init
Browse files
README.md
CHANGED
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@@ -12069,6 +12069,63 @@ model-index:
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| 12069 |
value: 89.12
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| 12070 |
task:
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| 12071 |
type: Classification
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| 12072 |
- dataset:
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| 12073 |
config: default
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| 12074 |
name: MTEB AlloprofRetrieval
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@@ -12360,6 +12417,23 @@ model-index:
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| 12360 |
value: 60.363
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| 12361 |
task:
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| 12362 |
type: Retrieval
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| 12363 |
- dataset:
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| 12364 |
config: default
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| 12365 |
name: MTEB BSARDRetrieval
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@@ -12651,6 +12725,166 @@ model-index:
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| 12651 |
value: 25.676
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| 12652 |
task:
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| 12653 |
type: Retrieval
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| 12654 |
- dataset:
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| 12655 |
config: fr
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| 12656 |
name: MTEB MintakaRetrieval (fr)
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@@ -12942,6 +13176,184 @@ model-index:
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| 12942 |
value: 32.064
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| 12943 |
task:
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| 12944 |
type: Retrieval
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| 12945 |
- dataset:
|
| 12946 |
config: default
|
| 12947 |
name: MTEB SICKFr
|
|
@@ -12969,6 +13381,164 @@ model-index:
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| 12969 |
value: 77.47140335069184
|
| 12970 |
task:
|
| 12971 |
type: STS
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|
| 12972 |
- dataset:
|
| 12973 |
config: default
|
| 12974 |
name: MTEB SyntecRetrieval
|
|
|
|
| 12069 |
value: 89.12
|
| 12070 |
task:
|
| 12071 |
type: Classification
|
| 12072 |
+
- dataset:
|
| 12073 |
+
config: default
|
| 12074 |
+
name: MTEB AlloProfClusteringP2P
|
| 12075 |
+
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
|
| 12076 |
+
split: test
|
| 12077 |
+
type: lyon-nlp/alloprof
|
| 12078 |
+
metrics:
|
| 12079 |
+
- type: main_score
|
| 12080 |
+
value: 66.7100274116735
|
| 12081 |
+
- type: v_measure
|
| 12082 |
+
value: 66.7100274116735
|
| 12083 |
+
- type: v_measure_std
|
| 12084 |
+
value: 2.065600197695283
|
| 12085 |
+
task:
|
| 12086 |
+
type: Clustering
|
| 12087 |
+
- dataset:
|
| 12088 |
+
config: default
|
| 12089 |
+
name: MTEB AlloProfClusteringS2S
|
| 12090 |
+
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
|
| 12091 |
+
split: test
|
| 12092 |
+
type: lyon-nlp/alloprof
|
| 12093 |
+
metrics:
|
| 12094 |
+
- type: main_score
|
| 12095 |
+
value: 47.67572024379311
|
| 12096 |
+
- type: v_measure
|
| 12097 |
+
value: 47.67572024379311
|
| 12098 |
+
- type: v_measure_std
|
| 12099 |
+
value: 3.1905282169494953
|
| 12100 |
+
task:
|
| 12101 |
+
type: Clustering
|
| 12102 |
+
- dataset:
|
| 12103 |
+
config: default
|
| 12104 |
+
name: MTEB AlloprofReranking
|
| 12105 |
+
revision: 65393d0d7a08a10b4e348135e824f385d420b0fd
|
| 12106 |
+
split: test
|
| 12107 |
+
type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
|
| 12108 |
+
metrics:
|
| 12109 |
+
- type: main_score
|
| 12110 |
+
value: 75.04647907753767
|
| 12111 |
+
- type: map
|
| 12112 |
+
value: 75.04647907753767
|
| 12113 |
+
- type: mrr
|
| 12114 |
+
value: 76.25801875154207
|
| 12115 |
+
- type: nAUC_map_diff1
|
| 12116 |
+
value: 56.38279442235466
|
| 12117 |
+
- type: nAUC_map_max
|
| 12118 |
