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1
+ ---
2
+ tags:
3
+ - mteb
4
+ model-index:
5
+ - name: AGE_Hybrid
6
+ results:
7
+ - task:
8
+ type: STS
9
+ dataset:
10
+ type: C-MTEB/AFQMC
11
+ name: MTEB AFQMC
12
+ config: default
13
+ split: validation
14
+ revision: None
15
+ metrics:
16
+ - type: cos_sim_pearson
17
+ value: 54.374695963209476
18
+ - type: cos_sim_spearman
19
+ value: 58.61378404489695
20
+ - type: euclidean_pearson
21
+ value: 57.400266024507914
22
+ - type: euclidean_spearman
23
+ value: 58.613784047084096
24
+ - type: manhattan_pearson
25
+ value: 57.38157387794458
26
+ - type: manhattan_spearman
27
+ value: 58.574259007541265
28
+ - task:
29
+ type: STS
30
+ dataset:
31
+ type: C-MTEB/ATEC
32
+ name: MTEB ATEC
33
+ config: default
34
+ split: test
35
+ revision: None
36
+ metrics:
37
+ - type: cos_sim_pearson
38
+ value: 54.45976756975548
39
+ - type: cos_sim_spearman
40
+ value: 58.02715269428664
41
+ - type: euclidean_pearson
42
+ value: 61.66384760865219
43
+ - type: euclidean_spearman
44
+ value: 58.02715269404729
45
+ - type: manhattan_pearson
46
+ value: 61.65225559810625
47
+ - type: manhattan_spearman
48
+ value: 58.01857808173552
49
+ - task:
50
+ type: Classification
51
+ dataset:
52
+ type: mteb/amazon_reviews_multi
53
+ name: MTEB AmazonReviewsClassification (zh)
54
+ config: zh
55
+ split: test
56
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
57
+ metrics:
58
+ - type: accuracy
59
+ value: 49.684000000000005
60
+ - type: f1
61
+ value: 48.65598525270613
62
+ - task:
63
+ type: STS
64
+ dataset:
65
+ type: C-MTEB/BQ
66
+ name: MTEB BQ
67
+ config: default
68
+ split: test
69
+ revision: None
70
+ metrics:
71
+ - type: cos_sim_pearson
72
+ value: 69.31255159649066
73
+ - type: cos_sim_spearman
74
+ value: 70.98203706268313
75
+ - type: euclidean_pearson
76
+ value: 70.00607736062557
77
+ - type: euclidean_spearman
78
+ value: 70.98203706225725
79
+ - type: manhattan_pearson
80
+ value: 69.99109520014915
81
+ - type: manhattan_spearman
82
+ value: 70.96937923489206
83
+ - task:
84
+ type: Clustering
85
+ dataset:
86
+ type: C-MTEB/CLSClusteringP2P
87
+ name: MTEB CLSClusteringP2P
88
+ config: default
89
+ split: test
90
+ revision: None
91
+ metrics:
92
+ - type: v_measure
93
+ value: 57.39428997427469
94
+ - task:
95
+ type: Clustering
96
+ dataset:
97
+ type: C-MTEB/CLSClusteringS2S
98
+ name: MTEB CLSClusteringS2S
99
+ config: default
100
+ split: test
101
+ revision: None
102
+ metrics:
103
+ - type: v_measure
104
+ value: 54.109596265048545
105
+ - task:
106
+ type: Reranking
107
+ dataset:
108
+ type: C-MTEB/CMedQAv1-reranking
109
+ name: MTEB CMedQAv1-reranking
110
+ config: default
111
+ split: test
112
+ revision: None
113
+ metrics:
114
+ - type: map
115
+ value: 89.37069472390765
116
+ - type: mrr
117
+ value: 91.35595238095239
118
+ - task:
119
+ type: Reranking
120
+ dataset:
121
+ type: C-MTEB/CMedQAv2-reranking
122
+ name: MTEB CMedQAv2-reranking
123
+ config: default
124
+ split: test
125
+ revision: None
126
+ metrics:
127
+ - type: map
128
+ value: 89.26794517307951
129
+ - type: mrr
130
+ value: 91.27345238095238
131
+ - task:
132
+ type: Retrieval
133
+ dataset:
134
+ type: C-MTEB/CmedqaRetrieval
135
+ name: MTEB CmedqaRetrieval
136
+ config: default
137
+ split: dev
138
+ revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
