Upload folder using huggingface_hub

5030c76 verified 11 months ago

149 kB

	---
	language:
	- multilingual
	- af
	- am
	- ar
	- as
	- az
	- be
	- bg
	- bn
	- br
	- bs
	- ca
	- cs
	- cy
	- da
	- de
	- el
	- en
	- eo
	- es
	- et
	- eu
	- fa
	- fi
	- fr
	- fy
	- ga
	- gd
	- gl
	- gu
	- ha
	- he
	- hi
	- hr
	- hu
	- hy
	- id
	- is
	- it
	- ja
	- jv
	- ka
	- kk
	- km
	- kn
	- ko
	- ku
	- ky
	- la
	- lo
	- lt
	- lv
	- mg
	- mk
	- ml
	- mn
	- mr
	- ms
	- my
	- ne
	- nl
	- 'no'
	- om
	- or
	- pa
	- pl
	- ps
	- pt
	- ro
	- ru
	- sa
	- sd
	- si
	- sk
	- sl
	- so
	- sq
	- sr
	- su
	- sv
	- sw
	- ta
	- te
	- th
	- tl
	- tr
	- ug
	- uk
	- ur
	- uz
	- vi
	- xh
	- yi
	- zh
	license: mit
	tags:
	- mteb
	- Sentence Transformers
	- sentence-similarity
	- sentence-transformers
	- mlx
	model-index:
	- name: multilingual-e5-small
	results:
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonCounterfactualClassification (en)
	type: mteb/amazon_counterfactual
	config: en
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 73.79104477611939
	- type: ap
	value: 36.9996434842022
	- type: f1
	value: 67.95453679103099
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonCounterfactualClassification (de)
	type: mteb/amazon_counterfactual
	config: de
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 71.64882226980728
	- type: ap
	value: 82.11942130026586
	- type: f1
	value: 69.87963421606715
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonCounterfactualClassification (en-ext)
	type: mteb/amazon_counterfactual
	config: en-ext
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 75.8095952023988
	- type: ap
	value: 24.46869495579561
	- type: f1
	value: 63.00108480037597
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonCounterfactualClassification (ja)
	type: mteb/amazon_counterfactual
	config: ja
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 64.186295503212
	- type: ap
	value: 15.496804690197042
	- type: f1
	value: 52.07153895475031
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonPolarityClassification
	type: mteb/amazon_polarity
	config: default
	split: test
	revision: e2d317d38cd51312af73b3d32a06d1a08b442046
	metrics:
	- type: accuracy
	value: 88.699325
	- type: ap
	value: 85.27039559917269
	- type: f1
	value: 88.65556295032513
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (en)
	type: mteb/amazon_reviews_multi
	config: en
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 44.69799999999999
	- type: f1
	value: 43.73187348654165
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (de)
	type: mteb/amazon_reviews_multi
	config: de
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 40.245999999999995
	- type: f1
	value: 39.3863530637684
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (es)
	type: mteb/amazon_reviews_multi
	config: es
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 40.394
	- type: f1
	value: 39.301223469483446
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (fr)
	type: mteb/amazon_reviews_multi
	config: fr
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 38.864
	- type: f1
	value: 37.97974261868003
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (ja)
	type: mteb/amazon_reviews_multi
	config: ja
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 37.682
	- type: f1
	value: 37.07399369768313
	- task:
	type: Classification
	dataset:
	name: MTEB AmazonReviewsClassification (zh)
	type: mteb/amazon_reviews_multi
	config: zh
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 37.504
	- type: f1
	value: 36.62317273874278
	- task:
	type: Retrieval
	dataset:
	name: MTEB ArguAna
	type: arguana
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 19.061
	- type: map_at_10
	value: 31.703
	- type: map_at_100
	value: 32.967
	- type: map_at_1000
	value: 33.001000000000005
	- type: map_at_3
	value: 27.466
	- type: map_at_5
	value: 29.564
	- type: mrr_at_1
	value: 19.559
	- type: mrr_at_10
	value: 31.874999999999996
	- type: mrr_at_100
	value: 33.146
	- type: mrr_at_1000
	value: 33.18
	- type: mrr_at_3
	value: 27.667
	- type: mrr_at_5
	value: 29.74
	- type: ndcg_at_1
	value: 19.061
	- type: ndcg_at_10
	value: 39.062999999999995
	- type: ndcg_at_100
	value: 45.184000000000005
	- type: ndcg_at_1000
	value: 46.115
	- type: ndcg_at_3
	value: 30.203000000000003
	- type: ndcg_at_5
	value: 33.953
	- type: precision_at_1
	value: 19.061
	- type: precision_at_10
	value: 6.279999999999999
	- type: precision_at_100
	value: 0.9129999999999999
	- type: precision_at_1000
	value: 0.099
	- type: precision_at_3
	value: 12.706999999999999
	- type: precision_at_5
	value: 9.431000000000001
	- type: recall_at_1
	value: 19.061
	- type: recall_at_10
	value: 62.802
	- type: recall_at_100
	value: 91.323
	- type: recall_at_1000
	value: 98.72
	- type: recall_at_3
	value: 38.122
	- type: recall_at_5
	value: 47.155
	- task:
	type: Clustering
	dataset:
	name: MTEB ArxivClusteringP2P
	type: mteb/arxiv-clustering-p2p
	config: default
	split: test
	revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
	metrics:
	- type: v_measure
	value: 39.22266660528253
	- task:
	type: Clustering
	dataset:
	name: MTEB ArxivClusteringS2S
	type: mteb/arxiv-clustering-s2s
	config: default
	split: test
	revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
	metrics:
	- type: v_measure
	value: 30.79980849482483
	- task:
	type: Reranking
	dataset:
	name: MTEB AskUbuntuDupQuestions
	type: mteb/askubuntudupquestions-reranking
	config: default
	split: test
	revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
	metrics:
	- type: map
	value: 57.8790068352054
	- type: mrr
	value: 71.78791276436706
	- task:
	type: STS
	dataset:
	name: MTEB BIOSSES
	type: mteb/biosses-sts
	config: default
	split: test
	revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
	metrics:
	- type: cos_sim_pearson
	value: 82.36328364043163
	- type: cos_sim_spearman
	value: 82.26211536195868
	- type: euclidean_pearson
	value: 80.3183865039173
	- type: euclidean_spearman
	value: 79.88495276296132
	- type: manhattan_pearson
	value: 80.14484480692127
	- type: manhattan_spearman
	value: 80.39279565980743
	- task:
	type: BitextMining
	dataset:
	name: MTEB BUCC (de-en)
	type: mteb/bucc-bitext-mining
	config: de-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 98.0375782881002
	- type: f1
	value: 97.86012526096033
	- type: precision
	value: 97.77139874739039
	- type: recall
	value: 98.0375782881002
	- task:
	type: BitextMining
	dataset:
	name: MTEB BUCC (fr-en)
	type: mteb/bucc-bitext-mining
	config: fr-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 93.35241030156286
	- type: f1
	value: 92.66050333846944
	- type: precision
	value: 92.3306919069631
	- type: recall
	value: 93.35241030156286
	- task:
	type: BitextMining
	dataset:
	name: MTEB BUCC (ru-en)
	type: mteb/bucc-bitext-mining
	config: ru-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 94.0699688257707
	- type: f1
	value: 93.50236693222492
	- type: precision
	value: 93.22791825424315
	- type: recall
	value: 94.0699688257707
	- task:
	type: BitextMining
	dataset:
	name: MTEB BUCC (zh-en)
	type: mteb/bucc-bitext-mining
	config: zh-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 89.25750394944708
	- type: f1
	value: 88.79234684921889
	- type: precision
	value: 88.57293312269616
	- type: recall
	value: 89.25750394944708
	- task:
	type: Classification
	dataset:
	name: MTEB Banking77Classification
	type: mteb/banking77
	config: default
	split: test
	revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
	metrics:
	- type: accuracy
	value: 79.41558441558442
	- type: f1
	value: 79.25886487487219
	- task:
	type: Clustering
	dataset:
	name: MTEB BiorxivClusteringP2P
	type: mteb/biorxiv-clustering-p2p
	config: default
	split: test
	revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
	metrics:
	- type: v_measure
	value: 35.747820820329736
	- task:
	type: Clustering
	dataset:
	name: MTEB BiorxivClusteringS2S
	type: mteb/biorxiv-clustering-s2s
	config: default
	split: test
	revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
	metrics:
	- type: v_measure
	value: 27.045143830596146
	- task:
	type: Retrieval
	dataset:
	name: MTEB CQADupstackRetrieval
	type: BeIR/cqadupstack
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 24.252999999999997
	- type: map_at_10
	value: 31.655916666666666
	- type: map_at_100
	value: 32.680749999999996
	- type: map_at_1000
	value: 32.79483333333334
	- type: map_at_3
	value: 29.43691666666666
	- type: map_at_5
	value: 30.717416666666665
	- type: mrr_at_1
	value: 28.602750000000004
	- type: mrr_at_10
	value: 35.56875
	- type: mrr_at_100
	value: 36.3595
	- type: mrr_at_1000
	value: 36.427749999999996
	- type: mrr_at_3
	value: 33.586166666666664
	- type: mrr_at_5
