Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results
multi-train
commited on
Commit
•
7269a36
1
Parent(s):
ba64f27
Update README.md
Browse files
README.md
CHANGED
@@ -25,6 +25,2502 @@ tags:
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- text-evaluation
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26 |
- prompt-retrieval
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- text-reranking
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28 |
---
|
29 |
|
30 |
# hkunlp/instructor-large
|
|
|
25 |
- text-evaluation
|
26 |
- prompt-retrieval
|
27 |
- text-reranking
|
28 |
+
- mteb
|
29 |
+
model-index:
|
30 |
+
- name: replicate-1227-large-full
|
31 |
+
results:
|
32 |
+
- task:
|
33 |
+
type: Classification
|
34 |
+
dataset:
|
35 |
+
type: mteb/amazon_counterfactual
|
36 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
37 |
+
config: en
|
38 |
+
split: test
|
39 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
40 |
+
metrics:
|
41 |
+
- type: accuracy
|
42 |
+
value: 88.13432835820896
|
43 |
+
- type: ap
|
44 |
+
value: 59.298209334395665
|
45 |
+
- type: f1
|
46 |
+
value: 83.31769058643586
|
47 |
+
- task:
|
48 |
+
type: Classification
|
49 |
+
dataset:
|
50 |
+
type: mteb/amazon_polarity
|
51 |
+
name: MTEB AmazonPolarityClassification
|
52 |
+
config: default
|
53 |
+
split: test
|
54 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
55 |
+
metrics:
|
56 |
+
- type: accuracy
|
57 |
+
value: 91.526375
|
58 |
+
- type: ap
|
59 |
+
value: 88.16327709705504
|
60 |
+
- type: f1
|
61 |
+
value: 91.51095801287843
|
62 |
+
- task:
|
63 |
+
type: Classification
|
64 |
+
dataset:
|
65 |
+
type: mteb/amazon_reviews_multi
|
66 |
+
name: MTEB AmazonReviewsClassification (en)
|
67 |
+
config: en
|
68 |
+
split: test
|
69 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
70 |
+
metrics:
|
71 |
+
- type: accuracy
|
72 |
+
value: 47.856
|
73 |
+
- type: f1
|
74 |
+
value: 45.41490917650942
|
75 |
+
- task:
|
76 |
+
type: Retrieval
|
77 |
+
dataset:
|
78 |
+
type: arguana
|
79 |
+
name: MTEB ArguAna
|
80 |
+
config: default
|
81 |
+
split: test
|
82 |
+
revision: None
|
83 |
+
metrics:
|
84 |
+
- type: map_at_1
|
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revision: None
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304 |
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513 |
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value: 25.185999999999996
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514 |
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515 |
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value: 26.533
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516 |
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517 |
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value: 26.657999999999998
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518 |
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|
519 |
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value: 22.201999999999998
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520 |
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521 |
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value: 23.923
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522 |
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523 |
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value: 20.522000000000002
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524 |
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525 |
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value: 29.522
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526 |
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527 |
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value: 30.644
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528 |
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|
529 |
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value: 30.713
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530 |
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- type: mrr_at_3
|
531 |
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value: 26.679000000000002
|
532 |
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|
533 |
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value: 28.483000000000004
|
534 |
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|
535 |
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value: 20.522000000000002
|
536 |
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|
537 |
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value: 30.656
|
538 |
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- type: ndcg_at_100
|
539 |
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value: 36.864999999999995
|
540 |
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- type: ndcg_at_1000
|
541 |
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value: 39.675
|
542 |
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|
543 |
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value: 25.319000000000003
|
544 |
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|
545 |
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value: 27.992
|
546 |
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|
547 |
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value: 20.522000000000002
|
548 |
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- type: precision_at_10
|
549 |
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value: 5.795999999999999
|
550 |
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|
551 |
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value: 1.027
|
552 |
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|
553 |
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value: 0.13999999999999999
|
554 |
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- type: precision_at_3
|
555 |
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value: 12.396
|
556 |
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- type: precision_at_5
|
557 |
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value: 9.328
|
558 |
+
- type: recall_at_1
|
559 |
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value: 16.407
|
560 |
+
- type: recall_at_10
|
561 |
+
value: 43.164
|
562 |
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- type: recall_at_100
|
563 |
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value: 69.695
|
564 |
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- type: recall_at_1000
|
565 |
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value: 89.41900000000001
|
566 |
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- type: recall_at_3
|
567 |
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value: 28.634999999999998
|
568 |
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- type: recall_at_5
|
569 |
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value: 35.308
|
570 |
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- task:
|
571 |
+
type: Retrieval
|
572 |
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dataset:
|
573 |
+
type: BeIR/cqadupstack
|
574 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
575 |
+
config: default
|
576 |
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split: test
|
577 |
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revision: None
|
578 |
+
metrics:
|
579 |
+
- type: map_at_1
|
580 |
+
value: 30.473
|
581 |
+
- type: map_at_10
|
582 |
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value: 41.676
|
583 |
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- type: map_at_100
|
584 |
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value: 43.120999999999995
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585 |
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- type: map_at_1000
|
586 |
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value: 43.230000000000004
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587 |
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|
588 |
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value: 38.306000000000004
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589 |
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- type: map_at_5
|
590 |
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value: 40.355999999999995
|
591 |
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|
592 |
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value: 37.536
|
593 |
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|
594 |
+
value: 47.643
|
595 |
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- type: mrr_at_100
|
596 |
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value: 48.508
|
597 |
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- type: mrr_at_1000
|
598 |
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value: 48.551
|
599 |
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- type: mrr_at_3
|
600 |
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value: 45.348
|
601 |
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- type: mrr_at_5
|
602 |
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value: 46.744
|
603 |
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- type: ndcg_at_1
|
604 |
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value: 37.536
|
605 |
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- type: ndcg_at_10
|
606 |
+
value: 47.823
|
607 |
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- type: ndcg_at_100
|
608 |
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value: 53.395
|
609 |
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- type: ndcg_at_1000
|
610 |
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value: 55.271
|
611 |
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- type: ndcg_at_3
|
612 |
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value: 42.768
|
613 |
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- type: ndcg_at_5
|
614 |
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value: 45.373000000000005
|
615 |
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- type: precision_at_1
|
616 |
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value: 37.536
|
617 |
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- type: precision_at_10
|
618 |
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value: 8.681
|
619 |
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- type: precision_at_100
|
620 |
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value: 1.34
|
621 |
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- type: precision_at_1000
|
622 |
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value: 0.165
|
623 |
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- type: precision_at_3
|
624 |
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value: 20.468
|
625 |
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- type: precision_at_5
|
626 |
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value: 14.495
|
627 |
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- type: recall_at_1
|
628 |
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value: 30.473
|
629 |
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- type: recall_at_10
|
630 |
+
value: 60.092999999999996
|
631 |
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- type: recall_at_100
|
632 |
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value: 82.733
|
633 |
+
- type: recall_at_1000
|
634 |
+
value: 94.875
|
635 |
+
- type: recall_at_3
|
636 |
+
value: 45.734
|
637 |
+
- type: recall_at_5
|
638 |
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value: 52.691