+
value: 20.009630947768642
|
| 12119 |
+
- type: nAUC_map_std
|
| 12120 |
+
value: 21.626818227466185
|
| 12121 |
+
- type: nAUC_mrr_diff1
|
| 12122 |
+
value: 56.33463291672874
|
| 12123 |
+
- type: nAUC_mrr_max
|
| 12124 |
+
value: 20.472794140230853
|
| 12125 |
+
- type: nAUC_mrr_std
|
| 12126 |
+
value: 21.491759650866392
|
| 12127 |
+
task:
|
| 12128 |
+
type: Reranking
|
| 12129 |
- dataset:
|
| 12130 |
config: default
|
| 12131 |
name: MTEB AlloprofRetrieval
|
|
|
|
| 12417 |
value: 60.363
|
| 12418 |
task:
|
| 12419 |
type: Retrieval
|
| 12420 |
+
- dataset:
|
| 12421 |
+
config: fr
|
| 12422 |
+
name: MTEB AmazonReviewsClassification (fr)
|
| 12423 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 12424 |
+
split: test
|
| 12425 |
+
type: mteb/amazon_reviews_multi
|
| 12426 |
+
metrics:
|
| 12427 |
+
- type: accuracy
|
| 12428 |
+
value: 52.622
|
| 12429 |
+
- type: f1
|
| 12430 |
+
value: 48.89589865194384
|
| 12431 |
+
- type: f1_weighted
|
| 12432 |
+
value: 48.89589865194384
|
| 12433 |
+
- type: main_score
|
| 12434 |
+
value: 52.622
|
| 12435 |
+
task:
|
| 12436 |
+
type: Classification
|
| 12437 |
- dataset:
|
| 12438 |
config: default
|
| 12439 |
name: MTEB BSARDRetrieval
|
|
|
|
| 12725 |
value: 25.676
|
| 12726 |
task:
|
| 12727 |
type: Retrieval
|
| 12728 |
+
- dataset:
|
| 12729 |
+
config: default
|
| 12730 |
+
name: MTEB HALClusteringS2S
|
| 12731 |
+
revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
|
| 12732 |
+
split: test
|
| 12733 |
+
type: lyon-nlp/clustering-hal-s2s
|
| 12734 |
+
metrics:
|
| 12735 |
+
- type: main_score
|
| 12736 |
+
value: 26.958035381361377
|
| 12737 |
+
- type: v_measure
|
| 12738 |
+
value: 26.958035381361377
|
| 12739 |
+
- type: v_measure_std
|
| 12740 |
+
value: 2.401353383071989
|
| 12741 |
+
task:
|
| 12742 |
+
type: Clustering
|
| 12743 |
+
- dataset:
|
| 12744 |
+
config: fr
|
| 12745 |
+
name: MTEB MLSUMClusteringP2P (fr)
|
| 12746 |
+
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
|
| 12747 |
+
split: test
|
| 12748 |
+
type: reciTAL/mlsum
|
| 12749 |
+
metrics:
|
| 12750 |
+
- type: main_score
|
| 12751 |
+
value: 46.15554988136895
|
| 12752 |
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- type: v_measure
|
| 12753 |
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value: 46.15554988136895
|
| 12754 |
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- type: v_measure_std
|
| 12755 |
+
value: 2.459531525134688
|
| 12756 |
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task:
|
| 12757 |
+
type: Clustering
|
| 12758 |
+
- dataset:
|
| 12759 |
+
config: fr
|
| 12760 |
+
name: MTEB MLSUMClusteringS2S (fr)
|
| 12761 |
+
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
|
| 12762 |
+
split: test
|
| 12763 |
+
type: reciTAL/mlsum
|
| 12764 |
+
metrics:
|
| 12765 |
+
- type: main_score
|
| 12766 |
+
value: 45.73187202144909
|
| 12767 |
+
- type: v_measure
|
| 12768 |
+
value: 45.73187202144909
|
| 12769 |
+
- type: v_measure_std
|
| 12770 |
+
value: 1.6402520163270633
|
| 12771 |
+
task:
|
| 12772 |
+
type: Clustering
|
| 12773 |
+
- dataset:
|
| 12774 |
+
config: fr
|
| 12775 |
+
name: MTEB MTOPDomainClassification (fr)
|
| 12776 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 12777 |
+
split: test
|
| 12778 |
+
type: mteb/mtop_domain
|
| 12779 |
+
metrics:
|
| 12780 |
+
- type: accuracy
|
| 12781 |
+
value: 95.78766050735986
|
| 12782 |
+
- type: f1
|
| 12783 |
+
value: 95.61497706645892
|
| 12784 |
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- type: f1_weighted
|
| 12785 |
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value: 95.79887587161483
|
| 12786 |
+
- type: main_score
|
| 12787 |
+
value: 95.78766050735986
|
| 12788 |
+
task:
|
| 12789 |
+
type: Classification
|
| 12790 |
+
- dataset:
|
| 12791 |
+
config: fr
|
| 12792 |
+
name: MTEB MTOPIntentClassification (fr)
|
| 12793 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 12794 |
+
split: test
|
| 12795 |
+
type: mteb/mtop_intent
|
| 12796 |
+
metrics:
|
| 12797 |
+
- type: accuracy
|
| 12798 |
+
value: 80.8800501096148
|
| 12799 |
+
- type: f1
|
| 12800 |
+
value: 53.9945274705194
|
| 12801 |
+
- type: f1_weighted
|
| 12802 |
+
value: 80.94438738414857
|
