4.5076 | 5950 | 0.0004 | - |
262
+ | 4.5455 | 6000 | 0.0272 | - |
263
+ | 4.5833 | 6050 | 0.0012 | - |
264
+ | 4.6212 | 6100 | 0.0006 | - |
265
+ | 4.6591 | 6150 | 0.0005 | - |
266
+ | 4.6970 | 6200 | 0.0011 | - |
267
+ | 4.7348 | 6250 | 0.0003 | - |
268
+ | 4.7727 | 6300 | 0.0003 | - |
269
+ | 4.8106 | 6350 | 0.0026 | - |
270
+ | 4.8485 | 6400 | 0.0007 | - |
271
+ | 4.8864 | 6450 | 0.0002 | - |
272
+ | 4.9242 | 6500 | 0.0007 | - |
273
+ | 4.9621 | 6550 | 0.0004 | - |
274
+ | 5.0 | 6600 | 0.0002 | - |
275
+ | 5.0379 | 6650 | 0.0002 | - |
276
+ | 5.0758 | 6700 | 0.0003 | - |
277
+ | 5.1136 | 6750 | 0.0004 | - |
278
+ | 5.1515 | 6800 | 0.0007 | - |
279
+ | 5.1894 | 6850 | 0.0002 | - |
280
+ | 5.2273 | 6900 | 0.0002 | - |
281
+ | 5.2652 | 6950 | 0.0001 | - |
282
+ | 5.3030 | 7000 | 0.0003 | - |
283
+ | 5.3409 | 7050 | 0.0001 | - |
284
+ | 5.3788 | 7100 | 0.0002 | - |
285
+ | 5.4167 | 7150 | 0.0003 | - |
286
+ | 5.4545 | 7200 | 0.0006 | - |
287
+ | 5.4924 | 7250 | 0.0002 | - |
288
+ | 5.5303 | 7300 | 0.0002 | - |
289
+ | 5.5682 | 7350 | 0.0002 | - |
290
+ | 5.6061 | 7400 | 0.0004 | - |
291
+ | 5.6439 | 7450 | 0.0003 | - |
292
+ | 5.6818 | 7500 | 0.0002 | - |
293
+ | 5.7197 | 7550 | 0.0002 | - |
294
+ | 5.7576 | 7600 | 0.0002 | - |
295
+ | 5.7955 | 7650 | 0.0005 | - |
296
+ | 5.8333 | 7700 | 0.0013 | - |
297
+ | 5.8712 | 7750 | 0.0002 | - |
298
+ | 5.9091 | 7800 | 0.0015 | - |
299
+ | 5.9470 | 7850 | 0.0001 | - |
300
+ | 5.9848 | 7900 | 0.0002 | - |
301
+ | 6.0227 | 7950 | 0.0001 | - |
302
+ | 6.0606 | 8000 | 0.0015 | - |
303
+ | 6.0985 | 8050 | 0.0004 | - |
304
+ | 6.1364 | 8100 | 0.0373 | - |
305
+ | 6.1742 | 8150 | 0.0003 | - |
306
+ | 6.2121 | 8200 | 0.0002 | - |
307
+ | 6.25 | 8250 | 0.0003 | - |
308
+ | 6.2879 | 8300 | 0.0003 | - |
309
+ | 6.3258 | 8350 | 0.0003 | - |
310
+ | 6.3636 | 8400 | 0.0002 | - |
311
+ | 6.4015 | 8450 | 0.0001 | - |
312
+ | 6.4394 | 8500 | 0.0004 | - |
313
+ | 6.4773 | 8550 | 0.0002 | - |
314
+ | 6.5152 | 8600 | 0.0002 | - |
315
+ | 6.5530 | 8650 | 0.0002 | - |
316
+ | 6.5909 | 8700 | 0.0004 | - |
317
+ | 6.6288 | 8750 | 0.0002 | - |
318
+ | 6.6667 | 8800 | 0.0001 | - |
319
+ | 6.7045 | 8850 | 0.0003 | - |
320
+ | 6.7424 | 8900 | 0.0001 | - |
321
+ | 6.7803 | 8950 | 0.0002 | - |
322
+ | 6.8182 | 9000 | 0.0003 | - |
323
+ | 6.8561 | 9050 | 0.0002 | - |
324
+ | 6.8939 | 9100 | 0.0002 | - |
325
+ | 6.9318 | 9150 | 0.0001 | - |
326
+ | 6.9697 | 9200 | 0.0001 | - |
