Erin commited on
Commit
edbaeef
1 Parent(s): 203afe0

Upload README.md

Browse files
Files changed (1) hide show
  1. README.md +354 -354
README.md CHANGED
@@ -14,17 +14,17 @@ model-index:
14
  revision: None
15
  metrics:
16
  - type: cos_sim_pearson
17
- value: 44.734816122831546
18
  - type: cos_sim_spearman
19
- value: 46.97006123331873
20
  - type: euclidean_pearson
21
- value: 45.38062036005061
22
  - type: euclidean_spearman
23
- value: 46.97006123331873
24
  - type: manhattan_pearson
25
- value: 45.25100462997557
26
  - type: manhattan_spearman
27
- value: 46.85418008817015
28
  - task:
29
  type: STS
30
  dataset:
@@ -35,17 +35,17 @@ model-index:
35
  revision: None
36
  metrics:
37
  - type: cos_sim_pearson
38
- value: 49.23835317471939
39
  - type: cos_sim_spearman
40
- value: 51.29611473119322
41
  - type: euclidean_pearson
42
- value: 53.41533188991713
43
  - type: euclidean_spearman
44
- value: 51.29611360495954
45
  - type: manhattan_pearson
46
- value: 53.42662771302782
47
  - type: manhattan_spearman
48
- value: 51.29682402789285
49
  - task:
50
  type: Classification
51
  dataset:
@@ -56,9 +56,9 @@ model-index:
56
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
57
  metrics:
58
  - type: accuracy
59
- value: 38.855999999999995
60
  - type: f1
61
- value: 36.96137480741953
62
  - task:
63
  type: STS
64
  dataset:
@@ -69,17 +69,17 @@ model-index:
69
  revision: None
70
  metrics:
71
  - type: cos_sim_pearson
72
- value: 61.79575529204537
73
  - type: cos_sim_spearman
74
- value: 64.96308773217001
75
  - type: euclidean_pearson
76
- value: 63.38747223113914
77
  - type: euclidean_spearman
78
- value: 64.96309119412786
79
  - type: manhattan_pearson
80
- value: 63.36833986897711
81
  - type: manhattan_spearman
82
- value: 64.95000035386369
83
  - task:
84
  type: Clustering
85
  dataset:
@@ -90,7 +90,7 @@ model-index:
90
  revision: None
91
  metrics:
92
  - type: v_measure
93
- value: 40.26570556670306
94
  - task:
95
  type: Clustering
96
  dataset:
@@ -101,7 +101,7 @@ model-index:
101
  revision: None
102
  metrics:
103
  - type: v_measure
104
- value: 37.68621168788469
105
  - task:
106
  type: Reranking
107
  dataset:
@@ -112,9 +112,9 @@ model-index:
112
  revision: None
113
  metrics:
114
  - type: map
115
- value: 84.40938491415716
116
  - type: mrr
117
- value: 86.86722222222222
118
  - task:
119
  type: Reranking
120
  dataset:
@@ -125,9 +125,9 @@ model-index:
125
  revision: None
126
  metrics:
127
  - type: map
128
- value: 85.2507433210034
129
  - type: mrr
130
- value: 87.58742063492063
131
  - task:
132
  type: Retrieval
133
  dataset:
@@ -138,65 +138,65 @@ model-index:
138
  revision: None
139
  metrics:
140
  - type: map_at_1
141
- value: 24.043999999999997
142
  - type: map_at_10
143
- value: 35.311
144
  - type: map_at_100
145
- value: 37.125
146
  - type: map_at_1000
147
- value: 37.26
148
  - type: map_at_3
149
- value: 31.342
150
  - type: map_at_5
151
- value: 33.613
152
  - type: mrr_at_1
153
- value: 36.909
154
  - type: mrr_at_10
155
- value: 44.373000000000005
156
  - type: mrr_at_100
157
- value: 45.367000000000004
158
  - type: mrr_at_1000
159
- value: 45.422000000000004
160
  - type: mrr_at_3
161
- value: 41.927
162
  - type: mrr_at_5
163
- value: 43.292
164
  - type: ndcg_at_1
165
- value: 36.909
166
  - type: ndcg_at_10
167
- value: 41.666
168
  - type: ndcg_at_100
169
- value: 48.915
170
  - type: ndcg_at_1000
171
- value: 51.348000000000006
172
  - type: ndcg_at_3
173
- value: 36.592
174
  - type: ndcg_at_5
175
- value: 38.787
176
  - type: precision_at_1
177
- value: 36.909
178
  - type: precision_at_10
179
- value: 9.327
180
  - type: precision_at_100
181
- value: 1.5230000000000001
182
  - type: precision_at_1000
183
  value: 0.183
184
  - type: precision_at_3
185
- value: 20.671999999999997
186
  - type: precision_at_5
187
- value: 15.179
188
  - type: recall_at_1
189
- value: 24.043999999999997
190
  - type: recall_at_10
191
- value: 51.370000000000005
192
  - type: recall_at_100
193
- value: 81.569
194
  - type: recall_at_1000
195
- value: 98.053
196
  - type: recall_at_3
197
- value: 36.120000000000005
198
  - type: recall_at_5
199
- value: 42.829
200
  - task:
201
  type: PairClassification
202
  dataset:
@@ -207,51 +207,51 @@ model-index:
207
  revision: None
208
  metrics:
209
  - type: cos_sim_accuracy
210
- value: 75.92303066746842
211
  - type: cos_sim_ap
212
- value: 84.39741959629595
213
  - type: cos_sim_f1
214
- value: 77.28710064333224
215
  - type: cos_sim_precision
216
- value: 72.41520228851655
217
  - type: cos_sim_recall
218
- value: 82.8618190320318
219
  - type: dot_accuracy
220
- value: 75.92303066746842
221
  - type: dot_ap
222
- value: 84.39592659189601
223
  - type: dot_f1
224
- value: 77.28710064333224
225
  - type: dot_precision
226
- value: 72.41520228851655
227
  - type: dot_recall
228
- value: 82.8618190320318
229
  - type: euclidean_accuracy
230
- value: 75.92303066746842
231
  - type: euclidean_ap
232
- value: 84.39741904478117
233
  - type: euclidean_f1
234
- value: 77.28710064333224
235
  - type: euclidean_precision
236
- value: 72.41520228851655
237
  - type: euclidean_recall
238
- value: 82.8618190320318
239
  - type: manhattan_accuracy
240
- value: 75.83884546001202
241
  - type: manhattan_ap
242
- value: 84.39482592167423
243
  - type: manhattan_f1
244
- value: 77.2419718612394
245
  - type: manhattan_precision
246
- value: 71.43424711958681
247
  - type: manhattan_recall
248
- value: 84.07762450315643
249
  - type: max_accuracy
250
- value: 75.92303066746842
251
  - type: max_ap
252
- value: 84.39741959629595
253
  - type: max_f1
254
- value: 77.28710064333224
255
  - task:
256
  type: Retrieval
257
  dataset:
@@ -262,65 +262,65 @@ model-index:
262
  revision: None
263
  metrics:
264
  - type: map_at_1
265
- value: 67.65
266
  - type: map_at_10
267
- value: 75.672
268
  - type: map_at_100
269
- value: 76.005
270
