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  revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
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  type: Clustering
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527
  - task:
528
  type: Clustering
529
  dataset:
530
- type: mlsum
531
  name: MTEB MLSUMClusteringP2P
532
  config: fr
533
  split: test
534
  revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
535
  metrics:
536
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- value: 39.196489283513955
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539
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540
  - task:
541
  type: Clustering
542
  dataset:
543
- type: mlsum
544
  name: MTEB MLSUMClusteringS2S
545
  config: fr
546
  split: test
547
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548
  metrics:
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  - task:
554
  type: Classification
555
  dataset:
@@ -560,11 +560,11 @@ model-index:
560
  revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
561
  metrics:
562
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563
- value: 86.88380833072345
564
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565
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566
  - type: f1_weighted
567
- value: 86.83432508604707
568
  - task:
569
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570
  dataset:
@@ -575,11 +575,11 @@ model-index:
575
  revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
576
  metrics:
577
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578
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580
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  - type: f1_weighted
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- value: 66.2871618019472
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  - task:
584
  type: Classification
585
  dataset:
@@ -590,11 +590,11 @@ model-index:
590
  revision: 18193f187b92da67168c655c9973a165ed9593dd
591
  metrics:
592
  - type: accuracy
593
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594
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595
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596
  - type: f1_weighted
597
- value: 73.78534895009892
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  - task:
599
  type: Clustering
600
  dataset:
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605
  revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
606
  metrics:
607
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608
- value: 53.94667838037061
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611
  - task:
612
  type: Clustering
613
  dataset:
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618
  revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
619
  metrics:
620
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624
  - task:
625
  type: Classification
626
  dataset:
@@ -631,11 +631,11 @@ model-index:
631
  revision: 4672e20407010da34463acc759c162ca9734bca6
632
  metrics:
633
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  - type: f1_weighted
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- value: 65.57615486214955
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  - task:
640
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641
  dataset:
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646
  revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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655
  type: Retrieval
656
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  - type: recall_at_3
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  - type: recall_at_5
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  - task:
874
  type: PairClassification
875
  dataset:
@@ -880,106 +880,106 @@ model-index:
880
  revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
881
  metrics:
882
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- value: 96.8222442899702
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  - type: euclidean_accuracy
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  - type: euclidean_precision
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910
  - type: euclidean_recall
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  - type: manhattan_accuracy
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  - type: manhattan_ap
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925
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926
  - type: max_f1
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- value: 89.28571428571428
928
  - task:
929
  type: PairClassification
930
  dataset:
931
- type: paws-x
932
  name: MTEB PawsX (fr)
933
  config: fr
934
  split: test
935
  revision: 8a04d940a42cd40658986fdd8e3da561533a3646
936
  metrics:
937
  - type: cos_sim_accuracy
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- value: 64.25
939
  - type: cos_sim_ap
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  - type: cos_sim_f1
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  - type: cos_sim_precision
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  - type: cos_sim_recall
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  - type: dot_recall
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959
  - type: euclidean_ap
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969
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- value: 63.03703703703704
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984
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985
  dataset:
@@ -990,17 +990,17 @@ model-index:
990
  revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
991
  metrics:
992
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998
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1000
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1001
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1002
  - type: manhattan_spearman
1003
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1004
  - task:
1005
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1006
  dataset:
@@ -1008,41 +1008,41 @@ model-index:
1008
  name: MTEB STS22 (fr)
1009
  config: fr
1010
  split: test
1011
- revision: eea2b4fe26a775864c896887d910b76a8098ad3f
1012
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1013
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1014
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1015
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1016
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1017
  - type: euclidean_pearson
1018
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1019
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1020
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1021
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1022
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1023
  - type: manhattan_spearman
1024
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1025
  - task:
1026
  type: STS
1027
  dataset:
1028
- type: PhilipMay/stsb_multi_mt
1029
  name: MTEB STSBenchmarkMultilingualSTS (fr)
1030
  config: fr
1031
  split: test
1032
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1033
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1034
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1035
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1037
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1040
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1045
- value: 86.98373812309134
1046
  - task:
1047
  type: Summarization
1048
  dataset:
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1053
  revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
1054
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1055
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1056
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1061
  - type: dot_spearman
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- value: 32.17186521965941
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  - task:
1064
  type: Reranking
1065
  dataset:
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1070
  revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
1071
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1072
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