	value: 34.73641666666666
	- type: ndcg_at_1
	value: 28.602750000000004
	- type: ndcg_at_10
	value: 36.06933333333334
	- type: ndcg_at_100
	value: 40.70141666666667
	- type: ndcg_at_1000
	value: 43.24341666666667
	- type: ndcg_at_3
	value: 32.307916666666664
	- type: ndcg_at_5
	value: 34.129999999999995
	- type: precision_at_1
	value: 28.602750000000004
	- type: precision_at_10
	value: 6.097666666666667
	- type: precision_at_100
	value: 0.9809166666666668
	- type: precision_at_1000
	value: 0.13766666666666663
	- type: precision_at_3
	value: 14.628166666666667
	- type: precision_at_5
	value: 10.266916666666667
	- type: recall_at_1
	value: 24.252999999999997
	- type: recall_at_10
	value: 45.31916666666667
	- type: recall_at_100
	value: 66.03575000000001
	- type: recall_at_1000
	value: 83.94708333333334
	- type: recall_at_3
	value: 34.71941666666666
	- type: recall_at_5
	value: 39.46358333333333
	- task:
	type: Retrieval
	dataset:
	name: MTEB ClimateFEVER
	type: climate-fever
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 9.024000000000001
	- type: map_at_10
	value: 15.644
	- type: map_at_100
	value: 17.154
	- type: map_at_1000
	value: 17.345
	- type: map_at_3
	value: 13.028
	- type: map_at_5
	value: 14.251
	- type: mrr_at_1
	value: 19.674
	- type: mrr_at_10
	value: 29.826999999999998
	- type: mrr_at_100
	value: 30.935000000000002
	- type: mrr_at_1000
	value: 30.987
	- type: mrr_at_3
	value: 26.645000000000003
	- type: mrr_at_5
	value: 28.29
	- type: ndcg_at_1
	value: 19.674
	- type: ndcg_at_10
	value: 22.545
	- type: ndcg_at_100
	value: 29.207
	- type: ndcg_at_1000
	value: 32.912
	- type: ndcg_at_3
	value: 17.952
	- type: ndcg_at_5
	value: 19.363
	- type: precision_at_1
	value: 19.674
	- type: precision_at_10
	value: 7.212000000000001
	- type: precision_at_100
	value: 1.435
	- type: precision_at_1000
	value: 0.212
	- type: precision_at_3
	value: 13.507
	- type: precision_at_5
	value: 10.397
	- type: recall_at_1
	value: 9.024000000000001
	- type: recall_at_10
	value: 28.077999999999996
	- type: recall_at_100
	value: 51.403
	- type: recall_at_1000
	value: 72.406
	- type: recall_at_3
	value: 16.768
	- type: recall_at_5
	value: 20.737
	- task:
	type: Retrieval
	dataset:
	name: MTEB DBPedia
	type: dbpedia-entity
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 8.012
	- type: map_at_10
	value: 17.138
	- type: map_at_100
	value: 24.146
	- type: map_at_1000
	value: 25.622
	- type: map_at_3
	value: 12.552
	- type: map_at_5
	value: 14.435
	- type: mrr_at_1
	value: 62.25000000000001
	- type: mrr_at_10
	value: 71.186
	- type: mrr_at_100
	value: 71.504
	- type: mrr_at_1000
	value: 71.514
	- type: mrr_at_3
	value: 69.333
	- type: mrr_at_5
	value: 70.408
	- type: ndcg_at_1
	value: 49.75
	- type: ndcg_at_10
	value: 37.76
	- type: ndcg_at_100
	value: 42.071
	- type: ndcg_at_1000
	value: 49.309
	- type: ndcg_at_3
	value: 41.644
	- type: ndcg_at_5
	value: 39.812999999999995
	- type: precision_at_1
	value: 62.25000000000001
	- type: precision_at_10
	value: 30.15
	- type: precision_at_100
	value: 9.753
	- type: precision_at_1000
	value: 1.9189999999999998
	- type: precision_at_3
	value: 45.667
	- type: precision_at_5
	value: 39.15
	- type: recall_at_1
	value: 8.012
	- type: recall_at_10
	value: 22.599
	- type: recall_at_100
	value: 48.068
	- type: recall_at_1000
	value: 71.328
	- type: recall_at_3
	value: 14.043
	- type: recall_at_5
	value: 17.124
	- task:
	type: Classification
	dataset:
	name: MTEB EmotionClassification
	type: mteb/emotion
	config: default
	split: test
	revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
	metrics:
	- type: accuracy
	value: 42.455
	- type: f1
	value: 37.59462649781862
	- task:
	type: Retrieval
	dataset:
	name: MTEB FEVER
	type: fever
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 58.092
	- type: map_at_10
	value: 69.586
	- type: map_at_100
	value: 69.968
	- type: map_at_1000
	value: 69.982
	- type: map_at_3
	value: 67.48100000000001
	- type: map_at_5
	value: 68.915
	- type: mrr_at_1
	value: 62.166
	- type: mrr_at_10
	value: 73.588
	- type: mrr_at_100
	value: 73.86399999999999
	- type: mrr_at_1000
	value: 73.868
	- type: mrr_at_3
	value: 71.6
	- type: mrr_at_5
	value: 72.99
	- type: ndcg_at_1
	value: 62.166
	- type: ndcg_at_10
	value: 75.27199999999999
	- type: ndcg_at_100
	value: 76.816
	- type: ndcg_at_1000
	value: 77.09700000000001
	- type: ndcg_at_3
	value: 71.36
	- type: ndcg_at_5
	value: 73.785
	- type: precision_at_1
	value: 62.166
	- type: precision_at_10
	value: 9.716
	- type: precision_at_100
	value: 1.065
	- type: precision_at_1000
	value: 0.11
	- type: precision_at_3
	value: 28.278
	- type: precision_at_5
	value: 18.343999999999998
	- type: recall_at_1
	value: 58.092
	- type: recall_at_10
	value: 88.73400000000001
	- type: recall_at_100
	value: 95.195
	- type: recall_at_1000
	value: 97.04599999999999
	- type: recall_at_3
	value: 78.45
	- type: recall_at_5
	value: 84.316
	- task:
	type: Retrieval
	dataset:
	name: MTEB FiQA2018
	type: fiqa
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 16.649
	- type: map_at_10
	value: 26.457000000000004
	- type: map_at_100
	value: 28.169
	- type: map_at_1000
	value: 28.352
	- type: map_at_3
	value: 23.305
	- type: map_at_5
	value: 25.169000000000004
	- type: mrr_at_1
	value: 32.407000000000004
	- type: mrr_at_10
	value: 40.922
	- type: mrr_at_100
	value: 41.931000000000004
	- type: mrr_at_1000
	value: 41.983
	- type: mrr_at_3
	value: 38.786
	- type: mrr_at_5
	value: 40.205999999999996
	- type: ndcg_at_1
	value: 32.407000000000004
	- type: ndcg_at_10
	value: 33.314
	- type: ndcg_at_100
	value: 40.312
	- type: ndcg_at_1000
	value: 43.685
	- type: ndcg_at_3
	value: 30.391000000000002
	- type: ndcg_at_5
	value: 31.525
	- type: precision_at_1
	value: 32.407000000000004
	- type: precision_at_10
	value: 8.966000000000001
	- type: precision_at_100
	value: 1.6019999999999999
	- type: precision_at_1000
	value: 0.22200000000000003
	- type: precision_at_3
	value: 20.165
	- type: precision_at_5
	value: 14.722
	- type: recall_at_1
	value: 16.649
	- type: recall_at_10
	value: 39.117000000000004
	- type: recall_at_100
	value: 65.726
	- type: recall_at_1000
	value: 85.784
	- type: recall_at_3
	value: 27.914
	- type: recall_at_5
	value: 33.289
	- task:
	type: Retrieval
	dataset:
	name: MTEB HotpotQA
	type: hotpotqa
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 36.253
	- type: map_at_10
	value: 56.16799999999999
	- type: map_at_100
	value: 57.06099999999999
	- type: map_at_1000
	value: 57.126
	- type: map_at_3
	value: 52.644999999999996
	- type: map_at_5
	value: 54.909
	- type: mrr_at_1
	value: 72.505
	- type: mrr_at_10
	value: 79.66
	- type: mrr_at_100
	value: 79.869
	- type: mrr_at_1000
	value: 79.88
	- type: mrr_at_3
	value: 78.411
	- type: mrr_at_5
	value: 79.19800000000001
	- type: ndcg_at_1
	value: 72.505
	- type: ndcg_at_10
	value: 65.094
	- type: ndcg_at_100
	value: 68.219
	- type: ndcg_at_1000
	value: 69.515
	- type: ndcg_at_3
	value: 59.99
	- type: ndcg_at_5
	value: 62.909000000000006
	- type: precision_at_1
	value: 72.505
	- type: precision_at_10
	value: 13.749
	- type: precision_at_100
	value: 1.619
	- type: precision_at_1000
	value: 0.179
	- type: precision_at_3
	value: 38.357
	- type: precision_at_5
	value: 25.313000000000002
	- type: recall_at_1
	value: 36.253
	- type: recall_at_10
	value: 68.744
	- type: recall_at_100
	value: 80.925
	- type: recall_at_1000
	value: 89.534
	- type: recall_at_3
	value: 57.535000000000004
	- type: recall_at_5
	value: 63.282000000000004
	- task:
	type: Classification
	dataset:
	name: MTEB ImdbClassification
	type: mteb/imdb
	config: default
	split: test
	revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
	metrics:
	- type: accuracy
	value: 80.82239999999999
	- type: ap
	value: 75.65895781725314
	- type: f1
	value: 80.75880969095746
	- task:
	type: Retrieval
	dataset:
	name: MTEB MSMARCO
	type: msmarco
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 21.624
	- type: map_at_10
	value: 34.075
	- type: map_at_100
	value: 35.229
	- type: map_at_1000
	value: 35.276999999999994
	- type: map_at_3
	value: 30.245
	- type: map_at_5
	value: 32.42
	- type: mrr_at_1
	value: 22.264
	- type: mrr_at_10
	value: 34.638000000000005
	- type: mrr_at_100
	value: 35.744
	- type: mrr_at_1000
	value: 35.787
	- type: mrr_at_3
	value: 30.891000000000002
	- type: mrr_at_5
	value: 33.042
	- type: ndcg_at_1
	value: 22.264
	- type: ndcg_at_10
	value: 40.991
	- type: ndcg_at_100
	value: 46.563
	- type: ndcg_at_1000
	value: 47.743
	- type: ndcg_at_3
	value: 33.198
	- type: ndcg_at_5
	value: 37.069
	- type: precision_at_1
	value: 22.264
	- type: precision_at_10
	value: 6.5089999999999995
	- type: precision_at_100
	value: 0.9299999999999999
	- type: precision_at_1000