  - type: map_at_1000
271
- value: 76.007
272
  - type: map_at_3
273
- value: 73.867
274
  - type: map_at_5
275
- value: 74.949
276
  - type: mrr_at_1
277
- value: 67.756
278
  - type: mrr_at_10
279
- value: 75.64
280
  - type: mrr_at_100
281
- value: 75.973
282
  - type: mrr_at_1000
283
- value: 75.97500000000001
284
  - type: mrr_at_3
285
- value: 73.867
286
  - type: mrr_at_5
287
- value: 74.984
288
  - type: ndcg_at_1
289
- value: 67.861
290
  - type: ndcg_at_10
291
- value: 79.393
292
  - type: ndcg_at_100
293
- value: 81.04400000000001
294
  - type: ndcg_at_1000
295
- value: 81.15299999999999
296
  - type: ndcg_at_3
297
- value: 75.767
298
  - type: ndcg_at_5
299
- value: 77.714
300
  - type: precision_at_1
301
- value: 67.861
302
  - type: precision_at_10
303
- value: 9.199
304
  - type: precision_at_100
305
- value: 0.9979999999999999
306
  - type: precision_at_1000
307
  value: 0.101
308
  - type: precision_at_3
309
- value: 27.222
310
  - type: precision_at_5
311
- value: 17.302
312
  - type: recall_at_1
313
- value: 67.65
314
  - type: recall_at_10
315
- value: 90.938
316
  - type: recall_at_100
317
- value: 98.736
318
  - type: recall_at_1000
319
  value: 99.684
320
  - type: recall_at_3
321
- value: 81.138
322
  - type: recall_at_5
323
- value: 85.827
324
  - task:
325
  type: Retrieval
326
  dataset:
@@ -331,65 +331,65 @@ model-index:
331
  revision: None
332
  metrics:
333
  - type: map_at_1
334
- value: 25.407000000000004
335
  - type: map_at_10
336
- value: 79.001
337
  - type: map_at_100
338
- value: 81.98299999999999
339
  - type: map_at_1000
340
- value: 82.021
341
  - type: map_at_3
342
- value: 54.25600000000001
343
  - type: map_at_5
344
- value: 68.918
345
  - type: mrr_at_1
346
- value: 89.14999999999999
347
  - type: mrr_at_10
348
- value: 92.548
349
  - type: mrr_at_100
350
- value: 92.61399999999999
351
  - type: mrr_at_1000
352
- value: 92.616
353
  - type: mrr_at_3
354
- value: 92.175
355
  - type: mrr_at_5
356
- value: 92.432
357
  - type: ndcg_at_1
358
- value: 89.14999999999999
359
  - type: ndcg_at_10
360
- value: 86.588
361
  - type: ndcg_at_100
362
- value: 89.48700000000001
363
  - type: ndcg_at_1000
364
- value: 89.84100000000001
365
  - type: ndcg_at_3
366
- value: 85.00999999999999
367
  - type: ndcg_at_5
368
- value: 84.301
369
  - type: precision_at_1
370
- value: 89.14999999999999
371
  - type: precision_at_10
372
- value: 41.71
373
  - type: precision_at_100
374
- value: 4.807
375
  - type: precision_at_1000
376
  value: 0.48900000000000005
377
  - type: precision_at_3
378
- value: 76.417
379
  - type: precision_at_5
380
- value: 64.95
381
  - type: recall_at_1
382
- value: 25.407000000000004
383
  - type: recall_at_10
384
- value: 88.221
385
  - type: recall_at_100
386
- value: 97.527
387
  - type: recall_at_1000
388
- value: 99.396
389
  - type: recall_at_3
390
- value: 56.751
391
  - type: recall_at_5
392
- value: 74.191
393
  - task:
394
  type: Retrieval
395
  dataset:
@@ -400,65 +400,65 @@ model-index:
400
  revision: None
401
  metrics:
402
  - type: map_at_1
403
- value: 47.599999999999994
404
  - type: map_at_10
405
- value: 57.15
406
  - type: map_at_100
407
- value: 57.789
408
  - type: map_at_1000
409
- value: 57.80800000000001
410
  - type: map_at_3
411
- value: 54.467
412
  - type: map_at_5
413
- value: 56.016999999999996
414
  - type: mrr_at_1
415
- value: 47.599999999999994
416
  - type: mrr_at_10
417
- value: 57.15
418
  - type: mrr_at_100
419
- value: 57.789
420
  - type: mrr_at_1000
421
- value: 57.80800000000001
422
  - type: mrr_at_3
423
- value: 54.467
424
  - type: mrr_at_5
425
- value: 56.016999999999996
426
  - type: ndcg_at_1
427
- value: 47.599999999999994
428
  - type: ndcg_at_10
429
- value: 62.304
430
  - type: ndcg_at_100
431
- value: 65.32900000000001
432
  - type: ndcg_at_1000
433
- value: 65.837
434
  - type: ndcg_at_3
435
- value: 56.757000000000005
436
  - type: ndcg_at_5
437
- value: 59.575
438
  - type: precision_at_1
439
- value: 47.599999999999994
440
  - type: precision_at_10
441
- value: 7.870000000000001
442
  - type: precision_at_100
443
- value: 0.9259999999999999
444
  - type: precision_at_1000
445
  value: 0.097
446
  - type: precision_at_3
447
  value: 21.133
448
  - type: precision_at_5
449
- value: 14.06
450
  - type: recall_at_1
451
- value: 47.599999999999994
452
  - type: recall_at_10
453
- value: 78.7
454
  - type: recall_at_100
455
- value: 92.60000000000001
456
  - type: recall_at_1000
457
  value: 96.6
458
  - type: recall_at_3
459
  value: 63.4
460
  - type: recall_at_5
461
- value: 70.3
462
  - task:
463
  type: Classification
464
  dataset:
@@ -469,9 +469,9 @@ model-index:
469
  revision: None
470
  metrics:
471
  - type: accuracy
472
- value: 48.28010773374375
473
  - type: f1
474
- value: 35.536995302144916
475
  - task:
476
  type: Classification
477
  dataset:
@@ -482,11 +482,11 @@ model-index:
482
  revision: None
483
  metrics:
484
  - type: accuracy
485
- value: 84.8405253283302
486
  - type: ap
487
- value: 52.35323515091401
488
  - type: f1
489
- value: 79.50069160202494
490
  - task:
491
  type: STS
492
  dataset:
@@ -497,17 +497,17 @@ model-index:
497
  revision: None
498
  metrics:
499
  - type: cos_sim_pearson
500
- value: 69.68404288794713
501
  - type: cos_sim_spearman
502
- value: 77.06824442481803
503
  - type: euclidean_pearson
504
- value: 75.47746745802166
505
  - type: euclidean_spearman
506
- value: 77.06825328995878
507
  - type: manhattan_pearson
508
- value: 75.46220581621667
509
  - type: manhattan_spearman
510
- value: 77.05100926919137
511
  - task:
512
  type: Retrieval
513
  dataset:
@@ -518,65 +518,65 @@ model-index:
518
  revision: None
519
  metrics:
520
  - type: map_at_1
521
- value: 65.36800000000001
522
  - type: map_at_10
523
- value: 74.29400000000001
524
  - type: map_at_100
525
- value: 74.653
526
  - type: map_at_1000
527
- value: 74.664
528
  - type: map_at_3
529
- value: 72.416
