upload evaluation result on mteb
Browse files
README.md
CHANGED
@@ -5,7 +5,2313 @@ tags:
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5 |
- feature-extraction
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6 |
- sentence-similarity
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7 |
- transformers
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8 |
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9 |
---
|
10 |
|
11 |
# embedder-100p
|
|
|
5 |
- feature-extraction
|
6 |
- sentence-similarity
|
7 |
- transformers
|
8 |
+
- mteb
|
9 |
+
model-index:
|
10 |
+
- name: embedder-100p
|
11 |
+
results:
|
12 |
+
- task:
|
13 |
+
type: Classification
|
14 |
+
dataset:
|
15 |
+
type: mteb/amazon_counterfactual
|
16 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
17 |
+
config: en
|
18 |
+
split: test
|
19 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
20 |
+
metrics:
|
21 |
+
- type: accuracy
|
22 |
+
value: 67.05970149253731
|
23 |
+
- type: ap
|
24 |
+
value: 30.376473854922846
|
25 |
+
- type: f1
|
26 |
+
value: 61.30474831792133
|
27 |
+
- task:
|
28 |
+
type: Classification
|
29 |
+
dataset:
|
30 |
+
type: mteb/amazon_polarity
|
31 |
+
name: MTEB AmazonPolarityClassification
|
32 |
+
config: default
|
33 |
+
split: test
|
34 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
35 |
+
metrics:
|
36 |
+
- type: accuracy
|
37 |
+
value: 70.40859999999999
|
38 |
+
- type: ap
|
39 |
+
value: 64.61614079870762
|
40 |
+
- type: f1
|
41 |
+
value: 70.28138858999333
|
42 |
+
- task:
|
43 |
+
type: Classification
|
44 |
+
dataset:
|
45 |
+
type: mteb/amazon_reviews_multi
|
46 |
+
name: MTEB AmazonReviewsClassification (en)
|
47 |
+
config: en
|
48 |
+
split: test
|
49 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
50 |
+
metrics:
|
51 |
+
- type: accuracy
|
52 |
+
value: 33.214
|
53 |
+
- type: f1
|
54 |
+
value: 33.123322451005755
|
55 |
+
- task:
|
56 |
+
type: Retrieval
|
57 |
+
dataset:
|
58 |
+
type: arguana
|
59 |
+
name: MTEB ArguAna
|
60 |
+
config: default
|
61 |
+
split: test
|
62 |
+
revision: None
|
63 |
+
metrics:
|
64 |
+
- type: map_at_1
|
65 |
+
value: 27.311999999999998
|
66 |
+
- type: map_at_10
|
67 |
+
value: 42.760999999999996
|
68 |
+
- type: map_at_100
|
69 |
+
value: 43.691
|
70 |
+
- type: map_at_1000
|
71 |
+
value: 43.698
|
72 |
+
- type: map_at_3
|
73 |
+
value: 37.091
|
74 |
+
- type: map_at_5
|
75 |
+
value: 40.398
|
76 |
+
- type: mrr_at_1
|
77 |
+
value: 28.377999999999997
|
78 |
+
- type: mrr_at_10
|
79 |
+
value: 43.138
|
80 |
+
- type: mrr_at_100
|
81 |
+
value: 44.088
|
82 |
+
- type: mrr_at_1000
|
83 |
+
value: 44.095
|
84 |
+
- type: mrr_at_3
|
85 |
+
value: 37.47
|
86 |
+
- type: mrr_at_5
|
87 |
+
value: 40.749
|
88 |
+
- type: ndcg_at_1
|
89 |
+
value: 27.311999999999998
|
90 |
+
- type: ndcg_at_10
|
91 |
+
value: 52.035
|
92 |
+
- type: ndcg_at_100
|
93 |
+
value: 55.891000000000005
|
94 |
+
- type: ndcg_at_1000
|
95 |
+
value: 56.043
|
96 |
+
- type: ndcg_at_3
|
97 |
+
value: 40.38
|
98 |
+
- type: ndcg_at_5
|
99 |
+
value: 46.364
|
100 |
+
- type: precision_at_1
|
101 |
+
value: 27.311999999999998
|
102 |
+
- type: precision_at_10
|
103 |
+
value: 8.193
|
104 |
+
- type: precision_at_100
|
105 |
+
value: 0.985
|
106 |
+
- type: precision_at_1000
|
107 |
+
value: 0.1
|
108 |
+
- type: precision_at_3
|
109 |
+
value: 16.643
|
110 |
+
- type: precision_at_5
|
111 |
+
value: 12.902
|
112 |
+
- type: recall_at_1
|
113 |
+
value: 27.311999999999998
|
114 |
+
- type: recall_at_10
|
115 |
+
value: 81.935
|
116 |
+
- type: recall_at_100
|
117 |
+
value: 98.506
|
118 |
+
- type: recall_at_1000
|
119 |
+
value: 99.644
|
120 |
+
- type: recall_at_3
|
121 |
+
value: 49.929
|
122 |
+
- type: recall_at_5
|
123 |
+
value: 64.509
|
124 |
+
- task:
|
125 |
+
type: Clustering
|
126 |
+
dataset:
|
127 |
+
type: mteb/arxiv-clustering-p2p
|
128 |
+
name: MTEB ArxivClusteringP2P
|
129 |
+
config: default
|
130 |
+
split: test
|
131 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
132 |
+
metrics:
|
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|
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type: mteb/banking77
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name: MTEB Banking77Classification
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192 |
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type: mteb/biorxiv-clustering-p2p
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name: MTEB BiorxivClusteringP2P
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203 |
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value: 37.35544823305565
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204 |
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205 |
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type: Clustering
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206 |
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dataset:
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type: mteb/biorxiv-clustering-s2s
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name: MTEB BiorxivClusteringS2S
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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214 |
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215 |
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type: BeIR/cqadupstack
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name: MTEB CQADupstackAndroidRetrieval
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config: default
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revision: None
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275 |
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value: 58.4
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value: 51.056000000000004
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dataset:
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type: BeIR/cqadupstack
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288 |
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name: MTEB CQADupstackEnglishRetrieval
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289 |
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config: default
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split: test
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revision: None
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metrics:
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294 |
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value: 23.46
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295 |
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296 |
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value: 7.605
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value: 1.291
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value: 0.185
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value: 16.582
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value: 12.051
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value: 23.46
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value: 50.080000000000005
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value: 70.161
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value: 86.009
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value: 36.229
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351 |
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352 |
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value: 42.055
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353 |
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dataset:
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356 |
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type: BeIR/cqadupstack
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357 |
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name: MTEB CQADupstackGamingRetrieval
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358 |
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config: default
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359 |
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split: test
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360 |
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revision: None
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metrics:
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363 |
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value: 35.515
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364 |
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackGisRetrieval
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value: 19.75
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458 |
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- task:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackMathematicaRetrieval
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500 |
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501 |
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502 |
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503 |
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531 |
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541 |
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544 |
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- task:
|
561 |
+
type: Retrieval
|
562 |
+
dataset:
|
563 |
+
type: BeIR/cqadupstack
|
564 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
565 |
+
config: default
|
566 |
+
split: test
|
567 |
+
revision: None
|
568 |
+
metrics:
|
569 |
+
- type: map_at_1
|
570 |
+
value: 25.041999999999998
|
571 |
+
- type: map_at_10
|
572 |
+
value: 35.61
|
573 |
+
- type: map_at_100
|
574 |
+
value: 37.002
|
575 |
+
- type: map_at_1000
|
576 |
+
value: 37.120999999999995
|
577 |
+
- type: map_at_3
|
578 |
+
value: 31.982
|
579 |
+
- type: map_at_5
|
580 |
+
value: 34.007
|
581 |
+
- type: mrr_at_1
|
582 |
+
value: 30.895
|
583 |
+
- type: mrr_at_10
|
584 |
+
value: 41.095
|
585 |
+
- type: mrr_at_100
|
586 |
+
value: 41.983
|
587 |
+
- type: mrr_at_1000
|
588 |
+
value: 42.031
|
589 |
+
- type: mrr_at_3
|
590 |
+
value: 38.114
|
591 |
+
- type: mrr_at_5
|
592 |
+
value: 39.798
|
593 |
+
- type: ndcg_at_1
|
594 |
+
value: 30.895
|
595 |
+
- type: ndcg_at_10
|
596 |
+
value: 42.138999999999996
|
597 |
+
- type: ndcg_at_100
|
598 |
+
value: 47.741
|
599 |
+
- type: ndcg_at_1000
|
600 |
+
value: 49.931
|
601 |
+
- type: ndcg_at_3
|
602 |
+
value: 36.179
|
603 |
+
- type: ndcg_at_5
|
604 |
+
value: 38.998
|
605 |
+
- type: precision_at_1
|
606 |
+
value: 30.895
|
607 |
+
- type: precision_at_10
|
608 |
+
value: 8.065
|
609 |
+
- type: precision_at_100
|
610 |
+
value: 1.274
|
611 |
+
- type: precision_at_1000
|
612 |
+
value: 0.165
|
613 |
+
- type: precision_at_3
|
614 |
+
value: 17.645
|
615 |
+
- type: precision_at_5
|
616 |
+
value: 12.955
|
617 |
+
- type: recall_at_1
|
618 |
+
value: 25.041999999999998
|
619 |
+
- type: recall_at_10
|
620 |
+
value: 56.169999999999995
|
621 |
+
- type: recall_at_100
|
622 |
+
value: 79.3
|
623 |
+
- type: recall_at_1000
|
624 |
+
value: 93.618
|
625 |
+
- type: recall_at_3
|
626 |
+
value: 39.359
|
627 |
+
- type: recall_at_5
|
628 |
+
value: 46.650000000000006
|
629 |
+
- task:
|
630 |
+
type: Retrieval
|
631 |
+
dataset:
|
632 |
+
type: BeIR/cqadupstack
|
633 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
634 |
+
config: default
|
635 |
+
split: test
|
636 |
+
revision: None
|
637 |
+
metrics:
|
638 |
+
- type: map_at_1
|
639 |
+
value: 23.854
|
640 |
+
- type: map_at_10
|
641 |
+
value: 32.088
|
642 |
+
- type: map_at_100
|
643 |
+
value: 33.511
|
644 |
+
- type: map_at_1000
|
645 |
+
value: 33.629999999999995
|
646 |
+
- type: map_at_3
|
647 |
+
value: 29.079
|
648 |
+
- type: map_at_5
|
649 |
+
value: 30.663
|
650 |
+
- type: mrr_at_1
|
651 |
+
value: 29.110000000000003
|
652 |
+
- type: mrr_at_10
|
653 |
+
value: 36.902
|
654 |
+
- type: mrr_at_100
|
655 |
+
value: 37.927
|
656 |
+
- type: mrr_at_1000
|
657 |
+
value: 37.99
|
658 |
+
- type: mrr_at_3
|
659 |
+
value: 34.285
|
660 |
+
- type: mrr_at_5
|
661 |
+
value: 35.757
|
662 |
+
- type: ndcg_at_1
|
663 |
+
value: 29.110000000000003
|
664 |
+
- type: ndcg_at_10
|
665 |
+
value: 37.429
|
666 |
+
- type: ndcg_at_100
|
667 |
+
value: 43.59
|
668 |
+
- type: ndcg_at_1000
|
669 |
+
value: 46.207
|
670 |
+
- type: ndcg_at_3
|
671 |
+
value: 32.394
|
672 |
+
- type: ndcg_at_5
|
673 |
+
value: 34.562
|
674 |
+
- type: precision_at_1
|
675 |
+
value: 29.110000000000003
|
676 |
+
- type: precision_at_10
|
677 |
+
value: 6.895
|
678 |
+
- type: precision_at_100
|
679 |
+
value: 1.176
|
680 |
+
- type: precision_at_1000
|
681 |
+
value: 0.158
|
682 |
+
- type: precision_at_3
|
683 |
+
value: 15.107000000000001
|
684 |
+
- type: precision_at_5
|
685 |
+
value: 10.982
|
686 |
+
- type: recall_at_1
|
687 |
+
value: 23.854
|
688 |
+
- type: recall_at_10
|
689 |
+
value: 48.589
|
690 |
+
- type: recall_at_100
|
691 |
+
value: 74.78
|
692 |
+
- type: recall_at_1000
|
693 |
+
value: 92.836
|
694 |
+
- type: recall_at_3
|
695 |
+
value: 34.489
|
696 |
+
- type: recall_at_5
|
697 |
+
value: 40.182
|
698 |
+
- task:
|
699 |
+
type: Retrieval
|
700 |
+
dataset:
|
701 |
+
type: BeIR/cqadupstack
|
702 |
+
name: MTEB CQADupstackStatsRetrieval
|
703 |
+
config: default
|
704 |
+
split: test
|
705 |
+
revision: None
|
706 |
+
metrics:
|
707 |
+
- type: map_at_1
|
708 |
+
value: 19.293
|
709 |
+
- type: map_at_10
|
710 |
+
value: 25.316
|
711 |
+
- type: map_at_100
|
712 |
+
value: 26.211000000000002