139
+ metrics:
140
+ - type: map_at_1
141
+ value: 27.367
142
+ - type: map_at_10
143
+ value: 40.595
144
+ - type: map_at_100
145
+ value: 42.522
146
+ - type: map_at_1000
147
+ value: 42.620999999999995
148
+ - type: map_at_3
149
+ value: 36.236000000000004
150
+ - type: map_at_5
151
+ value: 38.716
152
+ - type: mrr_at_1
153
+ value: 41.510000000000005
154
+ - type: mrr_at_10
155
+ value: 49.617
156
+ - type: mrr_at_100
157
+ value: 50.595
158
+ - type: mrr_at_1000
159
+ value: 50.632999999999996
160
+ - type: mrr_at_3
161
+ value: 47.124
162
+ - type: mrr_at_5
163
+ value: 48.565000000000005
164
+ - type: ndcg_at_1
165
+ value: 41.510000000000005
166
+ - type: ndcg_at_10
167
+ value: 47.259
168
+ - type: ndcg_at_100
169
+ value: 54.535
170
+ - type: ndcg_at_1000
171
+ value: 56.21000000000001
172
+ - type: ndcg_at_3
173
+ value: 41.921
174
+ - type: ndcg_at_5
175
+ value: 44.230999999999995
176
+ - type: precision_at_1
177
+ value: 41.510000000000005
178
+ - type: precision_at_10
179
+ value: 10.448
180
+ - type: precision_at_100
181
+ value: 1.629
182
+ - type: precision_at_1000
183
+ value: 0.184
184
+ - type: precision_at_3
185
+ value: 23.623
186
+ - type: precision_at_5
187
+ value: 17.183999999999997
188
+ - type: recall_at_1
189
+ value: 27.367
190
+ - type: recall_at_10
191
+ value: 57.809
192
+ - type: recall_at_100
193
+ value: 87.698
194
+ - type: recall_at_1000
195
+ value: 98.883
196
+ - type: recall_at_3
197
+ value: 41.738
198
+ - type: recall_at_5
199
+ value: 48.868
200
+ - task:
201
+ type: PairClassification
202
+ dataset:
203
+ type: C-MTEB/CMNLI
204
+ name: MTEB Cmnli
205
+ config: default
206
+ split: validation
207
+ revision: None
208
+ metrics:
209
+ - type: cos_sim_accuracy
210
+ value: 81.3950691521347
211
+ - type: cos_sim_ap
212
+ value: 89.42479623257792
213
+ - type: cos_sim_f1
214
+ value: 82.7800599533696
215
+ - type: cos_sim_precision
216
+ value: 78.81606765327696
217
+ - type: cos_sim_recall
218
+ value: 87.16389992985738
219
+ - type: dot_accuracy
220
+ value: 81.3950691521347
221
+ - type: dot_ap
222
+ value: 89.44637882076245
223
+ - type: dot_f1
224
+ value: 82.7800599533696
225
+ - type: dot_precision
226
+ value: 78.81606765327696
227
+ - type: dot_recall
228
+ value: 87.16389992985738
229
+ - type: euclidean_accuracy
230
+ value: 81.3950691521347
231
+ - type: euclidean_ap
232
+ value: 89.42479382288857
233
+ - type: euclidean_f1
234
+ value: 82.7800599533696
235
+ - type: euclidean_precision
236
+ value: 78.81606765327696
237
+ - type: euclidean_recall
238
+ value: 87.16389992985738
239
+ - type: manhattan_accuracy
240
+ value: 81.53938665063139
241
+ - type: manhattan_ap
242
+ value: 89.41695475090047
243
+ - type: manhattan_f1
244
+ value: 82.76245551601423
245
+ - type: manhattan_precision
246
+ value: 78.91834570519617
247
+ - type: manhattan_recall
248
+ value: 87.00023380874444
249
+ - type: max_accuracy
250
+ value: 81.53938665063139
251
+ - type: max_ap
252
+ value: 89.44637882076245
253
+ - type: max_f1
254
+ value: 82.7800599533696
255
+ - task:
256
+ type: Retrieval
257
+ dataset:
258
+ type: C-MTEB/CovidRetrieval
259
+ name: MTEB CovidRetrieval
260
+ config: default
261
+ split: dev
262
+ revision: 1271c7809071a13532e05f25fb53511ffce77117
263
+ metrics:
264
+ - type: map_at_1
265
+ value: 71.918
266
+ - type: map_at_10
267
