mmock commited on
Commit
9f145d8
·
verified ·
1 Parent(s): c33a52c

Upload folder using huggingface_hub

Browse files
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 +1,506 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - setfit
4
+ - sentence-transformers
5
+ - text-classification
6
+ - generated_from_setfit_trainer
7
+ widget:
8
+ - text: dataright np^sin 2 np^pi 224 t | Audio
9
+ - text: robust way to ask the database for its current transaction state. | AtomicTests
10
+ - text: the string marking the beginning of a print statement. | Environment
11
+ - text: handled otherwise by a particular method. | StringMethods
12
+ - text: table. | PlotAccessor
13
+ metrics:
14
+ - accuracy
15
+ pipeline_tag: text-classification
16
+ library_name: setfit
17
+ inference: false
18
+ ---
19
+
20
+ # SetFit
21
+
22
+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. A MultiOutputClassifier instance is used for classification.
23
+
24
+ The model has been trained using an efficient few-shot learning technique that involves:
25
+
26
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
27
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
28
+
29
+ ## Model Details
30
+
31
+ ### Model Description
32
+ - **Model Type:** SetFit
33
+ <!-- - **Sentence Transformer:** [Unknown](https://huggingface.co/unknown) -->
34
+ - **Classification head:** a MultiOutputClassifier instance
35
+ - **Maximum Sequence Length:** 128 tokens
36
+ <!-- - **Number of Classes:** Unknown -->
37
+ <!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
38
+ <!-- - **Language:** Unknown -->
39
+ <!-- - **License:** Unknown -->
40
+
41
+ ### Model Sources
42
+
43
+ - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
44
+ - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
45
+ - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
46
+
47
+ ## Uses
48
+
49
+ ### Direct Use for Inference
50
+
51
+ First install the SetFit library:
52
+
53
+ ```bash
54
+ pip install setfit
55
+ ```
56
+
57
+ Then you can load this model and run inference.
58
+
59
+ ```python
60
+ from setfit import SetFitModel
61
+
62
+ # Download from the 🤗 Hub
63
+ model = SetFitModel.from_pretrained("setfit_model_id")
64
+ # Run inference
65
+ preds = model("table. | PlotAccessor")
66
+ ```
67
+
68
+ <!--
69
+ ### Downstream Use
70
+
71
+ *List how someone could finetune this model on their own dataset.*
72
+ -->
73
+
74
+ <!--
75
+ ### Out-of-Scope Use
76
+
77
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
78
+ -->
79
+
80
+ <!--
81
+ ## Bias, Risks and Limitations
82
+
83
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
84
+ -->
85
+
86
+ <!--
87
+ ### Recommendations
88
+
89
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
90
+ -->
91
+
92
+ ## Training Details
93
+
94