|
713 |
+
- type: map_at_1000
|
714 |
+
value: 26.316
|
715 |
+
- type: map_at_3
|
716 |
+
value: 23.200000000000003
|
717 |
+
- type: map_at_5
|
718 |
+
value: 24.538
|
719 |
+
- type: mrr_at_1
|
720 |
+
value: 21.471999999999998
|
721 |
+
- type: mrr_at_10
|
722 |
+
value: 27.583000000000002
|
723 |
+
- type: mrr_at_100
|
724 |
+
value: 28.371000000000002
|
725 |
+
- type: mrr_at_1000
|
726 |
+
value: 28.455000000000002
|
727 |
+
- type: mrr_at_3
|
728 |
+
value: 25.613000000000003
|
729 |
+
- type: mrr_at_5
|
730 |
+
value: 26.863
|
731 |
+
- type: ndcg_at_1
|
732 |
+
value: 21.471999999999998
|
733 |
+
- type: ndcg_at_10
|
734 |
+
value: 28.925
|
735 |
+
- type: ndcg_at_100
|
736 |
+
value: 33.489000000000004
|
737 |
+
- type: ndcg_at_1000
|
738 |
+
value: 36.313
|
739 |
+
- type: ndcg_at_3
|
740 |
+
value: 25.003999999999998
|
741 |
+
- type: ndcg_at_5
|
742 |
+
value: 27.232
|
743 |
+
- type: precision_at_1
|
744 |
+
value: 21.471999999999998
|
745 |
+
- type: precision_at_10
|
746 |
+
value: 4.693
|
747 |
+
- type: precision_at_100
|
748 |
+
value: 0.762
|
749 |
+
- type: precision_at_1000
|
750 |
+
value: 0.108
|
751 |
+
- type: precision_at_3
|
752 |
+
value: 10.838000000000001
|
753 |
+
- type: precision_at_5
|
754 |
+
value: 7.945
|
755 |
+
- type: recall_at_1
|
756 |
+
value: 19.293
|
757 |
+
- type: recall_at_10
|
758 |
+
value: 37.63
|
759 |
+
- type: recall_at_100
|
760 |
+
value: 58.818000000000005
|
761 |
+
- type: recall_at_1000
|
762 |
+
value: 80.026
|
763 |
+
- type: recall_at_3
|
764 |
+
value: 27.389000000000003
|
765 |
+
- type: recall_at_5
|
766 |
+
value: 32.71
|
767 |
+
- task:
|
768 |
+
type: Retrieval
|
769 |
+
dataset:
|
770 |
+
type: BeIR/cqadupstack
|
771 |
+
name: MTEB CQADupstackTexRetrieval
|
772 |
+
config: default
|
773 |
+
split: test
|
774 |
+
revision: None
|
775 |
+
metrics:
|
776 |
+
- type: map_at_1
|
777 |
+
value: 12.087
|
778 |
+
- type: map_at_10
|
779 |
+
value: 17.777
|
780 |
+
- type: map_at_100
|
781 |
+
value: 18.837
|
782 |
+
- type: map_at_1000
|
783 |
+
value: 18.973000000000003
|
784 |
+
- type: map_at_3
|
785 |
+
value: 15.956999999999999
|
786 |
+
- type: map_at_5
|
787 |
+
value: 16.902
|
788 |
+
- type: mrr_at_1
|
789 |
+
value: 14.763000000000002
|
790 |
+
- type: mrr_at_10
|
791 |
+
value: 20.8
|
792 |
+
- type: mrr_at_100
|
793 |
+
value: 21.757
|
794 |
+
- type: mrr_at_1000
|
795 |
+
value: 21.85
|
796 |
+
- type: mrr_at_3
|
797 |
+
value: 18.989
|
798 |
+
- type: mrr_at_5
|
799 |
+
value: 19.905
|
800 |
+
- type: ndcg_at_1
|
801 |
+
value: 14.763000000000002
|
802 |
+
- type: ndcg_at_10
|
803 |
+
value: 21.512999999999998
|
804 |
+
- type: ndcg_at_100
|
805 |
+
value: 26.822000000000003
|
806 |
+
- type: ndcg_at_1000
|
807 |
+
value: 30.270999999999997
|
808 |
+
- type: ndcg_at_3
|
809 |
+
value: 18.16
|
810 |
+
- type: ndcg_at_5
|
811 |
+
value: 19.573999999999998
|
812 |
+
- type: precision_at_1
|
813 |
+
value: 14.763000000000002
|
814 |
+
- type: precision_at_10
|
815 |
+
value: 4.043
|
816 |
+
- type: precision_at_100
|
817 |
+
value: 0.7979999999999999
|
818 |
+
- type: precision_at_1000
|
819 |
+
value: 0.128
|
820 |
+
- type: precision_at_3
|
821 |
+
value: 8.741
|
822 |
+
- type: precision_at_5
|
823 |
+
value: 6.325
|
824 |
+
- type: recall_at_1
|
825 |
+
value: 12.087
|
826 |
+
- type: recall_at_10
|
827 |
+
value: 29.805
|
828 |
+
- type: recall_at_100
|
829 |
+
value: 53.787
|
830 |
+
- type: recall_at_1000
|
831 |
+
value: 78.884
|
832 |
+
- type: recall_at_3
|
833 |
+
value: 20.497
|
834 |
+
- type: recall_at_5
|
835 |
+
value: 24.148
|
836 |
+
- task:
|
837 |
+
type: Retrieval
|
838 |
+
dataset:
|
839 |
+
type: BeIR/cqadupstack
|
840 |
+
name: MTEB CQADupstackUnixRetrieval
|
841 |
+
config: default
|
842 |
+
split: test
|
843 |
+
revision: None
|
844 |
+
metrics:
|
845 |
+
- type: map_at_1
|
846 |
+
value: 22.099
|
847 |
+
- type: map_at_10
|
848 |
+
value: 29.487999999999996
|
849 |
+
- type: map_at_100
|
850 |
+
value: 30.553
|
851 |
+
- type: map_at_1000
|
852 |
+
value: 30.669999999999998
|
853 |
+
- type: map_at_3
|
854 |
+
value: 27.250000000000004
|
855 |
+
- type: map_at_5
|
856 |
+
value: 28.416000000000004
|
857 |
+
- type: mrr_at_1
|
858 |
+
value: 26.026
|
859 |
+
- type: mrr_at_10
|
860 |
+
value: 33.238
|
861 |
+
- type: mrr_at_100
|
862 |
+
value: 34.114
|
863 |
+
- type: mrr_at_1000
|
864 |
+
value: 34.188
|
865 |
+
- type: mrr_at_3
|
866 |
+
value: 31.157
|
867 |
+
- type: mrr_at_5
|
868 |
+
value: 32.262
|
869 |
+
- type: ndcg_at_1
|
870 |
+
value: 26.026
|
871 |
+
- type: ndcg_at_10
|
872 |
+
value: 34.036
|
873 |
+
- type: ndcg_at_100
|
874 |
+
value: 39.443
|
875 |
+
- type: ndcg_at_1000
|
876 |
+
value: 42.181999999999995
|
877 |
+
- type: ndcg_at_3
|
878 |
+
value: 29.942
|
879 |
+
- type: ndcg_at_5
|
880 |
+
value: 31.682
|
881 |
+
- type: precision_at_1
|
882 |
+
value: 26.026
|
883 |
+
- type: precision_at_10
|
884 |
+
value: 5.7090000000000005
|
885 |
+
- type: precision_at_100
|
886 |
+
value: 0.9560000000000001
|
887 |
+
- type: precision_at_1000
|
888 |
+
value: 0.131
|
889 |
+
- type: precision_at_3
|
890 |
+
value: 13.495
|
891 |
+
- type: precision_at_5
|
892 |
+
value: 9.366
|
893 |
+
- type: recall_at_1
|
894 |
+
value: 22.099
|
895 |
+
- type: recall_at_10
|
896 |
+
value: 44.098
|
897 |
+
- type: recall_at_100
|
898 |
+
value: 68.726
|
899 |
+
- type: recall_at_1000
|
900 |
+
value: 87.992
|
901 |
+
- type: recall_at_3
|
902 |
+
value: 32.902
|
903 |
+
- type: recall_at_5
|
904 |
+
value: 37.389
|
905 |
+
- task:
|
906 |
+
type: Retrieval
|
907 |
+
dataset:
|
908 |
+
type: BeIR/cqadupstack
|
909 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
910 |
+
config: default
|
911 |
+
split: test
|
912 |
+
revision: None
|
913 |
+
metrics:
|
914 |
+
- type: map_at_1
|
915 |
+
value: 19.195
|
916 |
+
- type: map_at_10
|
917 |
+
value: 27.298000000000002
|
918 |
+
- type: map_at_100
|
919 |
+
value: 28.875
|
920 |
+
- type: map_at_1000
|
921 |
+
value: 29.151
|
922 |
+
- type: map_at_3
|
923 |
+
value: 24.595
|
924 |
+
- type: map_at_5
|
925 |
+
value: 25.926
|
926 |
+
- type: mrr_at_1
|
927 |
+
value: 23.913
|
928 |
+
- type: mrr_at_10
|
929 |
+
value: 31.696999999999996
|
930 |
+
- type: mrr_at_100
|
931 |
+
value: 32.728
|
932 |
+
- type: mrr_at_1000
|
933 |
+
value: 32.808
|
934 |
+
- type: mrr_at_3
|
935 |
+
value: 29.249000000000002
|
936 |
+
- type: mrr_at_5
|
937 |
+
value: 30.623
|
938 |
+
- type: ndcg_at_1
|
939 |
+
value: 23.913
|
940 |
+
- type: ndcg_at_10
|
941 |
+
value: 32.745999999999995
|
942 |
+
- type: ndcg_at_100
|
943 |
+
value: 38.663
|
944 |
+
- type: ndcg_at_1000
|
945 |
+
value: 41.984
|
946 |
+
- type: ndcg_at_3
|
947 |
+
value: 28.272000000000002
|
948 |
+
- type: ndcg_at_5
|
949 |
+
value: 30.184
|
950 |
+
- type: precision_at_1
|
951 |
+
value: 23.913
|
952 |
+
- type: precision_at_10
|
953 |
+
value: 6.601
|
954 |
+
- type: precision_at_100
|
955 |
+
value: 1.462
|
956 |
+
- type: precision_at_1000
|
957 |
+
value: 0.241
|
958 |
+
- type: precision_at_3
|
959 |
+
value: 13.439
|
960 |
+
- type: precision_at_5
|
961 |
+
value: 10.079
|
962 |
+
- type: recall_at_1
|
963 |
+
value: 19.195
|
964 |
+
- type: recall_at_10
|
965 |
+
value: 42.933
|
966 |
+
- type: recall_at_100
|
967 |
+
value: 69.762
|
968 |
+
- type: recall_at_1000
|
969 |
+
value: 91.57
|
970 |
+
- type: recall_at_3
|
971 |
+
value: 30.302
|
972 |
+
- type: recall_at_5
|
973 |
+
value: 35.17
|
974 |
+
- task:
|
975 |
+
type: Retrieval
|
976 |
+
dataset:
|
977 |
+
type: BeIR/cqadupstack
|
978 |
+
name: MTEB CQADupstackWordpressRetrieval
|
979 |
+
config: default
|
980 |
+
split: test
|
981 |
+
revision: None
|
982 |
+
metrics:
|
983 |
+
- type: map_at_1
|
984 |
+
value: 13.816999999999998
|
985 |
+
- type: map_at_10
|
986 |
+
value: 19.314
|
987 |
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|
988 |
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value: 20.328
|
989 |
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|
990 |
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value: 20.439
|
991 |
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- type: map_at_3
|
992 |
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value: 16.658
|
993 |
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|
994 |
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value: 18.169
|
995 |
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- type: mrr_at_1
|
996 |
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value: 15.342
|
997 |
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- type: mrr_at_10
|
998 |
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value: 21.098
|
999 |
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- type: mrr_at_100
|
1000 |
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value: 22.031
|
1001 |
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- type: mrr_at_1000
|
1002 |
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value: 22.126
|
1003 |
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|
1004 |
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value: 18.453
|
1005 |
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|
1006 |
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value: 19.923
|
1007 |
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|
1008 |
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value: 15.342
|
1009 |
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- type: ndcg_at_10
|
1010 |
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value: 23.558
|
1011 |
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- type: ndcg_at_100
|
1012 |
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value: 28.889
|
1013 |
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- type: ndcg_at_1000
|
1014 |
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value: 31.89
|
1015 |
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|
1016 |
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value: 18.186
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1017 |
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|
1018 |
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value: 20.751
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1019 |
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|
1020 |
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value: 15.342
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1021 |
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|
1022 |
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value: 4.011
|
1023 |
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- type: precision_at_100
|
1024 |
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value: 0.749
|
1025 |
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- type: precision_at_1000
|
1026 |
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value: 0.109
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1027 |
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- type: precision_at_3
|
1028 |
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value: 7.763000000000001
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1029 |
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- type: precision_at_5
|
1030 |
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value: 6.026
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1031 |
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- type: recall_at_1
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1032 |
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value: 13.816999999999998
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1033 |
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- type: recall_at_10
|
1034 |
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value: 35.459
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1035 |
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- type: recall_at_100
|
1036 |
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value: 60.612
|
1037 |
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- type: recall_at_1000
|
1038 |
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value: 83.174
|
1039 |
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- type: recall_at_3
|
1040 |
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value: 20.601
|
1041 |
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- type: recall_at_5
|
1042 |
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value: 26.83
|
1043 |
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- task:
|
1044 |
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type: Retrieval
|
1045 |
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dataset:
|
1046 |
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type: climate-fever
|
1047 |
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name: MTEB ClimateFEVER
|
1048 |
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config: default
|
1049 |
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split: test
|
1050 |
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revision: None
|
1051 |
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metrics:
|
1052 |
+
- type: map_at_1
|
1053 |
+
value: 8.770999999999999
|
1054 |
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- type: map_at_10
|
1055 |
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value: 14.948
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1056 |
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|
1057 |
