Mihaiii commited on
Commit
deb3159
·
verified ·
1 Parent(s): 2556ba9

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +468 -0
README.md CHANGED
@@ -6,6 +6,474 @@ tags:
6
  - sentence-transformers
7
  - feature-extraction
8
  - sentence-similarity
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9
  ---
10
  # gte-micro
11
 
 
6
  - sentence-transformers
7
  - feature-extraction
8
  - sentence-similarity
9
+ - gte
10
+ - mteb
11
+ model-index:
12
+ - name: gte-micro
13
+ results:
14
+ - task:
15
+ type: Classification
16
+ dataset:
17
+ type: mteb/amazon_counterfactual
18
+ name: MTEB AmazonCounterfactualClassification (en)
19
+ config: en
20
+ split: test
21
+ revision: e8379541af4e31359cca9fbcf4b00f2671dba205
22
+ metrics:
23
+ - type: accuracy
24
+ value: 68.82089552238806
25
+ - type: ap
26
+ value: 31.260622493912688
27
+ - type: f1
28
+ value: 62.701989024087304
29
+ - task:
30
+ type: Classification
31
+ dataset:
32
+ type: mteb/amazon_polarity
33
+ name: MTEB AmazonPolarityClassification
34
+ config: default
35
+ split: test
36
+ revision: e2d317d38cd51312af73b3d32a06d1a08b442046
37
+ metrics:
38
+ - type: accuracy
39
+ value: 77.11532499999998
40
+ - type: ap
41
+ value: 71.29001033390622
42
+ - type: f1
43
+ value: 77.0225646895571
44
+ - task:
45
+ type: Classification
46
+ dataset:
47
+ type: mteb/amazon_reviews_multi
48
+ name: MTEB AmazonReviewsClassification (en)
49
+ config: en
50
+ split: test
51
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
52
+ metrics:
53
+ - type: accuracy
54
+ value: 40.93600000000001
55
+ - type: f1
56
+ value: 39.24591989399245
57
+ - task:
58
+ type: Clustering
59
+ dataset:
60
+ type: mteb/arxiv-clustering-p2p
61
+ name: MTEB ArxivClusteringP2P
62
+ config: default
63
+ split: test
64
+ revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
65
+ metrics:
66
+ - type: v_measure
67
+ value: 35.237007515497126
68
+ - task:
69
+ type: Clustering
70
+ dataset:
71
+ type: mteb/arxiv-clustering-s2s
72
+ name: MTEB ArxivClusteringS2S
73
+ config: default
74
+ split: test
75
+ revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
76
+ metrics:
77
+ - type: v_measure
78
+ value: 31.08692637060412
79
+ - task:
80
+ type: Reranking
81
+ dataset:
82
+ type: mteb/askubuntudupquestions-reranking
83
+ name: MTEB AskUbuntuDupQuestions
84
+ config: default
85
+ split: test
86
+ revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
87
+ metrics:
88
+ - type: map
89
+ value: 55.312310786737015
90
+ - type: mrr
91
+ value: 69.50842017324011
92
+ - task:
93
+ type: Classification
94
+ dataset:
95
+ type: mteb/banking77
96
+ name: MTEB Banking77Classification
97
+ config: default
98
+ split: test
99
+ revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
100
+ metrics:
101
+ - type: accuracy
102
+ value: 69.56168831168831
103
+ - type: f1
104
+ value: 68.14675364705445
105
+ - task:
106
+ type: Clustering
107
+ dataset:
108
+ type: mteb/biorxiv-clustering-p2p
109
+ name: MTEB BiorxivClusteringP2P
110
+ config: default
111
+ split: test
112
+ revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
113
+ metrics:
114
+ - type: v_measure
115
+ value: 30.20098791829512
116
+ - task:
117
+ type: Clustering
118
+ dataset:
119
+ type: mteb/biorxiv-clustering-s2s
120
+ name: MTEB BiorxivClusteringS2S
121
+ config: default
122
+ split: test
123
+ revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
124
+ metrics:
125
+ - type: v_measure
126
+ value: 27.38014535599197
127
+ - task:
128
+ type: Classification
129
+ dataset:
130
+ type: mteb/emotion
131
+ name: MTEB EmotionClassification
132
+ config: default
133
+ split: test
134
+ revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
135
+ metrics:
136
+ - type: accuracy
137
+ value: 46.224999999999994
138
+ - type: f1
139
+ value: 39.319662595355354
140
+ - task:
141
+ type: Classification
142
+ dataset:
143
+ type: mteb/imdb
144
+ name: MTEB ImdbClassification
145
+ config: default
146
+ split: test
147
+ revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
148
+ metrics:
149
+ - type: accuracy
150
+ value: 62.17159999999999
151
+ - type: ap
152
+ value: 58.35784294974692
153
+ - type: f1
154
+ value: 61.8942294000012
155
+ - task:
156
+ type: Classification
157
+ dataset:
158
+ type: mteb/mtop_domain
159
+ name: MTEB MTOPDomainClassification (en)
160
+ config: en
161
+ split: test
162
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
163
+ metrics:
164
+ - type: accuracy
165
+ value: 86.68946648426811
166
+ - type: f1
167
+ value: 86.26529827823835
168
+ - task:
169
+ type: Classification
170
+ dataset:
171
+ type: mteb/mtop_intent
172
+ name: MTEB MTOPIntentClassification (en)
173
+ config: en
174
+ split: test
175
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
176
+ metrics:
177
+ - type: accuracy
178
+ value: 49.69676242590059
179
+ - type: f1
180
+ value: 33.74537894406717
181
+ - task:
182
+ type: Classification
183
+ dataset:
184
+ type: mteb/amazon_massive_intent
185
+ name: MTEB MassiveIntentClassification (en)
186
+ config: en
187
+ split: test
188
+ revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
189
+ metrics:
190
+ - type: accuracy
191
+ value: 59.028244788164095
192
+ - type: f1
193
+ value: 55.31452888309622
194
+ - task:
195
+ type: Classification
196
+ dataset:
197
+ type: mteb/amazon_massive_scenario
198
+ name: MTEB MassiveScenarioClassification (en)
199
+ config: en
200
+ split: test
201
+ revision: 7d571f92784cd94a019292a1f45445077d0ef634
202
+ metrics:
203
+ - type: accuracy
204
+ value: 66.58708809683928
205
+ - type: f1
206
+ value: 65.90050839709882
207
+ - task:
208
+ type: Clustering
209
+ dataset:
210
+ type: mteb/medrxiv-clustering-p2p
211
+ name: MTEB MedrxivClusteringP2P
212
+ config: default
213
+ split: test
214
+ revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
215
+ metrics:
216
+ - type: v_measure
217
+ value: 27.16644221915073
218
+ - task:
219
+ type: Clustering
220
+ dataset:
221
+ type: mteb/medrxiv-clustering-s2s
222
+ name: MTEB MedrxivClusteringS2S
223
+ config: default
224
+ split: test
225
+ revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
226
+ metrics:
227
+ - type: v_measure
228
+ value: 27.5164150501441
229
+ - task:
230
+ type: Clustering
231
+ dataset:
232
+ type: mteb/reddit-clustering
233
+ name: MTEB RedditClustering
234
+ config: default
235
+ split: test
236
+ revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
237
+ metrics:
238
+ - type: v_measure
239
+ value: 45.61660066180842
240
+ - task:
241
+ type: Clustering
242
+ dataset:
243
+ type: mteb/reddit-clustering-p2p
244
+ name: MTEB RedditClusteringP2P
245
+ config: default
246
+ split: test
247
+ revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
248
+ metrics:
249
+ - type: v_measure
250
+ value: 47.86938629331837
251
+ - task:
252
+ type: PairClassification
253
+ dataset:
254
+ type: mteb/sprintduplicatequestions-pairclassification
255
+ name: MTEB SprintDuplicateQuestions
256
+ config: default
257
+ split: test
258
+ revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
259
+ metrics:
260
+ - type: cos_sim_accuracy
261
+ value: 99.7980198019802
262
+ - type: cos_sim_ap
263
+ value: 94.25805747549842
264
+ - type: cos_sim_f1
265
+ value: 89.56262425447315
266
+ - type: cos_sim_precision
267
+ value: 89.03162055335969
268
+ - type: cos_sim_recall
269
+ value: 90.10000000000001
270
+ - type: dot_accuracy
271
+ value: 99.7980198019802
272
+ - type: dot_ap
273
+ value: 94.25806137565444
274
+ - type: dot_f1
275
+ value: 89.56262425447315
276
+ - type: dot_precision
277
+ value: 89.03162055335969
278
+ - type: dot_recall
279
+ value: 90.10000000000001
280
+ - type: euclidean_accuracy
281
+ value: 99.7980198019802
282
+ - type: euclidean_ap
283
+ value: 94.25805747549843
284
+ - type: euclidean_f1
285
+ value: 89.56262425447315
286
+ - type: euclidean_precision
287
+ value: 89.03162055335969
288
+ - type: euclidean_recall
289
+ value: 90.10000000000001
290
+ - type: manhattan_accuracy
291
+ value: 99.7980198019802
292
+ - type: manhattan_ap
293
+ value: 94.35547438808531
294
+ - type: manhattan_f1
295
+ value: 89.78574987543598
296
+ - type: manhattan_precision
297
+ value: 89.47368421052632
298
+ - type: manhattan_recall
299
+ value: 90.10000000000001
300
+ - type: max_accuracy
301
+ value: 99.7980198019802
302
+ - type: max_ap
303
+ value: 94.35547438808531
304
+ - type: max_f1
305
+ value: 89.78574987543598
306
+ - task:
307
+ type: Clustering
308
+ dataset:
309
+ type: mteb/stackexchange-clustering
310
+ name: MTEB StackExchangeClustering
311
+ config: default
312
+ split: test
313
+ revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
314
+ metrics:
315
+ - type: v_measure
316
+ value: 52.619948149973
317
+ - task:
318
+ type: Clustering
319
+ dataset:
320
+ type: mteb/stackexchange-clustering-p2p
321
+ name: MTEB StackExchangeClusteringP2P
322
+ config: default
323
+ split: test
324
+ revision: 815ca46b2622cec33ccafc3735d572c266efdb44
325
+ metrics:
326
+ - type: v_measure
327
+ value: 30.050148689318583
328
+ - task:
329
+ type: Classification
330
+ dataset:
331
+ type: mteb/toxic_conversations_50k
332
+ name: MTEB ToxicConversationsClassification
333
+ config: default
334
+ split: test
335
+ revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
336
+ metrics:
337
+ - type: accuracy
338
+ value: 66.1018
339
+ - type: ap
340
+ value: 12.152100246603089
341
+ - type: f1
342
+ value: 50.78295258419767
343
+ - task:
344
+ type: Classification
345
+ dataset:
346
+ type: mteb/tweet_sentiment_extraction
347
+ name: MTEB TweetSentimentExtractionClassification
348
+ config: default
349
+ split: test
350
+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
351
+ metrics:
352
+ - type: accuracy
353
+ value: 60.77532541029994
354
+ - type: f1
355
+ value: 60.7949438635894
356
+ - task:
357
+ type: Clustering
358
+ dataset:
359
+ type: mteb/twentynewsgroups-clustering
360
+ name: MTEB TwentyNewsgroupsClustering
361
+ config: default
362
+ split: test
363