+ value: 80.068
268
+ - type: map_at_100
269
+ value: 80.297
270
+ - type: map_at_1000
271
+ value: 80.30199999999999
272
+ - type: map_at_3
273
+ value: 78.40700000000001
274
+ - type: map_at_5
275
+ value: 79.467
276
+ - type: mrr_at_1
277
+ value: 72.287
278
+ - type: mrr_at_10
279
+ value: 80.123
280
+ - type: mrr_at_100
281
+ value: 80.34599999999999
282
+ - type: mrr_at_1000
283
+ value: 80.35
284
+ - type: mrr_at_3
285
+ value: 78.50399999999999
286
+ - type: mrr_at_5
287
+ value: 79.56800000000001
288
+ - type: ndcg_at_1
289
+ value: 72.181
290
+ - type: ndcg_at_10
291
+ value: 83.664
292
+ - type: ndcg_at_100
293
+ value: 84.61800000000001
294
+ - type: ndcg_at_1000
295
+ value: 84.75
296
+ - type: ndcg_at_3
297
+ value: 80.353
298
+ - type: ndcg_at_5
299
+ value: 82.242
300
+ - type: precision_at_1
301
+ value: 72.181
302
+ - type: precision_at_10
303
+ value: 9.579
304
+ - type: precision_at_100
305
+ value: 1.0
306
+ - type: precision_at_1000
307
+ value: 0.101
308
+ - type: precision_at_3
309
+ value: 28.837000000000003
310
+ - type: precision_at_5
311
+ value: 18.251
312
+ - type: recall_at_1
313
+ value: 71.918
314
+ - type: recall_at_10
315
+ value: 94.784
316
+ - type: recall_at_100
317
+ value: 98.946
318
+ - type: recall_at_1000
319
+ value: 100.0
320
+ - type: recall_at_3
321
+ value: 85.88
322
+ - type: recall_at_5
323
+ value: 90.411
324
+ - task:
325
+ type: Retrieval
326
+ dataset:
327
+ type: C-MTEB/DuRetrieval
328
+ name: MTEB DuRetrieval
329
+ config: default
330
+ split: dev
331
+ revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
332
+ metrics:
333
+ - type: map_at_1
334
+ value: 26.898
335
+ - type: map_at_10
336
+ value: 82.80999999999999
337
+ - type: map_at_100
338
+ value: 85.41499999999999
339
+ - type: map_at_1000
340
+ value: 85.449
341
+ - type: map_at_3
342
+ value: 57.692
343
+ - type: map_at_5
344
+ value: 72.921
345
+ - type: mrr_at_1
346
+ value: 92.15
347
+ - type: mrr_at_10
348
+ value: 94.489
349
+ - type: mrr_at_100
350
+ value: 94.549
351
+ - type: mrr_at_1000
352
+ value: 94.551
353
+ - type: mrr_at_3
354
+ value: 94.22500000000001
355
+ - type: mrr_at_5
356
+ value: 94.375
357
+ - type: ndcg_at_1
358
+ value: 92.15
359
+ - type: ndcg_at_10
360
+ value: 89.283
361
+ - type: ndcg_at_100
362
+ value: 91.63900000000001
363
+ - type: ndcg_at_1000
364
+ value: 91.94600000000001
365
+ - type: ndcg_at_3
366
+ value: 88.631
367
+ - type: ndcg_at_5
368
+ value: 87.576
369
+ - type: precision_at_1
370
+ value: 92.15
371
+ - type: precision_at_10
372
+ value: 42.47
373
+ - type: precision_at_100
374
+ value: 4.814
375
+ - type: precision_at_1000
376
+ value: 0.48900000000000005
377
+ - type: precision_at_3
378
+ value: 79.567
379
+ - type: precision_at_5
380
+ value: 67.2
381
+ - type: recall_at_1
382
+ value: 26.898
383
+ - type: recall_at_10
384
+ value: 89.934
385
+ - type: recall_at_100
386
+ value: 97.898
387
+ - type: recall_at_1000
388
+ value: 99.485
389
+ - type: recall_at_3
390
+ value: 59.504000000000005
391
+ - type: recall_at_5
392
+ value: 76.827
393
+ - task:
394
+ type: Retrieval
395
+ dataset:
396
+ type: C-MTEB/EcomRetrieval
397
+ name: MTEB EcomRetrieval
398
+ config: default
399
+ split: dev
400
+ revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
401
+ metrics:
402
+ - type: map_at_1
403
+ value: 54.0
404
+ - type: map_at_10