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value: 16.668
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1058 |
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1059 |
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value: 16.865
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1060 |
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|
1061 |
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value: 12.264
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1062 |
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|
1063 |
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value: 13.623
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1064 |
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|
1065 |
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value: 18.502
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1066 |
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- type: mrr_at_10
|
1067 |
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value: 28.782000000000004
|
1068 |
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- type: mrr_at_100
|
1069 |
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value: 29.875
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1070 |
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- type: mrr_at_1000
|
1071 |
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value: 29.929
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1072 |
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|
1073 |
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value: 25.147000000000002
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1074 |
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- type: mrr_at_5
|
1075 |
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value: 27.322000000000003
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1076 |
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- type: ndcg_at_1
|
1077 |
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value: 18.502
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1078 |
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- type: ndcg_at_10
|
1079 |
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value: 21.815
|
1080 |
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- type: ndcg_at_100
|
1081 |
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value: 29.174
|
1082 |
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- type: ndcg_at_1000
|
1083 |
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value: 32.946999999999996
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1084 |
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- type: ndcg_at_3
|
1085 |
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value: 16.833000000000002
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1086 |
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- type: ndcg_at_5
|
1087 |
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value: 18.792
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1088 |
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- type: precision_at_1
|
1089 |
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value: 18.502
|
1090 |
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- type: precision_at_10
|
1091 |
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value: 7.016
|
1092 |
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- type: precision_at_100
|
1093 |
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value: 1.486
|
1094 |
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- type: precision_at_1000
|
1095 |
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value: 0.219
|
1096 |
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- type: precision_at_3
|
1097 |
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value: 12.421
|
1098 |
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- type: precision_at_5
|
1099 |
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value: 10.15
|
1100 |
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- type: recall_at_1
|
1101 |
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value: 8.770999999999999
|
1102 |
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- type: recall_at_10
|
1103 |
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value: 27.542
|
1104 |
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- type: recall_at_100
|
1105 |
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value: 53.481
|
1106 |
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- type: recall_at_1000
|
1107 |
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value: 74.67399999999999
|
1108 |
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- type: recall_at_3
|
1109 |
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value: 15.986
|
1110 |
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- type: recall_at_5
|
1111 |
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value: 20.669
|
1112 |
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- task:
|
1113 |
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type: Retrieval
|
1114 |
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dataset:
|
1115 |
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type: dbpedia-entity
|
1116 |
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name: MTEB DBPedia
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1117 |
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config: default
|
1118 |
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split: test
|
1119 |
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revision: None
|
1120 |
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metrics:
|
1121 |
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- type: map_at_1
|
1122 |
+
value: 6.0249999999999995
|
1123 |
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- type: map_at_10
|
1124 |
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value: 11.924
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1125 |
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|
1126 |
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value: 15.801000000000002
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1127 |
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- type: map_at_1000
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1128 |
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value: 16.878999999999998
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1129 |
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|
1130 |
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value: 9.031
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1131 |
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- type: map_at_5
|
1132 |
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value: 10.181
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1133 |
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|
1134 |
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value: 48.0
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1135 |
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|
1136 |
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value: 56.928
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1137 |
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- type: mrr_at_100
|
1138 |
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value: 57.619
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1139 |
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|
1140 |
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value: 57.646
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1141 |
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|
1142 |
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value: 55.25
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1143 |
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- type: mrr_at_5
|
1144 |
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value: 55.974999999999994
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1145 |
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- type: ndcg_at_1
|
1146 |
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value: 36.875
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1147 |
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- type: ndcg_at_10
|
1148 |
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value: 26.508
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1149 |
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- type: ndcg_at_100
|
1150 |
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value: 29.692
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1151 |
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- type: ndcg_at_1000
|
1152 |
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value: 36.658
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1153 |
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- type: ndcg_at_3
|
1154 |
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value: 30.764000000000003
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1155 |
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|
1156 |
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value: 28.049000000000003
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1157 |
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- type: precision_at_1
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1158 |
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value: 48.0
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1159 |
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|
1160 |
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value: 21.175
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1161 |
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- type: precision_at_100
|
1162 |
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value: 6.535
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1163 |
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- type: precision_at_1000
|
1164 |
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value: 1.6230000000000002
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1165 |
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- type: precision_at_3
|
1166 |
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value: 34.75
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1167 |
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- type: precision_at_5
|
1168 |
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value: 27.700000000000003
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1169 |
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- type: recall_at_1
|
1170 |
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value: 6.0249999999999995
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1171 |
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- type: recall_at_10
|
1172 |
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value: 16.454
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1173 |
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- type: recall_at_100
|
1174 |
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value: 35.026
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1175 |
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- type: recall_at_1000
|
1176 |
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value: 58.031
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1177 |
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- type: recall_at_3
|
1178 |
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value: 10.058
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1179 |
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- type: recall_at_5
|
1180 |
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value: 12.145999999999999
|
1181 |
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- task:
|
1182 |
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type: Classification
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1183 |
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dataset:
|
1184 |
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type: mteb/emotion
|
1185 |
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name: MTEB EmotionClassification
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1186 |
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config: default
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1187 |
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split: test
|
1188 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
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1189 |
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metrics:
|
1190 |
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- type: accuracy
|
1191 |
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value: 43.470000000000006
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1192 |
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- type: f1
|
1193 |
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value: 39.27142511079909
|
1194 |
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- task:
|
1195 |
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type: Retrieval
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1196 |
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dataset:
|
1197 |
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type: fiqa
|
1198 |
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name: MTEB FiQA2018