+ ### Training Set Metrics
95
+ | Training set | Min | Median | Max |
96
+ |:-------------|:----|:-------|:----|
97
+ | Word count | 3 | 8.9868 | 28 |
98
+
99
+ ### Training Hyperparameters
100
+ - batch_size: (32, 32)
101
+ - num_epochs: (10, 10)
102
+ - max_steps: -1
103
+ - sampling_strategy: oversampling
104
+ - num_iterations: 20
105
+ - body_learning_rate: (2e-05, 1e-05)
106
+ - head_learning_rate: 0.01
107
+ - loss: CosineSimilarityLoss
108
+ - distance_metric: cosine_distance
109
+ - margin: 0.25
110
+ - end_to_end: False
111
+ - use_amp: False
112
+ - warmup_proportion: 0.1
113
+ - l2_weight: 0.01
114
+ - seed: 42
115
+ - eval_max_steps: -1
116
+ - load_best_model_at_end: False
117
+
118
+ ### Training Results
119
+ | Epoch | Step | Training Loss | Validation Loss |
120
+ |:------:|:-----:|:-------------:|:---------------:|
121
+ | 0.0006 | 1 | 0.2743 | - |
122
+ | 0.0292 | 50 | 0.3546 | - |
123
+ | 0.0585 | 100 | 0.3106 | - |
124
+ | 0.0877 | 150 | 0.2652 | - |
125
+ | 0.1170 | 200 | 0.2543 | - |
126
+ | 0.1462 | 250 | 0.2544 | - |
127
+ | 0.1754 | 300 | 0.2521 | - |
128
+ | 0.2047 | 350 | 0.2508 | - |
129
+ | 0.2339 | 400 | 0.2485 | - |
130
+ | 0.2632 | 450 | 0.2499 | - |
131
+ | 0.2924 | 500 | 0.2453 | - |
132
+ | 0.3216 | 550 | 0.2414 | - |
133
+ | 0.3509 | 600 | 0.2379 | - |
134
+ | 0.3801 | 650 | 0.2426 | - |
135
+ | 0.4094 | 700 | 0.2383 | - |
136
+ | 0.4386 | 750 | 0.2385 | - |
137
+ | 0.4678 | 800 | 0.2402 | - |
138
+ | 0.4971 | 850 | 0.2329 | - |
139
+ | 0.5263 | 900 | 0.2328 | - |
140
+ | 0.5556 | 950 | 0.2309 | - |
141
+ | 0.5848 | 1000 | 0.228 | - |
142
+ | 0.6140 | 1050 | 0.2149 | - |
143
+ | 0.6433 | 1100 | 0.2053 | - |
144
+ | 0.6725 | 1150 | 0.1997 | - |
145
+ | 0.7018 | 1200 | 0.1978 | - |
146
+ | 0.7310 | 1250 | 0.1896 | - |
147
+ | 0.7602 | 1300 | 0.1775 | - |
148
+ | 0.7895 | 1350 | 0.1629 | - |
149
+ | 0.8187 | 1400 | 0.1571 | - |
150
+ | 0.8480 | 1450 | 0.1493 | - |
151
+ | 0.8772 | 1500 | 0.1445 | - |
152
+ | 0.9064 | 1550 | 0.1345 | - |
153
+ | 0.9357 | 1600 | 0.1306 | - |
154
+ | 0.9649 | 1650 | 0.1276 | - |
155
+ | 0.9942 | 1700 | 0.1181 | - |
156
+ | 1.0234 | 1750 | 0.1081 | - |
157
+ | 1.0526 | 1800 | 0.1081 | - |
158
+ | 1.0819 | 1850 | 0.1006 | - |
159
+ | 1.1111 | 1900 | 0.0892 | - |
160
+ | 1.1404 | 1950 | 0.0996 | - |
161
+ | 1.1696 | 2000 | 0.0912 | - |
162
+ | 1.1988 | 2050 | 0.0868 | - |
163
+ | 1.2281 | 2100 | 0.089 | - |
164
+ | 1.2573 | 2150 | 0.078 | - |
165
+ | 1.2865 | 2200 | 0.0864 | - |
166
+ | 1.3158 | 2250 | 0.0719 | - |
167
+ | 1.3450 | 2300 | 0.0675 | - |
168
+ | 1.3743 | 2350 | 0.0669 | - |
169
+ | 1.4035 | 2400 | 0.0666 | - |
170
+ | 1.4327 | 2450 | 0.074 | - |
171
+ | 1.4620 | 2500 | 0.0671 | - |
172
+ | 1.4912 | 2550 | 0.0663 | - |
173
+ | 1.5205 | 2600 | 0.0599 | - |
174
+ | 1.5497 | 2650 | 0.0612 | - |