| 12803 |
+
- type: main_score
|
| 12804 |
+
value: 80.8800501096148
|
| 12805 |
+
task:
|
| 12806 |
+
type: Classification
|
| 12807 |
+
- dataset:
|
| 12808 |
+
config: fra
|
| 12809 |
+
name: MTEB MasakhaNEWSClassification (fra)
|
| 12810 |
+
revision: 18193f187b92da67168c655c9973a165ed9593dd
|
| 12811 |
+
split: test
|
| 12812 |
+
type: mteb/masakhanews
|
| 12813 |
+
metrics:
|
| 12814 |
+
- type: accuracy
|
| 12815 |
+
value: 83.6255924170616
|
| 12816 |
+
- type: f1
|
| 12817 |
+
value: 79.70294641135138
|
| 12818 |
+
- type: f1_weighted
|
| 12819 |
+
value: 83.33457992982105
|
| 12820 |
+
- type: main_score
|
| 12821 |
+
value: 83.6255924170616
|
| 12822 |
+
task:
|
| 12823 |
+
type: Classification
|
| 12824 |
+
- dataset:
|
| 12825 |
+
config: fra
|
| 12826 |
+
name: MTEB MasakhaNEWSClusteringP2P (fra)
|
| 12827 |
+
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
| 12828 |
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split: test
|
| 12829 |
+
type: masakhane/masakhanews
|
| 12830 |
+
metrics:
|
| 12831 |
+
- type: main_score
|
| 12832 |
+
value: 77.1970570860131
|
| 12833 |
+
- type: v_measure
|
| 12834 |
+
value: 77.1970570860131
|
| 12835 |
+
- type: v_measure_std
|
| 12836 |
+
value: 22.0055550035463
|
| 12837 |
+
task:
|
| 12838 |
+
type: Clustering
|
| 12839 |
+
- dataset:
|
| 12840 |
+
config: fra
|
| 12841 |
+
name: MTEB MasakhaNEWSClusteringS2S (fra)
|
| 12842 |
+
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
| 12843 |
+
split: test
|
| 12844 |
+
type: masakhane/masakhanews
|
| 12845 |
+
metrics:
|
| 12846 |
+
- type: main_score
|
| 12847 |
+
value: 65.92601417312947
|
| 12848 |
+
- type: v_measure
|
| 12849 |
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value: 65.92601417312947
|
| 12850 |
+
- type: v_measure_std
|
| 12851 |
+
value: 30.421071440935687
|
| 12852 |
+
task:
|
| 12853 |
+
type: Clustering
|
| 12854 |
+
- dataset:
|
| 12855 |
+
config: fr
|
| 12856 |
+
name: MTEB MassiveIntentClassification (fr)
|
| 12857 |
+
revision: 4672e20407010da34463acc759c162ca9734bca6
|
| 12858 |
+
split: test
|
| 12859 |
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type: mteb/amazon_massive_intent
|
| 12860 |
+
metrics:
|
| 12861 |
+
- type: accuracy
|
| 12862 |
+
value: 69.5359784801614
|
| 12863 |
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- type: f1
|
| 12864 |
+
value: 64.640488940591
|
| 12865 |
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- type: f1_weighted
|
| 12866 |
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value: 67.85916565361048
|
| 12867 |
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- type: main_score
|
| 12868 |
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value: 69.5359784801614
|
| 12869 |
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task:
|
| 12870 |
+
type: Classification
|
| 12871 |
+
- dataset:
|
| 12872 |
+
config: fr
|
| 12873 |
+
name: MTEB MassiveScenarioClassification (fr)
|
| 12874 |
+
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
|
| 12875 |
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split: test
|
| 12876 |
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type: mteb/amazon_massive_scenario
|
| 12877 |
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metrics:
|
| 12878 |
+
- type: accuracy
|
| 12879 |
+
value: 78.52723604572965
|
| 12880 |
+
- type: f1
|
| 12881 |
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value: 77.1995224144067
|
| 12882 |
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- type: f1_weighted
|
| 12883 |
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value: 78.1215987283123
|
| 12884 |
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- type: main_score
|
| 12885 |
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value: 78.52723604572965
|
| 12886 |
+
task:
|
| 12887 |
+
type: Classification
|
| 12888 |
- dataset:
|
| 12889 |
config: fr
|
| 12890 |
name: MTEB MintakaRetrieval (fr)
|
|
|
|
| 13176 |
value: 32.064
|
| 13177 |
task:
|
| 13178 |
type: Retrieval
|
| 13179 |
+
- dataset:
|
| 13180 |
+
config: fr
|
| 13181 |
+
name: MTEB OpusparcusPC (fr)
|
| 13182 |
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revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