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1199 |
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config: default
|
1200 |
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split: test
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1201 |
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revision: None
|
1202 |
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metrics:
|
1203 |
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- type: map_at_1
|
1204 |
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value: 14.071
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1205 |
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- type: map_at_10
|
1206 |
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value: 23.455000000000002
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1207 |
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|
1208 |
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1209 |
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- type: map_at_1000
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1210 |
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value: 25.55
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1211 |
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|
1212 |
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value: 20.164
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1213 |
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1214 |
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value: 21.654999999999998
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1215 |
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1216 |
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value: 28.395
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1217 |
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1218 |
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value: 37.21
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1219 |
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1220 |
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value: 38.086999999999996
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1221 |
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1222 |
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value: 38.145
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1223 |
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1224 |
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value: 34.336
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1225 |
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1226 |
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value: 35.795
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1227 |
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1228 |
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value: 28.395
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1229 |
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1230 |
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value: 30.595
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1231 |
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1232 |
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value: 37.885000000000005
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1233 |
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1234 |
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value: 41.55
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1235 |
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1236 |
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1237 |
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1238 |
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value: 27.528999999999996
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1239 |
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1240 |
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value: 28.395
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1241 |
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|
1242 |
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value: 8.92
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1243 |
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|
1244 |
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value: 1.6389999999999998
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1245 |
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1246 |
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value: 0.22999999999999998
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1247 |
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|
1248 |
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value: 18.004
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1249 |
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- type: precision_at_5
|
1250 |
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value: 13.302
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1251 |
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|
1252 |
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value: 14.071
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1253 |
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|
1254 |
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value: 37.635000000000005
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1255 |
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1256 |
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1257 |
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1258 |
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1259 |
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|
1260 |
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1261 |
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- type: recall_at_5
|
1262 |
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value: 28.621999999999996
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1263 |
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- task:
|
1264 |
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type: Classification
|
1265 |
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dataset:
|
1266 |
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type: mteb/imdb
|
1267 |
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name: MTEB ImdbClassification
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1268 |
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config: default
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1269 |
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split: test
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1270 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1271 |
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metrics:
|
1272 |
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- type: accuracy
|
1273 |
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value: 67.2992
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1274 |
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- type: ap
|
1275 |
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1276 |
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1277 |
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1278 |
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|
1279 |
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1280 |
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dataset:
|
1281 |
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type: mteb/mtop_domain
|
1282 |
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name: MTEB MTOPDomainClassification (en)
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1283 |
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config: en
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1284 |
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split: test
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1285 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1286 |
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metrics:
|
1287 |
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- type: accuracy
|
1288 |
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value: 91.81714546283631
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1289 |
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- type: f1
|
1290 |
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value: 91.67516531750526
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1291 |
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- task:
|
1292 |
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|
1293 |
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dataset:
|
1294 |
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type: mteb/mtop_intent
|
1295 |
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name: MTEB MTOPIntentClassification (en)
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1296 |
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config: en
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1297 |
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1298 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1299 |
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metrics:
|
1300 |
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- type: accuracy
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1301 |
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value: 74.69904240766073
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1302 |
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- type: f1
|
1303 |
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value: 57.9559746458099
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1304 |
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- task:
|
1305 |
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type: Classification
|
1306 |
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dataset:
|
1307 |
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type: mteb/amazon_massive_intent
|
1308 |
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name: MTEB MassiveIntentClassification (en)
|
1309 |
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config: en
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1310 |
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1311 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1312 |
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metrics:
|
1313 |
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1314 |
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value: 71.76866173503699
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1315 |
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|
1316 |
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1317 |
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- task:
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1318 |
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1319 |
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dataset:
|
1320 |
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type: mteb/amazon_massive_scenario
|
1321 |
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name: MTEB MassiveScenarioClassification (en)
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1322 |
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config: en
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1323 |
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split: test
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1324 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1325 |
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metrics:
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1326 |
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1327 |
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1328 |
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- type: f1
|
1329 |
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value: 77.66496420028315
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1330 |
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- task:
|
1331 |
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type: Clustering
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1332 |
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dataset:
|
1333 |
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type: mteb/medrxiv-clustering-p2p
|
1334 |
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name: MTEB MedrxivClusteringP2P
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1335 |
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1336 |
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1337 |
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1338 |
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metrics:
|
1339 |
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1340 |
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value: 36.5297446116069
|
1341 |
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- task:
|
1342 |
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|
1343 |
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dataset:
|
1344 |
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type: mteb/medrxiv-clustering-s2s
|
1345 |
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name: MTEB MedrxivClusteringS2S
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1346 |
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1347 |
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1348 |