	value: 0.10300000000000001
	- type: precision_at_3
	value: 14.216999999999999
	- type: precision_at_5
	value: 10.487
	- type: recall_at_1
	value: 21.624
	- type: recall_at_10
	value: 62.303
	- type: recall_at_100
	value: 88.124
	- type: recall_at_1000
	value: 97.08
	- type: recall_at_3
	value: 41.099999999999994
	- type: recall_at_5
	value: 50.381
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (en)
	type: mteb/mtop_domain
	config: en
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 91.06703146374831
	- type: f1
	value: 90.86867815863172
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (de)
	type: mteb/mtop_domain
	config: de
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 87.46970977740209
	- type: f1
	value: 86.36832872036588
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (es)
	type: mteb/mtop_domain
	config: es
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 89.26951300867245
	- type: f1
	value: 88.93561193959502
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (fr)
	type: mteb/mtop_domain
	config: fr
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 84.22799874725963
	- type: f1
	value: 84.30490069236556
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (hi)
	type: mteb/mtop_domain
	config: hi
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 86.02007888131948
	- type: f1
	value: 85.39376041027991
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPDomainClassification (th)
	type: mteb/mtop_domain
	config: th
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 85.34900542495481
	- type: f1
	value: 85.39859673336713
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (en)
	type: mteb/mtop_intent
	config: en
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 71.078431372549
	- type: f1
	value: 53.45071102002276
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (de)
	type: mteb/mtop_intent
	config: de
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 65.85798816568047
	- type: f1
	value: 46.53112748993529
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (es)
	type: mteb/mtop_intent
	config: es
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 67.96864576384256
	- type: f1
	value: 45.966703022829506
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (fr)
	type: mteb/mtop_intent
	config: fr
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 61.31537738803633
	- type: f1
	value: 45.52601712835461
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (hi)
	type: mteb/mtop_intent
	config: hi
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 66.29616349946218
	- type: f1
	value: 47.24166485726613
	- task:
	type: Classification
	dataset:
	name: MTEB MTOPIntentClassification (th)
	type: mteb/mtop_intent
	config: th
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 67.51537070524412
	- type: f1
	value: 49.463476319014276
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (af)
	type: mteb/amazon_massive_intent
	config: af
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.06792199058508
	- type: f1
	value: 54.094921857502285
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (am)
	type: mteb/amazon_massive_intent
	config: am
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 51.960322797579025
	- type: f1
	value: 48.547371223370945
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ar)
	type: mteb/amazon_massive_intent
	config: ar
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 54.425016812373904
	- type: f1
	value: 50.47069202054312
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (az)
	type: mteb/amazon_massive_intent
	config: az
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 59.798251513113655
	- type: f1
	value: 57.05013069086648
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (bn)
	type: mteb/amazon_massive_intent
	config: bn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 59.37794216543376
	- type: f1
	value: 56.3607992649805
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (cy)
	type: mteb/amazon_massive_intent
	config: cy
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 46.56018829858777
	- type: f1
	value: 43.87319715715134
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (da)
	type: mteb/amazon_massive_intent
	config: da
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 62.9724277067922
	- type: f1
	value: 59.36480066245562
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (de)
	type: mteb/amazon_massive_intent
	config: de
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 62.72696704774715
	- type: f1
	value: 59.143595966615855
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (el)
	type: mteb/amazon_massive_intent
	config: el
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 61.5971755211836
	- type: f1
	value: 59.169445724946726
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (en)
	type: mteb/amazon_massive_intent
	config: en
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 70.29589778076665
	- type: f1
	value: 67.7577001808977
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (es)
	type: mteb/amazon_massive_intent
	config: es
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 66.31136516476126
	- type: f1
	value: 64.52032955983242
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (fa)
	type: mteb/amazon_massive_intent
	config: fa
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.54472091459314
	- type: f1
	value: 61.47903120066317
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (fi)
	type: mteb/amazon_massive_intent
	config: fi
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 61.45595158036314
	- type: f1
	value: 58.0891846024637
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (fr)
	type: mteb/amazon_massive_intent
	config: fr
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.47074646940149
	- type: f1
	value: 62.84830858877575
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (he)
	type: mteb/amazon_massive_intent
	config: he
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 58.046402151983855
	- type: f1
	value: 55.269074430533195
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (hi)
	type: mteb/amazon_massive_intent
	config: hi
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 64.06523201075991
	- type: f1
	value: 61.35339643021369
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (hu)
	type: mteb/amazon_massive_intent
	config: hu
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 60.954942837928726
	- type: f1
	value: 57.07035922704846
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (hy)
	type: mteb/amazon_massive_intent
	config: hy
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.404169468728995
	- type: f1
	value: 53.94259011839138
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (id)
	type: mteb/amazon_massive_intent
	config: id
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 64.16610625420309
	- type: f1
	value: 61.337103431499365
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (is)
	type: mteb/amazon_massive_intent
	config: is
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 52.262945527908535
	- type: f1
	value: 49.7610691598921
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (it)
	type: mteb/amazon_massive_intent
	config: it
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.54472091459314
	- type: f1
	value: 63.469099018440154
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ja)
	type: mteb/amazon_massive_intent
	config: ja
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 68.22797579018157
	- type: f1
	value: 64.89098471083001
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (jv)
	type: mteb/amazon_massive_intent
	config: jv
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 50.847343644922674
	- type: f1
	value: 47.8536963168393
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ka)
	type: mteb/amazon_massive_intent
	config: ka
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 48.45326160053799
	- type: f1
	value: 46.370078045805556
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (km)
	type: mteb/amazon_massive_intent
	config: km
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 42.83120376597175
	- type: f1
	value: 39.68948521599982
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (kn)
	type: mteb/amazon_massive_intent
	config: kn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.5084061869536
	- type: f1
	value: 53.961876160401545
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ko)
	type: mteb/amazon_massive_intent
	config: ko
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 63.7895090786819
	- type: f1
	value: 61.134223684676
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (lv)
	type: mteb/amazon_massive_intent