|
| 13183 |
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split: test
|
| 13184 |
+
type: GEM/opusparcus
|
| 13185 |
+
metrics:
|
| 13186 |
+
- type: cosine_accuracy
|
| 13187 |
+
value: 82.62942779291554
|
| 13188 |
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- type: cosine_accuracy_threshold
|
| 13189 |
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value: 83.4860622882843
|
| 13190 |
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- type: cosine_ap
|
| 13191 |
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value: 93.39616519364185
|
| 13192 |
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- type: cosine_f1
|
| 13193 |
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value: 88.03378695448146
|
| 13194 |
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- type: cosine_f1_threshold
|
| 13195 |
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value: 83.4860622882843
|
| 13196 |
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- type: cosine_precision
|
| 13197 |
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value: 83.45195729537367
|
| 13198 |
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- type: cosine_recall
|
| 13199 |
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value: 93.14796425024826
|
| 13200 |
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- type: dot_accuracy
|
| 13201 |
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value: 82.62942779291554
|
| 13202 |
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- type: dot_accuracy_threshold
|
| 13203 |
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value: 83.4860622882843
|
| 13204 |
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- type: dot_ap
|
| 13205 |
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value: 93.39616519364185
|
| 13206 |
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- type: dot_f1
|
| 13207 |
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value: 88.03378695448146
|
| 13208 |
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- type: dot_f1_threshold
|
| 13209 |
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value: 83.4860622882843
|
| 13210 |
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- type: dot_precision
|
| 13211 |
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value: 83.45195729537367
|
| 13212 |
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- type: dot_recall
|
| 13213 |
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value: 93.14796425024826
|
| 13214 |
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- type: euclidean_accuracy
|
| 13215 |
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value: 82.62942779291554
|
| 13216 |
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- type: euclidean_accuracy_threshold
|
| 13217 |
+
value: 57.4698805809021
|
| 13218 |
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- type: euclidean_ap
|
| 13219 |
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value: 93.39616519364185
|
| 13220 |
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- type: euclidean_f1
|
| 13221 |
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value: 88.03378695448146
|
| 13222 |
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- type: euclidean_f1_threshold
|
| 13223 |
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value: 57.4698805809021
|
| 13224 |
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- type: euclidean_precision
|
| 13225 |
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value: 83.45195729537367
|
| 13226 |
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- type: euclidean_recall
|
| 13227 |
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value: 93.14796425024826
|
| 13228 |
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- type: main_score
|
| 13229 |
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value: 93.39616519364185
|
| 13230 |
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- type: manhattan_accuracy
|
| 13231 |
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value: 82.62942779291554
|
| 13232 |
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- type: manhattan_accuracy_threshold
|
| 13233 |