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1349 |
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metrics:
|
1350 |
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|
1351 |
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value: 32.93068854285488
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1352 |
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- task:
|
1353 |
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1354 |
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dataset:
|
1355 |
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type: nfcorpus
|
1356 |
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name: MTEB NFCorpus
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1357 |
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config: default
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1358 |
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split: test
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1359 |
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revision: None
|
1360 |
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metrics:
|
1361 |
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|
1362 |
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value: 3.005
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1363 |
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1364 |
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value: 8.125
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1365 |
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1366 |
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1367 |
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1368 |
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1369 |
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1370 |
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1371 |
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1372 |
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1373 |
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1374 |
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1375 |
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1376 |
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1377 |
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1378 |
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1379 |
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1380 |
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1381 |
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1382 |
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value: 41.589
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1383 |
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1384 |
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1385 |
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1386 |
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value: 31.889
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1387 |
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1388 |
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1389 |
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1390 |
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value: 26.191
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1391 |
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1392 |
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1393 |
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1394 |
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value: 29.625
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1395 |
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1396 |
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value: 28.588
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1397 |
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1398 |
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value: 33.745999999999995
|
1399 |
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- type: precision_at_10
|
1400 |
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value: 21.146
|
1401 |
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- type: precision_at_100
|
1402 |
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value: 7.736999999999999
|
1403 |
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- type: precision_at_1000
|
1404 |
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value: 2.08
|
1405 |
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- type: precision_at_3
|
1406 |
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value: 29.102
|
1407 |
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- type: precision_at_5
|
1408 |
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value: 26.316
|
1409 |
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- type: recall_at_1
|
1410 |
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value: 3.005
|
1411 |
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- type: recall_at_10
|
1412 |
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value: 12.29
|
1413 |
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- type: recall_at_100
|
1414 |
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value: 30.06
|
1415 |
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- type: recall_at_1000
|
1416 |
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value: 63.148
|
1417 |
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- type: recall_at_3
|
1418 |
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value: 6.587
|
1419 |
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- type: recall_at_5
|
1420 |
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value: 9.095
|
1421 |
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- task:
|
1422 |
+
type: Retrieval
|
1423 |
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dataset:
|
1424 |
+
type: nq
|
1425 |
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name: MTEB NQ
|
1426 |
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config: default
|
1427 |
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split: test
|
1428 |
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revision: None
|
1429 |
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metrics:
|
1430 |
+
- type: map_at_1
|
1431 |
+
value: 19.839000000000002
|
1432 |
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- type: map_at_10
|
1433 |
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value: 31.424999999999997
|
1434 |
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- type: map_at_100
|
1435 |
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value: 32.641999999999996
|
1436 |
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- type: map_at_1000
|
1437 |
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value: 32.704
|
1438 |
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- type: map_at_3
|
1439 |
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value: 27.742
|
1440 |
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- type: map_at_5
|
1441 |
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value: 29.854999999999997
|
1442 |
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- type: mrr_at_1
|
1443 |
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value: 22.451
|
1444 |
+
- type: mrr_at_10
|
1445 |
+
value: 33.632
|
1446 |
+
- type: mrr_at_100
|
1447 |
+
value: 34.653
|
1448 |
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- type: mrr_at_1000
|
1449 |
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value: 34.699000000000005
|
1450 |
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- type: mrr_at_3
|
1451 |
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value: 30.427
|
1452 |
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- type: mrr_at_5
|
1453 |
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value: 32.263
|
1454 |
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- type: ndcg_at_1
|
1455 |
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value: 22.422
|
1456 |
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- type: ndcg_at_10
|
1457 |
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value: 37.929
|
1458 |
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- type: ndcg_at_100
|
1459 |
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value: 43.667
|
1460 |
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- type: ndcg_at_1000
|
1461 |
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value: 45.231
|
1462 |
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- type: ndcg_at_3
|
1463 |
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value: 30.814999999999998
|
1464 |
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- type: ndcg_at_5
|
1465 |
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value: 34.379
|
1466 |
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- type: precision_at_1
|
1467 |
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value: 22.422
|
1468 |
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- type: precision_at_10
|
1469 |
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value: 6.59
|
1470 |
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- type: precision_at_100
|
1471 |
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value: 0.9860000000000001
|
1472 |
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- type: precision_at_1000
|
1473 |
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value: 0.11399999999999999
|
1474 |
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- type: precision_at_3
|
1475 |
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value: 14.301
|
1476 |
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- type: precision_at_5
|
1477 |
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value: 10.626
|
1478 |
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- type: recall_at_1
|
1479 |
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value: 19.839000000000002
|
1480 |
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- type: recall_at_10
|
1481 |
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value: 55.769999999999996
|
1482 |
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- type: recall_at_100
|
1483 |
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value: 81.733
|
1484 |
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- type: recall_at_1000
|
1485 |
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value: 93.559
|
1486 |
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- type: recall_at_3
|
1487 |
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value: 37.078
|
1488 |
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- type: recall_at_5
|
1489 |
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value: 45.318999999999996
|
1490 |
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- task:
|
1491 |
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type: Retrieval
|
1492 |
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dataset:
|
1493 |
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type: quora
|
1494 |
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name: MTEB QuoraRetrieval
|
1495 |
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config: default
|
1496 |
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split: test
|
1497 |
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revision: None
|
1498 |
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metrics:
|
1499 |
+
- type: map_at_1
|
1500 |
+
value: 67.534
|
1501 |
+
- type: map_at_10
|
1502 |
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value: 81.447
|
1503 |
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- type: map_at_100
|
1504 |
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value: 82.15299999999999
|
1505 |
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- type: map_at_1000
|
1506 |
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value: 82.172
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1507 |
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- type: map_at_3
|
1508 |
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value: 78.408
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1509 |
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- type: map_at_5
|
1510 |
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value: 80.264
|
1511 |
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- type: mrr_at_1
|
1512 |
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value: 77.75999999999999
|
1513 |
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- type: mrr_at_10
|
1514 |
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value: 84.602
|
1515 |
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- type: mrr_at_100
|
1516 |
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value: 84.762
|
1517 |
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- type: mrr_at_1000
|
1518 |
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value: 84.764
|
1519 |
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- type: mrr_at_3
|
1520 |
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value: 83.488
|
1521 |
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- type: mrr_at_5
|
1522 |
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value: 84.21600000000001
|
1523 |
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- type: ndcg_at_1
|
1524 |
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value: 77.79
|
1525 |
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- type: ndcg_at_10