	config: lv
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 54.98991257565569
	- type: f1
	value: 52.579862862826296
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ml)
	type: mteb/amazon_massive_intent
	config: ml
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 61.90316072629456
	- type: f1
	value: 58.203024538290336
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (mn)
	type: mteb/amazon_massive_intent
	config: mn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.09818426361802
	- type: f1
	value: 54.22718458445455
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ms)
	type: mteb/amazon_massive_intent
	config: ms
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 58.991257565568255
	- type: f1
	value: 55.84892781767421
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (my)
	type: mteb/amazon_massive_intent
	config: my
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 55.901143241425686
	- type: f1
	value: 52.25264332199797
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (nb)
	type: mteb/amazon_massive_intent
	config: nb
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 61.96368527236047
	- type: f1
	value: 58.927243876153454
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (nl)
	type: mteb/amazon_massive_intent
	config: nl
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.64223268325489
	- type: f1
	value: 62.340453718379706
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (pl)
	type: mteb/amazon_massive_intent
	config: pl
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 64.52589105581708
	- type: f1
	value: 61.661113187022174
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (pt)
	type: mteb/amazon_massive_intent
	config: pt
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 66.84599865501009
	- type: f1
	value: 64.59342572873005
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ro)
	type: mteb/amazon_massive_intent
	config: ro
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 60.81035642232684
	- type: f1
	value: 57.5169089806797
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ru)
	type: mteb/amazon_massive_intent
	config: ru
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.75991930060525
	- type: f1
	value: 62.89531115787938
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (sl)
	type: mteb/amazon_massive_intent
	config: sl
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 56.51647612642906
	- type: f1
	value: 54.33154780100043
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (sq)
	type: mteb/amazon_massive_intent
	config: sq
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.985877605917956
	- type: f1
	value: 54.46187524463802
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (sv)
	type: mteb/amazon_massive_intent
	config: sv
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 65.03026227303296
	- type: f1
	value: 62.34377392877748
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (sw)
	type: mteb/amazon_massive_intent
	config: sw
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 53.567585743106925
	- type: f1
	value: 50.73770655983206
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ta)
	type: mteb/amazon_massive_intent
	config: ta
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.2595830531271
	- type: f1
	value: 53.657327291708626
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (te)
	type: mteb/amazon_massive_intent
	config: te
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 57.82784129119032
	- type: f1
	value: 54.82518072665301
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (th)
	type: mteb/amazon_massive_intent
	config: th
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 64.06859448554137
	- type: f1
	value: 63.00185280500495
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (tl)
	type: mteb/amazon_massive_intent
	config: tl
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 58.91055817081371
	- type: f1
	value: 55.54116301224262
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (tr)
	type: mteb/amazon_massive_intent
	config: tr
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 63.54404841963686
	- type: f1
	value: 59.57650946030184
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (ur)
	type: mteb/amazon_massive_intent
	config: ur
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 59.27706792199059
	- type: f1
	value: 56.50010066083435
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (vi)
	type: mteb/amazon_massive_intent
	config: vi
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 64.0719569603228
	- type: f1
	value: 61.817075925647956
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (zh-CN)
	type: mteb/amazon_massive_intent
	config: zh-CN
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 68.23806321452591
	- type: f1
	value: 65.24917026029749
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveIntentClassification (zh-TW)
	type: mteb/amazon_massive_intent
	config: zh-TW
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 62.53530598520511
	- type: f1
	value: 61.71131132295768
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (af)
	type: mteb/amazon_massive_scenario
	config: af
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 63.04303967720243
	- type: f1
	value: 60.3950085685985
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (am)
	type: mteb/amazon_massive_scenario
	config: am
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 56.83591123066578
	- type: f1
	value: 54.95059828830849
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ar)
	type: mteb/amazon_massive_scenario
	config: ar
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 59.62340282447881
	- type: f1
	value: 59.525159996498225
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (az)
	type: mteb/amazon_massive_scenario
	config: az
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 60.85406859448555
	- type: f1
	value: 59.129299095681276
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (bn)
	type: mteb/amazon_massive_scenario
	config: bn
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 62.76731674512441
	- type: f1
	value: 61.159560612627715
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (cy)
	type: mteb/amazon_massive_scenario
	config: cy
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 50.181573638197705
	- type: f1
	value: 46.98422176289957
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (da)
	type: mteb/amazon_massive_scenario
	config: da
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.92737054472092
	- type: f1
	value: 67.69135611952979
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (de)
	type: mteb/amazon_massive_scenario
	config: de
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 69.18964357767318
	- type: f1
	value: 68.46106138186214
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (el)
	type: mteb/amazon_massive_scenario
	config: el
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 67.0712844653665
	- type: f1
	value: 66.75545422473901
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (en)
	type: mteb/amazon_massive_scenario
	config: en
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 74.4754539340955
	- type: f1
	value: 74.38427146553252
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (es)
	type: mteb/amazon_massive_scenario
	config: es
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 69.82515131136518
	- type: f1
	value: 69.63516462173847
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (fa)
	type: mteb/amazon_massive_scenario
	config: fa
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.70880968392737
	- type: f1
	value: 67.45420662567926
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (fi)
	type: mteb/amazon_massive_scenario
	config: fi
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 65.95494283792871
	- type: f1
	value: 65.06191009049222
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (fr)
	type: mteb/amazon_massive_scenario
	config: fr
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.75924680564896
	- type: f1
	value: 68.30833379585945
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (he)
	type: mteb/amazon_massive_scenario
	config: he
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 63.806321452589096
	- type: f1
	value: 63.273048243765054
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (hi)
	type: mteb/amazon_massive_scenario
	config: hi
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 67.68997982515133
	- type: f1
	value: 66.54703855381324
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (hu)
	type: mteb/amazon_massive_scenario
	config: hu
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 66.46940147948891
	- type: f1