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value: 1306.7530632019043
|
| 13234 |
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- type: manhattan_ap
|
| 13235 |
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value: 93.34098710518775
|
| 13236 |
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- type: manhattan_f1
|
| 13237 |
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value: 87.78409090909089
|
| 13238 |
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- type: manhattan_f1_threshold
|
| 13239 |
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value: 1335.2685928344727
|
| 13240 |
+
- type: manhattan_precision
|
| 13241 |
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value: 83.89140271493213
|
| 13242 |
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- type: manhattan_recall
|
| 13243 |
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value: 92.05561072492551
|
| 13244 |
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- type: max_ap
|
| 13245 |
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value: 93.39616519364185
|
| 13246 |
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- type: max_f1
|
| 13247 |
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value: 88.03378695448146
|
| 13248 |
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- type: max_precision
|
| 13249 |
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value: 83.89140271493213
|
| 13250 |
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- type: max_recall
|
| 13251 |
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value: 93.14796425024826
|
| 13252 |
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- type: similarity_accuracy
|
| 13253 |
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value: 82.62942779291554
|
| 13254 |
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- type: similarity_accuracy_threshold
|
| 13255 |
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value: 83.4860622882843
|
| 13256 |
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- type: similarity_ap
|
| 13257 |
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value: 93.39616519364185
|
| 13258 |
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- type: similarity_f1
|
| 13259 |
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value: 88.03378695448146
|
| 13260 |
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- type: similarity_f1_threshold
|
| 13261 |
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value: 83.4860622882843
|
| 13262 |
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- type: similarity_precision
|
| 13263 |
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value: 83.45195729537367
|
| 13264 |
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- type: similarity_recall
|
| 13265 |
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value: 93.14796425024826
|
| 13266 |
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task:
|
| 13267 |
+
type: PairClassification
|
| 13268 |
+
- dataset:
|
| 13269 |
+
config: fr
|
| 13270 |
+
name: MTEB PawsXPairClassification (fr)
|
| 13271 |
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revision: 8a04d940a42cd40658986fdd8e3da561533a3646
|
| 13272 |
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split: test
|
| 13273 |
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type: google-research-datasets/paws-x
|
| 13274 |
+
metrics:
|
| 13275 |
+
- type: cosine_accuracy
|
| 13276 |
+
value: 60.8
|
| 13277 |
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- type: cosine_accuracy_threshold
|
| 13278 |
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value: 98.90193939208984
|
| 13279 |
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- type: cosine_ap
|
| 13280 |
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value: 60.50913122978733
|
| 13281 |
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- type: cosine_f1
|
| 13282 |
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value: 62.69411339833874
|
| 13283 |
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- type: cosine_f1_threshold
|
| 13284 |
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value: 95.17210125923157