530
  - type: map_at_5
531
- value: 73.658
532
  - type: mrr_at_1
533
- value: 67.50699999999999
534
  - type: mrr_at_10
535
- value: 74.85300000000001
536
  - type: mrr_at_100
537
- value: 75.17399999999999
538
  - type: mrr_at_1000
539
- value: 75.184
540
  - type: mrr_at_3
541
- value: 73.235
542
  - type: mrr_at_5
543
- value: 74.298
544
  - type: ndcg_at_1
545
- value: 67.50699999999999
546
  - type: ndcg_at_10
547
- value: 77.948
548
  - type: ndcg_at_100
549
- value: 79.55499999999999
550
  - type: ndcg_at_1000
551
- value: 79.864
552
  - type: ndcg_at_3
553
- value: 74.434
554
  - type: ndcg_at_5
555
- value: 76.504
556
  - type: precision_at_1
557
- value: 67.50699999999999
558
  - type: precision_at_10
559
- value: 9.423
560
  - type: precision_at_100
561
- value: 1.022
562
  - type: precision_at_1000
563
  value: 0.105
564
  - type: precision_at_3
565
- value: 27.975
566
  - type: precision_at_5
567
- value: 17.891000000000002
568
  - type: recall_at_1
569
- value: 65.36800000000001
570
  - type: recall_at_10
571
- value: 88.633
572
  - type: recall_at_100
573
- value: 95.889
574
  - type: recall_at_1000
575
- value: 98.346
576
  - type: recall_at_3
577
- value: 79.404
578
  - type: recall_at_5
579
- value: 84.292
580
  - task:
581
  type: Classification
582
  dataset:
@@ -587,9 +587,9 @@ model-index:
587
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
588
  metrics:
589
  - type: accuracy
590
- value: 67.45124411566913
591
  - type: f1
592
- value: 64.77175074397455
593
  - task:
594
  type: Classification
595
  dataset:
@@ -600,9 +600,9 @@ model-index:
600
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
601
  metrics:
602
  - type: accuracy
603
- value: 73.08002689979824
604
  - type: f1
605
- value: 72.65358173635958
606
  - task:
607
  type: Retrieval
608
  dataset:
@@ -613,65 +613,65 @@ model-index:
613
  revision: None
614
  metrics:
615
  - type: map_at_1
616
- value: 48.699999999999996
617
  - type: map_at_10
618
- value: 54.871
619
  - type: map_at_100
620
- value: 55.381
621
  - type: map_at_1000
622
- value: 55.43599999999999
623
  - type: map_at_3
624
- value: 53.367
625
  - type: map_at_5
626
- value: 54.257
627
  - type: mrr_at_1
628
- value: 48.699999999999996
629
  - type: mrr_at_10
630
- value: 54.871
631
  - type: mrr_at_100
632
- value: 55.381
633
  - type: mrr_at_1000
634
- value: 55.43599999999999
635
  - type: mrr_at_3
636
- value: 53.367
637
  - type: mrr_at_5
638
- value: 54.257
639
  - type: ndcg_at_1
640
- value: 48.699999999999996
641
  - type: ndcg_at_10
642
- value: 57.94200000000001
643
  - type: ndcg_at_100
644
- value: 60.75000000000001
645
  - type: ndcg_at_1000
646
- value: 62.400999999999996
647
  - type: ndcg_at_3
648
- value: 54.867
649
  - type: ndcg_at_5
650
- value: 56.493
651
  - type: precision_at_1
652
- value: 48.699999999999996
653
  - type: precision_at_10
654
- value: 6.76
655
  - type: precision_at_100
656
- value: 0.815
657
  - type: precision_at_1000
658
  value: 0.095
659
  - type: precision_at_3
660
- value: 19.733
661
  - type: precision_at_5
662
- value: 12.64
663
  - type: recall_at_1
664
- value: 48.699999999999996
665
  - type: recall_at_10
666
- value: 67.60000000000001
667
  - type: recall_at_100
668
- value: 81.5
669
  - type: recall_at_1000
670
- value: 94.89999999999999
671
  - type: recall_at_3
672
- value: 59.199999999999996
673
  - type: recall_at_5
674
- value: 63.2
675
  - task:
676
  type: Classification
677
  dataset:
@@ -682,9 +682,9 @@ model-index:
682
  revision: None
683
  metrics:
684
  - type: accuracy
685
- value: 71.27000000000001
686
  - type: f1
687
- value: 70.46516219039894
688
  - task:
689
  type: PairClassification
690
  dataset:
@@ -695,51 +695,51 @@ model-index:
695
  revision: None
696
  metrics:
697
  - type: cos_sim_accuracy
698
- value: 69.89713048186248
699
  - type: cos_sim_ap
700
- value: 74.75296949416844
701
  - type: cos_sim_f1
702
- value: 73.0820399113082
703
  - type: cos_sim_precision
704
- value: 62.99694189602446
705
  - type: cos_sim_recall
706
- value: 87.0116156282999
707
  - type: dot_accuracy
708
- value: 69.89713048186248
709
  - type: dot_ap
710
- value: 74.75289228002875
711
  - type: dot_f1
712
- value: 73.0820399113082
713
  - type: dot_precision
714
- value: 62.99694189602446
715
  - type: dot_recall
716
- value: 87.0116156282999
717
  - type: euclidean_accuracy
718
- value: 69.89713048186248
719
  - type: euclidean_ap
720
- value: 74.75289228002875
721
  - type: euclidean_f1
722
- value: 73.0820399113082
723
  - type: euclidean_precision
724
- value: 62.99694189602446
725
  - type: euclidean_recall
726
- value: 87.0116156282999
727
  - type: manhattan_accuracy
728
- value: 69.9512723335138
729
  - type: manhattan_ap
730
- value: 74.63572749955489
731
  - type: manhattan_f1
732
- value: 72.80663465735486
733
  - type: manhattan_precision
734
- value: 62.05357142857143
735
  - type: manhattan_recall
736
- value: 88.0675818373812
737
  - type: max_accuracy
738
- value: 69.9512723335138
739
  - type: max_ap
740
- value: 74.75296949416844
741
  - type: max_f1
742
- value: 73.0820399113082
743
  - task:
744
  type: Classification
745
  dataset:
@@ -750,11 +750,11 @@ model-index:
750
  revision: None
751
  metrics:
752
  - type: accuracy
753
- value: 91.38
754
  - type: ap
755
- value: 89.14371766660247
756
  - type: f1
757
- value: 91.3668296299526
758
  - task:
759
  type: STS
760
  dataset:
@@ -765,17 +765,17 @@ model-index:
765
  revision: None
766
  metrics:
767
  - type: cos_sim_pearson
768
- value: 23.621683997579606
769
  - type: cos_sim_spearman
770
- value: 29.46714129804792
771
  - type: euclidean_pearson
772
- value: 29.841725912733487
773
  - type: euclidean_spearman
774
- value: 29.466951993706992
775
  - type: manhattan_pearson
776
- value: 29.853598937043625
777
  - type: manhattan_spearman
778
- value: 29.42340511723847
779
  - task:
780
  type: STS
781
  dataset:
@@ -786,17 +786,17 @@ model-index:
786
  revision: None
787
  metrics:
788
  - type: cos_sim_pearson
789
- value: 34.86196986379606
790
  - type: cos_sim_spearman
791
- value: 37.316873994339986
792
  - type: euclidean_pearson
793
- value: 35.52672274329054
794
  - type: euclidean_spearman
795
- value: 37.316799507511014
796
  - type: manhattan_pearson
797
- value: 35.55879437844226
798
  - type: manhattan_spearman
799
- value: 37.369433247035474
800
  - task:
801
  type: STS
802
  dataset:
@@ -807,17 +807,17 @@ model-index:
807
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
808
  metrics:
809
  - type: cos_sim_pearson
810
- value: 68.7924534800626
811
  - type: cos_sim_spearman
812
- value: 69.45014686127368
813
  - type: euclidean_pearson
814
- value: 69.12500964503516
815
  - type: euclidean_spearman
816
- value: 69.45014686127368
817
  - type: manhattan_pearson
818
- value: 70.53825064823806
819
  - type: manhattan_spearman
820
- value: 70.67595198226869
821
  - task:
822
  type: STS
823
  dataset:
@@ -828,17 +828,17 @@ model-index:
828
  revision: None
829
  metrics:
830
  - type: cos_sim_pearson
831
- value: 79.02281275805849
832
  - type: cos_sim_spearman
833
- value: 79.69275718339352
834
  - type: euclidean_pearson
835
- value: 79.39660648560955
836
  - type: euclidean_spearman
837
- value: 79.69291851788452
838
  - type: manhattan_pearson
839
- value: 79.3382690172365
840
  - type: manhattan_spearman
841
- value: 79.63605584076028
842
  - task:
843
  type: Reranking
844
  dataset:
@@ -849,9 +849,9 @@ model-index:
849
  revision: None
850
  metrics:
851
  - type: map
852
- value: 66.1994271234341
853
  - type: mrr
854
- value: 75.76681067371655
855
  - task:
856
  type: Retrieval
857
  dataset:
@@ -862,65 +862,65 @@ model-index:
862
  revision: None
863
  metrics:
864
  - type: map_at_1
865
- value: 26.594
866
  - type: map_at_10
867
- value: 75.27199999999999
868
  - type: map_at_100
869
- value: 78.96
870
  - type: map_at_1000
871
- value: 79.032
872
  - type: map_at_3
873
- value: 52.76
874
  - type: map_at_5
875
- value: 64.967
876
  - type: mrr_at_1
877
- value: 88.721
878
  - type: mrr_at_10
879
- value: 91.38
880
  - type: mrr_at_100
881
- value: 91.484
882
  - type: mrr_at_1000
883
- value: 91.489
884
  - type: mrr_at_3
885
- value: 90.901
886
  - type: mrr_at_5
887
- value: 91.21000000000001
888
  - type: ndcg_at_1
889
- value: 88.721
890
  - type: ndcg_at_10
891
- value: 83.099
892
  - type: ndcg_at_100
893
- value: 86.938
894
  - type: ndcg_at_1000
895
- value: 87.644
896
  - type: ndcg_at_3
897
- value: 84.573
898
  - type: ndcg_at_5
899
- value: 83.131
900
  - type: precision_at_1
901
- value: 88.721
902
  - type: precision_at_10
903
- value: 41.506
904
  - type: precision_at_100
905
- value: 4.99
906
  - type: precision_at_1000
907
  value: 0.515
908
  - type: precision_at_3
909
- value: 74.214
910
  - type: precision_at_5
911
- value: 62.244
912
  - type: recall_at_1
913
- value: 26.594
914
  - type: recall_at_10
915
- value: 82.121
916
  - type: recall_at_100
917
- value: 94.643
918
  - type: recall_at_1000
919
- value: 98.261
920
  - type: recall_at_3
921
- value: 54.539
922
  - type: recall_at_5
923
- value: 68.573
924
  - task:
925
  type: Classification
926
  dataset:
@@ -931,9 +931,9 @@ model-index:
931
  revision: None
932
  metrics:
933
  - type: accuracy
934
- value: 51.845
935
  - type: f1
936
- value: 49.97529772676145
937
  - task:
938
  type: Clustering
939
  dataset:
@@ -944,7 +944,7 @@ model-index:
944
  revision: None
945
  metrics:
946
  - type: v_measure
947
- value: 62.34936773593232
948
  - task:
949
  type: Clustering
950
  dataset:
@@ -955,7 +955,7 @@ model-index:
955
  revision: None
956
  metrics:
957
  - type: v_measure
958
- value: 58.65057354232379
959
  - task:
960
  type: Retrieval
961
  dataset:
@@ -966,65 +966,65 @@ model-index:
966
  revision: None
967
  metrics:
968
  - type: map_at_1
969
- value: 52.2
970
  - type: map_at_10
971
- value: 62.669
972
  - type: map_at_100
973
- value: 63.239000000000004
974
  - type: map_at_1000
975
- value: 63.253
976
  - type: map_at_3
977
- value: 60.267
978
  - type: map_at_5
979
- value: 61.772000000000006
980
  - type: mrr_at_1
981
- value: 52.2
982
  - type: mrr_at_10
983
- value: 62.669
984
  - type: mrr_at_100
985
- value: 63.239000000000004
986
  - type: mrr_at_1000
987
- value: 63.253
988
  - type: mrr_at_3
989
- value: 60.267
990
  - type: mrr_at_5
991
- value: 61.772000000000006
992
  - type: ndcg_at_1
993
- value: 52.2
994
  - type: ndcg_at_10
995
- value: 67.583
996
  - type: ndcg_at_100
997
- value: 70.30499999999999
998
  - type: ndcg_at_1000
999
- value: 70.652
1000
  - type: ndcg_at_3
1001
- value: 62.775999999999996
1002
  - type: ndcg_at_5
1003
- value: 65.47
1004
  - type: precision_at_1
1005
- value: 52.2
1006
  - type: precision_at_10
1007
- value: 8.290000000000001
1008
  - type: precision_at_100
1009
- value: 0.955
1010
  - type: precision_at_1000
1011
  value: 0.098
1012
  - type: precision_at_3
1013
- value: 23.333000000000002
1014
  - type: precision_at_5
1015
- value: 15.299999999999999
1016
  - type: recall_at_1
1017
- value: 52.2
1018
  - type: recall_at_10
1019
- value: 82.89999999999999
1020
  - type: recall_at_100
1021
- value: 95.5
1022
  - type: recall_at_1000
1023
  value: 98.2
1024
  - type: recall_at_3
1025
- value: 70.0
1026
  - type: recall_at_5
1027
- value: 76.5
1028
  - task:
1029
  type: Classification
1030
  dataset:
@@ -1035,11 +1035,11 @@ model-index:
1035
  revision: None
1036
  metrics:
1037
  - type: accuracy
1038
- value: 86.64999999999999
1039
  - type: ap
1040
- value: 69.90209999390807
1041
  - type: f1
1042
- value: 84.9231810656075
1043
  - task:
1044
  type: Reranking
1045
  dataset:
@@ -1050,7 +1050,7 @@ model-index:
1050
  revision: None
1051
  metrics:
1052
  - type: map
1053
- value: 28.09825725416088
1054
  - type: mrr
1055
- value: 26.95912698412698
1056
  ---
 