	value: 65.91017343463396
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (hy)
	type: mteb/amazon_massive_scenario
	config: hy
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 59.49899125756556
	- type: f1
	value: 57.90333469917769
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (id)
	type: mteb/amazon_massive_scenario
	config: id
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 67.9219905850706
	- type: f1
	value: 67.23169403762938
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (is)
	type: mteb/amazon_massive_scenario
	config: is
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 56.486213853396094
	- type: f1
	value: 54.85282355583758
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (it)
	type: mteb/amazon_massive_scenario
	config: it
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 69.04169468728985
	- type: f1
	value: 68.83833333320462
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ja)
	type: mteb/amazon_massive_scenario
	config: ja
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 73.88702084734365
	- type: f1
	value: 74.04474735232299
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (jv)
	type: mteb/amazon_massive_scenario
	config: jv
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 56.63416274377943
	- type: f1
	value: 55.11332211687954
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ka)
	type: mteb/amazon_massive_scenario
	config: ka
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 52.23604572965702
	- type: f1
	value: 50.86529813991055
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (km)
	type: mteb/amazon_massive_scenario
	config: km
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 46.62407531943511
	- type: f1
	value: 43.63485467164535
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (kn)
	type: mteb/amazon_massive_scenario
	config: kn
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 59.15601882985878
	- type: f1
	value: 57.522837510959924
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ko)
	type: mteb/amazon_massive_scenario
	config: ko
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 69.84532616005382
	- type: f1
	value: 69.60021127179697
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (lv)
	type: mteb/amazon_massive_scenario
	config: lv
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 56.65770006724949
	- type: f1
	value: 55.84219135523227
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ml)
	type: mteb/amazon_massive_scenario
	config: ml
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 66.53665097511768
	- type: f1
	value: 65.09087787792639
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (mn)
	type: mteb/amazon_massive_scenario
	config: mn
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 59.31405514458642
	- type: f1
	value: 58.06135303831491
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ms)
	type: mteb/amazon_massive_scenario
	config: ms
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 64.88231338264964
	- type: f1
	value: 62.751099407787926
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (my)
	type: mteb/amazon_massive_scenario
	config: my
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 58.86012104909213
	- type: f1
	value: 56.29118323058282
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (nb)
	type: mteb/amazon_massive_scenario
	config: nb
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 67.37390719569602
	- type: f1
	value: 66.27922244885102
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (nl)
	type: mteb/amazon_massive_scenario
	config: nl
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 70.8675184936113
	- type: f1
	value: 70.22146529932019
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (pl)
	type: mteb/amazon_massive_scenario
	config: pl
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.2212508406187
	- type: f1
	value: 67.77454802056282
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (pt)
	type: mteb/amazon_massive_scenario
	config: pt
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.18090114324143
	- type: f1
	value: 68.03737625431621
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ro)
	type: mteb/amazon_massive_scenario
	config: ro
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 64.65030262273034
	- type: f1
	value: 63.792945486912856
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ru)
	type: mteb/amazon_massive_scenario
	config: ru
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 69.48217888365838
	- type: f1
	value: 69.96028997292197
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (sl)
	type: mteb/amazon_massive_scenario
	config: sl
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 60.17821116341627
	- type: f1
	value: 59.3935969827171
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (sq)
	type: mteb/amazon_massive_scenario
	config: sq
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 62.86146603900471
	- type: f1
	value: 60.133692735032376
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (sv)
	type: mteb/amazon_massive_scenario
	config: sv
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 70.89441829186282
	- type: f1
	value: 70.03064076194089
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (sw)
	type: mteb/amazon_massive_scenario
	config: sw
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 58.15063887020847
	- type: f1
	value: 56.23326278499678
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ta)
	type: mteb/amazon_massive_scenario
	config: ta
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 59.43846671149966
	- type: f1
	value: 57.70440450281974
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (te)
	type: mteb/amazon_massive_scenario
	config: te
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 60.8507061197041
	- type: f1
	value: 59.22916396061171
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (th)
	type: mteb/amazon_massive_scenario
	config: th
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 70.65568258238063
	- type: f1
	value: 69.90736239440633
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (tl)
	type: mteb/amazon_massive_scenario
	config: tl
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 60.8843308675185
	- type: f1
	value: 59.30332663713599
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (tr)
	type: mteb/amazon_massive_scenario
	config: tr
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.05312710154674
	- type: f1
	value: 67.44024062594775
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (ur)
	type: mteb/amazon_massive_scenario
	config: ur
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 62.111634162743776
	- type: f1
	value: 60.89083013084519
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (vi)
	type: mteb/amazon_massive_scenario
	config: vi
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 67.44115669132482
	- type: f1
	value: 67.92227541674552
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (zh-CN)
	type: mteb/amazon_massive_scenario
	config: zh-CN
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 74.4687289845326
	- type: f1
	value: 74.16376793486025
	- task:
	type: Classification
	dataset:
	name: MTEB MassiveScenarioClassification (zh-TW)
	type: mteb/amazon_massive_scenario
	config: zh-TW
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 68.31876260928043
	- type: f1
	value: 68.5246745215607
	- task:
	type: Clustering
	dataset:
	name: MTEB MedrxivClusteringP2P
	type: mteb/medrxiv-clustering-p2p
	config: default
	split: test
	revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
	metrics:
	- type: v_measure
	value: 30.90431696479766
	- task:
	type: Clustering
	dataset:
	name: MTEB MedrxivClusteringS2S
	type: mteb/medrxiv-clustering-s2s
	config: default
	split: test
	revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
	metrics:
	- type: v_measure
	value: 27.259158476693774
	- task:
	type: Reranking
	dataset:
	name: MTEB MindSmallReranking
	type: mteb/mind_small
	config: default
	split: test
	revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
	metrics:
	- type: map
	value: 30.28445330838555
	- type: mrr
	value: 31.15758529581164
	- task:
	type: Retrieval
	dataset:
	name: MTEB NFCorpus
	type: nfcorpus
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 5.353
	- type: map_at_10
	value: 11.565
	- type: map_at_100
	value: 14.097000000000001
	- type: map_at_1000
	value: 15.354999999999999
	- type: map_at_3
	value: 8.749
	- type: map_at_5
	value: 9.974
	- type: mrr_at_1
	value: 42.105
	- type: mrr_at_10
	value: 50.589
	- type: mrr_at_100
	value: 51.187000000000005
	- type: mrr_at_1000
	value: 51.233
	- type: mrr_at_3
	value: 48.246
	- type: mrr_at_5
	value: 49.546
	- type: ndcg_at_1
