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1
+ ---
2
+ tags:
3
+ - mteb
4
+ model-index:
5
+ - name: bge-2048-15G
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: 35.144052273688665
18
+ - type: cos_sim_spearman
19
+ value: 36.03131554905942
20
+ - type: euclidean_pearson
21
+ value: 34.95481744048328
22
+ - type: euclidean_spearman
23
+ value: 36.0313155504039
24
+ - type: manhattan_pearson
25
+ value: 35.01398244390669
26
+ - type: manhattan_spearman
27
+ value: 36.07582645320379
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: 42.12829268908657
39
+ - type: cos_sim_spearman
40
+ value: 42.59932326711113
41
+ - type: euclidean_pearson
42
+ value: 45.0728007358798
43
+ - type: euclidean_spearman
44
+ value: 42.59932101508718
45
+ - type: manhattan_pearson
46
+ value: 45.0740044376148
47
+ - type: manhattan_spearman
48
+ value: 42.59773917033953
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: 39.32600000000001
60
+ - type: f1
61
+ value: 37.552594883461666
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: 50.01347417982947
73
+ - type: cos_sim_spearman
74
+ value: 50.93232950078808
75
+ - type: euclidean_pearson
76
+ value: 50.18139878220082
77
+ - type: euclidean_spearman
78
+ value: 50.932329500482474
79
+ - type: manhattan_pearson
80
+ value: 50.239972396501244
81
+ - type: manhattan_spearman
82
+ value: 50.98304741370781
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: 35.30752153686832
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: 37.87520358227087
105
+ - task:
106
+ type: Reranking
107
+ dataset:
108
+ type: C-MTEB/CMedQAv1-reranking
109
+ name: MTEB CMedQAv1
110
+ config: default
111
+ split: test
112
+ revision: None
113
+ metrics:
114
+ - type: map
115
+ value: 76.70424054530682
116
+ - type: mrr
117
+ value: 80.55007936507937
118
+ - task:
119
+ type: Reranking
120
+ dataset:
121
+ type: C-MTEB/CMedQAv2-reranking
122
+ name: MTEB CMedQAv2
123
+ config: default
124
+ split: test
125
+ revision: None
126
+ metrics:
127
+ - type: map
128
+ value: 78.28031561021152
129
+ - type: mrr
130
+ value: 81.80051587301587
131
+ - task:
132
+ type: Retrieval
133
+ dataset:
134
+ type: C-MTEB/CmedqaRetrieval
135
+ name: MTEB CmedqaRetrieval
136
+ config: default
137
+ split: dev
138
+ revision: None
139
+ metrics:
140
+ - type: map_at_1
141
+ value: 19.296
142
+ - type: map_at_10
143
+ value: 28.706
144
+ - type: map_at_100
145
+ value: 30.462
146
+ - type: map_at_1000
147
+ value: 30.622
148
+ - type: map_at_3
149
+ value: 25.56
150
+ - type: map_at_5
151
+ value: 27.223999999999997
152
+ - type: mrr_at_1
153
+ value: 29.857
154
+ - type: mrr_at_10
155
+ value: 37.214999999999996
156
+ - type: mrr_at_100
157
+ value: 38.26
158
+ - type: mrr_at_1000
159
+ value: 38.330999999999996
160
+ - type: mrr_at_3
161
+ value: 34.959
162
+ - type: mrr_at_5
163
+ value: 36.18
164
+ - type: ndcg_at_1
165
+ value: 29.857
166
+ - type: ndcg_at_10
167
+ value: 34.509
168
+ - type: ndcg_at_100
169
+ value: 41.884
170
+ - type: ndcg_at_1000
171
+ value: 45.023
172
+ - type: ndcg_at_3
173
+ value: 30.288999999999998
174
+ - type: ndcg_at_5
175
+ value: 31.886
176
+ - type: precision_at_1
177
+ value: 29.857
178
+ - type: precision_at_10
179
+ value: 7.779
180
+ - type: precision_at_100
181
+ value: 1.383
182
+ - type: precision_at_1000
183
+ value: 0.178
184
+ - type: precision_at_3
185
+ value: 17.179
186
+ - type: precision_at_5
187
+ value: 12.443
188
+ - type: recall_at_1
189
+ value: 19.296
190
+ - type: recall_at_10
191
+ value: 43.221
192
+ - type: recall_at_100
193
+ value: 74.09700000000001
194
+ - type: recall_at_1000
195
+ value: 95.735
196
+ - type: recall_at_3
197
+ value: 30.436999999999998
198
+ - type: recall_at_5
199
+ value: 35.5
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: 63.6440168370415
211
+ - type: cos_sim_ap
212
+ value: 68.79549034123916
213