|
639 |
+
- task:
|
640 |
+
type: Retrieval
|
641 |
+
dataset:
|
642 |
+
type: BeIR/cqadupstack
|
643 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
644 |
+
config: default
|
645 |
+
split: test
|
646 |
+
revision: None
|
647 |
+
metrics:
|
648 |
+
- type: map_at_1
|
649 |
+
value: 29.976000000000003
|
650 |
+
- type: map_at_10
|
651 |
+
value: 41.097
|
652 |
+
- type: map_at_100
|
653 |
+
value: 42.547000000000004
|
654 |
+
- type: map_at_1000
|
655 |
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value: 42.659000000000006
|
656 |
+
- type: map_at_3
|
657 |
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value: 37.251
|
658 |
+
- type: map_at_5
|
659 |
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value: 39.493
|
660 |
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- type: mrr_at_1
|
661 |
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value: 37.557
|
662 |
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- type: mrr_at_10
|
663 |
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value: 46.605000000000004
|
664 |
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- type: mrr_at_100
|
665 |
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value: 47.487
|
666 |
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- type: mrr_at_1000
|
667 |
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value: 47.54
|
668 |
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- type: mrr_at_3
|
669 |
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value: 43.721
|
670 |
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- type: mrr_at_5
|
671 |
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value: 45.411
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672 |
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- type: ndcg_at_1
|
673 |
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value: 37.557
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674 |
+
- type: ndcg_at_10
|
675 |
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value: 47.449000000000005
|
676 |
+
- type: ndcg_at_100
|
677 |
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value: 53.052
|
678 |
+
- type: ndcg_at_1000
|
679 |
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value: 55.010999999999996
|
680 |
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- type: ndcg_at_3
|
681 |
+
value: 41.439
|
682 |
+
- type: ndcg_at_5
|
683 |
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value: 44.292
|
684 |
+
- type: precision_at_1
|
685 |
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value: 37.557
|
686 |
+
- type: precision_at_10
|
687 |
+
value: 8.847
|
688 |
+
- type: precision_at_100
|
689 |
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value: 1.357
|
690 |
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- type: precision_at_1000
|
691 |
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value: 0.16999999999999998
|
692 |
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- type: precision_at_3
|
693 |
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value: 20.091
|
694 |
+
- type: precision_at_5
|
695 |
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value: 14.384
|
696 |
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- type: recall_at_1
|
697 |
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value: 29.976000000000003
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698 |
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- type: recall_at_10
|
699 |
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value: 60.99099999999999
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700 |
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- type: recall_at_100
|
701 |
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value: 84.245
|
702 |
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- type: recall_at_1000
|
703 |
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value: 96.97200000000001
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704 |
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- type: recall_at_3
|
705 |
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value: 43.794
|
706 |
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- type: recall_at_5
|
707 |
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value: 51.778999999999996
|
708 |
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- task:
|
709 |
+
type: Retrieval
|
710 |
+
dataset:
|
711 |
+
type: BeIR/cqadupstack
|
712 |
+
name: MTEB CQADupstackRetrieval
|
713 |
+
config: default
|
714 |
+
split: test
|
715 |
+
revision: None
|
716 |
+
metrics:
|
717 |
+
- type: map_at_1
|
718 |
+
value: 28.099166666666665
|
719 |
+
- type: map_at_10
|
720 |
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value: 38.1365
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721 |
+
- type: map_at_100
|
722 |
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value: 39.44491666666667
|
723 |
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|
724 |
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value: 39.55858333333334
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725 |
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|
726 |
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value: 35.03641666666666
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727 |
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|
728 |
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value: 36.79833333333334
|
729 |
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|
730 |
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value: 33.39966666666667
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731 |
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|
732 |
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value: 42.42583333333333
|
733 |
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|
734 |
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value: 43.28575
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735 |
+
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|
736 |
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value: 43.33741666666667
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737 |
+
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|
738 |
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value: 39.94975
|
739 |
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|
740 |
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value: 41.41633333333334
|
741 |
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- type: ndcg_at_1
|
742 |
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value: 33.39966666666667
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743 |
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|
744 |
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value: 43.81741666666667
|
745 |
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|
746 |
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value: 49.08166666666667
|
747 |
+
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|
748 |
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value: 51.121166666666674
|
749 |
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|
750 |
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value: 38.73575
|
751 |
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|
752 |
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value: 41.18158333333333
|
753 |
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|
754 |
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value: 33.39966666666667
|
755 |
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|
756 |
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value: 7.738916666666667
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757 |
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|
758 |
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value: 1.2265833333333331
|
759 |
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|
760 |
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value: 0.15983333333333336
|
761 |
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|
762 |
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value: 17.967416666666665
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763 |
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- type: precision_at_5
|
764 |
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value: 12.78675
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765 |
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- type: recall_at_1
|
766 |
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value: 28.099166666666665
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767 |
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- type: recall_at_10
|
768 |
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value: 56.27049999999999
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769 |
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|
770 |
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value: 78.93291666666667
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771 |
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|
772 |
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value: 92.81608333333334
|
773 |
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|
774 |
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value: 42.09775
|
775 |
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- type: recall_at_5
|
776 |
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value: 48.42533333333334
|
777 |
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- task:
|
778 |
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type: Retrieval
|
779 |
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dataset:
|
780 |
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type: BeIR/cqadupstack
|
781 |
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name: MTEB CQADupstackStatsRetrieval
|
782 |
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config: default
|
783 |
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split: test
|
784 |
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revision: None
|
785 |
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metrics:
|
786 |
+
- type: map_at_1
|
787 |
+
value: 23.663
|
788 |
+
- type: map_at_10
|
789 |
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value: 30.377
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790 |
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|
791 |
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value: 31.426
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792 |
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|
793 |
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value: 31.519000000000002
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794 |
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|
795 |
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796 |
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|
797 |
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value: 29.256999999999998
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798 |
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|
799 |
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value: 26.687
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800 |
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|
801 |
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value: 33.107
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802 |
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|
803 |