|
| 13285 |
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- type: cosine_precision
|
| 13286 |
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value: 46.51661307609861
|
| 13287 |
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- type: cosine_recall
|
| 13288 |
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value: 96.12403100775194
|
| 13289 |
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- type: dot_accuracy
|
| 13290 |
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value: 60.8
|
| 13291 |
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- type: dot_accuracy_threshold
|
| 13292 |
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value: 98.9019513130188
|
| 13293 |
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- type: dot_ap
|
| 13294 |
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value: 60.49770725998639
|
| 13295 |
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- type: dot_f1
|
| 13296 |
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value: 62.69411339833874
|
| 13297 |
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- type: dot_f1_threshold
|
| 13298 |
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value: 95.17210721969604
|
| 13299 |
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- type: dot_precision
|
| 13300 |
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value: 46.51661307609861
|
| 13301 |
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- type: dot_recall
|
| 13302 |
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value: 96.12403100775194
|
| 13303 |
+
- type: euclidean_accuracy
|
| 13304 |
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value: 60.8
|
| 13305 |
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- type: euclidean_accuracy_threshold
|
| 13306 |
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value: 14.819307625293732
|
| 13307 |
+
- type: euclidean_ap
|
| 13308 |
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value: 60.50917425308617
|
| 13309 |
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- type: euclidean_f1
|
| 13310 |
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value: 62.69411339833874
|
| 13311 |
+
- type: euclidean_f1_threshold
|
| 13312 |
+
value: 31.07377290725708
|
| 13313 |
+
- type: euclidean_precision
|
| 13314 |
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value: 46.51661307609861
|
| 13315 |
+
- type: euclidean_recall
|
| 13316 |
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value: 96.12403100775194
|
| 13317 |
+
- type: main_score
|
| 13318 |
+
value: 60.73371250119265
|
| 13319 |
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- type: manhattan_accuracy
|
| 13320 |
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value: 60.9
|
| 13321 |
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- type: manhattan_accuracy_threshold
|
| 13322 |
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value: 354.8734188079834
|
| 13323 |
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- type: manhattan_ap
|
| 13324 |
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value: 60.73371250119265
|
| 13325 |
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- type: manhattan_f1
|
| 13326 |
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value: 62.70506744440393
|
| 13327 |
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- type: manhattan_f1_threshold
|
| 13328 |
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value: 711.578369140625
|
| 13329 |
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- type: manhattan_precision
|
| 13330 |
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value: 46.73913043478261
|
| 13331 |
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- type: manhattan_recall
|
| 13332 |
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value: 95.23809523809523
|
| 13333 |
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- type: max_ap
|
| 13334 |
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value: 60.73371250119265
|
| 13335 |
+
- type: max_f1
|
| 13336 |
+
value: 62.70506744440393
|
| 13337 |
+
- type: max_precision
|
| 13338 |
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value: 46.73913043478261