|
1526 |
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value: 85.55199999999999
|
1527 |
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- type: ndcg_at_100
|
1528 |
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value: 87.104
|
1529 |
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- type: ndcg_at_1000
|
1530 |
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value: 87.259
|
1531 |
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- type: ndcg_at_3
|
1532 |
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value: 82.396
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1533 |
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- type: ndcg_at_5
|
1534 |
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value: 84.065
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1535 |
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- type: precision_at_1
|
1536 |
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value: 77.79
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1537 |
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- type: precision_at_10
|
1538 |
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value: 13.103000000000002
|
1539 |
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- type: precision_at_100
|
1540 |
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value: 1.5190000000000001
|
1541 |
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- type: precision_at_1000
|
1542 |
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value: 0.156
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1543 |
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- type: precision_at_3
|
1544 |
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value: 36.153
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1545 |
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- type: precision_at_5
|
1546 |
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value: 23.854
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1547 |
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- type: recall_at_1
|
1548 |
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value: 67.534
|
1549 |
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- type: recall_at_10
|
1550 |
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value: 93.57
|
1551 |
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- type: recall_at_100
|
1552 |
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value: 99.10799999999999
|
1553 |
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- type: recall_at_1000
|
1554 |
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value: 99.911
|
1555 |
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- type: recall_at_3
|
1556 |
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value: 84.565
|
1557 |
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- type: recall_at_5
|
1558 |
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value: 89.242
|
1559 |
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- task:
|
1560 |
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type: Clustering
|
1561 |
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dataset:
|
1562 |
+
type: mteb/reddit-clustering
|
1563 |
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name: MTEB RedditClustering
|
1564 |
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config: default
|
1565 |
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split: test
|
1566 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1567 |
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metrics:
|
1568 |
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- type: v_measure
|
1569 |
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value: 50.692859418431055
|
1570 |
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- task:
|
1571 |
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type: Clustering
|
1572 |
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dataset:
|
1573 |
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type: mteb/reddit-clustering-p2p
|
1574 |
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name: MTEB RedditClusteringP2P
|
1575 |
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config: default
|
1576 |
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split: test
|
1577 |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16
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1578 |
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metrics:
|
1579 |
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- type: v_measure
|
1580 |
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value: 54.60918566392905
|
1581 |
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- task:
|
1582 |
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type: Retrieval
|
1583 |
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dataset:
|
1584 |
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type: scidocs
|
1585 |
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name: MTEB SCIDOCS
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1586 |
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config: default
|
1587 |
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split: test
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1588 |
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revision: None
|
1589 |
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metrics:
|
1590 |
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- type: map_at_1
|
1591 |
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value: 3.723
|
1592 |
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- type: map_at_10
|
1593 |
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value: 9.524000000000001
|
1594 |
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- type: map_at_100
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1595 |
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value: 11.407
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1596 |
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- type: map_at_1000
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1597 |
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value: 11.721
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1598 |
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- type: map_at_3
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1599 |
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value: 6.678000000000001
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1600 |
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- type: map_at_5
|
1601 |
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value: 7.881
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1602 |
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- type: mrr_at_1
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1603 |
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value: 18.2
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1604 |
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|
1605 |
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value: 28.349999999999998
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1606 |
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- type: mrr_at_100
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1607 |
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value: 29.528
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1608 |
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- type: mrr_at_1000
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1609 |
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value: 29.601
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1610 |
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- type: mrr_at_3
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1611 |
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value: 25.15
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1612 |
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- type: mrr_at_5
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1613 |
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value: 26.765
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1614 |
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- type: ndcg_at_1
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1615 |
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value: 18.2
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1616 |
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- type: ndcg_at_10
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1617 |
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value: 16.603
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1618 |
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- type: ndcg_at_100
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1619 |
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value: 24.331
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1620 |
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- type: ndcg_at_1000
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1621 |
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value: 30.086000000000002
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1622 |
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- type: ndcg_at_3
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1623 |
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value: 15.151
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1624 |
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1625 |
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value: 13.199
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1626 |
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- type: precision_at_1
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1627 |
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value: 18.2
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1628 |
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- type: precision_at_10
|
1629 |
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value: 8.86
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1630 |
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- type: precision_at_100
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1631 |
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value: 2.012
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1632 |
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- type: precision_at_1000
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1633 |
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value: 0.33999999999999997
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1634 |
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- type: precision_at_3
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1635 |
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value: 14.2
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1636 |
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- type: precision_at_5
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1637 |
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value: 11.559999999999999
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1638 |
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- type: recall_at_1
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1639 |
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value: 3.723
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1640 |
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- type: recall_at_10
|
1641 |
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value: 17.965
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1642 |
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- type: recall_at_100
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1643 |
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value: 40.803
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1644 |
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- type: recall_at_1000
|
1645 |
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value: 69.053
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1646 |
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- type: recall_at_3
|
1647 |
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value: 8.633000000000001
|
1648 |
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- type: recall_at_5
|
1649 |
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value: 11.722000000000001
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1650 |
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- task:
|
1651 |
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type: STS
|
1652 |
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dataset:
|
1653 |
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type: mteb/sickr-sts
|
1654 |
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name: MTEB SICK-R
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1655 |
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config: default
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1656 |
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split: test
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1657 |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1658 |
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metrics:
|
1659 |
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- type: cos_sim_pearson
|
1660 |