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value: 34.055
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804 |
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|
805 |
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value: 34.117999999999995
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806 |
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|
807 |
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value: 31.058000000000003
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808 |
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|
809 |
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value: 32.14
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810 |
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|
811 |
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value: 26.687
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812 |
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|
813 |
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value: 34.615
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814 |
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|
815 |
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value: 39.776
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816 |
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|
817 |
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value: 42.05
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818 |
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|
819 |
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value: 30.322
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820 |
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|
821 |
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value: 32.157000000000004
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822 |
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|
823 |
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value: 26.687
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824 |
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|
825 |
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value: 5.491
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826 |
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|
827 |
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value: 0.877
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828 |
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|
829 |
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value: 0.11499999999999999
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830 |
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|
831 |
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value: 13.139000000000001
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832 |
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|
833 |
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value: 9.049
|
834 |
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- type: recall_at_1
|
835 |
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value: 23.663
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836 |
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|
837 |
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value: 45.035
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838 |
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|
839 |
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value: 68.554
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840 |
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- type: recall_at_1000
|
841 |
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value: 85.077
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842 |
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|
843 |
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value: 32.982
|
844 |
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- type: recall_at_5
|
845 |
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value: 37.688
|
846 |
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- task:
|
847 |
+
type: Retrieval
|
848 |
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dataset:
|
849 |
+
type: BeIR/cqadupstack
|
850 |
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name: MTEB CQADupstackTexRetrieval
|
851 |
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config: default
|
852 |
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split: test
|
853 |
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revision: None
|
854 |
+
metrics:
|
855 |
+
- type: map_at_1
|
856 |
+
value: 17.403
|
857 |
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- type: map_at_10
|
858 |
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value: 25.197000000000003
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859 |
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|
860 |
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value: 26.355
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861 |
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|
862 |
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value: 26.487
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863 |
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|
864 |
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value: 22.733
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865 |
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|
866 |
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value: 24.114
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867 |
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|
868 |
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value: 21.37
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869 |
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|
870 |
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value: 29.091
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871 |
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|
872 |
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value: 30.018
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873 |
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|
874 |
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value: 30.096
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875 |
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|
876 |
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value: 26.887
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877 |
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|
878 |
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value: 28.157
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879 |
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|
880 |
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value: 21.37
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881 |
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|
882 |
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value: 30.026000000000003
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883 |
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|
884 |
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value: 35.416
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885 |
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|
886 |
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value: 38.45
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887 |
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|
888 |
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value: 25.764
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889 |
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|
890 |
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value: 27.742
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891 |
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|
892 |
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value: 21.37
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893 |
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|
894 |
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value: 5.609
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895 |
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|
896 |
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value: 0.9860000000000001
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897 |
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|
898 |
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value: 0.14300000000000002
|
899 |
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|
900 |
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value: 12.423
|
901 |
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- type: precision_at_5
|
902 |
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value: 9.009
|
903 |
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- type: recall_at_1
|
904 |
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value: 17.403
|
905 |
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- type: recall_at_10
|
906 |
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value: 40.573
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907 |
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- type: recall_at_100
|
908 |
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value: 64.818
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909 |
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- type: recall_at_1000
|
910 |
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value: 86.53699999999999
|
911 |
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- type: recall_at_3
|
912 |
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value: 28.493000000000002
|
913 |
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- type: recall_at_5
|
914 |
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value: 33.660000000000004
|
915 |
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- task:
|
916 |
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type: Retrieval
|
917 |
+
dataset:
|
918 |
+
type: BeIR/cqadupstack
|
919 |
+
name: MTEB CQADupstackUnixRetrieval
|
920 |
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config: default
|
921 |
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split: test
|
922 |
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revision: None
|
923 |
+
metrics:
|
924 |
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- type: map_at_1
|
925 |
+
value: 28.639
|
926 |
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- type: map_at_10
|
927 |
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value: 38.951
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928 |
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|
929 |
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value: 40.238
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930 |
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|
931 |
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value: 40.327
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932 |
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|
933 |
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value: 35.842
|
934 |
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- type: map_at_5
|
935 |
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value: 37.617
|
936 |
+
- type: mrr_at_1
|
937 |
+
value: 33.769
|
938 |
+
- type: mrr_at_10
|
939 |
+
value: 43.088
|
940 |
+
- type: mrr_at_100
|
941 |
+
value: 44.03
|
942 |
+
- type: mrr_at_1000
|
943 |
+
value: 44.072
|
944 |
+
- type: mrr_at_3
|
945 |
+
value: 40.656
|
946 |
+
- type: mrr_at_5
|
947 |
+
value: 42.138999999999996
|
948 |