14
  revision: None
15
  metrics:
16
  - type: cos_sim_pearson
17
+ value: 44.80910972039708
18
  - type: cos_sim_spearman
19
+ value: 46.97947004057185
20
  - type: euclidean_pearson
21
+ value: 45.36774158404125
22
  - type: euclidean_spearman
23
+ value: 46.97947004232487
24
  - type: manhattan_pearson
25
+ value: 45.23486628014998
26
  - type: manhattan_spearman
27
+ value: 46.87721960765866
28
  - task:
29
  type: STS
30
  dataset:
 
35
  revision: None
36
  metrics:
37
  - type: cos_sim_pearson
38
+ value: 49.5294624928126
39
  - type: cos_sim_spearman
40
+ value: 51.34771777448503
41
  - type: euclidean_pearson
42
+ value: 53.56859824288157
43
  - type: euclidean_spearman
44
+ value: 51.34771439634126
45
  - type: manhattan_pearson
46
+ value: 53.581640877132685
47
  - type: manhattan_spearman
48
+ value: 51.349656519071274
49
  - task:
50
  type: Classification
51
  dataset:
 
56
  revision: 1399c76144fd37290681b995c656ef9b2e06e26d
57
  metrics:
58
  - type: accuracy
59
+ value: 39.318
60
  - type: f1
61
+ value: 37.37720144558489
62
  - task:
63
  type: STS
64
  dataset:
 
69
  revision: None
70
  metrics:
71
  - type: cos_sim_pearson
72
+ value: 62.12016334764962
73
  - type: cos_sim_spearman
74
+ value: 65.08208654969742
75
  - type: euclidean_pearson
76
+ value: 63.53078822303454
77
  - type: euclidean_spearman
78
+ value: 65.0820865487212
79
  - type: manhattan_pearson
80
+ value: 63.510532363654725
81
  - type: manhattan_spearman
82
+ value: 65.06622789125241
83
  - task:
84
  type: Clustering
85
  dataset:
 
90
  revision: None
91
  metrics:
92
  - type: v_measure
93
+ value: 39.5071157612481
94
  - task:
95
  type: Clustering
96
  dataset:
 
101
  revision: None
102
  metrics:
103
  - type: v_measure
104
+ value: 37.99964332311132
105
  - task:
106
  type: Reranking
107
  dataset:
 
112
  revision: None
113
  metrics:
114
  - type: map
115
+ value: 84.67010533089491
116
  - type: mrr
117
+ value: 86.99488095238095
118
  - task:
119
  type: Reranking
120
  dataset:
 
125
  revision: None
126
  metrics:
127
  - type: map
128
+ value: 85.27288868896477
129
  - type: mrr
130
+ value: 87.5929761904762
131
  - task:
132
  type: Retrieval
133
  dataset:
 
138
  revision: None
139
  metrics:
140
  - type: map_at_1
141
+ value: 23.949
142
  - type: map_at_10
143
+ value: 35.394
144
  - type: map_at_100
145
+ value: 37.235
146
  - type: map_at_1000
147
+ value: 37.364999999999995
148
  - type: map_at_3
149
+ value: 31.433
150
  - type: map_at_5
151
+ value: 33.668
152
  - type: mrr_at_1
153
+ value: 36.834
154
  - type: mrr_at_10
155
+ value: 44.451
156
  - type: mrr_at_100
157
+ value: 45.445
158
  - type: mrr_at_1000
159
+ value: 45.501000000000005
160
  - type: mrr_at_3
161
+ value: 42.010999999999996
162
  - type: mrr_at_5
163
+ value: 43.34
164
  - type: ndcg_at_1
165
+ value: 36.834
166
  - type: ndcg_at_10
167
+ value: 41.803000000000004
168
  - type: ndcg_at_100
169
+ value: 49.091
170
  - type: ndcg_at_1000
171
+ value: 51.474
172
  - type: ndcg_at_3
173
+ value: 36.736000000000004
174
  - type: ndcg_at_5
175
+ value: 38.868
176
  - type: precision_at_1
177
+ value: 36.834
178
  - type: precision_at_10
179
+ value: 9.354999999999999
180
  - type: precision_at_100
181
+ value: 1.5310000000000001
182
  - type: precision_at_1000
183
  value: 0.183
184
  - type: precision_at_3
185
+ value: 20.78
186
  - type: precision_at_5
187
+ value: 15.238999999999999
188
  - type: recall_at_1
189
+ value: 23.949
190
  - type: recall_at_10
191
+ value: 51.68000000000001
192
  - type: recall_at_100
193
+ value: 81.938
194
  - type: recall_at_1000
195
+ value: 98.091
196
  - type: recall_at_3
197
+ value: 36.408
198
  - type: recall_at_5
199
+ value: 42.952
200
  - task:
201
  type: PairClassification
202
  dataset:
 
207
  revision: None
208
  metrics:
209
  - type: cos_sim_accuracy
210
+ value: 76.24774503908598
211
  - type: cos_sim_ap
212
+ value: 84.76081551540754
213
  - type: cos_sim_f1
214
+ value: 77.76321537789427
215
  - type: cos_sim_precision
216
+ value: 72.96577167452347
217
  - type: cos_sim_recall
218
+ value: 83.23591302314706
219
  - type: dot_accuracy
220
+ value: 76.24774503908598
221
  - type: dot_ap
222
+ value: 84.75968761251127
223
  - type: dot_f1
224
+ value: 77.76321537789427
225
  - type: dot_precision
226
+ value: 72.96577167452347
227
  - type: dot_recall
228
+ value: 83.23591302314706
229
  - type: euclidean_accuracy
230
+ value: 76.24774503908598
231
  - type: euclidean_ap
232
+ value: 84.7608250840413
233
  - type: euclidean_f1
234
+ value: 77.76321537789427
235
  - type: euclidean_precision
236
+ value: 72.96577167452347
237
  - type: euclidean_recall
238
+ value: 83.23591302314706
239
  - type: manhattan_accuracy
240
+ value: 76.19963920625375
241
  - type: manhattan_ap
242
+ value: 84.76313920535411
243
  - type: manhattan_f1
244
+ value: 77.74253527288636
245
  - type: manhattan_precision
246
+ value: 73.0374023838882
247
  - type: manhattan_recall
248
+ value: 83.09562777647884
249
  - type: max_accuracy
250
+ value: 76.24774503908598
251
  - type: max_ap
252
+ value: 84.76313920535411
253
  - type: max_f1
254
+ value: 77.76321537789427
255
  - task:
256
  type: Retrieval
257
  dataset:
 