+ - type: cos_sim_f1
214
+ value: 69.1282620766241
215
+ - type: cos_sim_precision
216
+ value: 57.20631030785726
217
+ - type: cos_sim_recall
218
+ value: 87.3275660509703
219
+ - type: dot_accuracy
220
+ value: 63.6440168370415
221
+ - type: dot_ap
222
+ value: 68.79977430584098
223
+ - type: dot_f1
224
+ value: 69.1282620766241
225
+ - type: dot_precision
226
+ value: 57.20631030785726
227
+ - type: dot_recall
228
+ value: 87.3275660509703
229
+ - type: euclidean_accuracy
230
+ value: 63.6440168370415
231
+ - type: euclidean_ap
232
+ value: 68.79548765330846
233
+ - type: euclidean_f1
234
+ value: 69.1282620766241
235
+ - type: euclidean_precision
236
+ value: 57.20631030785726
237
+ - type: euclidean_recall
238
+ value: 87.3275660509703
239
+ - type: manhattan_accuracy
240
+ value: 63.6440168370415
241
+ - type: manhattan_ap
242
+ value: 68.7809534749333
243
+ - type: manhattan_f1
244
+ value: 69.1069621999448
245
+ - type: manhattan_precision
246
+ value: 56.95876288659794
247
+ - type: manhattan_recall
248
+ value: 87.84194528875379
249
+ - type: max_accuracy
250
+ value: 63.6440168370415
251
+ - type: max_ap
252
+ value: 68.79977430584098
253
+ - type: max_f1
254
+ value: 69.1282620766241
255
+ - task:
256
+ type: Retrieval
257
+ dataset:
258
+ type: C-MTEB/CovidRetrieval
259
+ name: MTEB CovidRetrieval
260
+ config: default
261
+ split: dev
262
+ revision: None
263
+ metrics:
264
+ - type: map_at_1
265
+ value: 60.485
266
+ - type: map_at_10
267
+ value: 71.15599999999999
268
+ - type: map_at_100
269
+ value: 71.504
270
+ - type: map_at_1000
271
+ value: 71.514
272
+ - type: map_at_3
273
+ value: 69.06400000000001
274
+ - type: map_at_5
275
+ value: 70.297
276
+ - type: mrr_at_1
277
+ value: 60.695
278
+ - type: mrr_at_10
279
+ value: 71.218
280
+ - type: mrr_at_100
281
+ value: 71.557
282
+ - type: mrr_at_1000
283
+ value: 71.568
284
+ - type: mrr_at_3
285
+ value: 69.21300000000001
286
+ - type: mrr_at_5
287
+ value: 70.393
288
+ - type: ndcg_at_1
289
+ value: 60.695
290
+ - type: ndcg_at_10
291
+ value: 75.899
292
+ - type: ndcg_at_100
293
+ value: 77.524
294
+ - type: ndcg_at_1000
295
+ value: 77.775
296
+ - type: ndcg_at_3
297
+ value: 71.72500000000001
298
+ - type: ndcg_at_5
299
+ value: 73.90299999999999
300
+ - type: precision_at_1
301
+ value: 60.695
302
+ - type: precision_at_10
303
+ value: 9.136
304
+ - type: precision_at_100
305
+ value: 0.991
306
+ - type: precision_at_1000
307
+ value: 0.101
308
+ - type: precision_at_3
309
+ value: 26.589000000000002
310
+ - type: precision_at_5
311
+ value: 17.028
312
+ - type: recall_at_1
313
+ value: 60.485
314
+ - type: recall_at_10
315
+ value: 90.49000000000001
316
+ - type: recall_at_100
317
+ value: 97.99799999999999
318
+ - type: recall_at_1000
319
+ value: 99.895
320
+ - type: recall_at_3
321
+ value: 79.215
322
+ - type: recall_at_5
323
+ value: 84.48400000000001
324
+ - task:
325
+ type: Retrieval
326
+ dataset:
327
+ type: C-MTEB/DuRetrieval
328
+ name: MTEB DuRetrieval
329
+ config: default
330
+ split: dev
331
+ revision: None
332
+ metrics:
333
+ - type: map_at_1
334
+ value: 20.649
335
+ - type: map_at_10
336
+ value: 59.345000000000006
337
+ - type: map_at_100
338
+ value: 63.31
339
+ - type: map_at_1000
340
+ value: 63.449
341
+ - type: map_at_3
342
+ value: 41.614000000000004
343
+ - type: map_at_5
344
+ value: 51.425
345
+ - type: mrr_at_1
346
+ value: 73.7
347
+ - type: mrr_at_10
348
+ value: 80.42200000000001
349
+ - type: mrr_at_100
350
+ value: 80.675
351
+ - type: mrr_at_1000
352
+ value: 80.685
353
+ - type: mrr_at_3
354
+ value: 79.292
355
+ - type: mrr_at_5
356
+ value: 79.952
357
+ - type: ndcg_at_1
358
+ value: 73.7
359
+ - type: ndcg_at_10
360
+ value: 69.685
361
+ - type: ndcg_at_100
362
+ value: 76.071
363
+ - type: ndcg_at_1000
364
+ value: 77.561
365
+ - type: ndcg_at_3
366
+ value: 68.43
367
+ - type: ndcg_at_5
368
+ value: 66.78