+
- type: ndcg_at_1
|
949 |
+
value: 33.769
|
950 |
+
- type: ndcg_at_10
|
951 |
+
value: 44.676
|
952 |
+
- type: ndcg_at_100
|
953 |
+
value: 50.416000000000004
|
954 |
+
- type: ndcg_at_1000
|
955 |
+
value: 52.227999999999994
|
956 |
+
- type: ndcg_at_3
|
957 |
+
value: 39.494
|
958 |
+
- type: ndcg_at_5
|
959 |
+
value: 42.013
|
960 |
+
- type: precision_at_1
|
961 |
+
value: 33.769
|
962 |
+
- type: precision_at_10
|
963 |
+
value: 7.668
|
964 |
+
- type: precision_at_100
|
965 |
+
value: 1.18
|
966 |
+
- type: precision_at_1000
|
967 |
+
value: 0.145
|
968 |
+
- type: precision_at_3
|
969 |
+
value: 18.221
|
970 |
+
- type: precision_at_5
|
971 |
+
value: 12.966
|
972 |
+
- type: recall_at_1
|
973 |
+
value: 28.639
|
974 |
+
- type: recall_at_10
|
975 |
+
value: 57.687999999999995
|
976 |
+
- type: recall_at_100
|
977 |
+
value: 82.541
|
978 |
+
- type: recall_at_1000
|
979 |
+
value: 94.896
|
980 |
+
- type: recall_at_3
|
981 |
+
value: 43.651
|
982 |
+
- type: recall_at_5
|
983 |
+
value: 49.925999999999995
|
984 |
+
- task:
|
985 |
+
type: Retrieval
|
986 |
+
dataset:
|
987 |
+
type: BeIR/cqadupstack
|
988 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
989 |
+
config: default
|
990 |
+
split: test
|
991 |
+
revision: None
|
992 |
+
metrics:
|
993 |
+
- type: map_at_1
|
994 |
+
value: 29.57
|
995 |
+
- type: map_at_10
|
996 |
+
value: 40.004
|
997 |
+
- type: map_at_100
|
998 |
+
value: 41.75
|
999 |
+
- type: map_at_1000
|
1000 |
+
value: 41.97
|
1001 |
+
- type: map_at_3
|
1002 |
+
value: 36.788
|
1003 |
+
- type: map_at_5
|
1004 |
+
value: 38.671
|
1005 |
+
- type: mrr_at_1
|
1006 |
+
value: 35.375
|
1007 |
+
- type: mrr_at_10
|
1008 |
+
value: 45.121
|
1009 |
+
- type: mrr_at_100
|
1010 |
+
value: 45.994
|
1011 |
+
- type: mrr_at_1000
|
1012 |
+
value: 46.04
|
1013 |
+
- type: mrr_at_3
|
1014 |
+
value: 42.227
|
1015 |
+
- type: mrr_at_5
|
1016 |
+
value: 43.995
|
1017 |
+
- type: ndcg_at_1
|
1018 |
+
value: 35.375
|
1019 |
+
- type: ndcg_at_10
|
1020 |
+
value: 46.392
|
1021 |
+
- type: ndcg_at_100
|
1022 |
+
value: 52.196
|
1023 |
+
- type: ndcg_at_1000
|
1024 |
+
value: 54.274
|
1025 |
+
- type: ndcg_at_3
|
1026 |
+
value: 41.163
|
1027 |
+
- type: ndcg_at_5
|
1028 |
+
value: 43.813
|
1029 |
+
- type: precision_at_1
|
1030 |
+
value: 35.375
|
1031 |
+
- type: precision_at_10
|
1032 |
+
value: 8.676
|
1033 |
+
- type: precision_at_100
|
1034 |
+
value: 1.678
|
1035 |
+
- type: precision_at_1000
|
1036 |
+
value: 0.253
|
1037 |
+
- type: precision_at_3
|
1038 |
+
value: 19.104
|
1039 |
+
- type: precision_at_5
|
1040 |
+
value: 13.913
|
1041 |
+
- type: recall_at_1
|
1042 |
+
value: 29.57
|
1043 |
+
- type: recall_at_10
|
1044 |
+
value: 58.779
|
1045 |
+
- type: recall_at_100
|
1046 |
+
value: 83.337
|
1047 |
+
- type: recall_at_1000
|
1048 |
+
value: 95.979
|
1049 |
+
- type: recall_at_3
|
1050 |
+
value: 44.005
|
1051 |
+
- type: recall_at_5
|
1052 |
+
value: 50.975
|
1053 |
+
- task:
|
1054 |
+
type: Retrieval
|
1055 |
+
dataset:
|
1056 |
+
type: BeIR/cqadupstack
|
1057 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1058 |
+
config: default
|
1059 |
+
split: test
|
1060 |
+
revision: None
|
1061 |
+
metrics:
|
1062 |
+
- type: map_at_1
|
1063 |
+
value: 20.832
|
1064 |
+
- type: map_at_10
|
1065 |
+
value: 29.733999999999998
|
1066 |
+
- type: map_at_100
|
1067 |
+
value: 30.727
|
1068 |
+
- type: map_at_1000
|
1069 |
+
value: 30.843999999999998
|
1070 |
+
- type: map_at_3
|
1071 |
+
value: 26.834999999999997
|
1072 |
+
- type: map_at_5
|
1073 |
+
value: 28.555999999999997
|
1074 |
+
- type: mrr_at_1
|
1075 |
+
value: 22.921
|
1076 |
+
- type: mrr_at_10
|
1077 |
+
value: 31.791999999999998
|
1078 |
+
- type: mrr_at_100
|
1079 |
+
value: 32.666000000000004
|
1080 |
+
- type: mrr_at_1000
|
1081 |
+
value: 32.751999999999995
|
1082 |
+
- type: mrr_at_3
|
1083 |
+
value: 29.144
|
1084 |
+
- type: mrr_at_5
|
1085 |
+
value: 30.622
|
1086 |
+
- type: ndcg_at_1
|
1087 |
+
value: 22.921
|
1088 |
+
- type: ndcg_at_10
|
1089 |
+
value: 34.915
|
1090 |
+
- type: ndcg_at_100
|
1091 |
+
value: 39.744
|
1092 |
+
- type: ndcg_at_1000
|
1093 |
+
value: 42.407000000000004
|
1094 |
+
- type: ndcg_at_3
|
1095 |
+
value: 29.421000000000003
|
1096 |
+
- type: ndcg_at_5
|
1097 |
+
value: 32.211
|
1098 |
+
- type: precision_at_1
|
1099 |
+
value: 22.921
|
1100 |
+
- type: precision_at_10
|
1101 |
+
value: 5.675
|
1102 |
+
- type: precision_at_100
|
1103 |
+
value: 0.872
|
1104 |
+
- type: precision_at_1000
|
1105 |
+
value: 0.121
|
1106 |
+
- type: precision_at_3
|
1107 |
+
value: 12.753999999999998
|
1108 |
+
- type: precision_at_5
|
1109 |
+
value: 9.353
|
1110 |
+
- type: recall_at_1
|
1111 |
+
value: 20.832
|
1112 |
+
- type: recall_at_10
|
1113 |
+
value: 48.795
|
1114 |
+
- type: recall_at_100
|
1115 |
+
value: 70.703
|
1116 |
+
- type: recall_at_1000
|
1117 |
+
value: 90.187
|
1118 |
+
- type: recall_at_3
|
1119 |
+
value: 34.455000000000005
|
1120 |
+
- type: recall_at_5
|
1121 |
+
value: 40.967
|
1122 |
+
- task:
|
1123 |
+
type: Retrieval
|
1124 |
+
dataset:
|
1125 |
+
type: climate-fever
|
1126 |
+
name: MTEB ClimateFEVER
|
1127 |
+
config: default
|
1128 |
+
split: test
|
1129 |
+
revision: None
|
1130 |
+
metrics:
|
1131 |
+
- type: map_at_1
|
1132 |
+
value: 10.334
|
1133 |
+
- type: map_at_10
|
1134 |
+
value: 19.009999999999998
|
1135 |
+
- type: map_at_100
|
1136 |
+
value: 21.129
|
1137 |
+
- type: map_at_1000
|
1138 |
+
value: 21.328
|
1139 |
+
- type: map_at_3
|
1140 |
+
value: 15.152
|
1141 |
+
- type: map_at_5
|
1142 |
+
value: 17.084
|
1143 |
+
- type: mrr_at_1
|
1144 |
+
value: 23.453
|
1145 |
+
- type: mrr_at_10
|
1146 |
+
value: 36.099
|
1147 |
+
- type: mrr_at_100
|
1148 |
+
value: 37.069
|
1149 |
+
- type: mrr_at_1000
|
1150 |
+
value: 37.104
|
1151 |
+
- type: mrr_at_3
|
1152 |
+
value: 32.096000000000004
|
1153 |
+
- type: mrr_at_5
|
1154 |
+
value: 34.451
|
1155 |
+
- type: ndcg_at_1
|
1156 |
+
value: 23.453
|
1157 |
+
- type: ndcg_at_10
|
1158 |
+
value: 27.739000000000004
|
1159 |
+
- type: ndcg_at_100
|
1160 |
+
value: 35.836
|
1161 |
+
- type: ndcg_at_1000
|
1162 |
+
value: 39.242
|
1163 |
+
- type: ndcg_at_3
|
1164 |
+
value: 21.263
|
1165 |
+
- type: ndcg_at_5
|
1166 |
+
value: 23.677
|
1167 |
+
- type: precision_at_1
|
1168 |
+
value: 23.453
|
1169 |
+
- type: precision_at_10
|
1170 |
+
value: 9.199
|
1171 |
+
- type: precision_at_100
|
1172 |
+
value: 1.791
|
1173 |
+
- type: precision_at_1000
|
1174 |
+
value: 0.242
|
1175 |
+
- type: precision_at_3
|
1176 |
+
value: 16.2
|
1177 |
+
- type: precision_at_5
|
1178 |
+
value: 13.147
|
1179 |
+
- type: recall_at_1
|
1180 |
+
value: 10.334
|
1181 |
+
- type: recall_at_10
|
1182 |
+
value: 35.177
|
1183 |
+
- type: recall_at_100
|
1184 |
+
value: 63.009
|
1185 |
+
- type: recall_at_1000
|
1186 |
+
value: 81.938
|
1187 |
+
- type: recall_at_3
|
1188 |
+
value: 19.914
|
1189 |
+
- type: recall_at_5
|
1190 |
+
value: 26.077
|
1191 |
+
- task:
|
1192 |
+
type: Retrieval
|
1193 |
+
dataset:
|
1194 |
+
type: dbpedia-entity
|
1195 |
+
name: MTEB DBPedia
|
1196 |
+
config: default
|
1197 |
+
split: test
|
1198 |
+
revision: None
|
1199 |
+
metrics:
|
1200 |
+
- type: map_at_1
|
1201 |
+
value: 8.212
|
1202 |
+
- type: map_at_10
|
1203 |
+
value: 17.386
|
1204 |
+
- type: map_at_100
|
1205 |
+
value: 24.234
|
1206 |
+
- type: map_at_1000
|
1207 |
+
value: 25.724999999999998
|
1208 |
+
- type: map_at_3
|
1209 |
+
value: 12.727
|
1210 |
+
- type: map_at_5
|
1211 |
+
value: 14.785
|
1212 |
+
- type: mrr_at_1
|
1213 |
+
value: 59.25
|
1214 |
+
- type: mrr_at_10
|
1215 |
+
value: 68.687
|
1216 |
+
- type: mrr_at_100
|
1217 |
+
value: 69.133
|
1218 |
+
- type: mrr_at_1000
|
1219 |
+
value: 69.14099999999999
|
1220 |
+
- type: mrr_at_3
|
1221 |
+
value: 66.917
|
1222 |
+
- type: mrr_at_5
|
1223 |
+
value: 67.742
|
1224 |
+
- type: ndcg_at_1
|
1225 |
+
value: 48.625
|
1226 |
+
- type: ndcg_at_10
|
1227 |
+
value: 36.675999999999995
|
1228 |
+
- type: ndcg_at_100
|
1229 |
+
value: 41.543
|
1230 |
+
- type: ndcg_at_1000
|
1231 |
+
value: 49.241
|
1232 |
+
- type: ndcg_at_3
|
1233 |
+
value: 41.373
|
1234 |
+
- type: ndcg_at_5
|
1235 |
+
value: 38.707
|
1236 |
+
- type: precision_at_1
|
1237 |
+
value: 59.25
|
1238 |
+
- type: precision_at_10
|
1239 |
+
value: 28.525
|
1240 |
+
- type: precision_at_100
|
1241 |
+
value: 9.027000000000001
|
1242 |
+
- type: precision_at_1000
|
1243 |
+
value: 1.8339999999999999
|
1244 |
+
- type: precision_at_3
|
1245 |
+
value: 44.833
|
1246 |
+
- type: precision_at_5
|
1247 |
+
value: 37.35
|
1248 |
+
- type: recall_at_1
|
1249 |
+
value: 8.212
|
1250 |
+
- type: recall_at_10
|
1251 |
+
value: 23.188
|
1252 |
+
- type: recall_at_100
|
1253 |
+
value: 48.613
|
1254 |
+
- type: recall_at_1000
|
1255 |
+
value: 73.093
|
1256 |
+
- type: recall_at_3
|
1257 |
+
value: 14.419
|
1258 |
+
- type: recall_at_5
|
1259 |
+
value: 17.798
|
1260 |
+
- task:
|
1261 |
+
type: Classification
|
1262 |
+
dataset:
|
1263 |
+
type: mteb/emotion
|
1264 |
+
name: MTEB EmotionClassification
|
1265 |
+
config: default
|
1266 |
+
split: test
|
1267 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1268 |
+
metrics:
|
1269 |
+
- type: accuracy
|
1270 |
+
value: 52.725
|
1271 |
+
- type: f1
|
1272 |
+
value: 46.50743309855908
|
1273 |
+
- task:
|
1274 |
+
type: Retrieval
|
1275 |
+
dataset:
|
1276 |
+
type: fever
|
1277 |
+
name: MTEB FEVER
|
1278 |
+
config: default
|
1279 |
+
split: test
|
1280 |
+
revision: None
|
1281 |
+
metrics:
|
1282 |
+
- type: map_at_1
|
1283 |
+
value: 55.086
|
1284 |
+
- type: map_at_10
|
1285 |
+
value: 66.914
|
1286 |
+
- type: map_at_100
|
1287 |
+
value: 67.321
|
1288 |
+
- type: map_at_1000
|
1289 |
+
value: 67.341
|
1290 |
+
- type: map_at_3
|
1291 |
+
value: 64.75800000000001
|
1292 |
+
- type: map_at_5
|
1293 |
+
value: 66.189
|
1294 |
+
- type: mrr_at_1
|
1295 |
+
value: 59.28600000000001
|
1296 |
+
- type: mrr_at_10
|
1297 |
+
value: 71.005
|
1298 |
+
- type: mrr_at_100
|
1299 |
+
value: 71.304
|
1300 |
+
- type: mrr_at_1000
|
1301 |
+
value: 71.313
|
1302 |
+
- type: mrr_at_3
|
1303 |
+
value: 69.037
|
1304 |
+
- type: mrr_at_5
|
1305 |
+
value: 70.35
|
1306 |
+
- type: ndcg_at_1
|
1307 |
+
value: 59.28600000000001
|
1308 |
+
- type: ndcg_at_10
|
1309 |
+
value: 72.695
|
1310 |
+
- type: ndcg_at_100
|
1311 |
+
value: 74.432
|
1312 |
+
- type: ndcg_at_1000
|
1313 |
+
value: 74.868
|
1314 |
+
- type: ndcg_at_3
|
1315 |
+
value: 68.72200000000001
|
1316 |
+
- type: ndcg_at_5
|
1317 |
+
value: 71.081
|
1318 |
+
- type: precision_at_1
|
1319 |
+
value: 59.28600000000001
|
1320 |
+
- type: precision_at_10
|
1321 |
+
value: 9.499
|
1322 |
+
- type: precision_at_100
|
1323 |
+
value: 1.052
|
1324 |
+
- type: precision_at_1000
|
1325 |
+
value: 0.11100000000000002
|
1326 |
+
- type: precision_at_3
|
1327 |
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value: 27.503
|
1328 |
+
- type: precision_at_5
|
1329 |
+
value: 17.854999999999997
|
1330 |
+
- type: recall_at_1
|
1331 |
+
value: 55.086
|
1332 |
+
- type: recall_at_10
|
1333 |
+
value: 86.453
|
1334 |
+
- type: recall_at_100
|
1335 |
+
value: 94.028
|
1336 |
+
- type: recall_at_1000
|
1337 |
+
value: 97.052
|
1338 |
+
- type: recall_at_3
|
1339 |
+
value: 75.821
|
1340 |
+
- type: recall_at_5
|
1341 |
+
value: 81.6
|
1342 |
+
- task:
|
1343 |
+
type: Retrieval
|
1344 |
+
dataset:
|
1345 |
+
type: fiqa
|
1346 |
+
name: MTEB FiQA2018
|
1347 |
+
config: default
|
1348 |
+
split: test
|
1349 |
+
revision: None
|
1350 |
+
metrics:
|
1351 |
+
- type: map_at_1
|
1352 |
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1355 |
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1361 |