175
+ | 1.5789 | 2700 | 0.056 | - |
176
+ | 1.6082 | 2750 | 0.0575 | - |
177
+ | 1.6374 | 2800 | 0.0553 | - |
178
+ | 1.6667 | 2850 | 0.0611 | - |
179
+ | 1.6959 | 2900 | 0.0535 | - |
180
+ | 1.7251 | 2950 | 0.0558 | - |
181
+ | 1.7544 | 3000 | 0.054 | - |
182
+ | 1.7836 | 3050 | 0.0552 | - |
183
+ | 1.8129 | 3100 | 0.0494 | - |
184
+ | 1.8421 | 3150 | 0.0489 | - |
185
+ | 1.8713 | 3200 | 0.0494 | - |
186
+ | 1.9006 | 3250 | 0.0468 | - |
187
+ | 1.9298 | 3300 | 0.0527 | - |
188
+ | 1.9591 | 3350 | 0.0496 | - |
189
+ | 1.9883 | 3400 | 0.0492 | - |
190
+ | 2.0175 | 3450 | 0.0415 | - |
191
+ | 2.0468 | 3500 | 0.0434 | - |
192
+ | 2.0760 | 3550 | 0.0456 | - |
193
+ | 2.1053 | 3600 | 0.0394 | - |
194
+ | 2.1345 | 3650 | 0.0387 | - |
195
+ | 2.1637 | 3700 | 0.0381 | - |
196
+ | 2.1930 | 3750 | 0.0378 | - |
197
+ | 2.2222 | 3800 | 0.0387 | - |
198
+ | 2.2515 | 3850 | 0.035 | - |
199
+ | 2.2807 | 3900 | 0.0384 | - |
200
+ | 2.3099 | 3950 | 0.0386 | - |
201
+ | 2.3392 | 4000 | 0.0379 | - |
202
+ | 2.3684 | 4050 | 0.0315 | - |
203
+ | 2.3977 | 4100 | 0.0372 | - |
204
+ | 2.4269 | 4150 | 0.0324 | - |
205
+ | 2.4561 | 4200 | 0.0319 | - |
206
+ | 2.4854 | 4250 | 0.0306 | - |
207
+ | 2.5146 | 4300 | 0.0309 | - |
208
+ | 2.5439 | 4350 | 0.0382 | - |
209
+ | 2.5731 | 4400 | 0.0314 | - |
210
+ | 2.6023 | 4450 | 0.0314 | - |
211
+ | 2.6316 | 4500 | 0.0254 | - |
212
+ | 2.6608 | 4550 | 0.0257 | - |
213
+ | 2.6901 | 4600 | 0.0325 | - |
214
+ | 2.7193 | 4650 | 0.0249 | - |
215
+ | 2.7485 | 4700 | 0.026 | - |
216
+ | 2.7778 | 4750 | 0.0298 | - |
217
+ | 2.8070 | 4800 | 0.0253 | - |
218
+ | 2.8363 | 4850 | 0.0306 | - |
219
+ | 2.8655 | 4900 | 0.0285 | - |
220
+ | 2.8947 | 4950 | 0.0273 | - |
221
+ | 2.9240 | 5000 | 0.029 | - |
222
+ | 2.9532 | 5050 | 0.0238 | - |
223
+ | 2.9825 | 5100 | 0.0287 | - |
224
+ | 3.0117 | 5150 | 0.0267 | - |
225
+ | 3.0409 | 5200 | 0.0259 | - |
226
+ | 3.0702 | 5250 | 0.0232 | - |
227
+ | 3.0994 | 5300 | 0.0269 | - |
228
+ | 3.1287 | 5350 | 0.0239 | - |
229
+ | 3.1579 | 5400 | 0.0268 | - |
230
+ | 3.1871 | 5450 | 0.0242 | - |
231
+ | 3.2164 | 5500 | 0.0264 | - |
232
+ | 3.2456 | 5550 | 0.0217 | - |
233
+ | 3.2749 | 5600 | 0.026 | - |
234
+ | 3.3041 | 5650 | 0.0248 | - |
235
+ | 3.3333 | 5700 | 0.0242 | - |
236
+ | 3.3626 | 5750 | 0.0239 | - |
237
+ | 3.3918 | 5800 | 0.0229 | - |
238
+ | 3.4211 | 5850 | 0.0205 | - |
239
+ | 3.4503 | 5900 | 0.0252 | - |
240
+ | 3.4795 | 5950 | 0.0208 | - |
241
+ | 3.5088 | 6000 | 0.024 | - |
242
+ | 3.5380 | 6050 | 0.025 | - |
243
+ | 3.5673 | 6100 | 0.0235 | - |
244
+ | 3.5965 | 6150 | 0.0228 | - |
245
+ | 3.6257 | 6200 | 0.0213 | - |
246
+ | 3.6550 | 6250 | 0.024 | - |
247
+ | 3.6842 | 6300 | 0.021 | - |
248
+ | 3.7135 | 6350 | 0.0236 | - |
249
+ | 3.7427 | 6400 | 0.0213 | - |
250