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value: 85.92797781212799
|
1661 |
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- type: cos_sim_spearman
|
1662 |
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value: 80.91206843308156
|
1663 |
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- type: euclidean_pearson
|
1664 |
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value: 83.13392453336924
|
1665 |
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- type: euclidean_spearman
|
1666 |
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value: 80.80408822887594
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1667 |
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- type: manhattan_pearson
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1668 |
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value: 83.02335189403584
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1669 |
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1670 |
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value: 80.79923937077382
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1671 |
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- task:
|
1672 |
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type: STS
|
1673 |
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dataset:
|
1674 |
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type: mteb/sts12-sts
|
1675 |
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name: MTEB STS12
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1676 |
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|
1677 |
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split: test
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1678 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
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1679 |
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metrics:
|
1680 |
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- type: cos_sim_pearson
|
1681 |
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value: 85.4017983656709
|
1682 |
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- type: cos_sim_spearman
|
1683 |
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value: 76.97735367672956
|
1684 |
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- type: euclidean_pearson
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1685 |
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value: 81.7824234578701
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1686 |
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- type: euclidean_spearman
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1687 |
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value: 75.28260048723786
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1688 |
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- type: manhattan_pearson
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1689 |
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value: 81.38214845806081
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1690 |
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- type: manhattan_spearman
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1691 |
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value: 74.96457943242224
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1692 |
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- task:
|
1693 |
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type: STS
|
1694 |
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dataset:
|
1695 |
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type: mteb/sts13-sts
|
1696 |
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name: MTEB STS13
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1697 |
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|
1698 |
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split: test
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1699 |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
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1700 |
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metrics:
|
1701 |
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- type: cos_sim_pearson
|
1702 |
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value: 81.38943576368895
|
1703 |
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- type: cos_sim_spearman
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1704 |
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value: 82.62953855483207
|
1705 |
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- type: euclidean_pearson
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1706 |
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value: 82.44174445208601
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1707 |
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- type: euclidean_spearman
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1708 |
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value: 82.82393564259752
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1709 |
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- type: manhattan_pearson
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1710 |
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value: 82.0592576486719
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1711 |
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1712 |
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|
1713 |
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- task:
|
1714 |
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type: STS
|
1715 |
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dataset:
|
1716 |
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type: mteb/sts14-sts
|
1717 |
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name: MTEB STS14
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1718 |
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1719 |
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1720 |
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1721 |
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|
1722 |
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1723 |
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value: 81.56920926205309
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1724 |
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1726 |
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- type: euclidean_pearson
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1727 |
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1728 |
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1729 |
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1730 |
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- type: manhattan_pearson
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1731 |
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1732 |
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1733 |
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|
1734 |
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- task:
|
1735 |
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type: STS
|
1736 |
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dataset:
|
1737 |
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|
1738 |
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1739 |
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1740 |
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1741 |
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1742 |
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|
1743 |
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1744 |
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value: 84.70673349392224
|
1745 |
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1747 |
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- type: euclidean_pearson
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1748 |
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1749 |
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1750 |
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1751 |
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- type: manhattan_pearson
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1752 |
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1753 |
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1754 |
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1755 |
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- task:
|
1756 |
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|
1757 |
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dataset:
|
1758 |
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|
1759 |
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1760 |
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1761 |
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1762 |
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1763 |
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|
1764 |
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1765 |
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1766 |
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1767 |
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1768 |
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- type: euclidean_pearson
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1769 |
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|
1770 |
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1771 |
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1772 |
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1774 |
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1776 |
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- task:
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1777 |
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1778 |
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dataset:
|
1779 |
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|
1780 |
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1781 |
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1782 |
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1784 |
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metrics:
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1785 |
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1787 |
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- type: cos_sim_spearman
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1789 |
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1797 |
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- task:
|
1798 |
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type: STS
|
1799 |
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dataset:
|
1800 |
+
type: mteb/sts22-crosslingual-sts
|
1801 |
+
name: MTEB STS22 (en)
|
1802 |
+
config: en
|
1803 |
+
split: test
|
1804 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
1805 |
+
metrics:
|
1806 |
+
- type: cos_sim_pearson
|
1807 |
+
value: 65.92377340266665
|
1808 |
+
- type: cos_sim_spearman
|
1809 |
+
value: 68.25861908141049
|
1810 |
+
- type: euclidean_pearson
|
1811 |
+
value: 67.74046333852377
|
1812 |
+
- type: euclidean_spearman
|
1813 |
+
value: 67.74440638624723
|
1814 |
+
- type: manhattan_pearson
|
1815 |
+
value: 67.72314507899021
|
1816 |
+
- type: manhattan_spearman
|
1817 |
+
value: 67.58993746063668
|
1818 |
+
- task:
|
1819 |
+
type: STS
|
1820 |
+
dataset:
|
1821 |
+
type: mteb/stsbenchmark-sts
|
1822 |
+
name: MTEB STSBenchmark
|
1823 |
+
config: default
|
1824 |
+
split: test
|
1825 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
1826 |
+
metrics:
|
1827 |
+
- type: cos_sim_pearson
|
1828 |
+
value: 84.01280176574436
|
1829 |
+
- type: cos_sim_spearman
|
1830 |
+
value: 84.2021805427655
|
1831 |
+
- type: euclidean_pearson
|
1832 |
+
value: 85.25937079924432
|
1833 |
+
- type: euclidean_spearman
|
1834 |
+
value: 84.7692260813728
|
1835 |
+
- type: manhattan_pearson
|
1836 |
+
value: 85.20370061224156
|
1837 |
+
- type: manhattan_spearman
|
1838 |
+
value: 84.68261435873887
|
1839 |
+
- task:
|
1840 |
+
type: Reranking
|
1841 |
+
dataset:
|
1842 |
+
type: mteb/scidocs-reranking
|
1843 |
+
name: MTEB SciDocsRR
|
1844 |
+
config: default
|
1845 |
+
split: test
|
1846 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
1847 |
+
metrics:
|
1848 |
+
- type: map
|
1849 |
+
value: 79.8274674627466
|
1850 |
+
- type: mrr
|
1851 |
+
value: 93.2766625168586
|
1852 |
+
- task:
|
1853 |
+
type: Retrieval
|
1854 |
+
dataset:
|
1855 |
+
type: scifact
|
1856 |
+
name: MTEB SciFact
|
1857 |
+
config: default
|
1858 |
+
split: test
|
1859 |
+
revision: None
|
1860 |
+
metrics:
|
1861 |
+
- type: map_at_1
|
1862 |
+
value: 44.917
|
1863 |
+
- type: map_at_10
|
1864 |
+
value: 54.809
|
1865 |
+
- type: map_at_100
|
1866 |
+
value: 55.544000000000004
|
1867 |
+
- type: map_at_1000
|
1868 |
+
value: 55.584999999999994
|
1869 |
+
- type: map_at_3
|
1870 |
+
value: 51.274
|
1871 |
+
- type: map_at_5
|
1872 |
+
value: 53.42
|
1873 |
+
- type: mrr_at_1
|
1874 |
+
value: 47.0
|
1875 |
+
- type: mrr_at_10
|
1876 |
+
value: 56.00000000000001
|
1877 |
+
- type: mrr_at_100
|
1878 |
+
value: 56.611
|
1879 |
+
- type: mrr_at_1000
|
1880 |
+
value: 56.647000000000006
|
1881 |
+
- type: mrr_at_3
|
1882 |
+
value: 53.166999999999994
|
1883 |
+
- type: mrr_at_5
|
1884 |
+
value: 54.883
|
1885 |
+
- type: ndcg_at_1
|
1886 |
+
value: 47.0
|
1887 |
+