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1362 |
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1366 |
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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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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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1392 |
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1393 |
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1394 |
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1395 |
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value: 28.652
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1397 |
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|
1398 |
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value: 21.204
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1399 |
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1400 |
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value: 22.262999999999998
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1401 |
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|
1402 |
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value: 52.447
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1403 |
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1404 |
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value: 78.045
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1405 |
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- type: recall_at_1000
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1406 |
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value: 94.419
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1407 |
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1408 |
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value: 38.064
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1409 |
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1410 |
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1411 |
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|
1412 |
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1413 |
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|
1414 |
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type: hotpotqa
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1415 |
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name: MTEB HotpotQA
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1416 |
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config: default
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1417 |
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split: test
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1418 |
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revision: None
|
1419 |
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metrics:
|
1420 |
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- type: map_at_1
|
1421 |
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value: 32.519
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1422 |
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- type: map_at_10
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1423 |
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1424 |
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1425 |
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1429 |
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1430 |
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1431 |
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1432 |
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1433 |
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1434 |
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1435 |
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1436 |
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1437 |
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1438 |
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1439 |
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1441 |
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1442 |
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1443 |
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1444 |
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1445 |
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1446 |
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1447 |
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1448 |
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1449 |
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1450 |
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1451 |
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value: 60.648
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1452 |
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1453 |
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1454 |
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1455 |
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1456 |
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1457 |
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1458 |
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1459 |
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1461 |
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1462 |
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1463 |
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value: 0.168
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1464 |
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1465 |
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value: 31.483
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1466 |
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1467 |
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value: 20.845
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1468 |
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1469 |
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value: 32.519
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1470 |
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1471 |
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1472 |
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1473 |
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1474 |
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1475 |
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1476 |
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- type: recall_at_3
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1477 |
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value: 47.225
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1478 |
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- type: recall_at_5
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1479 |
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value: 52.113
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1480 |
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- task:
|
1481 |
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type: Classification
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1482 |
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dataset:
|
1483 |
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type: mteb/imdb
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1484 |
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name: MTEB ImdbClassification
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1485 |
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config: default
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1486 |
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split: test
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1487 |
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1488 |
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metrics:
|
1489 |
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- type: accuracy
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1490 |
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value: 88.3168
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1491 |
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- type: ap
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1492 |
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value: 83.80165516037135
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1493 |
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1494 |
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1495 |
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- task:
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1496 |
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1497 |
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dataset:
|
1498 |
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type: msmarco
|
1499 |
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name: MTEB MSMARCO
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1500 |
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config: default
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1501 |
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split: dev
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1502 |
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revision: None
|
1503 |
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metrics:
|
1504 |
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1505 |
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value: 20.724999999999998
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1506 |
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1507 |
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1508 |
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1509 |
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1511 |
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1513 |
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1514 |
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1515 |
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1516 |
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1517 |
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value: 21.361
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1518 |
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1519 |
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value: 33.323
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1520 |
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1521 |
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1522 |
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1523 |
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1524 |
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1525 |
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1527 |
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1529 |
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1530 |
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1531 |
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1532 |
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1533 |
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1534 |
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1535 |
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value: 46.775
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1536 |
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1537 |
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1538 |
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1539 |
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value: 35.543
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1540 |
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1541 |