369
+ - type: precision_at_1
370
+ value: 73.7
371
+ - type: precision_at_10
372
+ value: 33.615
373
+ - type: precision_at_100
374
+ value: 4.466
375
+ - type: precision_at_1000
376
+ value: 0.483
377
+ - type: precision_at_3
378
+ value: 60.93300000000001
379
+ - type: precision_at_5
380
+ value: 50.62
381
+ - type: recall_at_1
382
+ value: 20.649
383
+ - type: recall_at_10
384
+ value: 71.678
385
+ - type: recall_at_100
386
+ value: 91.107
387
+ - type: recall_at_1000
388
+ value: 98.489
389
+ - type: recall_at_3
390
+ value: 44.757000000000005
391
+ - type: recall_at_5
392
+ value: 57.853
393
+ - task:
394
+ type: Retrieval
395
+ dataset:
396
+ type: C-MTEB/EcomRetrieval
397
+ name: MTEB EcomRetrieval
398
+ config: default
399
+ split: dev
400
+ revision: None
401
+ metrics:
402
+ - type: map_at_1
403
+ value: 33.0
404
+ - type: map_at_10
405
+ value: 43.988
406
+ - type: map_at_100
407
+ value: 44.798
408
+ - type: map_at_1000
409
+ value: 44.840999999999994
410
+ - type: map_at_3
411
+ value: 41.25
412
+ - type: map_at_5
413
+ value: 42.91
414
+ - type: mrr_at_1
415
+ value: 33.0
416
+ - type: mrr_at_10
417
+ value: 43.988
418
+ - type: mrr_at_100
419
+ value: 44.798
420
+ - type: mrr_at_1000
421
+ value: 44.840999999999994
422
+ - type: mrr_at_3
423
+ value: 41.25
424
+ - type: mrr_at_5
425
+ value: 42.91
426
+ - type: ndcg_at_1
427
+ value: 33.0
428
+ - type: ndcg_at_10
429
+ value: 49.544
430
+ - type: ndcg_at_100
431
+ value: 53.605999999999995
432
+ - type: ndcg_at_1000
433
+ value: 54.764
434
+ - type: ndcg_at_3
435
+ value: 43.887
436
+ - type: ndcg_at_5
437
+ value: 46.907
438
+ - type: precision_at_1
439
+ value: 33.0
440
+ - type: precision_at_10
441
+ value: 6.710000000000001
442
+ - type: precision_at_100
443
+ value: 0.864
444
+ - type: precision_at_1000
445
+ value: 0.096
446
+ - type: precision_at_3
447
+ value: 17.166999999999998
448
+ - type: precision_at_5
449
+ value: 11.78
450
+ - type: recall_at_1
451
+ value: 33.0
452
+ - type: recall_at_10
453
+ value: 67.10000000000001
454
+ - type: recall_at_100
455
+ value: 86.4
456
+ - type: recall_at_1000
457
+ value: 95.6
458
+ - type: recall_at_3
459
+ value: 51.5
460
+ - type: recall_at_5
461
+ value: 58.9
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: 421605374b29664c5fc098418fe20ada9bd55f8a
470
+ metrics:
471
+ - type: accuracy
472
+ value: 47.741439015005774
473
+ - type: f1
474
+ value: 35.474522593244856
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: b7c64bd89eb87f8ded463478346f76731f07bf8b
483
+ metrics:
484
+ - type: accuracy
485
+ value: 84.18386491557224
486
+ - type: ap
487
+ value: 50.331823892307895
488
+ - type: f1
489
+ value: 78.46423899842871
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: 61.27982183684614
501
+ - type: cos_sim_spearman
502
+ value: 66.68643494062978
503
+ - type: euclidean_pearson
504
+ value: 65.18446288753343
505
+ - type: euclidean_spearman
506
+ value: 66.68643272258043
507
+ - type: manhattan_pearson
508
+ value: 65.4169819947427
509
+ - type: manhattan_spearman
510
+ value: 66.92322208196136
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: 23.220821016871753
522
+ - type: mrr
523
+ value: 21.65793650793651
524
+ - task:
525
+ type: Retrieval
526
+ dataset:
527
+ type: C-MTEB/MMarcoRetrieval
528
+ name: MTEB MMarcoRetrieval
529
+ config: default
530
+ split: dev
531
+ revision: None
532
+ metrics:
533
+ - type: map_at_1
534
+ value: 48.725
535
+ - type: map_at_10
536
+ value: 59.06
537
+ - type: map_at_100
538
+ value: 59.638999999999996
539
+ - type: map_at_1000
540
+ value: 59.666
541
+ - type: map_at_3
542
+ value: 56.528999999999996
543
+ - type: map_at_5
544
+ value: 58.099999999999994
545
+ - type: mrr_at_1
546
+ value: 50.559
547
+ - type: mrr_at_10
548
+ value: 59.852000000000004
549
+ - type: mrr_at_100
550
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+ ---