327
+ | 7.0076 | 9250 | 0.0002 | - |
328
+ | 7.0455 | 9300 | 0.0002 | - |
329
+ | 7.0833 | 9350 | 0.0002 | - |
330
+ | 7.1212 | 9400 | 0.0001 | - |
331
+ | 7.1591 | 9450 | 0.0002 | - |
332
+ | 7.1970 | 9500 | 0.0003 | - |
333
+ | 7.2348 | 9550 | 0.0005 | - |
334
+ | 7.2727 | 9600 | 0.0002 | - |
335
+ | 7.3106 | 9650 | 0.0002 | - |
336
+ | 7.3485 | 9700 | 0.0002 | - |
337
+ | 7.3864 | 9750 | 0.0002 | - |
338
+ | 7.4242 | 9800 | 0.0002 | - |
339
+ | 7.4621 | 9850 | 0.0001 | - |
340
+ | 7.5 | 9900 | 0.0001 | - |
341
+ | 7.5379 | 9950 | 0.0002 | - |
342
+ | 7.5758 | 10000 | 0.0001 | - |
343
+ | 7.6136 | 10050 | 0.0001 | - |
344
+ | 7.6515 | 10100 | 0.0001 | - |
345
+ | 7.6894 | 10150 | 0.0002 | - |
346
+ | 7.7273 | 10200 | 0.0002 | - |
347
+ | 7.7652 | 10250 | 0.0001 | - |
348
+ | 7.8030 | 10300 | 0.0002 | - |
349
+ | 7.8409 | 10350 | 0.0003 | - |
350
+ | 7.8788 | 10400 | 0.0002 | - |
351
+ | 7.9167 | 10450 | 0.0002 | - |
352
+ | 7.9545 | 10500 | 0.0001 | - |
353
+ | 7.9924 | 10550 | 0.0002 | - |
354
+ | 8.0303 | 10600 | 0.0002 | - |
355
+ | 8.0682 | 10650 | 0.0002 | - |
356
+ | 8.1061 | 10700 | 0.0002 | - |
357
+ | 8.1439 | 10750 | 0.0001 | - |
358
+ | 8.1818 | 10800 | 0.0001 | - |
359
+ | 8.2197 | 10850 | 0.0001 | - |
360
+ | 8.2576 | 10900 | 0.0001 | - |
361
+ | 8.2955 | 10950 | 0.0001 | - |
362
+ | 8.3333 | 11000 | 0.0002 | - |
363
+ | 8.3712 | 11050 | 0.0007 | - |
364
+ | 8.4091 | 11100 | 0.0001 | - |
365
+ | 8.4470 | 11150 | 0.0002 | - |
366
+ | 8.4848 | 11200 | 0.0001 | - |
367
+ | 8.5227 | 11250 | 0.0002 | - |
368
+ | 8.5606 | 11300 | 0.0001 | - |
369
+ | 8.5985 | 11350 | 0.0001 | - |
370
+ | 8.6364 | 11400 | 0.0001 | - |
371
+ | 8.6742 | 11450 | 0.0001 | - |
372
+ | 8.7121 | 11500 | 0.0002 | - |
373
+ | 8.75 | 11550 | 0.0001 | - |
374
+ | 8.7879 | 11600 | 0.0001 | - |
375
+ | 8.8258 | 11650 | 0.0001 | - |
376
+ | 8.8636 | 11700 | 0.0001 | - |
377
+ | 8.9015 | 11750 | 0.0001 | - |
378
+ | 8.9394 | 11800 | 0.0001 | - |
379
+ | 8.9773 | 11850 | 0.0001 | - |
380
+ | 9.0152 | 11900 | 0.0001 | - |
381
+ | 9.0530 | 11950 | 0.0001 | - |
382
+ | 9.0909 | 12000 | 0.0001 | - |
383
+ | 9.1288 | 12050 | 0.0001 | - |
384
+ | 9.1667 | 12100 | 0.0002 | - |
385
+ | 9.2045 | 12150 | 0.0001 | - |
386
+ | 9.2424 | 12200 | 0.0001 | - |
387
+ | 9.2803 | 12250 | 0.0002 | - |
388
+ | 9.3182 | 12300 | 0.0002 | - |
389
+ | 9.3561 | 12350 | 0.0002 | - |
390
+ | 9.3939 | 12400 | 0.0001 | - |
391