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value: 21.361
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1542 |
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1543 |
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value: 6.3740000000000006
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1544 |
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1545 |
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value: 0.931
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1546 |
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1547 |
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value: 0.104
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1548 |
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1549 |
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value: 13.514999999999999
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1550 |
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1551 |
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value: 10.100000000000001
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1552 |
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1553 |
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value: 20.724999999999998
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1554 |
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|
1555 |
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value: 61.034
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1556 |
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|
1557 |
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value: 88.062
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1558 |
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|
1559 |
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value: 97.86399999999999
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1560 |
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- type: recall_at_3
|
1561 |
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value: 39.072
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1562 |
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- type: recall_at_5
|
1563 |
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value: 48.53
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1564 |
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- task:
|
1565 |
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|
1566 |
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dataset:
|
1567 |
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type: mteb/mtop_domain
|
1568 |
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name: MTEB MTOPDomainClassification (en)
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1569 |
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config: en
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1570 |
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split: test
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1571 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1572 |
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metrics:
|
1573 |
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- type: accuracy
|
1574 |
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value: 93.8919288645691
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1575 |
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- type: f1
|
1576 |
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value: 93.57059586398059
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1577 |
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- task:
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1578 |
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1579 |
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dataset:
|
1580 |
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type: mteb/mtop_intent
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1581 |
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name: MTEB MTOPIntentClassification (en)
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config: en
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1583 |
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1584 |
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value: 67.97993616051072
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1589 |
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value: 48.244319183606535
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1590 |
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1591 |
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1592 |
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dataset:
|
1593 |
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type: mteb/amazon_massive_intent
|
1594 |
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name: MTEB MassiveIntentClassification (en)
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1595 |
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config: en
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1597 |
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1598 |
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1599 |
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1600 |
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1601 |
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1602 |
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1603 |
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1604 |
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1605 |
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dataset:
|
1606 |
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1607 |
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1608 |
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1609 |
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1610 |
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1611 |
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1612 |
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1613 |
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1614 |
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1615 |
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1616 |
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- task:
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1617 |
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1618 |
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dataset:
|
1619 |
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1620 |
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name: MTEB MedrxivClusteringP2P
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1621 |
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metrics:
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1625 |
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1626 |
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1627 |
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- task:
|
1628 |
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1629 |
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dataset:
|
1630 |
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type: mteb/medrxiv-clustering-s2s
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1631 |
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1632 |
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1633 |
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1634 |
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1637 |
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- task:
|
1639 |
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1640 |
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dataset:
|
1641 |
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type: mteb/mind_small
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1642 |
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1643 |
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1644 |
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1645 |
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1646 |
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1647 |
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value: 31.68189362520352
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1650 |
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1651 |
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- task:
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1652 |
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1653 |
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dataset:
|
1654 |
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type: nfcorpus
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1655 |
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1656 |
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config: default
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1657 |
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1658 |
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revision: None
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1659 |
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metrics:
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1660 |
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1661 |
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value: 6.078
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1662 |
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1709 |
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1711 |
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1715 |
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1718 |
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- type: recall_at_5
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1719 |
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value: 13.158
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1720 |
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- task:
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1721 |
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1722 |
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dataset:
|
1723 |
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type: nq
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1724 |
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name: MTEB NQ
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1725 |
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config: default
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1726 |
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split: test
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1727 |
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revision: None
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1728 |
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metrics:
|
1729 |
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1730 |
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value: 26.91
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1731 |
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1732 |
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1746 |
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value: 45.146
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1747 |
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1748 |
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1750 |
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1752 |
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value: 30.272
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1756 |
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1758 |