	value: 40.402
	- type: ndcg_at_10
	value: 31.009999999999998
	- type: ndcg_at_100
	value: 28.026
	- type: ndcg_at_1000
	value: 36.905
	- type: ndcg_at_3
	value: 35.983
	- type: ndcg_at_5
	value: 33.764
	- type: precision_at_1
	value: 42.105
	- type: precision_at_10
	value: 22.786
	- type: precision_at_100
	value: 6.916
	- type: precision_at_1000
	value: 1.981
	- type: precision_at_3
	value: 33.333
	- type: precision_at_5
	value: 28.731
	- type: recall_at_1
	value: 5.353
	- type: recall_at_10
	value: 15.039
	- type: recall_at_100
	value: 27.348
	- type: recall_at_1000
	value: 59.453
	- type: recall_at_3
	value: 9.792
	- type: recall_at_5
	value: 11.882
	- task:
	type: Retrieval
	dataset:
	name: MTEB NQ
	type: nq
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 33.852
	- type: map_at_10
	value: 48.924
	- type: map_at_100
	value: 49.854
	- type: map_at_1000
	value: 49.886
	- type: map_at_3
	value: 44.9
	- type: map_at_5
	value: 47.387
	- type: mrr_at_1
	value: 38.035999999999994
	- type: mrr_at_10
	value: 51.644
	- type: mrr_at_100
	value: 52.339
	- type: mrr_at_1000
	value: 52.35999999999999
	- type: mrr_at_3
	value: 48.421
	- type: mrr_at_5
	value: 50.468999999999994
	- type: ndcg_at_1
	value: 38.007000000000005
	- type: ndcg_at_10
	value: 56.293000000000006
	- type: ndcg_at_100
	value: 60.167
	- type: ndcg_at_1000
	value: 60.916000000000004
	- type: ndcg_at_3
	value: 48.903999999999996
	- type: ndcg_at_5
	value: 52.978
	- type: precision_at_1
	value: 38.007000000000005
	- type: precision_at_10
	value: 9.041
	- type: precision_at_100
	value: 1.1199999999999999
	- type: precision_at_1000
	value: 0.11900000000000001
	- type: precision_at_3
	value: 22.084
	- type: precision_at_5
	value: 15.608
	- type: recall_at_1
	value: 33.852
	- type: recall_at_10
	value: 75.893
	- type: recall_at_100
	value: 92.589
	- type: recall_at_1000
	value: 98.153
	- type: recall_at_3
	value: 56.969
	- type: recall_at_5
	value: 66.283
	- task:
	type: Retrieval
	dataset:
	name: MTEB QuoraRetrieval
	type: quora
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 69.174
	- type: map_at_10
	value: 82.891
	- type: map_at_100
	value: 83.545
	- type: map_at_1000
	value: 83.56700000000001
	- type: map_at_3
	value: 79.944
	- type: map_at_5
	value: 81.812
	- type: mrr_at_1
	value: 79.67999999999999
	- type: mrr_at_10
	value: 86.279
	- type: mrr_at_100
	value: 86.39
	- type: mrr_at_1000
	value: 86.392
	- type: mrr_at_3
	value: 85.21
	- type: mrr_at_5
	value: 85.92999999999999
	- type: ndcg_at_1
	value: 79.69000000000001
	- type: ndcg_at_10
	value: 86.929
	- type: ndcg_at_100
	value: 88.266
	- type: ndcg_at_1000
	value: 88.428
	- type: ndcg_at_3
	value: 83.899
	- type: ndcg_at_5
	value: 85.56700000000001
	- type: precision_at_1
	value: 79.69000000000001
	- type: precision_at_10
	value: 13.161000000000001
	- type: precision_at_100
	value: 1.513
	- type: precision_at_1000
	value: 0.156
	- type: precision_at_3
	value: 36.603
	- type: precision_at_5
	value: 24.138
	- type: recall_at_1
	value: 69.174
	- type: recall_at_10
	value: 94.529
	- type: recall_at_100
	value: 99.15
	- type: recall_at_1000
	value: 99.925
	- type: recall_at_3
	value: 85.86200000000001
	- type: recall_at_5
	value: 90.501
	- task:
	type: Clustering
	dataset:
	name: MTEB RedditClustering
	type: mteb/reddit-clustering
	config: default
	split: test
	revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
	metrics:
	- type: v_measure
	value: 39.13064340585255
	- task:
	type: Clustering
	dataset:
	name: MTEB RedditClusteringP2P
	type: mteb/reddit-clustering-p2p
	config: default
	split: test
	revision: 282350215ef01743dc01b456c7f5241fa8937f16
	metrics:
	- type: v_measure
	value: 58.97884249325877
	- task:
	type: Retrieval
	dataset:
	name: MTEB SCIDOCS
	type: scidocs
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 3.4680000000000004
	- type: map_at_10
	value: 7.865
	- type: map_at_100
	value: 9.332
	- type: map_at_1000
	value: 9.587
	- type: map_at_3
	value: 5.800000000000001
	- type: map_at_5
	value: 6.8790000000000004
	- type: mrr_at_1
	value: 17.0
	- type: mrr_at_10
	value: 25.629
	- type: mrr_at_100
	value: 26.806
	- type: mrr_at_1000
	value: 26.889000000000003
	- type: mrr_at_3
	value: 22.8
	- type: mrr_at_5
	value: 24.26
	- type: ndcg_at_1
	value: 17.0
	- type: ndcg_at_10
	value: 13.895
	- type: ndcg_at_100
	value: 20.491999999999997
	- type: ndcg_at_1000
	value: 25.759999999999998
	- type: ndcg_at_3
	value: 13.347999999999999
	- type: ndcg_at_5
	value: 11.61
	- type: precision_at_1
	value: 17.0
	- type: precision_at_10
	value: 7.090000000000001
	- type: precision_at_100
	value: 1.669
	- type: precision_at_1000
	value: 0.294
	- type: precision_at_3
	value: 12.3
	- type: precision_at_5
	value: 10.02
	- type: recall_at_1
	value: 3.4680000000000004
	- type: recall_at_10
	value: 14.363000000000001
	- type: recall_at_100
	value: 33.875
	- type: recall_at_1000
	value: 59.711999999999996
	- type: recall_at_3
	value: 7.483
	- type: recall_at_5
	value: 10.173
	- task:
	type: STS
	dataset:
	name: MTEB SICK-R
	type: mteb/sickr-sts
	config: default
	split: test
	revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
	metrics:
	- type: cos_sim_pearson
	value: 83.04084311714061
	- type: cos_sim_spearman
	value: 77.51342467443078
	- type: euclidean_pearson
	value: 80.0321166028479
	- type: euclidean_spearman
	value: 77.29249114733226
	- type: manhattan_pearson
	value: 80.03105964262431
	- type: manhattan_spearman
	value: 77.22373689514794
	- task:
	type: STS
	dataset:
	name: MTEB STS12
	type: mteb/sts12-sts
	config: default
	split: test
	revision: a0d554a64d88156834ff5ae9920b964011b16384
	metrics:
	- type: cos_sim_pearson
	value: 84.1680158034387
	- type: cos_sim_spearman
	value: 76.55983344071117
	- type: euclidean_pearson
	value: 79.75266678300143
	- type: euclidean_spearman
	value: 75.34516823467025
	- type: manhattan_pearson
	value: 79.75959151517357
	- type: manhattan_spearman
	value: 75.42330344141912
	- task:
	type: STS
	dataset:
	name: MTEB STS13
	type: mteb/sts13-sts
	config: default
	split: test
	revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
	metrics:
	- type: cos_sim_pearson
	value: 76.48898993209346
	- type: cos_sim_spearman
	value: 76.96954120323366
	- type: euclidean_pearson
	value: 76.94139109279668
	- type: euclidean_spearman
	value: 76.85860283201711
	- type: manhattan_pearson
	value: 76.6944095091912
	- type: manhattan_spearman
	value: 76.61096912972553
	- task:
	type: STS
	dataset:
	name: MTEB STS14
	type: mteb/sts14-sts
	config: default
	split: test
	revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
	metrics:
	- type: cos_sim_pearson
	value: 77.85082366246944
	- type: cos_sim_spearman
	value: 75.52053350101731
	- type: euclidean_pearson
	value: 77.1165845070926
	- type: euclidean_spearman
	value: 75.31216065884388
	- type: manhattan_pearson
	value: 77.06193941833494
	- type: manhattan_spearman
	value: 75.31003701700112
	- task:
	type: STS
	dataset:
	name: MTEB STS15
	type: mteb/sts15-sts
	config: default
	split: test
	revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
	metrics:
	- type: cos_sim_pearson
	value: 86.36305246526497
	- type: cos_sim_spearman
	value: 87.11704613927415
	- type: euclidean_pearson
	value: 86.04199125810939
	- type: euclidean_spearman
	value: 86.51117572414263
	- type: manhattan_pearson
	value: 86.0805106816633
	- type: manhattan_spearman
	value: 86.52798366512229
	- task:
	type: STS
	dataset:
	name: MTEB STS16
	type: mteb/sts16-sts
	config: default
	split: test
	revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
	metrics:
	- type: cos_sim_pearson
	value: 82.18536255599724
	- type: cos_sim_spearman
	value: 83.63377151025418
	- type: euclidean_pearson
	value: 83.24657467993141
	- type: euclidean_spearman
	value: 84.02751481993825
	- type: manhattan_pearson
	value: 83.11941806582371
	- type: manhattan_spearman
	value: 83.84251281019304
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (ko-ko)
	type: mteb/sts17-crosslingual-sts
	config: ko-ko
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 78.95816528475514
	- type: cos_sim_spearman
	value: 78.86607380120462
	- type: euclidean_pearson
	value: 78.51268699230545
	- type: euclidean_spearman
	value: 79.11649316502229
	- type: manhattan_pearson
	value: 78.32367302808157
	- type: manhattan_spearman
	value: 78.90277699624637
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (ar-ar)
	type: mteb/sts17-crosslingual-sts
	config: ar-ar
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 72.89126914997624
	- type: cos_sim_spearman
	value: 73.0296921832678
	- type: euclidean_pearson
	value: 71.50385903677738
	- type: euclidean_spearman
	value: 73.13368899716289
	- type: manhattan_pearson