+ | 3.7719 | 6450 | 0.0188 | - |
251
+ | 3.8012 | 6500 | 0.0239 | - |
252
+ | 3.8304 | 6550 | 0.0244 | - |
253
+ | 3.8596 | 6600 | 0.0228 | - |
254
+ | 3.8889 | 6650 | 0.0219 | - |
255
+ | 3.9181 | 6700 | 0.0251 | - |
256
+ | 3.9474 | 6750 | 0.02 | - |
257
+ | 3.9766 | 6800 | 0.0209 | - |
258
+ | 4.0058 | 6850 | 0.0204 | - |
259
+ | 4.0351 | 6900 | 0.022 | - |
260
+ | 4.0643 | 6950 | 0.0197 | - |
261
+ | 4.0936 | 7000 | 0.019 | - |
262
+ | 4.1228 | 7050 | 0.0212 | - |
263
+ | 4.1520 | 7100 | 0.0201 | - |
264
+ | 4.1813 | 7150 | 0.021 | - |
265
+ | 4.2105 | 7200 | 0.0219 | - |
266
+ | 4.2398 | 7250 | 0.0223 | - |
267
+ | 4.2690 | 7300 | 0.0236 | - |
268
+ | 4.2982 | 7350 | 0.0206 | - |
269
+ | 4.3275 | 7400 | 0.02 | - |
270
+ | 4.3567 | 7450 | 0.0223 | - |
271
+ | 4.3860 | 7500 | 0.0212 | - |
272
+ | 4.4152 | 7550 | 0.0205 | - |
273
+ | 4.4444 | 7600 | 0.0212 | - |
274
+ | 4.4737 | 7650 | 0.0189 | - |
275
+ | 4.5029 | 7700 | 0.0213 | - |
276
+ | 4.5322 | 7750 | 0.021 | - |
277
+ | 4.5614 | 7800 | 0.0212 | - |
278
+ | 4.5906 | 7850 | 0.0196 | - |
279
+ | 4.6199 | 7900 | 0.0187 | - |
280
+ | 4.6491 | 7950 | 0.0185 | - |
281
+ | 4.6784 | 8000 | 0.017 | - |
282
+ | 4.7076 | 8050 | 0.0211 | - |
283
+ | 4.7368 | 8100 | 0.0177 | - |
284
+ | 4.7661 | 8150 | 0.0208 | - |
285
+ | 4.7953 | 8200 | 0.0235 | - |
286
+ | 4.8246 | 8250 | 0.0196 | - |
287
+ | 4.8538 | 8300 | 0.0193 | - |
288
+ | 4.8830 | 8350 | 0.0185 | - |
289
+ | 4.9123 | 8400 | 0.022 | - |
290
+ | 4.9415 | 8450 | 0.0196 | - |
291
+ | 4.9708 | 8500 | 0.0196 | - |
292
+ | 5.0 | 8550 | 0.0227 | - |
293
+ | 5.0292 | 8600 | 0.0188 | - |
294
+ | 5.0585 | 8650 | 0.0183 | - |
295
+ | 5.0877 | 8700 | 0.0192 | - |
296
+ | 5.1170 | 8750 | 0.0219 | - |
297
+ | 5.1462 | 8800 | 0.0181 | - |
298
+ | 5.1754 | 8850 | 0.0173 | - |
299
+ | 5.2047 | 8900 | 0.0178 | - |
300
+ | 5.2339 | 8950 | 0.0183 | - |
301
+ | 5.2632 | 9000 | 0.0199 | - |
302
+ | 5.2924 | 9050 | 0.0194 | - |
303
+ | 5.3216 | 9100 | 0.0219 | - |
304
+ | 5.3509 | 9150 | 0.0218 | - |
305
+ | 5.3801 | 9200 | 0.0186 | - |
306
+ | 5.4094 | 9250 | 0.0202 | - |
307
+ | 5.4386 | 9300 | 0.0195 | - |
308
+ | 5.4678 | 9350 | 0.0181 | - |
309
+ | 5.4971 | 9400 | 0.0197 | - |
310
+ | 5.5263 | 9450 | 0.0176 | - |
311
+ | 5.5556 | 9500 | 0.0181 | - |
312
+ | 5.5848 | 9550 | 0.0193 | - |
313
+ | 5.6140 | 9600 | 0.0183 | - |
314
+ | 5.6433 | 9650 | 0.0206 | - |
315
+ | 5.6725 | 9700 | 0.0191 | - |
316
+ | 5.7018 | 9750 | 0.0179 | - |
317
+ | 5.7310 | 9800 | 0.0192 | - |
318
+ | 5.7602 | 9850 | 0.0184 | - |
319
+ | 5.7895 | 9900 | 0.0194 | - |
320
+ | 5.8187 | 9950 | 0.0186 | - |
321
+ | 5.8480 | 10000 | 0.0193 | - |
322
+ | 5.8772 | 10050 | 0.0176 | - |
323
+ | 5.9064 | 10100 | 0.0187 | - |
324
+ | 5.9357 | 10150 | 0.0193 | - |
325
+ | 5.9649 | 10200 | 0.0199 | - |
326