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|
1762 |
+
value: 41.02
|
1763 |
+
- type: ndcg_at_5
|
1764 |
+
value: 45.742
|
1765 |
+
- type: precision_at_1
|
1766 |
+
value: 30.272
|
1767 |
+
- type: precision_at_10
|
1768 |
+
value: 8.537
|
1769 |
+
- type: precision_at_100
|
1770 |
+
value: 1.124
|
1771 |
+
- type: precision_at_1000
|
1772 |
+
value: 0.12
|
1773 |
+
- type: precision_at_3
|
1774 |
+
value: 18.907
|
1775 |
+
- type: precision_at_5
|
1776 |
+
value: 14.085
|
1777 |
+
- type: recall_at_1
|
1778 |
+
value: 26.91
|
1779 |
+
- type: recall_at_10
|
1780 |
+
value: 71.787
|
1781 |
+
- type: recall_at_100
|
1782 |
+
value: 92.656
|
1783 |
+
- type: recall_at_1000
|
1784 |
+
value: 98.368
|
1785 |
+
- type: recall_at_3
|
1786 |
+
value: 49.001
|
1787 |
+
- type: recall_at_5
|
1788 |
+
value: 59.917
|
1789 |
+
- task:
|
1790 |
+
type: Retrieval
|
1791 |
+
dataset:
|
1792 |
+
type: quora
|
1793 |
+
name: MTEB QuoraRetrieval
|
1794 |
+
config: default
|
1795 |
+
split: test
|
1796 |
+
revision: None
|
1797 |
+
metrics:
|
1798 |
+
- type: map_at_1
|
1799 |
+
value: 70.557
|
1800 |
+
- type: map_at_10
|
1801 |
+
value: 84.729
|
1802 |
+
- type: map_at_100
|
1803 |
+
value: 85.369
|
1804 |
+
- type: map_at_1000
|
1805 |
+
value: 85.382
|
1806 |
+
- type: map_at_3
|
1807 |
+
value: 81.72
|
1808 |
+
- type: map_at_5
|
1809 |
+
value: 83.613
|
1810 |
+
- type: mrr_at_1
|
1811 |
+
value: 81.3
|
1812 |
+
- type: mrr_at_10
|
1813 |
+
value: 87.488
|
1814 |
+
- type: mrr_at_100
|
1815 |
+
value: 87.588
|
1816 |
+
- type: mrr_at_1000
|
1817 |
+
value: 87.589
|
1818 |
+
- type: mrr_at_3
|
1819 |
+
value: 86.53
|
1820 |
+
- type: mrr_at_5
|
1821 |
+
value: 87.18599999999999
|
1822 |
+
- type: ndcg_at_1
|
1823 |
+
value: 81.28999999999999
|
1824 |
+
- type: ndcg_at_10
|
1825 |
+
value: 88.442
|
1826 |
+
- type: ndcg_at_100
|
1827 |
+
value: 89.637
|
1828 |
+
- type: ndcg_at_1000
|
1829 |
+
value: 89.70700000000001
|
1830 |
+
- type: ndcg_at_3
|
1831 |
+
value: 85.55199999999999
|
1832 |
+
- type: ndcg_at_5
|
1833 |
+
value: 87.154
|
1834 |
+
- type: precision_at_1
|
1835 |
+
value: 81.28999999999999
|
1836 |
+
- type: precision_at_10
|
1837 |
+
value: 13.489999999999998
|
1838 |
+
- type: precision_at_100
|
1839 |
+
value: 1.54
|
1840 |
+
- type: precision_at_1000
|
1841 |
+
value: 0.157
|
1842 |
+
- type: precision_at_3
|
1843 |
+
value: 37.553
|
1844 |
+
- type: precision_at_5
|
1845 |
+
value: 24.708
|
1846 |
+
- type: recall_at_1
|
1847 |
+
value: 70.557
|
1848 |
+
- type: recall_at_10
|
1849 |
+
value: 95.645
|
1850 |
+
- type: recall_at_100
|
1851 |
+
value: 99.693
|
1852 |
+
- type: recall_at_1000
|
1853 |
+
value: 99.995
|
1854 |
+
- type: recall_at_3
|
1855 |
+
value: 87.359
|
1856 |
+
- type: recall_at_5
|
1857 |
+
value: 91.89699999999999
|
1858 |
+
- task:
|
1859 |
+
type: Clustering
|
1860 |
+
dataset:
|
1861 |
+
type: mteb/reddit-clustering
|
1862 |
+
name: MTEB RedditClustering
|
1863 |
+
config: default
|
1864 |
+
split: test
|
1865 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1866 |
+
metrics:
|
1867 |
+
- type: v_measure
|
1868 |
+
value: 63.65060114776209
|
1869 |
+
- task:
|
1870 |
+
type: Clustering
|
1871 |
+
dataset:
|
1872 |
+
type: mteb/reddit-clustering-p2p
|
1873 |
+
name: MTEB RedditClusteringP2P
|
1874 |
+
config: default
|
1875 |
+
split: test
|
1876 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1877 |
+
metrics:
|
1878 |
+
- type: v_measure
|
1879 |
+
value: 64.63271250680617
|
1880 |
+
- task:
|
1881 |
+
type: Retrieval
|
1882 |
+
dataset:
|
1883 |
+
type: scidocs
|
1884 |
+
name: MTEB SCIDOCS
|
1885 |
+
config: default
|
1886 |
+
split: test
|
1887 |
+
revision: None
|
1888 |
+
metrics:
|
1889 |
+
- type: map_at_1
|
1890 |
+
value: 4.263
|
1891 |
+
- type: map_at_10
|
1892 |
+
value: 10.801
|
1893 |
+
- type: map_at_100
|
1894 |
+
value: 12.888
|
1895 |
+
- type: map_at_1000
|
1896 |
+
value: 13.224
|
1897 |
+
- type: map_at_3
|
1898 |
+
value: 7.362
|
1899 |
+
- type: map_at_5
|
1900 |
+
value: 9.149000000000001
|
1901 |
+
- type: mrr_at_1
|
1902 |
+
value: 21.0
|
1903 |
+
- type: mrr_at_10
|
1904 |
+
value: 31.416
|
1905 |
+
- type: mrr_at_100
|
1906 |
+
value: 32.513
|
1907 |
+
- type: mrr_at_1000
|
1908 |
+
value: 32.58
|
1909 |
+
- type: mrr_at_3
|
1910 |
+
value: 28.116999999999997
|
1911 |
+
- type: mrr_at_5
|
1912 |
+
value: 29.976999999999997
|
1913 |
+
- type: ndcg_at_1
|
1914 |
+
value: 21.0
|
1915 |
+
- type: ndcg_at_10
|
1916 |
+
value: 18.551000000000002
|
1917 |
+
- type: ndcg_at_100
|
1918 |
+
value: 26.657999999999998
|
1919 |
+
- type: ndcg_at_1000
|
1920 |
+
value: 32.485
|
1921 |
+
- type: ndcg_at_3
|
1922 |
+
value: 16.834
|
1923 |
+
- type: ndcg_at_5
|
1924 |
+
value: 15.204999999999998
|
1925 |
+
- type: precision_at_1
|
1926 |
+
value: 21.0
|
1927 |
+
- type: precision_at_10
|
1928 |
+
value: 9.84
|
1929 |
+
- type: precision_at_100
|
1930 |
+
value: 2.16
|
1931 |
+
- type: precision_at_1000
|
1932 |
+
value: 0.35500000000000004
|
1933 |
+
- type: precision_at_3
|
1934 |
+
value: 15.667
|
1935 |
+
- type: precision_at_5
|
1936 |
+
value: 13.62
|
1937 |
+
- type: recall_at_1
|
1938 |
+
value: 4.263
|
1939 |
+
- type: recall_at_10
|
1940 |
+
value: 19.922
|
1941 |
+
- type: recall_at_100
|
1942 |
+
value: 43.808
|
1943 |
+
- type: recall_at_1000
|
1944 |
+
value: 72.14500000000001
|
1945 |
+
- type: recall_at_3
|
1946 |
+
value: 9.493
|
1947 |
+
- type: recall_at_5
|
1948 |
+
value: 13.767999999999999
|
1949 |
+
- task:
|
1950 |
+
type: STS
|
1951 |
+
dataset:
|
1952 |
+
type: mteb/sickr-sts
|
1953 |
+
name: MTEB SICK-R
|
1954 |
+
config: default
|
1955 |
+
split: test
|
1956 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1957 |
+
metrics:
|
1958 |
+
- type: cos_sim_spearman
|
1959 |
+
value: 81.27446313317233
|
1960 |
+
- task:
|
1961 |
+
type: STS
|
1962 |
+
dataset:
|
1963 |
+
type: mteb/sts12-sts
|
1964 |
+
name: MTEB STS12
|
1965 |
+
config: default
|
1966 |
+
split: test
|
1967 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1968 |
+
metrics:
|
1969 |
+
- type: cos_sim_spearman
|
1970 |
+
value: 76.27963301217527
|
1971 |
+
- task:
|
1972 |
+
type: STS
|
1973 |
+
dataset:
|
1974 |
+
type: mteb/sts13-sts
|
1975 |
+
name: MTEB STS13
|
1976 |
+
config: default
|
1977 |
+
split: test
|
1978 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1979 |
+
metrics:
|
1980 |
+
- type: cos_sim_spearman
|
1981 |
+
value: 88.18495048450949
|
1982 |
+
- task:
|
1983 |
+
type: STS
|
1984 |
+
dataset:
|
1985 |
+
type: mteb/sts14-sts
|
1986 |
+
name: MTEB STS14
|
1987 |
+
config: default
|
1988 |
+
split: test
|
1989 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
1990 |
+
metrics:
|
1991 |
+
- type: cos_sim_spearman
|
1992 |
+
value: 81.91982338692046
|
1993 |
+
- task:
|
1994 |
+
type: STS
|
1995 |
+
dataset:
|
1996 |
+
type: mteb/sts15-sts
|
1997 |
+
name: MTEB STS15
|
1998 |
+
config: default
|
1999 |
+
split: test
|
2000 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2001 |
+
metrics:
|
2002 |
+
- type: cos_sim_spearman
|
2003 |
+
value: 89.00896818385291
|
2004 |
+
- task:
|
2005 |
+
type: STS
|
2006 |
+
dataset:
|
2007 |
+
type: mteb/sts16-sts
|
2008 |
+
name: MTEB STS16
|
2009 |
+
config: default
|
2010 |
+
split: test
|
2011 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2012 |
+
metrics:
|
2013 |
+
- type: cos_sim_spearman
|
2014 |
+
value: 85.48814644586132
|
2015 |
+
- task:
|
2016 |
+
type: STS
|
2017 |
+
dataset:
|
2018 |
+
type: mteb/sts17-crosslingual-sts
|
2019 |
+
name: MTEB STS17 (en-en)
|
2020 |
+
config: en-en
|
2021 |
+
split: test
|
2022 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2023 |
+
metrics:
|
2024 |
+
- type: cos_sim_spearman
|
2025 |
+
value: 90.30116926966582
|
2026 |
+
- task:
|
2027 |
+
type: STS
|
2028 |
+
dataset:
|
2029 |
+
type: mteb/sts22-crosslingual-sts
|
2030 |
+
name: MTEB STS22 (en)
|
2031 |
+
config: en
|
2032 |
+
split: test
|
2033 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2034 |
+
metrics:
|
2035 |
+
- type: cos_sim_spearman
|
2036 |
+
value: 67.74132963032342
|
2037 |
+
- task:
|
2038 |
+
type: STS
|
2039 |
+
dataset:
|
2040 |
+
type: mteb/stsbenchmark-sts
|
2041 |
+
name: MTEB STSBenchmark
|
2042 |
+
config: default
|
2043 |
+
split: test
|
2044 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2045 |
+
metrics:
|
2046 |
+
- type: cos_sim_spearman
|
2047 |
+
value: 86.87741355780479
|
2048 |
+
- task:
|
2049 |
+
type: Reranking
|
2050 |
+
dataset:
|
2051 |
+
type: mteb/scidocs-reranking
|
2052 |
+
name: MTEB SciDocsRR
|
2053 |
+
config: default
|
2054 |
+
split: test
|
2055 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2056 |
+
metrics:
|
2057 |
+
- type: map
|
2058 |
+
value: 82.0019012295875
|
2059 |
+
- type: mrr
|
2060 |
+
value: 94.70267024188593
|
2061 |
+
- task:
|
2062 |
+
type: Retrieval
|
2063 |
+
dataset:
|
2064 |
+
type: scifact
|
2065 |
+
name: MTEB SciFact
|
2066 |
+
config: default
|
2067 |
+
split: test
|
2068 |
+
revision: None
|
2069 |
+
metrics:
|
2070 |
+
- type: map_at_1
|
2071 |
+
value: 50.05
|
2072 |
+
- type: map_at_10
|
2073 |
+
value: 59.36
|
2074 |
+
- type: map_at_100
|
2075 |
+
value: 59.967999999999996
|
2076 |
+
- type: map_at_1000
|
2077 |
+
value: 60.023
|
2078 |
+
- type: map_at_3
|
2079 |
+
value: 56.515
|
2080 |
+
- type: map_at_5
|
2081 |
+
value: 58.272999999999996
|
2082 |
+
- type: mrr_at_1
|
2083 |
+
value: 53.0
|
2084 |
+
- type: mrr_at_10
|
2085 |
+
value: 61.102000000000004
|
2086 |
+
- type: mrr_at_100
|
2087 |
+
value: 61.476
|
2088 |
+
- type: mrr_at_1000
|
2089 |
+
value: 61.523
|
2090 |
+
- type: mrr_at_3
|
2091 |
+
value: 58.778
|
2092 |
+
- type: mrr_at_5
|
2093 |
+
value: 60.128
|
2094 |
+
- type: ndcg_at_1
|
2095 |
+
value: 53.0
|
2096 |
+
- type: ndcg_at_10
|
2097 |
+
value: 64.43100000000001
|
2098 |
+
- type: ndcg_at_100
|
2099 |
+
value: 66.73599999999999
|
2100 |
+
- type: ndcg_at_1000
|
2101 |
+
value: 68.027
|
2102 |
+
- type: ndcg_at_3
|
2103 |
+
value: 59.279
|
2104 |
+
- type: ndcg_at_5
|
2105 |
+
value: 61.888
|
2106 |
+
- type: precision_at_1
|
2107 |
+
value: 53.0
|
2108 |
+
- type: precision_at_10
|
2109 |
+
value: 8.767
|
2110 |
+
- type: precision_at_100
|
2111 |
+
value: 1.01
|
2112 |
+
- type: precision_at_1000
|
2113 |
+
value: 0.11100000000000002
|
2114 |
+
- type: precision_at_3
|
2115 |
+
value: 23.444000000000003
|
2116 |
+
- type: precision_at_5
|
2117 |
+
value: 15.667
|
2118 |
+
- type: recall_at_1
|
2119 |
+
value: 50.05
|
2120 |
+
- type: recall_at_10
|
2121 |
+
value: 78.511
|
2122 |
+
- type: recall_at_100
|
2123 |
+
value: 88.5
|
2124 |
+
- type: recall_at_1000
|
2125 |
+
value: 98.333
|
2126 |
+
- type: recall_at_3
|
2127 |
+
value: 64.117
|
2128 |
+
- type: recall_at_5
|
2129 |
+
value: 70.867
|
2130 |
+
- task:
|
2131 |
+
type: PairClassification
|
2132 |
+
dataset:
|
2133 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
2134 |
+
name: MTEB SprintDuplicateQuestions
|
2135 |
+
config: default
|
2136 |
+
split: test
|
2137 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2138 |
+
metrics:
|
2139 |
+
- type: cos_sim_accuracy
|
2140 |
+
value: 99.72178217821782
|
2141 |
+
- type: cos_sim_ap
|
2142 |
+
value: 93.0728601593541
|
2143 |
+
- type: cos_sim_f1
|
2144 |
+
value: 85.6727976766699
|
2145 |
+
- type: cos_sim_precision
|
2146 |
+
value: 83.02063789868667
|
2147 |
+
- type: cos_sim_recall
|
2148 |
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value: 88.5
|
2149 |
+
- type: dot_accuracy
|
2150 |
+
value: 99.72178217821782
|
2151 |
+
- type: dot_ap
|
2152 |
+
value: 93.07287396168348
|
2153 |
+
- type: dot_f1
|
2154 |
+
value: 85.6727976766699
|
2155 |
+
- type: dot_precision
|
2156 |
+
value: 83.02063789868667