|
| 13339 |
+
- type: max_recall
|
| 13340 |
+
value: 96.12403100775194
|
| 13341 |
+
- type: similarity_accuracy
|
| 13342 |
+
value: 60.8
|
| 13343 |
+
- type: similarity_accuracy_threshold
|
| 13344 |
+
value: 98.90193939208984
|
| 13345 |
+
- type: similarity_ap
|
| 13346 |
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value: 60.50913122978733
|
| 13347 |
+
- type: similarity_f1
|
| 13348 |
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value: 62.69411339833874
|
| 13349 |
+
- type: similarity_f1_threshold
|
| 13350 |
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value: 95.17210125923157
|
| 13351 |
+
- type: similarity_precision
|
| 13352 |
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value: 46.51661307609861
|
| 13353 |
+
- type: similarity_recall
|
| 13354 |
+
value: 96.12403100775194
|
| 13355 |
+
task:
|
| 13356 |
+
type: PairClassification
|
| 13357 |
- dataset:
|
| 13358 |
config: default
|
| 13359 |
name: MTEB SICKFr
|
|
|
|
| 13381 |
value: 77.47140335069184
|
| 13382 |
task:
|
| 13383 |
type: STS
|
| 13384 |
+
- dataset:
|
| 13385 |
+
config: fr
|
| 13386 |
+
name: MTEB STS22 (fr)
|
| 13387 |
+
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
|
| 13388 |
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split: test
|
| 13389 |
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type: mteb/sts22-crosslingual-sts
|
| 13390 |
+
metrics:
|
| 13391 |
+
- type: cosine_pearson
|
| 13392 |
+
value: 77.1356210910051
|
| 13393 |
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- type: cosine_spearman
|
| 13394 |
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value: 81.7065039306575
|
| 13395 |
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- type: euclidean_pearson
|
| 13396 |
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value: 79.32575551712296
|
| 13397 |
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- type: euclidean_spearman
|
| 13398 |
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value: 81.75624482168821
|
| 13399 |
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- type: main_score
|
| 13400 |
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value: 81.7065039306575
|
| 13401 |
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- type: manhattan_pearson
|
| 13402 |
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value: 81.05436417153798
|
| 13403 |
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- type: manhattan_spearman
|
| 13404 |
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value: 82.13370902176736
|
| 13405 |
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- type: pearson
|
| 13406 |
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value: 77.1356210910051
|
| 13407 |
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- type: spearman
|
| 13408 |
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value: 81.7065039306575
|
| 13409 |
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task:
|
| 13410 |
+
type: STS
|
| 13411 |
+
- dataset:
|
| 13412 |
+
config: de-fr
|
| 13413 |
+
name: MTEB STS22 (de-fr)
|
| 13414 |
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revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
|
| 13415 |
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split: test
|
| 13416 |
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type: mteb/sts22-crosslingual-sts
|
| 13417 |
+
metrics:
|
| 13418 |
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- type: cosine_pearson
|
| 13419 |
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value: 61.40659325490285
|
| 13420 |
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- type: cosine_spearman
|
| 13421 |
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value: 64.21007088135842
|
| 13422 |
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- type: euclidean_pearson
|
| 13423 |
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value: 61.051174476106
|
| 13424 |
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- type: euclidean_spearman
|
| 13425 |
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value: 64.21007088135842
|
| 13426 |
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- type: main_score