+ | 5.9942 | 10250 | 0.0169 | - |
327
+ | 6.0234 | 10300 | 0.017 | - |
328
+ | 6.0526 | 10350 | 0.0207 | - |
329
+ | 6.0819 | 10400 | 0.0188 | - |
330
+ | 6.1111 | 10450 | 0.018 | - |
331
+ | 6.1404 | 10500 | 0.0184 | - |
332
+ | 6.1696 | 10550 | 0.0153 | - |
333
+ | 6.1988 | 10600 | 0.0173 | - |
334
+ | 6.2281 | 10650 | 0.0172 | - |
335
+ | 6.2573 | 10700 | 0.0188 | - |
336
+ | 6.2865 | 10750 | 0.02 | - |
337
+ | 6.3158 | 10800 | 0.0193 | - |
338
+ | 6.3450 | 10850 | 0.0188 | - |
339
+ | 6.3743 | 10900 | 0.0183 | - |
340
+ | 6.4035 | 10950 | 0.0185 | - |
341
+ | 6.4327 | 11000 | 0.0203 | - |
342
+ | 6.4620 | 11050 | 0.018 | - |
343
+ | 6.4912 | 11100 | 0.0184 | - |
344
+ | 6.5205 | 11150 | 0.0182 | - |
345
+ | 6.5497 | 11200 | 0.0173 | - |
346
+ | 6.5789 | 11250 | 0.0173 | - |
347
+ | 6.6082 | 11300 | 0.0189 | - |
348
+ | 6.6374 | 11350 | 0.0167 | - |
349
+ | 6.6667 | 11400 | 0.0169 | - |
350
+ | 6.6959 | 11450 | 0.0171 | - |
351
+ | 6.7251 | 11500 | 0.0174 | - |
352
+ | 6.7544 | 11550 | 0.0169 | - |
353
+ | 6.7836 | 11600 | 0.0193 | - |
354
+ | 6.8129 | 11650 | 0.0184 | - |
355
+ | 6.8421 | 11700 | 0.0175 | - |
356
+ | 6.8713 | 11750 | 0.0173 | - |
357
+ | 6.9006 | 11800 | 0.0146 | - |
358
+ | 6.9298 | 11850 | 0.0163 | - |
359
+ | 6.9591 | 11900 | 0.0173 | - |
360
+ | 6.9883 | 11950 | 0.0196 | - |
361
+ | 7.0175 | 12000 | 0.0188 | - |
362
+ | 7.0468 | 12050 | 0.0182 | - |
363
+ | 7.0760 | 12100 | 0.0168 | - |
364
+ | 7.1053 | 12150 | 0.0169 | - |
365
+ | 7.1345 | 12200 | 0.0164 | - |
366
+ | 7.1637 | 12250 | 0.0159 | - |
367
+ | 7.1930 | 12300 | 0.0187 | - |
368
+ | 7.2222 | 12350 | 0.0197 | - |
369
+ | 7.2515 | 12400 | 0.0186 | - |
370
+ | 7.2807 | 12450 | 0.0163 | - |
371
+ | 7.3099 | 12500 | 0.0178 | - |
372
+ | 7.3392 | 12550 | 0.0184 | - |
373
+ | 7.3684 | 12600 | 0.0184 | - |
374
+ | 7.3977 | 12650 | 0.0177 | - |
375
+ | 7.4269 | 12700 | 0.0157 | - |
376
+ | 7.4561 | 12750 | 0.0184 | - |
377
+ | 7.4854 | 12800 | 0.0184 | - |
378
+ | 7.5146 | 12850 | 0.0182 | - |
379
+ | 7.5439 | 12900 | 0.0182 | - |
380
+ | 7.5731 | 12950 | 0.0169 | - |
381
+ | 7.6023 | 13000 | 0.0182 | - |
382
+ | 7.6316 | 13050 | 0.0156 | - |
383
+ | 7.6608 | 13100 | 0.0173 | - |
384
+ | 7.6901 | 13150 | 0.0159 | - |
385
+ | 7.7193 | 13200 | 0.0167 | - |
386
+ | 7.7485 | 13250 | 0.0175 | - |
387
+ | 7.7778 | 13300 | 0.016 | - |
388
+ | 7.8070 | 13350 | 0.0175 | - |
389
+ | 7.8363 | 13400 | 0.0169 | - |
390
+ | 7.8655 | 13450 | 0.0167 | - |
391
+ | 7.8947 | 13500 | 0.0159 | - |
392
+ | 7.9240 | 13550 | 0.0168 | - |
393
+ | 7.9532 | 13600 | 0.0183 | - |
394
+ | 7.9825 | 13650 | 0.0162 | - |
395
+ | 8.0117 | 13700 | 0.0162 | - |
396
+ | 8.0409 | 13750 | 0.017 | - |
397
+ | 8.0702 | 13800 | 0.018 | - |
398
+ | 8.0994 | 13850 | 0.0161 | - |
399
+ | 8.1287 | 13900 | 0.0159 | - |