- type: ndcg_at_10
|
1888 |
+
value: 59.948
|
1889 |
+
- type: ndcg_at_100
|
1890 |
+
value: 63.214999999999996
|
1891 |
+
- type: ndcg_at_1000
|
1892 |
+
value: 64.331
|
1893 |
+
- type: ndcg_at_3
|
1894 |
+
value: 53.690000000000005
|
1895 |
+
- type: ndcg_at_5
|
1896 |
+
value: 56.99999999999999
|
1897 |
+
- type: precision_at_1
|
1898 |
+
value: 47.0
|
1899 |
+
- type: precision_at_10
|
1900 |
+
value: 8.433
|
1901 |
+
- type: precision_at_100
|
1902 |
+
value: 1.0170000000000001
|
1903 |
+
- type: precision_at_1000
|
1904 |
+
value: 0.11100000000000002
|
1905 |
+
- type: precision_at_3
|
1906 |
+
value: 21.0
|
1907 |
+
- type: precision_at_5
|
1908 |
+
value: 14.667
|
1909 |
+
- type: recall_at_1
|
1910 |
+
value: 44.917
|
1911 |
+
- type: recall_at_10
|
1912 |
+
value: 74.483
|
1913 |
+
- type: recall_at_100
|
1914 |
+
value: 89.1
|
1915 |
+
- type: recall_at_1000
|
1916 |
+
value: 98.0
|
1917 |
+
- type: recall_at_3
|
1918 |
+
value: 58.15
|
1919 |
+
- type: recall_at_5
|
1920 |
+
value: 66.033
|
1921 |
+
- task:
|
1922 |
+
type: PairClassification
|
1923 |
+
dataset:
|
1924 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
1925 |
+
name: MTEB SprintDuplicateQuestions
|
1926 |
+
config: default
|
1927 |
+
split: test
|
1928 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
1929 |
+
metrics:
|
1930 |
+
- type: cos_sim_accuracy
|
1931 |
+
value: 99.66534653465347
|
1932 |
+
- type: cos_sim_ap
|
1933 |
+
value: 90.67883265196161
|
1934 |
+
- type: cos_sim_f1
|
1935 |
+
value: 82.81327389796928
|
1936 |
+
- type: cos_sim_precision
|
1937 |
+
value: 82.04121687929342
|
1938 |
+
- type: cos_sim_recall
|
1939 |
+
value: 83.6
|
1940 |
+
- type: dot_accuracy
|
1941 |
+
value: 99.6009900990099
|
1942 |
+
- type: dot_ap
|
1943 |
+
value: 85.37859661864812
|
1944 |
+
- type: dot_f1
|
1945 |
+
value: 79.68285431119922
|
1946 |
+
- type: dot_precision
|
1947 |
+
value: 78.97838899803537
|
1948 |
+
- type: dot_recall
|
1949 |
+
value: 80.4
|
1950 |
+
- type: euclidean_accuracy
|
1951 |
+
value: 99.66435643564357
|
1952 |
+
- type: euclidean_ap
|
1953 |
+
value: 90.28983244955693
|
1954 |
+
- type: euclidean_f1
|
1955 |
+
value: 82.47925817471938
|
1956 |
+
- type: euclidean_precision
|
1957 |
+
value: 80.55290753098188
|
1958 |
+
- type: euclidean_recall
|
1959 |
+
value: 84.5
|
1960 |
+
- type: manhattan_accuracy
|
1961 |
+
value: 99.65247524752475
|
1962 |
+
- type: manhattan_ap
|
1963 |
+
value: 89.75455639322132
|
1964 |
+
- type: manhattan_f1
|
1965 |
+
value: 81.63682864450128
|
1966 |
+
- type: manhattan_precision
|
1967 |
+
value: 83.56020942408377
|
1968 |
+
- type: manhattan_recall
|
1969 |
+
value: 79.80000000000001
|
1970 |
+
- type: max_accuracy
|
1971 |
+
value: 99.66534653465347
|
1972 |
+
- type: max_ap
|
1973 |
+
value: 90.67883265196161
|
1974 |
+
- type: max_f1
|
1975 |
+
value: 82.81327389796928
|
1976 |
+
- task:
|
1977 |
+
type: Clustering
|
1978 |
+
dataset:
|
1979 |
+
type: mteb/stackexchange-clustering
|
1980 |
+
name: MTEB StackExchangeClustering
|
1981 |
+
config: default
|
1982 |
+
split: test
|
1983 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
1984 |
+
metrics:
|
1985 |
+
- type: v_measure
|
1986 |
+
value: 53.295453205851
|
1987 |
+
- task:
|
1988 |
+
type: Clustering
|
1989 |
+
dataset:
|
1990 |
+
type: mteb/stackexchange-clustering-p2p
|
1991 |
+
name: MTEB StackExchangeClusteringP2P
|
1992 |
+
config: default
|
1993 |
+
split: test
|
1994 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
1995 |
+
metrics:
|
1996 |
+
- type: v_measure
|
1997 |
+
value: 32.64179363201445
|
1998 |
+
- task:
|
1999 |
+
type: Reranking
|
2000 |
+
dataset:
|
2001 |
+
type: mteb/stackoverflowdupquestions-reranking
|
2002 |
+
name: MTEB StackOverflowDupQuestions
|
2003 |
+
config: default
|
2004 |
+
split: test
|
2005 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2006 |
+
metrics:
|
2007 |
+
- type: map
|
2008 |
+
value: 47.103383708653894
|
2009 |
+
- type: mrr
|
2010 |
+
value: 47.64253618113912
|
2011 |
+
- task:
|
2012 |
+
type: Summarization
|
2013 |
+
dataset:
|
2014 |
+
type: mteb/summeval
|
2015 |
+
name: MTEB SummEval
|
2016 |
+
config: default
|
2017 |
+
split: test
|
2018 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2019 |
+
metrics:
|
2020 |
+
- type: cos_sim_pearson
|
2021 |
+
value: 30.794109958863856
|
2022 |
+
- type: cos_sim_spearman
|
2023 |
+
value: 32.38893238877061
|
2024 |
+
- type: dot_pearson
|
2025 |
+
value: 25.573206015466006
|
2026 |
+
- type: dot_spearman
|
2027 |
+
value: 26.69770548172811
|
2028 |
+
- task:
|
2029 |
+
type: Retrieval
|
2030 |
+
dataset:
|
2031 |
+
type: trec-covid
|
2032 |
+
name: MTEB TRECCOVID
|
2033 |
+
config: default
|
2034 |
+
split: test
|
2035 |
+
revision: None
|
2036 |
+
metrics:
|
2037 |
+
- type: map_at_1
|
2038 |
+
value: 0.159
|
2039 |
+
- type: map_at_10
|
2040 |
+
value: 0.9979999999999999
|
2041 |
+
- type: map_at_100
|
2042 |
+
value: 5.806
|
2043 |
+
- type: map_at_1000
|
2044 |
+
value: 16.575
|
2045 |
+
- type: map_at_3
|
2046 |
+
value: 0.391
|
2047 |
+
- type: map_at_5
|
2048 |
+
value: 0.596
|
2049 |
+
- type: mrr_at_1
|
2050 |
+
value: 56.00000000000001
|
2051 |
+
- type: mrr_at_10
|
2052 |
+
value: 68.7
|
2053 |
+
- type: mrr_at_100
|
2054 |
+
value: 68.892
|
2055 |
+
- type: mrr_at_1000
|
2056 |
+
value: 68.892
|
2057 |
+
- type: mrr_at_3
|
2058 |
+
value: 65.667
|
2059 |
+
- type: mrr_at_5
|
2060 |
+
value: 68.367
|
2061 |
+
- type: ndcg_at_1
|
2062 |
+
value: 51.0
|
2063 |
+
- type: ndcg_at_10
|
2064 |
+
value: 45.1
|
2065 |
+
- type: ndcg_at_100
|
2066 |
+
value: 36.834
|
2067 |
+
- type: ndcg_at_1000
|
2068 |
+
value: 39.329
|
2069 |
+
- type: ndcg_at_3
|
2070 |
+
value: 49.458
|
2071 |
+
- type: ndcg_at_5
|
2072 |
+
value: 48.177
|
2073 |
+
- type: precision_at_1
|
2074 |
+
value: 56.00000000000001
|
2075 |
+
- type: precision_at_10
|
2076 |
+
value: 47.8
|
2077 |
+
- type: precision_at_100
|
2078 |
+
value: 38.6
|
2079 |
+
- type: precision_at_1000
|
2080 |
+
value: 18.285999999999998
|
2081 |
+
- type: precision_at_3
|
2082 |
+
value: 54.0
|
2083 |
+
- type: precision_at_5
|
2084 |
+
value: 52.400000000000006
|
2085 |
+
- type: recall_at_1
|
2086 |
+
value: 0.159
|
2087 |
+
- type: recall_at_10
|
2088 |
+
value: 1.2510000000000001
|
2089 |
+
- type: recall_at_100
|
2090 |
+
value: 9.237
|
2091 |
+
- type: recall_at_1000
|
2092 |
+
value: 38.984
|
2093 |
+
- type: recall_at_3
|
2094 |
+
value: 0.44
|
2095 |
+
- type: recall_at_5
|
2096 |
+
value: 0.7080000000000001
|
2097 |
+
- task:
|
2098 |
+
type: Retrieval
|
2099 |
+
dataset:
|
2100 |
+
type: webis-touche2020
|
2101 |
+
name: MTEB Touche2020
|
2102 |
+
config: default
|
2103 |
+
split: test
|
2104 |
+
revision: None
|
2105 |
+
metrics:
|
2106 |
+
- type: map_at_1
|
2107 |
+
value: 1.6660000000000001
|
2108 |
+
- type: map_at_10
|
2109 |
+
value: 7.444000000000001
|
2110 |
+
- type: map_at_100
|
2111 |
+
value: 12.078
|
2112 |
+
- type: map_at_1000
|
2113 |
+
value: 13.716999999999999
|
2114 |
+
- type: map_at_3
|
2115 |
+
value: 4.06
|
2116 |
+
- type: map_at_5
|
2117 |
+
value: 5.172000000000001
|
2118 |
+
- type: mrr_at_1
|
2119 |
+
value: 20.408
|
2120 |
+
- type: mrr_at_10
|
2121 |
+
value: 33.547
|
2122 |
+
- type: mrr_at_100
|
2123 |
+
value: 35.281
|
2124 |
+
- type: mrr_at_1000
|
2125 |
+
value: 35.289
|
2126 |
+
- type: mrr_at_3
|
2127 |
+
value: 29.252
|
2128 |
+
- type: mrr_at_5
|
2129 |
+
value: 31.19
|
2130 |
+
- type: ndcg_at_1
|
2131 |
+
value: 18.367
|
2132 |
+
- type: ndcg_at_10
|
2133 |
+
value: 18.848000000000003
|
2134 |
+
- type: ndcg_at_100
|
2135 |
+
value: 29.938
|
2136 |
+
- type: ndcg_at_1000
|
2137 |
+
value: 42.792
|
2138 |
+
- type: ndcg_at_3
|
2139 |
+
value: 20.005
|
2140 |
+
- type: ndcg_at_5
|
2141 |
+
value: 18.617
|
2142 |
+
- type: precision_at_1
|
2143 |
+
value: 20.408
|
2144 |
+
- type: precision_at_10
|
2145 |
+
value: 17.143
|
2146 |
+
- type: precision_at_100
|
2147 |
+
value: 6.571000000000001
|
2148 |
+
- type: precision_at_1000
|
2149 |
+
value: 1.492
|
2150 |
+
- type: precision_at_3
|
2151 |
+
value: 21.088
|
2152 |
+
- type: precision_at_5
|
2153 |
+
value: 18.776
|
2154 |
+
- type: recall_at_1
|
2155 |
+
value: 1.6660000000000001
|
2156 |
+
- type: recall_at_10
|
2157 |
+
value: 12.736
|
2158 |
+
- type: recall_at_100
|
2159 |
+
value: 41.485
|
2160 |
+
- type: recall_at_1000
|
2161 |
+
value: 80.301
|
2162 |
+
- type: recall_at_3
|
2163 |
+
value: 5.137
|
2164 |
+
- type: recall_at_5
|
2165 |
+
value: 7.317
|
2166 |
+
- task:
|
2167 |
+
type: Classification
|
2168 |
+
dataset:
|
2169 |
+
type: mteb/toxic_conversations_50k
|
2170 |
+
name: MTEB ToxicConversationsClassification
|
2171 |
+
config: default
|
2172 |
+
split: test
|
2173 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2174 |
+
metrics:
|
2175 |
+
- type: accuracy
|
2176 |
+
value: 67.4808
|
2177 |
+
- type: ap
|
2178 |
+
value: 12.474767995994732
|
2179 |
+
- type: f1
|
2180 |
+
value: 51.7199877262739
|
2181 |
+
- task:
|
2182 |
+
type: Classification
|
2183 |
+
dataset:
|
2184 |
+
type: mteb/tweet_sentiment_extraction
|
2185 |
+
name: MTEB TweetSentimentExtractionClassification
|
2186 |
+
config: default
|
2187 |
+
split: test
|
2188 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2189 |
+
metrics:
|
2190 |
+
- type: accuracy
|
2191 |
+
value: 55.62252405206565
|
2192 |
+
- type: f1
|
2193 |
+
value: 55.87133173318741
|
2194 |
+
- task:
|
2195 |
+
type: Clustering
|
2196 |
+
dataset:
|
2197 |
+
type: mteb/twentynewsgroups-clustering
|
2198 |
+
name: MTEB TwentyNewsgroupsClustering
|
2199 |
+
config: default
|
2200 |
+
split: test
|
2201 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2202 |
+
metrics:
|
2203 |
+
- type: v_measure
|
2204 |
+
value: 45.75265994155206
|
2205 |
+
- task:
|
2206 |
+
type: PairClassification
|
2207 |
+
dataset:
|
2208 |
+
type: mteb/twittersemeval2015-pairclassification
|
2209 |
+
name: MTEB TwitterSemEval2015
|
2210 |
+
config: default
|
2211 |
+
split: test
|
2212 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2213 |
+
metrics:
|
2214 |
+
- type: cos_sim_accuracy
|
2215 |
+
value: 84.16284198605233
|
2216 |
+
- type: cos_sim_ap
|
2217 |
+
value: 67.7713341907894
|
2218 |
+
- type: cos_sim_f1
|
2219 |
+
value: 63.007767732076914
|
2220 |
+
- type: cos_sim_precision
|
2221 |
+
value: 60.89096726556732
|
2222 |
+
- type: cos_sim_recall
|
2223 |
+
value: 65.27704485488127
|
2224 |
+
- type: dot_accuracy
|
2225 |
+
value: 80.60439887941826
|
2226 |
+
- type: dot_ap
|
2227 |
+
value: 55.17279708911177
|
2228 |
+
- type: dot_f1
|
2229 |
+
value: 55.023250784038055
|
2230 |
+
- type: dot_precision
|
2231 |
+
value: 46.619021440351844
|
2232 |
+
- type: dot_recall
|
2233 |
+
value: 67.12401055408971
|
2234 |
+
- type: euclidean_accuracy
|
2235 |
+
value: 84.75889610776659
|
2236 |
+
- type: euclidean_ap
|
2237 |
+
value: 69.339283557053
|
2238 |
+
- type: euclidean_f1
|
2239 |
+
value: 64.72887151929653
|
2240 |
+
- type: euclidean_precision
|
2241 |
+
value: 60.254661209640744
|
2242 |
+
- type: euclidean_recall
|
2243 |
+
value: 69.92084432717678
|
2244 |
+
- type: manhattan_accuracy
|
2245 |
+
value: 84.84234368480658
|
2246 |
+
- type: manhattan_ap
|
2247 |
+
value: 69.50781739580388
|
2248 |
+
- type: manhattan_f1
|
2249 |
+
value: 64.78766430738119
|
2250 |
+
- type: manhattan_precision
|
2251 |
+
value: 62.17855409995148
|
2252 |
+
- type: manhattan_recall
|
2253 |
+
value: 67.62532981530343
|
2254 |
+
- type: max_accuracy
|
2255 |
+
value: 84.84234368480658
|
2256 |
+
- type: max_ap
|
2257 |
+
value: 69.50781739580388
|
2258 |
+
- type: max_f1
|
2259 |
+
value: 64.78766430738119
|
2260 |
+
- task:
|
2261 |
+
type: PairClassification
|
2262 |
+
dataset:
|
2263 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2264 |
+
name: MTEB TwitterURLCorpus
|
2265 |
+
config: default
|
2266 |
+
split: test
|
2267 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2268 |
+
metrics:
|
2269 |
+
- type: cos_sim_accuracy
|
2270 |
+
value: 88.46198626149726
|
2271 |
+
- type: cos_sim_ap
|
2272 |
+
value: 84.64910523561979
|
2273 |
+
- type: cos_sim_f1
|
2274 |
+
value: 77.18601251827143
|
2275 |
+
- type: cos_sim_precision
|
2276 |
+
value: 75.19900679179142
|
2277 |
+
- type: cos_sim_recall
|
2278 |
+
value: 79.28087465352634
|
2279 |
+
- type: dot_accuracy
|
2280 |
+
value: 86.79512554818179
|
2281 |
+
- type: dot_ap
|
2282 |
+
value: 80.43209362097343
|
2283 |
+
- type: dot_f1
|
2284 |
+
value: 74.18943791589976
|
2285 |
+
- type: dot_precision
|
2286 |
+
value: 68.65828092243187
|
2287 |
+
- type: dot_recall
|
2288 |
+
value: 80.68986757006468
|
2289 |
+
- type: euclidean_accuracy
|
2290 |
+
value: 88.2368921488726
|
2291 |
+
- type: euclidean_ap
|
2292 |
+
value: 84.27906162916011
|
2293 |
+
- type: euclidean_f1
|
2294 |
+
value: 76.62216238453198
|
2295 |
+
- type: euclidean_precision
|
2296 |
+
value: 74.49640026179914
|
2297 |
+
- type: euclidean_recall
|
2298 |
+
value: 78.87280566676932
|
2299 |
+
- type: manhattan_accuracy
|
2300 |
+
value: 88.29122521054062
|
2301 |
+
- type: manhattan_ap
|
2302 |
+
value: 84.2549146077175
|
2303 |
+
- type: manhattan_f1
|
2304 |
+
value: 76.60077590984667
|
2305 |
+
- type: manhattan_precision
|
2306 |
+
value: 73.63784897350287
|
2307 |
+
- type: manhattan_recall
|
2308 |
+
value: 79.81213427779488
|
2309 |
+
- type: max_accuracy
|
2310 |
+
value: 88.46198626149726
|
2311 |
+
- type: max_ap
|
2312 |
+
value: 84.64910523561979
|
2313 |
+
- type: max_f1
|
2314 |
+
value: 77.18601251827143
|
2315 |
---
|
2316 |
|
2317 |
# embedder-100p
|