|
| 13427 |
+
value: 64.21007088135842
|
| 13428 |
+
- type: manhattan_pearson
|
| 13429 |
+
value: 60.225817072214525
|
| 13430 |
+
- type: manhattan_spearman
|
| 13431 |
+
value: 64.32288638294209
|
| 13432 |
+
- type: pearson
|
| 13433 |
+
value: 61.40659325490285
|
| 13434 |
+
- type: spearman
|
| 13435 |
+
value: 64.21007088135842
|
| 13436 |
+
task:
|
| 13437 |
+
type: STS
|
| 13438 |
+
- dataset:
|
| 13439 |
+
config: fr-pl
|
| 13440 |
+
name: MTEB STS22 (fr-pl)
|
| 13441 |
+
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
|
| 13442 |
+
split: test
|
| 13443 |
+
type: mteb/sts22-crosslingual-sts
|
| 13444 |
+
metrics:
|
| 13445 |
+
- type: cosine_pearson
|
| 13446 |
+
value: 88.17138238483673
|
| 13447 |
+
- type: cosine_spearman
|
| 13448 |
+
value: 84.51542547285167
|
| 13449 |
+
- type: euclidean_pearson
|
| 13450 |
+
value: 87.99782696047525
|
| 13451 |
+
- type: euclidean_spearman
|
| 13452 |
+
value: 84.51542547285167
|
| 13453 |
+
- type: main_score
|
| 13454 |
+
value: 84.51542547285167
|
| 13455 |
+
- type: manhattan_pearson
|
| 13456 |
+
value: 85.811937669563
|
| 13457 |
+
- type: manhattan_spearman
|
| 13458 |
+
value: 84.51542547285167
|
| 13459 |
+
- type: pearson
|
| 13460 |
+
value: 88.17138238483673
|
| 13461 |
+
- type: spearman
|
| 13462 |
+
value: 84.51542547285167
|
| 13463 |
+
task:
|
| 13464 |
+
type: STS
|
| 13465 |
+
- dataset:
|
| 13466 |
+
config: fr
|
| 13467 |
+
name: MTEB STSBenchmarkMultilingualSTS (fr)
|
| 13468 |
+
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
|
| 13469 |
+
split: test
|
| 13470 |
+
type: mteb/stsb_multi_mt
|
| 13471 |
+
metrics:
|
| 13472 |
+
- type: cosine_pearson
|
| 13473 |
+
value: 79.98375089796882
|
| 13474 |
+
- type: cosine_spearman
|
| 13475 |
+
value: 81.06570417849169
|
| 13476 |
+
- type: euclidean_pearson
|
| 13477 |
+
value: 79.44759787417051
|
| 13478 |
+
- type: euclidean_spearman
|
| 13479 |
+
value: 81.06430479357311
|
| 13480 |
+
- type: main_score
|
| 13481 |
+
value: 81.06570417849169
|
| 13482 |
+
- type: manhattan_pearson
|
| 13483 |
+
value: 79.34683573713086
|
| 13484 |
+
- type: manhattan_spearman
|
| 13485 |
+
value: 81.00584846124926
|
| 13486 |
+
- type: pearson
|
| 13487 |
+
value: 79.98375089796882
|
| 13488 |
+
- type: spearman
|
| 13489 |
+
value: 81.06570417849169
|
| 13490 |
+
task:
|
| 13491 |
+
type: STS
|
| 13492 |
+
- dataset:
|
| 13493 |
+
config: default
|
| 13494 |
+
name: MTEB SummEvalFr
|
| 13495 |
+
revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
|
| 13496 |
+
split: test
|
| 13497 |
+
type: lyon-nlp/summarization-summeval-fr-p2p
|
| 13498 |
+
metrics:
|
| 13499 |
+
- type: cosine_pearson
|
| 13500 |
+
value: 31.198220154029464
|
| 13501 |
+
- type: cosine_spearman
|
| 13502 |
+
value: 30.886000528607877
|
| 13503 |
+
- type: dot_pearson
|
| 13504 |
+
value: 31.19822718500702
|
| 13505 |
+
- type: dot_spearman
|
| 13506 |
+
value: 30.86590068433314
|
| 13507 |
+
- type: main_score
|
| 13508 |
+
value: 30.886000528607877
|
| 13509 |
+
- type: pearson
|
| 13510 |
+
value: 31.198220154029464
|
| 13511 |
+
- type: spearman
|
| 13512 |
+
value: 30.886000528607877
|
| 13513 |
+
task:
|
| 13514 |
+
type: Summarization
|
| 13515 |
+
- dataset:
|
| 13516 |
+
config: default
|
| 13517 |
+
name: MTEB SyntecReranking
|
| 13518 |
+
revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
|
| 13519 |
+
split: test
|
| 13520 |
+
type: lyon-nlp/mteb-fr-reranking-syntec-s2p
|
| 13521 |
+
metrics:
|
| 13522 |
+
- type: main_score
|
| 13523 |
+
value: 86.6
|
| 13524 |
+
- type: map
|
| 13525 |
+
value: 86.6
|
| 13526 |
+
- type: mrr
|
| 13527 |
+
value: 86.6
|
| 13528 |
+
- type: nAUC_map_diff1
|
| 13529 |
+
value: 59.66160008216082
|
| 13530 |
+
- type: nAUC_map_max
|
| 13531 |
+
value: 19.768885092568734
|
| 13532 |
+
- type: nAUC_map_std
|
| 13533 |
+
value: 44.66975354255961
|
| 13534 |
+
- type: nAUC_mrr_diff1
|
| 13535 |
+
value: 59.66160008216082
|
| 13536 |
+
- type: nAUC_mrr_max
|
| 13537 |
+
value: 19.768885092568734
|
| 13538 |
+
- type: nAUC_mrr_std
|
| 13539 |
+
value: 44.66975354255961
|
| 13540 |
+
task:
|
| 13541 |
+
type: Reranking
|
| 13542 |
- dataset:
|
| 13543 |
config: default
|
| 13544 |
name: MTEB SyntecRetrieval
|