400
+ | 8.1579 | 13950 | 0.0185 | - |
401
+ | 8.1871 | 14000 | 0.017 | - |
402
+ | 8.2164 | 14050 | 0.0167 | - |
403
+ | 8.2456 | 14100 | 0.0154 | - |
404
+ | 8.2749 | 14150 | 0.0166 | - |
405
+ | 8.3041 | 14200 | 0.0173 | - |
406
+ | 8.3333 | 14250 | 0.0156 | - |
407
+ | 8.3626 | 14300 | 0.0175 | - |
408
+ | 8.3918 | 14350 | 0.0144 | - |
409
+ | 8.4211 | 14400 | 0.0198 | - |
410
+ | 8.4503 | 14450 | 0.0184 | - |
411
+ | 8.4795 | 14500 | 0.0168 | - |
412
+ | 8.5088 | 14550 | 0.0183 | - |
413
+ | 8.5380 | 14600 | 0.0175 | - |
414
+ | 8.5673 | 14650 | 0.0155 | - |
415
+ | 8.5965 | 14700 | 0.0168 | - |
416
+ | 8.6257 | 14750 | 0.0179 | - |
417
+ | 8.6550 | 14800 | 0.0162 | - |
418
+ | 8.6842 | 14850 | 0.0181 | - |
419
+ | 8.7135 | 14900 | 0.017 | - |
420
+ | 8.7427 | 14950 | 0.0169 | - |
421
+ | 8.7719 | 15000 | 0.0177 | - |
422
+ | 8.8012 | 15050 | 0.0174 | - |
423
+ | 8.8304 | 15100 | 0.015 | - |
424
+ | 8.8596 | 15150 | 0.0159 | - |
425
+ | 8.8889 | 15200 | 0.0191 | - |
426
+ | 8.9181 | 15250 | 0.0168 | - |
427
+ | 8.9474 | 15300 | 0.0147 | - |
428
+ | 8.9766 | 15350 | 0.0166 | - |
429
+ | 9.0058 | 15400 | 0.0163 | - |
430
+ | 9.0351 | 15450 | 0.0156 | - |
431
+ | 9.0643 | 15500 | 0.0171 | - |
432
+ | 9.0936 | 15550 | 0.0168 | - |
433
+ | 9.1228 | 15600 | 0.0174 | - |
434
+ | 9.1520 | 15650 | 0.0152 | - |
435
+ | 9.1813 | 15700 | 0.017 | - |
436
+ | 9.2105 | 15750 | 0.0172 | - |
437
+ | 9.2398 | 15800 | 0.0149 | - |
438
+ | 9.2690 | 15850 | 0.0172 | - |
439
+ | 9.2982 | 15900 | 0.0161 | - |
440
+ | 9.3275 | 15950 | 0.0174 | - |
441
+ | 9.3567 | 16000 | 0.0181 | - |
442
+ | 9.3860 | 16050 | 0.0167 | - |
443
+ | 9.4152 | 16100 | 0.0159 | - |
444
+ | 9.4444 | 16150 | 0.0157 | - |
445
+ | 9.4737 | 16200 | 0.0174 | - |
446
+ | 9.5029 | 16250 | 0.0155 | - |
447
+ | 9.5322 | 16300 | 0.0158 | - |
448
+ | 9.5614 | 16350 | 0.0164 | - |
449
+ | 9.5906 | 16400 | 0.0165 | - |
450
+ | 9.6199 | 16450 | 0.0164 | - |
451
+ | 9.6491 | 16500 | 0.0155 | - |
452
+ | 9.6784 | 16550 | 0.0164 | - |
453
+ | 9.7076 | 16600 | 0.016 | - |
454
+ | 9.7368 | 16650 | 0.0154 | - |
455
+ | 9.7661 | 16700 | 0.0171 | - |
456
+ | 9.7953 | 16750 | 0.0173 | - |
457
+ | 9.8246 | 16800 | 0.0158 | - |
458
+ | 9.8538 | 16850 | 0.0169 | - |
459
+ | 9.8830 | 16900 | 0.0163 | - |
460
+ | 9.9123 | 16950 | 0.0177 | - |
461
+ | 9.9415 | 17000 | 0.0167 | - |
462
+ | 9.9708 | 17050 | 0.0172 | - |
463
+ | 10.0 | 17100 | 0.0172 | - |
464
+
465
+ ### Framework Versions
466
+ - Python: 3.10.8
467
+ - SetFit: 1.1.2
468
+ - Sentence Transformers: 5.0.0
469
+ - Transformers: 4.54.1
470
+ - PyTorch: 2.7.1+cu126
471
+ - Datasets: 3.6.0
472
+ - Tokenizers: 0.21.4
473
+
474
+ ## Citation
475
+
476
+ ### BibTeX
477
+ ```bibtex
478
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
479
+ doi = {10.48550/ARXIV.2209.11055},