+ | 9.4318 | 12450 | 0.0003 | - |
392
+ | 9.4697 | 12500 | 0.0001 | - |
393
+ | 9.5076 | 12550 | 0.0001 | - |
394
+ | 9.5455 | 12600 | 0.0001 | - |
395
+ | 9.5833 | 12650 | 0.0002 | - |
396
+ | 9.6212 | 12700 | 0.0001 | - |
397
+ | 9.6591 | 12750 | 0.0002 | - |
398
+ | 9.6970 | 12800 | 0.0002 | - |
399
+ | 9.7348 | 12850 | 0.0001 | - |
400
+ | 9.7727 | 12900 | 0.0001 | - |
401
+ | 9.8106 | 12950 | 0.0001 | - |
402
+ | 9.8485 | 13000 | 0.0001 | - |
403
+ | 9.8864 | 13050 | 0.0001 | - |
404
+ | 9.9242 | 13100 | 0.0001 | - |
405
+ | 9.9621 | 13150 | 0.0001 | - |
406
+ | 10.0 | 13200 | 0.0002 | - |
407
+
408
+ ### Framework Versions
409
+ - Python: 3.11.8
410
+ - SetFit: 1.1.0.dev0
411
+ - Sentence Transformers: 2.6.1
412
+ - Transformers: 4.39.3
413
+ - PyTorch: 1.13.1+cu117
414
+ - Datasets: 2.19.0
415
+ - Tokenizers: 0.15.2
416
+
417
+ ## Citation
418
+
419
+ ### BibTeX
420
+ ```bibtex
421
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
422
+ doi = {10.48550/ARXIV.2209.11055},
423
+ url = {https://arxiv.org/abs/2209.11055},
424
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
425
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
426
+ title = {Efficient Few-Shot Learning Without Prompts},
427
+ publisher = {arXiv},
428
+ year = {2022},
429
+ copyright = {Creative Commons Attribution 4.0 International}
430
+ }
431
+ ```
432
+
433
+ <!--
434
+ ## Glossary
435
+
436
+ *Clearly define terms in order to be accessible across audiences.*
437
+ -->
438
+
439
+ <!--
440
+ ## Model Card Authors
441
+
442
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
443
+ -->
444
+
445
+ <!--
446
+ ## Model Card Contact
447
+
448
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
449
+ -->
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": "4.39.3",
23
+ "vocab_size": 30527
24
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "2.0.0",
4
+ "transformers": "4.7.0",
5
+ "pytorch": "1.9.0+cu102"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null
9
+ }
config_setfit.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "normalize_embeddings": false,
3
+ "labels": null
4
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:468f98b1e5b3ba7e2c3d6c228915536191946c308a9746f122e454d532ffb162
3
+ size 437967672
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3d602f4ba884361f2ed14170468d13e2a3cb8f67bbf0a3f0e6a39eb7381ab9c1
3
+ size 214836
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