	value: 71.47421463379519
	- type: manhattan_spearman
	value: 73.03383242946575
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (en-ar)
	type: mteb/sts17-crosslingual-sts
	config: en-ar
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 59.22923684492637
	- type: cos_sim_spearman
	value: 57.41013211368396
	- type: euclidean_pearson
	value: 61.21107388080905
	- type: euclidean_spearman
	value: 60.07620768697254
	- type: manhattan_pearson
	value: 59.60157142786555
	- type: manhattan_spearman
	value: 59.14069604103739
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (en-de)
	type: mteb/sts17-crosslingual-sts
	config: en-de
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 76.24345978774299
	- type: cos_sim_spearman
	value: 77.24225743830719
	- type: euclidean_pearson
	value: 76.66226095469165
	- type: euclidean_spearman
	value: 77.60708820493146
	- type: manhattan_pearson
	value: 76.05303324760429
	- type: manhattan_spearman
	value: 76.96353149912348
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (en-en)
	type: mteb/sts17-crosslingual-sts
	config: en-en
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 85.50879160160852
	- type: cos_sim_spearman
	value: 86.43594662965224
	- type: euclidean_pearson
	value: 86.06846012826577
	- type: euclidean_spearman
	value: 86.02041395794136
	- type: manhattan_pearson
	value: 86.10916255616904
	- type: manhattan_spearman
	value: 86.07346068198953
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (en-tr)
	type: mteb/sts17-crosslingual-sts
	config: en-tr
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 58.39803698977196
	- type: cos_sim_spearman
	value: 55.96910950423142
	- type: euclidean_pearson
	value: 58.17941175613059
	- type: euclidean_spearman
	value: 55.03019330522745
	- type: manhattan_pearson
	value: 57.333358138183286
	- type: manhattan_spearman
	value: 54.04614023149965
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (es-en)
	type: mteb/sts17-crosslingual-sts
	config: es-en
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 70.98304089637197
	- type: cos_sim_spearman
	value: 72.44071656215888
	- type: euclidean_pearson
	value: 72.19224359033983
	- type: euclidean_spearman
	value: 73.89871188913025
	- type: manhattan_pearson
	value: 71.21098311547406
	- type: manhattan_spearman
	value: 72.93405764824821
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (es-es)
	type: mteb/sts17-crosslingual-sts
	config: es-es
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 85.99792397466308
	- type: cos_sim_spearman
	value: 84.83824377879495
	- type: euclidean_pearson
	value: 85.70043288694438
	- type: euclidean_spearman
	value: 84.70627558703686
	- type: manhattan_pearson
	value: 85.89570850150801
	- type: manhattan_spearman
	value: 84.95806105313007
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (fr-en)
	type: mteb/sts17-crosslingual-sts
	config: fr-en
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 72.21850322994712
	- type: cos_sim_spearman
	value: 72.28669398117248
	- type: euclidean_pearson
	value: 73.40082510412948
	- type: euclidean_spearman
	value: 73.0326539281865
	- type: manhattan_pearson
	value: 71.8659633964841
	- type: manhattan_spearman
	value: 71.57817425823303
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (it-en)
	type: mteb/sts17-crosslingual-sts
	config: it-en
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 75.80921368595645
	- type: cos_sim_spearman
	value: 77.33209091229315
	- type: euclidean_pearson
	value: 76.53159540154829
	- type: euclidean_spearman
	value: 78.17960842810093
	- type: manhattan_pearson
	value: 76.13530186637601
	- type: manhattan_spearman
	value: 78.00701437666875
	- task:
	type: STS
	dataset:
	name: MTEB STS17 (nl-en)
	type: mteb/sts17-crosslingual-sts
	config: nl-en
	split: test
	revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
	metrics:
	- type: cos_sim_pearson
	value: 74.74980608267349
	- type: cos_sim_spearman
	value: 75.37597374318821
	- type: euclidean_pearson
	value: 74.90506081911661
	- type: euclidean_spearman
	value: 75.30151613124521
	- type: manhattan_pearson
	value: 74.62642745918002
	- type: manhattan_spearman
	value: 75.18619716592303
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (en)
	type: mteb/sts22-crosslingual-sts
	config: en
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 59.632662289205584
	- type: cos_sim_spearman
	value: 60.938543391610914
	- type: euclidean_pearson
	value: 62.113200529767056
	- type: euclidean_spearman
	value: 61.410312633261164
	- type: manhattan_pearson
	value: 61.75494698945686
	- type: manhattan_spearman
	value: 60.92726195322362
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (de)
	type: mteb/sts22-crosslingual-sts
	config: de
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 45.283470551557244
	- type: cos_sim_spearman
	value: 53.44833015864201
	- type: euclidean_pearson
	value: 41.17892011120893
	- type: euclidean_spearman
	value: 53.81441383126767
	- type: manhattan_pearson
	value: 41.17482200420659
	- type: manhattan_spearman
	value: 53.82180269276363
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (es)
	type: mteb/sts22-crosslingual-sts
	config: es
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 60.5069165306236
	- type: cos_sim_spearman
	value: 66.87803259033826
	- type: euclidean_pearson
	value: 63.5428979418236
	- type: euclidean_spearman
	value: 66.9293576586897
	- type: manhattan_pearson
	value: 63.59789526178922
	- type: manhattan_spearman
	value: 66.86555009875066
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (pl)
	type: mteb/sts22-crosslingual-sts
	config: pl
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 28.23026196280264
	- type: cos_sim_spearman
	value: 35.79397812652861
	- type: euclidean_pearson
	value: 17.828102102767353
	- type: euclidean_spearman
	value: 35.721501145568894
	- type: manhattan_pearson
	value: 17.77134274219677
	- type: manhattan_spearman
	value: 35.98107902846267
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (tr)
	type: mteb/sts22-crosslingual-sts
	config: tr
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 56.51946541393812
	- type: cos_sim_spearman
	value: 63.714686006214485
	- type: euclidean_pearson
	value: 58.32104651305898
	- type: euclidean_spearman
	value: 62.237110895702216
	- type: manhattan_pearson
	value: 58.579416468759185
	- type: manhattan_spearman
	value: 62.459738981727
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (ar)
	type: mteb/sts22-crosslingual-sts
	config: ar
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 48.76009839569795
	- type: cos_sim_spearman
	value: 56.65188431953149
	- type: euclidean_pearson
	value: 50.997682160915595
	- type: euclidean_spearman
	value: 55.99910008818135
	- type: manhattan_pearson
	value: 50.76220659606342
	- type: manhattan_spearman
	value: 55.517347595391456
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (ru)
	type: mteb/sts22-crosslingual-sts
	config: ru
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 51.232731157702425
	- type: cos_sim_spearman
	value: 59.89531877658345
	- type: euclidean_pearson
	value: 49.937914570348376
	- type: euclidean_spearman
	value: 60.220905659334036
	- type: manhattan_pearson
	value: 50.00987996844193
	- type: manhattan_spearman
	value: 60.081341480977926
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (zh)
	type: mteb/sts22-crosslingual-sts
	config: zh
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 54.717524559088005
	- type: cos_sim_spearman
	value: 66.83570886252286
	- type: euclidean_pearson
	value: 58.41338625505467
	- type: euclidean_spearman
	value: 66.68991427704938
	- type: manhattan_pearson
	value: 58.78638572916807
	- type: manhattan_spearman
	value: 66.58684161046335
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (fr)
	type: mteb/sts22-crosslingual-sts
	config: fr
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 73.2962042954962
	- type: cos_sim_spearman
	value: 76.58255504852025
	- type: euclidean_pearson
	value: 75.70983192778257
	- type: euclidean_spearman
	value: 77.4547684870542
	- type: manhattan_pearson
	value: 75.75565853870485
	- type: manhattan_spearman
	value: 76.90208974949428
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (de-en)
	type: mteb/sts22-crosslingual-sts
	config: de-en
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 54.47396266924846
	- type: cos_sim_spearman
	value: 56.492267162048606
	- type: euclidean_pearson
	value: 55.998505203070195
	- type: euclidean_spearman
	value: 56.46447012960222
	- type: manhattan_pearson
	value: 54.873172394430995
	- type: manhattan_spearman
	value: 56.58111534551218
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (es-en)
	type: mteb/sts22-crosslingual-sts