+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
364
+ metrics:
365
+ - type: v_measure
366
+ value: 40.793779391259136
367
+ - task:
368
+ type: PairClassification
369
+ dataset:
370
+ type: mteb/twittersemeval2015-pairclassification
371
+ name: MTEB TwitterSemEval2015
372
+ config: default
373
+ split: test
374
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
375
+ metrics:
376
+ - type: cos_sim_accuracy
377
+ value: 83.10186564940096
378
+ - type: cos_sim_ap
379
+ value: 63.85437966517539
380
+ - type: cos_sim_f1
381
+ value: 60.5209914011128
382
+ - type: cos_sim_precision
383
+ value: 58.11073336571151
384
+ - type: cos_sim_recall
385
+ value: 63.13984168865435
386
+ - type: dot_accuracy
387
+ value: 83.10186564940096
388
+ - type: dot_ap
389
+ value: 63.85440662982004
390
+ - type: dot_f1
391
+ value: 60.5209914011128
392
+ - type: dot_precision
393
+ value: 58.11073336571151
394
+ - type: dot_recall
395
+ value: 63.13984168865435
396
+ - type: euclidean_accuracy
397
+ value: 83.10186564940096
398
+ - type: euclidean_ap
399
+ value: 63.85438236123812
400
+ - type: euclidean_f1
401
+ value: 60.5209914011128
402
+ - type: euclidean_precision
403
+ value: 58.11073336571151
404
+ - type: euclidean_recall
405
+ value: 63.13984168865435
406
+ - type: manhattan_accuracy
407
+ value: 82.95881266018954
408
+ - type: manhattan_ap
409
+ value: 63.548796919332496
410
+ - type: manhattan_f1
411
+ value: 60.2080461210678
412
+ - type: manhattan_precision
413
+ value: 57.340654094055864
414
+ - type: manhattan_recall
415
+ value: 63.377308707124016
416
+ - type: max_accuracy
417
+ value: 83.10186564940096
418
+ - type: max_ap
419
+ value: 63.85440662982004
420
+ - type: max_f1
421
+ value: 60.5209914011128
422
+ - task:
423
+ type: PairClassification
424
+ dataset:
425
+ type: mteb/twitterurlcorpus-pairclassification
426
+ name: MTEB TwitterURLCorpus
427
+ config: default
428
+ split: test
429
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
430
+ metrics:
431
+ - type: cos_sim_accuracy
432
+ value: 87.93417937672217
433
+ - type: cos_sim_ap
434
+ value: 84.07115019218789
435
+ - type: cos_sim_f1
436
+ value: 75.7513225528083
437
+ - type: cos_sim_precision
438
+ value: 73.8748627881449
439
+ - type: cos_sim_recall
440
+ value: 77.72559285494303
441
+ - type: dot_accuracy
442
+ value: 87.93417937672217
443
+ - type: dot_ap
444
+ value: 84.0711576640934
445
+ - type: dot_f1
446
+ value: 75.7513225528083
447
+ - type: dot_precision
448
+ value: 73.8748627881449
449
+ - type: dot_recall
450
+ value: 77.72559285494303
451
+ - type: euclidean_accuracy
452
+ value: 87.93417937672217
453
+ - type: euclidean_ap
454
+ value: 84.07114662252135
455
+ - type: euclidean_f1
456
+ value: 75.7513225528083
457
+ - type: euclidean_precision
458
+ value: 73.8748627881449
459
+ - type: euclidean_recall
460
+ value: 77.72559285494303
461
+ - type: manhattan_accuracy
462
+ value: 87.90507237940001
463
+ - type: manhattan_ap
464
+ value: 84.00643428398385
465
+ - type: manhattan_f1
466
+ value: 75.80849007508735
467
+ - type: manhattan_precision
468
+ value: 73.28589909443726
469
+ - type: manhattan_recall
470
+ value: 78.51093316907914
471
+ - type: max_accuracy
472
+ value: 87.93417937672217
473
+ - type: max_ap
474
+ value: 84.0711576640934
475
+ - type: max_f1
476
+ value: 75.80849007508735
477
  ---
478
  # gte-micro
479