262
  revision: None
263
  metrics:
264
  - type: map_at_1
265
+ value: 66.149
266
  - type: map_at_10
267
+ value: 75.22999999999999
268
  - type: map_at_100
269
+ value: 75.536
270
  - type: map_at_1000
271
+ value: 75.542
272
  - type: map_at_3
273
+ value: 73.384
274
  - type: map_at_5
275
+ value: 74.459
276
  - type: mrr_at_1
277
+ value: 66.28
278
  - type: mrr_at_10
279
+ value: 75.232
280
  - type: mrr_at_100
281
+ value: 75.52799999999999
282
  - type: mrr_at_1000
283
+ value: 75.534
284
  - type: mrr_at_3
285
+ value: 73.446
286
  - type: mrr_at_5
287
+ value: 74.473
288
  - type: ndcg_at_1
289
+ value: 66.386
290
  - type: ndcg_at_10
291
+ value: 79.295
292
  - type: ndcg_at_100
293
+ value: 80.741
294
  - type: ndcg_at_1000
295
+ value: 80.891
296
  - type: ndcg_at_3
297
+ value: 75.613
298
  - type: ndcg_at_5
299
+ value: 77.46300000000001
300
  - type: precision_at_1
301
+ value: 66.386
302
  - type: precision_at_10
303
+ value: 9.283
304
  - type: precision_at_100
305
+ value: 0.996
306
  - type: precision_at_1000
307
  value: 0.101
308
  - type: precision_at_3
309
+ value: 27.503
310
  - type: precision_at_5
311
+ value: 17.408
312
  - type: recall_at_1
313
+ value: 66.149
314
  - type: recall_at_10
315
+ value: 91.886
316
  - type: recall_at_100
317
+ value: 98.52499999999999
318
  - type: recall_at_1000
319
  value: 99.684
320
  - type: recall_at_3
321
+ value: 81.849
322
  - type: recall_at_5
323
+ value: 86.275
324
  - task:
325
  type: Retrieval
326
  dataset:
 
331
  revision: None
332
  metrics:
333
  - type: map_at_1
334
+ value: 25.166
335
  - type: map_at_10
336
+ value: 78.805
337
  - type: map_at_100
338
+ value: 81.782
339
  - type: map_at_1000
340
+ value: 81.818
341
  - type: map_at_3
342
+ value: 54.226
343
  - type: map_at_5
344
+ value: 68.783
345
  - type: mrr_at_1
346
+ value: 88.6
347
  - type: mrr_at_10
348
+ value: 92.244
349
  - type: mrr_at_100
350
+ value: 92.31899999999999
351
  - type: mrr_at_1000
352
+ value: 92.321
353
  - type: mrr_at_3
354
+ value: 91.867
355
  - type: mrr_at_5
356
+ value: 92.119
357
  - type: ndcg_at_1
358
+ value: 88.6
359
  - type: ndcg_at_10
360
+ value: 86.432
361
  - type: ndcg_at_100
362
+ value: 89.357
363
  - type: ndcg_at_1000
364
+ value: 89.688
365
  - type: ndcg_at_3
366
+ value: 84.90299999999999
367
  - type: ndcg_at_5
368
+ value: 84.137
369
  - type: precision_at_1
370
+ value: 88.6
371
  - type: precision_at_10
372
+ value: 41.685
373
  - type: precision_at_100
374
+ value: 4.811
375
  - type: precision_at_1000
376
  value: 0.48900000000000005
377
  - type: precision_at_3
378
+ value: 76.44999999999999
379
  - type: precision_at_5
380
+ value: 64.87
381
  - type: recall_at_1
382
+ value: 25.166
383
  - type: recall_at_10
384
+ value: 88.227
385
  - type: recall_at_100
386
+ value: 97.597
387
  - type: recall_at_1000
388
+ value: 99.359
389
  - type: recall_at_3
390
+ value: 56.946
391
  - type: recall_at_5
392
+ value: 74.261
393
  - task:
394
  type: Retrieval
395
  dataset:
 
400
  revision: None
401
  metrics:
402
  - type: map_at_1
403
+ value: 48.3
404
  - type: map_at_10
405
+ value: 57.635999999999996
406
  - type: map_at_100
407
+ value: 58.306000000000004
408
  - type: map_at_1000
409
+ value: 58.326
410
  - type: map_at_3
411
+ value: 54.900000000000006
412
  - type: map_at_5
413
+ value: 56.620000000000005
414
  - type: mrr_at_1
415
+ value: 48.3
416
  - type: mrr_at_10
417
+ value: 57.635999999999996
418
  - type: mrr_at_100
419
+ value: 58.306000000000004
420
  - type: mrr_at_1000
421
+ value: 58.326
422
  - type: mrr_at_3
423
+ value: 54.900000000000006
424
  - type: mrr_at_5
425
+ value: 56.620000000000005
426
  - type: ndcg_at_1
427
+ value: 48.3
428
  - type: ndcg_at_10
429
+ value: 62.638000000000005
430
  - type: ndcg_at_100
431
+ value: 65.726
432
  - type: ndcg_at_1000
433
+ value: 66.253
434
  - type: ndcg_at_3
435
+ value: 57.081
436
  - type: ndcg_at_5
437
+ value: 60.217
438
  - type: precision_at_1
439
+ value: 48.3
440
  - type: precision_at_10
441
+ value: 7.85
442
  - type: precision_at_100
443
+ value: 0.9249999999999999
444
  - type: precision_at_1000
445
  value: 0.097
446
  - type: precision_at_3
447
  value: 21.133
448
  - type: precision_at_5
449
+ value: 14.219999999999999
450
  - type: recall_at_1
451
+ value: 48.3
452
  - type: recall_at_10
453
+ value: 78.5
454
  - type: recall_at_100
455
+ value: 92.5
456
  - type: recall_at_1000
457
  value: 96.6
458
  - type: recall_at_3
459
  value: 63.4
460
  - type: recall_at_5
461
+ value: 71.1
462
  - task:
463
  type: Classification
464
  dataset:
 
469
  revision: None
470
  metrics:
471
  - type: accuracy
472
+ value: 47.9646017699115
473
  - type: f1
474
+ value: 35.03552351349023
475
  - task:
476
  type: Classification
477
  dataset:
 
482
  revision: None
483
  metrics:
484
  - type: accuracy
485
+ value: 84.8968105065666
486
  - type: ap
487
+ value: 52.564605306946774
488
  - type: f1
489
+ value: 79.59880155481291
490
  - task:
491
  type: STS
492
  dataset:
 
497
  revision: None
498
  metrics:
499
  - type: cos_sim_pearson
500
+ value: 70.03662039861051
501
  - type: cos_sim_spearman
502
+ value: 76.9642260444222
503
  - type: euclidean_pearson
504
+ value: 75.47376966815843
505
  - type: euclidean_spearman
506
+ value: 76.9642282583736
507
  - type: manhattan_pearson
508
+ value: 75.45535385433548
509
  - type: manhattan_spearman
510
+ value: 76.94609742735338
511
  - task:
512
  type: Retrieval
513
  dataset:
 