480
+ url = {https://arxiv.org/abs/2209.11055},
481
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
482
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
483
+ title = {Efficient Few-Shot Learning Without Prompts},
484
+ publisher = {arXiv},
485
+ year = {2022},
486
+ copyright = {Creative Commons Attribution 4.0 International}
487
+ }
488
+ ```
489
+
490
+ <!--
491
+ ## Glossary
492
+
493
+ *Clearly define terms in order to be accessible across audiences.*
494
+ -->
495
+
496
+ <!--
497
+ ## Model Card Authors
498
+
499
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
500
+ -->
501
+
502
+ <!--
503
+ ## Model Card Contact
504
+
505
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
506
+ -->
config.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "BertModel"
4
+ ],
5
+ "attention_probs_dropout_prob": 0.1,
6
+ "classifier_dropout": null,
7
+ "gradient_checkpointing": false,
8
+ "hidden_act": "gelu",
9
+ "hidden_dropout_prob": 0.1,
10
+ "hidden_size": 384,
11
+ "initializer_range": 0.02,
12
+ "intermediate_size": 1536,
13
+ "layer_norm_eps": 1e-12,
14
+ "max_position_embeddings": 512,
15
+ "model_type": "bert",
16
+ "num_attention_heads": 12,
17
+ "num_hidden_layers": 6,
18
+ "pad_token_id": 0,
19
+ "position_embedding_type": "absolute",
20
+ "torch_dtype": "float32",
21
+ "transformers_version": "4.54.1",
22
+ "type_vocab_size": 2,
23
+ "use_cache": true,
24
+ "vocab_size": 30522
25
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,14 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "5.0.0",
4
+ "transformers": "4.54.1",
5
+ "pytorch": "2.7.1+cu126"
6
+ },
7
+ "model_type": "SentenceTransformer",
8
+ "prompts": {
9
+ "query": "",
10
+ "document": ""
11
+ },
12
+ "default_prompt_name": null,
13
+ "similarity_fn_name": "cosine"
14
+ }
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 sha256:5052f07e64a2b914783cb2722a93e76212e3eb45b8deb0967e7d01d067edbbca
3
+ size 90864192
model_head.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fad1256d65ecb9b2fe102f9e908ab41e9a02f86e17cc54b70701d1f1ec1d4f2e
3
+ size 18017
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": 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 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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": false,
45
+ "cls_token": "[CLS]",
46
+ "do_basic_tokenize": true,
47
+ "do_lower_case": true,
48
+ "extra_special_tokens": {},
49
+ "mask_token": "[MASK]",
50
+ "model_max_length": 128,
51
+ "never_split": null,
52
+ "pad_token": "[PAD]",
53
+ "sep_token": "[SEP]",
54
+ "strip_accents": null,
55
+ "tokenize_chinese_chars": true,
56
+ "tokenizer_class": "BertTokenizer",
57
+ "unk_token": "[UNK]"
58
+ }
vocab.txt ADDED
The diff for this file is too large to render. See raw diff