|
2157 |
+
- type: dot_recall
|
2158 |
+
value: 88.5
|
2159 |
+
- type: euclidean_accuracy
|
2160 |
+
value: 99.72178217821782
|
2161 |
+
- type: euclidean_ap
|
2162 |
+
value: 93.07285657982895
|
2163 |
+
- type: euclidean_f1
|
2164 |
+
value: 85.6727976766699
|
2165 |
+
- type: euclidean_precision
|
2166 |
+
value: 83.02063789868667
|
2167 |
+
- type: euclidean_recall
|
2168 |
+
value: 88.5
|
2169 |
+
- type: manhattan_accuracy
|
2170 |
+
value: 99.72475247524753
|
2171 |
+
- type: manhattan_ap
|
2172 |
+
value: 93.02792973059809
|
2173 |
+
- type: manhattan_f1
|
2174 |
+
value: 85.7727737973388
|
2175 |
+
- type: manhattan_precision
|
2176 |
+
value: 87.84067085953879
|
2177 |
+
- type: manhattan_recall
|
2178 |
+
value: 83.8
|
2179 |
+
- type: max_accuracy
|
2180 |
+
value: 99.72475247524753
|
2181 |
+
- type: max_ap
|
2182 |
+
value: 93.07287396168348
|
2183 |
+
- type: max_f1
|
2184 |
+
value: 85.7727737973388
|
2185 |
+
- task:
|
2186 |
+
type: Clustering
|
2187 |
+
dataset:
|
2188 |
+
type: mteb/stackexchange-clustering
|
2189 |
+
name: MTEB StackExchangeClustering
|
2190 |
+
config: default
|
2191 |
+
split: test
|
2192 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2193 |
+
metrics:
|
2194 |
+
- type: v_measure
|
2195 |
+
value: 68.77583615550819
|
2196 |
+
- task:
|
2197 |
+
type: Clustering
|
2198 |
+
dataset:
|
2199 |
+
type: mteb/stackexchange-clustering-p2p
|
2200 |
+
name: MTEB StackExchangeClusteringP2P
|
2201 |
+
config: default
|
2202 |
+
split: test
|
2203 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2204 |
+
metrics:
|
2205 |
+
- type: v_measure
|
2206 |
+
value: 36.151636938606956
|
2207 |
+
- task:
|
2208 |
+
type: Reranking
|
2209 |
+
dataset:
|
2210 |
+
type: mteb/stackoverflowdupquestions-reranking
|
2211 |
+
name: MTEB StackOverflowDupQuestions
|
2212 |
+
config: default
|
2213 |
+
split: test
|
2214 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2215 |
+
metrics:
|
2216 |
+
- type: map
|
2217 |
+
value: 52.16607939471187
|
2218 |
+
- type: mrr
|
2219 |
+
value: 52.95172046091163
|
2220 |
+
- task:
|
2221 |
+
type: Summarization
|
2222 |
+
dataset:
|
2223 |
+
type: mteb/summeval
|
2224 |
+
name: MTEB SummEval
|
2225 |
+
config: default
|
2226 |
+
split: test
|
2227 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2228 |
+
metrics:
|
2229 |
+
- type: cos_sim_pearson
|
2230 |
+
value: 31.314646669495666
|
2231 |
+
- type: cos_sim_spearman
|
2232 |
+
value: 31.83562491439455
|
2233 |
+
- type: dot_pearson
|
2234 |
+
value: 31.314590842874157
|
2235 |
+
- type: dot_spearman
|
2236 |
+
value: 31.83363065810437
|
2237 |
+
- task:
|
2238 |
+
type: Retrieval
|
2239 |
+
dataset:
|
2240 |
+
type: trec-covid
|
2241 |
+
name: MTEB TRECCOVID
|
2242 |
+
config: default
|
2243 |
+
split: test
|
2244 |
+
revision: None
|
2245 |
+
metrics:
|
2246 |
+
- type: map_at_1
|
2247 |
+
value: 0.198
|
2248 |
+
- type: map_at_10
|
2249 |
+
value: 1.3010000000000002
|
2250 |
+
- type: map_at_100
|
2251 |
+
value: 7.2139999999999995
|
2252 |
+
- type: map_at_1000
|
2253 |
+
value: 20.179
|
2254 |
+
- type: map_at_3
|
2255 |
+
value: 0.528
|
2256 |
+
- type: map_at_5
|
2257 |
+
value: 0.8019999999999999
|
2258 |
+
- type: mrr_at_1
|
2259 |
+
value: 72.0
|
2260 |
+
- type: mrr_at_10
|
2261 |
+
value: 83.39999999999999
|
2262 |
+
- type: mrr_at_100
|
2263 |
+
value: 83.39999999999999
|
2264 |
+
- type: mrr_at_1000
|
2265 |
+
value: 83.39999999999999
|
2266 |
+
- type: mrr_at_3
|
2267 |
+
value: 81.667
|
2268 |
+
- type: mrr_at_5
|
2269 |
+
value: 83.06700000000001
|
2270 |
+
- type: ndcg_at_1
|
2271 |
+
value: 66.0
|
2272 |
+
- type: ndcg_at_10
|
2273 |
+
value: 58.059000000000005
|
2274 |
+
- type: ndcg_at_100
|
2275 |
+
value: 44.316
|
2276 |
+
- type: ndcg_at_1000
|
2277 |
+
value: 43.147000000000006
|
2278 |
+
- type: ndcg_at_3
|
2279 |
+
value: 63.815999999999995
|
2280 |
+
- type: ndcg_at_5
|
2281 |
+
value: 63.005
|
2282 |
+
- type: precision_at_1
|
2283 |
+
value: 72.0
|
2284 |
+
- type: precision_at_10
|
2285 |
+
value: 61.4
|
2286 |
+
- type: precision_at_100
|
2287 |
+
value: 45.62
|
2288 |
+
- type: precision_at_1000
|
2289 |
+
value: 19.866
|
2290 |
+
- type: precision_at_3
|
2291 |
+
value: 70.0
|
2292 |
+
- type: precision_at_5
|
2293 |
+
value: 68.8
|
2294 |
+
- type: recall_at_1
|
2295 |
+
value: 0.198
|
2296 |
+
- type: recall_at_10
|
2297 |
+
value: 1.517
|
2298 |
+
- type: recall_at_100
|
2299 |
+
value: 10.587
|
2300 |
+
- type: recall_at_1000
|
2301 |
+
value: 41.233
|
2302 |
+
- type: recall_at_3
|
2303 |
+
value: 0.573
|
2304 |
+
- type: recall_at_5
|
2305 |
+
value: 0.907
|
2306 |
+
- task:
|
2307 |
+
type: Retrieval
|
2308 |
+
dataset:
|
2309 |
+
type: webis-touche2020
|
2310 |
+
name: MTEB Touche2020
|
2311 |
+
config: default
|
2312 |
+
split: test
|
2313 |
+
revision: None
|
2314 |
+
metrics:
|
2315 |
+
- type: map_at_1
|
2316 |
+
value: 1.894
|
2317 |
+
- type: map_at_10
|
2318 |
+
value: 8.488999999999999
|
2319 |
+
- type: map_at_100
|
2320 |
+
value: 14.445
|
2321 |
+
- type: map_at_1000
|
2322 |
+
value: 16.078
|
2323 |
+
- type: map_at_3
|
2324 |
+
value: 4.589
|
2325 |
+
- type: map_at_5
|
2326 |
+
value: 6.019
|
2327 |
+
- type: mrr_at_1
|
2328 |
+
value: 22.448999999999998
|
2329 |
+
- type: mrr_at_10
|
2330 |
+
value: 39.82
|
2331 |
+
- type: mrr_at_100
|
2332 |
+
value: 40.752
|
2333 |
+
- type: mrr_at_1000
|
2334 |
+
value: 40.771
|
2335 |
+
- type: mrr_at_3
|
2336 |
+
value: 34.354
|
2337 |
+
- type: mrr_at_5
|
2338 |
+
value: 37.721
|
2339 |
+
- type: ndcg_at_1
|
2340 |
+
value: 19.387999999999998
|
2341 |
+
- type: ndcg_at_10
|
2342 |
+
value: 21.563
|
2343 |
+
- type: ndcg_at_100
|
2344 |
+
value: 33.857
|
2345 |
+
- type: ndcg_at_1000
|
2346 |
+
value: 46.199
|
2347 |
+
- type: ndcg_at_3
|
2348 |
+
value: 22.296
|
2349 |
+
- type: ndcg_at_5
|
2350 |
+
value: 21.770999999999997
|
2351 |
+
- type: precision_at_1
|
2352 |
+
value: 22.448999999999998
|
2353 |
+
- type: precision_at_10
|
2354 |
+
value: 19.796
|
2355 |
+
- type: precision_at_100
|
2356 |
+
value: 7.142999999999999
|
2357 |
+
- type: precision_at_1000
|
2358 |
+
value: 1.541
|
2359 |
+
- type: precision_at_3
|
2360 |
+
value: 24.490000000000002
|
2361 |
+
- type: precision_at_5
|
2362 |
+
value: 22.448999999999998
|
2363 |
+
- type: recall_at_1
|
2364 |
+
value: 1.894
|
2365 |
+
- type: recall_at_10
|
2366 |
+
value: 14.931
|
2367 |
+
- type: recall_at_100
|
2368 |
+
value: 45.524
|
2369 |
+
- type: recall_at_1000
|
2370 |
+
value: 83.243
|
2371 |
+
- type: recall_at_3
|
2372 |
+
value: 5.712
|
2373 |
+
- type: recall_at_5
|
2374 |
+
value: 8.386000000000001
|
2375 |
+
- task:
|
2376 |
+
type: Classification
|
2377 |
+
dataset:
|
2378 |
+
type: mteb/toxic_conversations_50k
|
2379 |
+
name: MTEB ToxicConversationsClassification
|
2380 |
+
config: default
|
2381 |
+
split: test
|
2382 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2383 |
+
metrics:
|
2384 |
+
- type: accuracy
|
2385 |
+
value: 71.049
|
2386 |
+
- type: ap
|
2387 |
+
value: 13.85116971310922
|
2388 |
+
- type: f1
|
2389 |
+
value: 54.37504302487686
|
2390 |
+
- task:
|
2391 |
+
type: Classification
|
2392 |
+
dataset:
|
2393 |
+
type: mteb/tweet_sentiment_extraction
|
2394 |
+
name: MTEB TweetSentimentExtractionClassification
|
2395 |
+
config: default
|
2396 |
+
split: test
|
2397 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2398 |
+
metrics:
|
2399 |
+
- type: accuracy
|
2400 |
+
value: 64.1312959818902
|
2401 |
+
- type: f1
|
2402 |
+
value: 64.11413877009383
|
2403 |
+
- task:
|
2404 |
+
type: Clustering
|
2405 |
+
dataset:
|
2406 |
+
type: mteb/twentynewsgroups-clustering
|
2407 |
+
name: MTEB TwentyNewsgroupsClustering
|
2408 |
+
config: default
|
2409 |
+
split: test
|
2410 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2411 |
+
metrics:
|
2412 |
+
- type: v_measure
|
2413 |
+
value: 54.13103431861502
|
2414 |
+
- task:
|
2415 |
+
type: PairClassification
|
2416 |
+
dataset:
|
2417 |
+
type: mteb/twittersemeval2015-pairclassification
|
2418 |
+
name: MTEB TwitterSemEval2015
|
2419 |
+
config: default
|
2420 |
+
split: test
|
2421 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2422 |
+
metrics:
|
2423 |
+
- type: cos_sim_accuracy
|
2424 |
+
value: 87.327889372355
|
2425 |
+
- type: cos_sim_ap
|
2426 |
+
value: 77.42059895975699
|
2427 |
+
- type: cos_sim_f1
|
2428 |
+
value: 71.02706903250873
|
2429 |
+
- type: cos_sim_precision
|
2430 |
+
value: 69.75324344950394
|
2431 |
+
- type: cos_sim_recall
|
2432 |
+
value: 72.34828496042216
|
2433 |
+
- type: dot_accuracy
|
2434 |
+
value: 87.327889372355
|
2435 |
+
- type: dot_ap
|
2436 |
+
value: 77.4209479346677
|
2437 |
+
- type: dot_f1
|
2438 |
+
value: 71.02706903250873
|
2439 |
+
- type: dot_precision
|
2440 |
+
value: 69.75324344950394
|
2441 |
+
- type: dot_recall
|
2442 |
+
value: 72.34828496042216
|
2443 |
+
- type: euclidean_accuracy
|
2444 |
+
value: 87.327889372355
|
2445 |
+
- type: euclidean_ap
|
2446 |
+
value: 77.42096495861037
|
2447 |
+
- type: euclidean_f1
|
2448 |
+
value: 71.02706903250873
|
2449 |
+
- type: euclidean_precision
|
2450 |
+
value: 69.75324344950394
|
2451 |
+
- type: euclidean_recall
|
2452 |
+
value: 72.34828496042216
|
2453 |
+
- type: manhattan_accuracy
|
2454 |
+
value: 87.31000774870358
|
2455 |
+
- type: manhattan_ap
|
2456 |
+
value: 77.38930750711619
|
2457 |
+
- type: manhattan_f1
|
2458 |
+
value: 71.07935314027831
|
2459 |
+
- type: manhattan_precision
|
2460 |
+
value: 67.70957726295677
|
2461 |
+
- type: manhattan_recall
|
2462 |
+
value: 74.80211081794195
|
2463 |
+
- type: max_accuracy
|
2464 |
+
value: 87.327889372355
|
2465 |
+
- type: max_ap
|
2466 |
+
value: 77.42096495861037
|
2467 |
+
- type: max_f1
|
2468 |
+
value: 71.07935314027831
|
2469 |
+
- task:
|
2470 |
+
type: PairClassification
|
2471 |
+
dataset:
|
2472 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2473 |
+
name: MTEB TwitterURLCorpus
|
2474 |
+
config: default
|
2475 |
+
split: test
|
2476 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2477 |
+
metrics:
|
2478 |
+
- type: cos_sim_accuracy
|
2479 |
+
value: 89.58939729110878
|
2480 |
+
- type: cos_sim_ap
|
2481 |
+
value: 87.17594155025475
|
2482 |
+
- type: cos_sim_f1
|
2483 |
+
value: 79.21146953405018
|
2484 |
+
- type: cos_sim_precision
|
2485 |
+
value: 76.8918527109307
|
2486 |
+
- type: cos_sim_recall
|
2487 |
+
value: 81.67539267015707
|
2488 |
+
- type: dot_accuracy
|
2489 |
+
value: 89.58939729110878
|
2490 |
+
- type: dot_ap
|
2491 |
+
value: 87.17593963273593
|
2492 |
+
- type: dot_f1
|
2493 |
+
value: 79.21146953405018
|
2494 |
+
- type: dot_precision
|
2495 |
+
value: 76.8918527109307
|
2496 |
+
- type: dot_recall
|
2497 |
+
value: 81.67539267015707
|
2498 |
+
- type: euclidean_accuracy
|
2499 |
+
value: 89.58939729110878
|
2500 |
+
- type: euclidean_ap
|
2501 |
+
value: 87.17592466925834
|
2502 |
+
- type: euclidean_f1
|
2503 |
+
value: 79.21146953405018
|
2504 |
+
- type: euclidean_precision
|
2505 |
+
value: 76.8918527109307
|
2506 |
+
- type: euclidean_recall
|
2507 |
+
value: 81.67539267015707
|
2508 |
+
- type: manhattan_accuracy
|
2509 |
+
value: 89.62626615438352
|
2510 |
+
- type: manhattan_ap
|
2511 |
+
value: 87.16589873161546
|
2512 |
+
- type: manhattan_f1
|
2513 |
+
value: 79.25143598295348
|
2514 |
+
- type: manhattan_precision
|
2515 |
+
value: 76.39494177323712
|
2516 |
+
- type: manhattan_recall
|
2517 |
+
value: 82.32984293193716
|
2518 |
+
- type: max_accuracy
|
2519 |
+
value: 89.62626615438352
|
2520 |
+
- type: max_ap
|
2521 |
+
value: 87.17594155025475
|
2522 |
+
- type: max_f1
|
2523 |
+
value: 79.25143598295348
|
2524 |
---
|
2525 |
|
2526 |
# hkunlp/instructor-large
|