518
  revision: None
519
  metrics:
520
  - type: map_at_1
521
+ value: 65.604
522
  - type: map_at_10
523
+ value: 74.522
524
  - type: map_at_100
525
+ value: 74.878
526
  - type: map_at_1000
527
+ value: 74.889
528
  - type: map_at_3
529
+ value: 72.61
530
  - type: map_at_5
531
+ value: 73.882
532
  - type: mrr_at_1
533
+ value: 67.75099999999999
534
  - type: mrr_at_10
535
+ value: 75.08399999999999
536
  - type: mrr_at_100
537
+ value: 75.402
538
  - type: mrr_at_1000
539
+ value: 75.412
540
  - type: mrr_at_3
541
+ value: 73.446
542
  - type: mrr_at_5
543
+ value: 74.531
544
  - type: ndcg_at_1
545
+ value: 67.75099999999999
546
  - type: ndcg_at_10
547
+ value: 78.172
548
  - type: ndcg_at_100
549
+ value: 79.753
550
  - type: ndcg_at_1000
551
+ value: 80.06400000000001
552
  - type: ndcg_at_3
553
+ value: 74.607
554
  - type: ndcg_at_5
555
+ value: 76.728
556
  - type: precision_at_1
557
+ value: 67.75099999999999
558
  - type: precision_at_10
559
+ value: 9.443999999999999
560
  - type: precision_at_100
561
+ value: 1.023
562
  - type: precision_at_1000
563
  value: 0.105
564
  - type: precision_at_3
565
+ value: 28.009
566
  - type: precision_at_5
567
+ value: 17.934
568
  - type: recall_at_1
569
+ value: 65.604
570
  - type: recall_at_10
571
+ value: 88.84100000000001
572
  - type: recall_at_100
573
+ value: 95.954
574
  - type: recall_at_1000
575
+ value: 98.425
576
  - type: recall_at_3
577
+ value: 79.497
578
  - type: recall_at_5
579
+ value: 84.515
580
  - task:
581
  type: Classification
582
  dataset:
 
587
  revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
588
  metrics:
589
  - type: accuracy
590
+ value: 67.64963012777405
591
  - type: f1
592
+ value: 65.01092085388518
593
  - task:
594
  type: Classification
595
  dataset:
 
600
  revision: 7d571f92784cd94a019292a1f45445077d0ef634
601
  metrics:
602
  - type: accuracy
603
+ value: 72.9724277067922
604
  - type: f1
605
+ value: 72.48003852874602
606
  - task:
607
  type: Retrieval
608
  dataset:
 
613
  revision: None
614
  metrics:
615
  - type: map_at_1
616
+ value: 48.9
617
  - type: map_at_10
618
+ value: 55.189
619
  - type: map_at_100
620
+ value: 55.687
621
  - type: map_at_1000
622
+ value: 55.74400000000001
623
  - type: map_at_3
624
+ value: 53.75
625
  - type: map_at_5
626
+ value: 54.555
627
  - type: mrr_at_1
628
+ value: 49.1
629
  - type: mrr_at_10
630
+ value: 55.289
631
  - type: mrr_at_100
632
+ value: 55.788000000000004
633
  - type: mrr_at_1000
634
+ value: 55.845
635
  - type: mrr_at_3
636
+ value: 53.849999999999994
637
  - type: mrr_at_5
638
+ value: 54.655
639
  - type: ndcg_at_1
640
+ value: 48.9
641
  - type: ndcg_at_10
642
+ value: 58.275
643
  - type: ndcg_at_100
644
+ value: 60.980000000000004
645
  - type: ndcg_at_1000
646
+ value: 62.672000000000004
647
  - type: ndcg_at_3
648
+ value: 55.282
649
  - type: ndcg_at_5
650
+ value: 56.749
651
  - type: precision_at_1
652
+ value: 48.9
653
  - type: precision_at_10
654
+ value: 6.800000000000001
655
  - type: precision_at_100
656
+ value: 0.8130000000000001
657
  - type: precision_at_1000
658
  value: 0.095
659
  - type: precision_at_3
660
+ value: 19.900000000000002
661
  - type: precision_at_5
662
+ value: 12.659999999999998
663
  - type: recall_at_1
664
+ value: 48.9
665
  - type: recall_at_10
666
+ value: 68.0
667
  - type: recall_at_100
668
+ value: 81.3
669
  - type: recall_at_1000
670
+ value: 95.0
671
  - type: recall_at_3
672
+ value: 59.699999999999996
673
  - type: recall_at_5
674
+ value: 63.3
675
  - task:
676
  type: Classification
677
  dataset:
 
682
  revision: None
683
  metrics:
684
  - type: accuracy
685
+ value: 71.53666666666668
686
  - type: f1
687
+ value: 70.74267338218574
688
  - task:
689
  type: PairClassification
690
  dataset:
 
695
  revision: None
696
  metrics:
697
  - type: cos_sim_accuracy
698
+ value: 70.43854899837575
699
  - type: cos_sim_ap
700
+ value: 75.25713109733296
701
  - type: cos_sim_f1
702
+ value: 73.18777292576418
703
  - type: cos_sim_precision
704
+ value: 62.397617274758
705
  - type: cos_sim_recall
706
+ value: 88.48996832101372
707
  - type: dot_accuracy
708
+ value: 70.43854899837575
709
  - type: dot_ap
710
+ value: 75.25713109733296
711
  - type: dot_f1
712
+ value: 73.18777292576418
713
  - type: dot_precision
714
+ value: 62.397617274758
715
  - type: dot_recall
716
+ value: 88.48996832101372
717
  - type: euclidean_accuracy
718
+ value: 70.43854899837575
719
  - type: euclidean_ap
720
+ value: 75.25713109733296
721
  - type: euclidean_f1
722
+ value: 73.18777292576418
723
  - type: euclidean_precision
724
+ value: 62.397617274758
725
  - type: euclidean_recall
726
+ value: 88.48996832101372
727
  - type: manhattan_accuracy
728
+ value: 70.60097455332972
729
  - type: manhattan_ap
730
+ value: 75.22177995740668
731
  - type: manhattan_f1
732
+ value: 73.13750532141337
733
  - type: manhattan_precision
734
+ value: 61.26961483594865
735
  - type: manhattan_recall
736
+ value: 90.70749736008447
737
  - type: max_accuracy
738
+ value: 70.60097455332972
739
  - type: max_ap
740
+ value: 75.25713109733296
741
  - type: max_f1
742
+ value: 73.18777292576418
743
  - task:
744
  type: Classification
745
  dataset:
 
750
  revision: None
751
  metrics:
752
  - type: accuracy
753
+ value: 91.3
754
  - type: ap
755
+ value: 89.03601366589187
756
  - type: f1
757
+ value: 91.28612226957141
758
  - task:
759
  type: STS
760
  dataset:
 
765
  revision: None
766
  metrics:
767
  - type: cos_sim_pearson
768
+ value: 24.254041798082984
769
  - type: cos_sim_spearman
770
+ value: 30.029755057178846
771
  - type: euclidean_pearson
772
+ value: 30.394005237465905
773
  - type: euclidean_spearman
774
+ value: 30.029751825186153
775
  - type: manhattan_pearson
776
+ value: 30.400683181995863
777
  - type: manhattan_spearman
778
+ value: 29.981240616043326
779
  - task:
780
  type: STS
781
  dataset:
 