405
+ value: 64.352
406
+ - type: map_at_100
407
+ value: 64.845
408
+ - type: map_at_1000
409
+ value: 64.85600000000001
410
+ - type: map_at_3
411
+ value: 62.017
412
+ - type: map_at_5
413
+ value: 63.437
414
+ - type: mrr_at_1
415
+ value: 54.0
416
+ - type: mrr_at_10
417
+ value: 64.352
418
+ - type: mrr_at_100
419
+ value: 64.845
420
+ - type: mrr_at_1000
421
+ value: 64.85600000000001
422
+ - type: mrr_at_3
423
+ value: 62.017
424
+ - type: mrr_at_5
425
+ value: 63.437
426
+ - type: ndcg_at_1
427
+ value: 54.0
428
+ - type: ndcg_at_10
429
+ value: 69.284
430
+ - type: ndcg_at_100
431
+ value: 71.544
432
+ - type: ndcg_at_1000
433
+ value: 71.82600000000001
434
+ - type: ndcg_at_3
435
+ value: 64.56
436
+ - type: ndcg_at_5
437
+ value: 67.096
438
+ - type: precision_at_1
439
+ value: 54.0
440
+ - type: precision_at_10
441
+ value: 8.469999999999999
442
+ - type: precision_at_100
443
+ value: 0.95
444
+ - type: precision_at_1000
445
+ value: 0.097
446
+ - type: precision_at_3
447
+ value: 23.967
448
+ - type: precision_at_5
449
+ value: 15.6
450
+ - type: recall_at_1
451
+ value: 54.0
452
+ - type: recall_at_10
453
+ value: 84.7
454
+ - type: recall_at_100
455
+ value: 95.0
456
+ - type: recall_at_1000
457
+ value: 97.2
458
+ - type: recall_at_3
459
+ value: 71.89999999999999
460
+ - type: recall_at_5
461
+ value: 78.0
462
+ - task:
463
+ type: Classification
464
+ dataset:
465
+ type: C-MTEB/IFlyTek-classification
466
+ name: MTEB IFlyTek
467
+ config: default
468
+ split: validation
469
+ revision: None
470
+ metrics:
471
+ - type: accuracy
472
+ value: 51.773759138130046
473
+ - type: f1
474
+ value: 40.26448545790716
475
+ - task:
476
+ type: Classification
477
+ dataset:
478
+ type: C-MTEB/JDReview-classification
479
+ name: MTEB JDReview
480
+ config: default
481
+ split: test
482
+ revision: None
483
+ metrics:
484
+ - type: accuracy
485
+ value: 86.94183864915573
486
+ - type: ap
487
+ value: 55.767096662593886
488
+ - type: f1
489
+ value: 81.6651183069687
490
+ - task:
491
+ type: STS
492
+ dataset:
493
+ type: C-MTEB/LCQMC
494
+ name: MTEB LCQMC
495
+ config: default
496
+ split: test
497
+ revision: None
498
+ metrics:
499
+ - type: cos_sim_pearson
500
+ value: 71.87746311678752
501
+ - type: cos_sim_spearman
502
+ value: 78.14244626549261
503
+ - type: euclidean_pearson
504
+ value: 77.64591562255025
505
+ - type: euclidean_spearman
506
+ value: 78.14244847987706
507
+ - type: manhattan_pearson
508
+ value: 77.6367858272359
509
+ - type: manhattan_spearman
510
+ value: 78.13184444922685
511
+ - task:
512
+ type: Reranking
513
+ dataset:
514
+ type: C-MTEB/Mmarco-reranking
515
+ name: MTEB MMarcoReranking
516
+ config: default
517
+ split: dev
518
+ revision: None
519
+ metrics:
520
+ - type: map
521
+ value: 29.638329783788777
522
+ - type: mrr
523
+ value: 28.496825396825397
524
+ - task:
525
+ type: Retrieval
526
+ dataset:
527
+ type: C-MTEB/MMarcoRetrieval
528
+ name: MTEB MMarcoRetrieval
529
+ config: default
530
+ split: dev
531
+ revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
532
+ metrics:
533
+ - type: map_at_1
534
+ value: 68.235
535
+ - type: map_at_10
536
+ value: 77.116
537
+ - type: map_at_100
538
+ value: 77.415
539
+ - type: map_at_1000
540
+ value: 77.42599999999999
541
+ - type: map_at_3
542
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+ ---