786
  revision: None
787
  metrics:
788
  - type: cos_sim_pearson
789
+ value: 35.09911024323138
790
  - type: cos_sim_spearman
791
+ value: 37.49790006053554
792
  - type: euclidean_pearson
793
+ value: 35.65689785105493
794
  - type: euclidean_spearman
795
+ value: 37.498032509597344
796
  - type: manhattan_pearson
797
+ value: 35.68350134483341
798
  - type: manhattan_spearman
799
+ value: 37.54046578100128
800
  - task:
801
  type: STS
802
  dataset:
 
807
  revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
808
  metrics:
809
  - type: cos_sim_pearson
810
+ value: 68.26707578158273
811
  - type: cos_sim_spearman
812
+ value: 69.19741429899995
813
  - type: euclidean_pearson
814
+ value: 68.53026048034656
815
  - type: euclidean_spearman
816
+ value: 69.1974135636389
817
  - type: manhattan_pearson
818
+ value: 70.02306646353263
819
  - type: manhattan_spearman
820
+ value: 70.46158498712836
821
  - task:
822
  type: STS
823
  dataset:
 
828
  revision: None
829
  metrics:
830
  - type: cos_sim_pearson
831
+ value: 78.88749955421177
832
  - type: cos_sim_spearman
833
+ value: 79.56695106617856
834
  - type: euclidean_pearson
835
+ value: 79.13787024514338
836
  - type: euclidean_spearman
837
+ value: 79.56690827015423
838
  - type: manhattan_pearson
839
+ value: 79.08154812411563
840
  - type: manhattan_spearman
841
+ value: 79.52391077945943
842
  - task:
843
  type: Reranking
844
  dataset:
 
849
  revision: None
850
  metrics:
851
  - type: map
852
+ value: 65.78663254562939
853
  - type: mrr
854
+ value: 74.9786877626248
855
  - task:
856
  type: Retrieval
857
  dataset:
 
862
  revision: None
863
  metrics:
864
  - type: map_at_1
865
+ value: 26.169999999999998
866
  - type: map_at_10
867
+ value: 74.009
868
  - type: map_at_100
869
+ value: 77.788
870
  - type: map_at_1000
871
+ value: 77.866
872
  - type: map_at_3
873
+ value: 51.861000000000004
874
  - type: map_at_5
875
+ value: 63.775000000000006
876
  - type: mrr_at_1
877
+ value: 87.748
878
  - type: mrr_at_10
879
+ value: 90.737
880
  - type: mrr_at_100
881
+ value: 90.84400000000001
882
  - type: mrr_at_1000
883
+ value: 90.849
884
  - type: mrr_at_3
885
+ value: 90.257
886
  - type: mrr_at_5
887
+ value: 90.54299999999999
888
  - type: ndcg_at_1
889
+ value: 87.748
890
  - type: ndcg_at_10
891
+ value: 82.114
892
  - type: ndcg_at_100
893
+ value: 86.148
894
  - type: ndcg_at_1000
895
+ value: 86.913
896
  - type: ndcg_at_3
897
+ value: 83.54599999999999
898
  - type: ndcg_at_5
899
+ value: 81.987
900
  - type: precision_at_1
901
+ value: 87.748
902
  - type: precision_at_10
903
+ value: 41.076
904
  - type: precision_at_100
905
+ value: 4.976
906
  - type: precision_at_1000
907
  value: 0.515
908
  - type: precision_at_3
909
+ value: 73.282
910
  - type: precision_at_5
911
+ value: 61.351
912
  - type: recall_at_1
913
+ value: 26.169999999999998
914
  - type: recall_at_10
915
+ value: 81.292
916
  - type: recall_at_100
917
+ value: 94.285
918
  - type: recall_at_1000
919
+ value: 98.221
920
  - type: recall_at_3
921
+ value: 53.824000000000005
922
  - type: recall_at_5
923
+ value: 67.547
924
  - task:
925
  type: Classification
926
  dataset:
 
931
  revision: None
932
  metrics:
933
  - type: accuracy
934
+ value: 51.564
935
  - type: f1
936
+ value: 49.711462885083286
937
  - task:
938
  type: Clustering
939
  dataset:
 
944
  revision: None
945
  metrics:
946
  - type: v_measure
947
+ value: 62.57078038998942
948
  - task:
949
  type: Clustering
950
  dataset:
 
955
  revision: None
956
  metrics:
957
  - type: v_measure
958
+ value: 57.842602165392144
959
  - task:
960
  type: Retrieval
961
  dataset:
 
966
  revision: None
967
  metrics:
968
  - type: map_at_1
969
+ value: 52.0
970
  - type: map_at_10
971
+ value: 62.932
972
  - type: map_at_100
973
+ value: 63.471999999999994
974
  - type: map_at_1000
975
+ value: 63.483999999999995
976
  - type: map_at_3
977
+ value: 60.516999999999996
978
  - type: map_at_5
979
+ value: 62.097
980
  - type: mrr_at_1
981
+ value: 52.0
982
  - type: mrr_at_10
983
+ value: 62.932
984
  - type: mrr_at_100
985
+ value: 63.471999999999994
986
  - type: mrr_at_1000
987
+ value: 63.483999999999995
988
  - type: mrr_at_3
989
+ value: 60.516999999999996
990
  - type: mrr_at_5
991
+ value: 62.097
992
  - type: ndcg_at_1
993
+ value: 52.0
994
  - type: ndcg_at_10
995
+ value: 67.963
996
  - type: ndcg_at_100
997
+ value: 70.598
998
  - type: ndcg_at_1000
999
+ value: 70.896
1000
  - type: ndcg_at_3
1001
+ value: 63.144
1002
  - type: ndcg_at_5
1003
+ value: 65.988
1004
  - type: precision_at_1
1005
+ value: 52.0
1006
  - type: precision_at_10
1007
+ value: 8.36
1008
  - type: precision_at_100
1009
+ value: 0.959
1010
  - type: precision_at_1000
1011
  value: 0.098
1012
  - type: precision_at_3
1013
+ value: 23.567
1014
  - type: precision_at_5
1015
+ value: 15.52
1016
  - type: recall_at_1
1017
+ value: 52.0
1018
  - type: recall_at_10
1019
+ value: 83.6
1020
  - type: recall_at_100
1021
+ value: 95.89999999999999
1022
  - type: recall_at_1000
1023
  value: 98.2
1024
  - type: recall_at_3
1025
+ value: 70.7
1026
  - type: recall_at_5
1027
+ value: 77.60000000000001
1028
  - task:
1029
  type: Classification
1030
  dataset:
 
1035
  revision: None
1036
  metrics:
1037
  - type: accuracy
1038
+ value: 86.65999999999998
1039
  - type: ap
1040
+ value: 69.91988858863054
1041
  - type: f1
1042
+ value: 84.92982698422784
1043
  - task:
1044
  type: Reranking
1045
  dataset:
 
1050
  revision: None
1051
  metrics:
1052
  - type: map
1053
+ value: 27.838972963193315
1054
  - type: mrr
1055
+ value: 26.65238095238095
1056
  ---