	config: es-en
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 69.87177267688686
	- type: cos_sim_spearman
	value: 74.57160943395763
	- type: euclidean_pearson
	value: 70.88330406826788
	- type: euclidean_spearman
	value: 74.29767636038422
	- type: manhattan_pearson
	value: 71.38245248369536
	- type: manhattan_spearman
	value: 74.53102232732175
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (it)
	type: mteb/sts22-crosslingual-sts
	config: it
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 72.80225656959544
	- type: cos_sim_spearman
	value: 76.52646173725735
	- type: euclidean_pearson
	value: 73.95710720200799
	- type: euclidean_spearman
	value: 76.54040031984111
	- type: manhattan_pearson
	value: 73.89679971946774
	- type: manhattan_spearman
	value: 76.60886958161574
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (pl-en)
	type: mteb/sts22-crosslingual-sts
	config: pl-en
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 70.70844249898789
	- type: cos_sim_spearman
	value: 72.68571783670241
	- type: euclidean_pearson
	value: 72.38800772441031
	- type: euclidean_spearman
	value: 72.86804422703312
	- type: manhattan_pearson
	value: 71.29840508203515
	- type: manhattan_spearman
	value: 71.86264441749513
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (zh-en)
	type: mteb/sts22-crosslingual-sts
	config: zh-en
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 58.647478923935694
	- type: cos_sim_spearman
	value: 63.74453623540931
	- type: euclidean_pearson
	value: 59.60138032437505
	- type: euclidean_spearman
	value: 63.947930832166065
	- type: manhattan_pearson
	value: 58.59735509491861
	- type: manhattan_spearman
	value: 62.082503844627404
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (es-it)
	type: mteb/sts22-crosslingual-sts
	config: es-it
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 65.8722516867162
	- type: cos_sim_spearman
	value: 71.81208592523012
	- type: euclidean_pearson
	value: 67.95315252165956
	- type: euclidean_spearman
	value: 73.00749822046009
	- type: manhattan_pearson
	value: 68.07884688638924
	- type: manhattan_spearman
	value: 72.34210325803069
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (de-fr)
	type: mteb/sts22-crosslingual-sts
	config: de-fr
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 54.5405814240949
	- type: cos_sim_spearman
	value: 60.56838649023775
	- type: euclidean_pearson
	value: 53.011731611314104
	- type: euclidean_spearman
	value: 58.533194841668426
	- type: manhattan_pearson
	value: 53.623067729338494
	- type: manhattan_spearman
	value: 58.018756154446926
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (de-pl)
	type: mteb/sts22-crosslingual-sts
	config: de-pl
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 13.611046866216112
	- type: cos_sim_spearman
	value: 28.238192909158492
	- type: euclidean_pearson
	value: 22.16189199885129
	- type: euclidean_spearman
	value: 35.012895679076564
	- type: manhattan_pearson
	value: 21.969771178698387
	- type: manhattan_spearman
	value: 32.456985088607475
	- task:
	type: STS
	dataset:
	name: MTEB STS22 (fr-pl)
	type: mteb/sts22-crosslingual-sts
	config: fr-pl
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 74.58077407011655
	- type: cos_sim_spearman
	value: 84.51542547285167
	- type: euclidean_pearson
	value: 74.64613843596234
	- type: euclidean_spearman
	value: 84.51542547285167
	- type: manhattan_pearson
	value: 75.15335973101396
	- type: manhattan_spearman
	value: 84.51542547285167
	- task:
	type: STS
	dataset:
	name: MTEB STSBenchmark
	type: mteb/stsbenchmark-sts
	config: default
	split: test
	revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
	metrics:
	- type: cos_sim_pearson
	value: 82.0739825531578
	- type: cos_sim_spearman
	value: 84.01057479311115
	- type: euclidean_pearson
	value: 83.85453227433344
	- type: euclidean_spearman
	value: 84.01630226898655
	- type: manhattan_pearson
	value: 83.75323603028978
	- type: manhattan_spearman
	value: 83.89677983727685
	- task:
	type: Reranking
	dataset:
	name: MTEB SciDocsRR
	type: mteb/scidocs-reranking
	config: default
	split: test
	revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
	metrics:
	- type: map
	value: 78.12945623123957
	- type: mrr
	value: 93.87738713719106
	- task:
	type: Retrieval
	dataset:
	name: MTEB SciFact
	type: scifact
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 52.983000000000004
	- type: map_at_10
	value: 62.946000000000005
	- type: map_at_100
	value: 63.514
	- type: map_at_1000
	value: 63.554
	- type: map_at_3
	value: 60.183
	- type: map_at_5
	value: 61.672000000000004
	- type: mrr_at_1
	value: 55.667
	- type: mrr_at_10
	value: 64.522
	- type: mrr_at_100
	value: 64.957
	- type: mrr_at_1000
	value: 64.995
	- type: mrr_at_3
	value: 62.388999999999996
	- type: mrr_at_5
	value: 63.639
	- type: ndcg_at_1
	value: 55.667
	- type: ndcg_at_10
	value: 67.704
	- type: ndcg_at_100
	value: 70.299
	- type: ndcg_at_1000
	value: 71.241
	- type: ndcg_at_3
	value: 62.866
	- type: ndcg_at_5
	value: 65.16999999999999
	- type: precision_at_1
	value: 55.667
	- type: precision_at_10
	value: 9.033
	- type: precision_at_100
	value: 1.053
	- type: precision_at_1000
	value: 0.11299999999999999
	- type: precision_at_3
	value: 24.444
	- type: precision_at_5
	value: 16.133
	- type: recall_at_1
	value: 52.983000000000004
	- type: recall_at_10
	value: 80.656
	- type: recall_at_100
	value: 92.5
	- type: recall_at_1000
	value: 99.667
	- type: recall_at_3
	value: 67.744
	- type: recall_at_5
	value: 73.433
	- task:
	type: PairClassification
	dataset:
	name: MTEB SprintDuplicateQuestions
	type: mteb/sprintduplicatequestions-pairclassification
	config: default
	split: test
	revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
	metrics:
	- type: cos_sim_accuracy
	value: 99.72772277227723
	- type: cos_sim_ap
	value: 92.17845897992215
	- type: cos_sim_f1
	value: 85.9746835443038
	- type: cos_sim_precision
	value: 87.07692307692308
	- type: cos_sim_recall
	value: 84.89999999999999
	- type: dot_accuracy
	value: 99.3039603960396
	- type: dot_ap
	value: 60.70244020124878
	- type: dot_f1
	value: 59.92742353551063
	- type: dot_precision
	value: 62.21743810548978
	- type: dot_recall
	value: 57.8
	- type: euclidean_accuracy
	value: 99.71683168316832
	- type: euclidean_ap
	value: 91.53997039964659
	- type: euclidean_f1
	value: 84.88372093023257
	- type: euclidean_precision
	value: 90.02242152466367
	- type: euclidean_recall
	value: 80.30000000000001
	- type: manhattan_accuracy
	value: 99.72376237623763
	- type: manhattan_ap
	value: 91.80756777790289
	- type: manhattan_f1
	value: 85.48468106479157
	- type: manhattan_precision
	value: 85.8728557013118
	- type: manhattan_recall
	value: 85.1
	- type: max_accuracy
	value: 99.72772277227723
	- type: max_ap
	value: 92.17845897992215
	- type: max_f1
	value: 85.9746835443038
	- task:
	type: Clustering
	dataset:
	name: MTEB StackExchangeClustering
	type: mteb/stackexchange-clustering
	config: default
	split: test
	revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
	metrics:
	- type: v_measure
	value: 53.52464042600003
	- task:
	type: Clustering
	dataset:
	name: MTEB StackExchangeClusteringP2P
	type: mteb/stackexchange-clustering-p2p
	config: default
	split: test
	revision: 815ca46b2622cec33ccafc3735d572c266efdb44
	metrics:
	- type: v_measure
	value: 32.071631948736
	- task:
	type: Reranking
	dataset:
	name: MTEB StackOverflowDupQuestions
	type: mteb/stackoverflowdupquestions-reranking
	config: default
	split: test
	revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
	metrics:
	- type: map
	value: 49.19552407604654
	- type: mrr
	value: 49.95269130379425
	- task:
	type: Summarization
	dataset:
	name: MTEB SummEval
	type: mteb/summeval
	config: default
	split: test
	revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
	metrics:
	- type: cos_sim_pearson
	value: 29.345293033095427
	- type: cos_sim_spearman
	value: 29.976931423258403
	- type: dot_pearson
	value: 27.047078008958408
	- type: dot_spearman
	value: 27.75894368380218
	- task:
	type: Retrieval
	dataset:
	name: MTEB TRECCOVID
	type: trec-covid
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 0.22
	- type: map_at_10
	value: 1.706
	- type: map_at_100
	value: 9.634
	- type: map_at_1000
	value: 23.665
	- type: map_at_3
	value: 0.5950000000000001
	- type: map_at_5
	value: 0.95
	- type: mrr_at_1
	value: 86.0
	- type: mrr_at_10
	value: 91.8
	- type: mrr_at_100
	value: 91.8
	- type: mrr_at_1000
	value: 91.8
	- type: mrr_at_3
	value: 91.0
	- type: mrr_at_5
	value: 91.8
	- type: ndcg_at_1
	value: 80.0
	- type: ndcg_at_10
	value: 72.573
	- type: ndcg_at_100
	value: 53.954
	- type: ndcg_at_1000
	value: 47.760999999999996
	- type: ndcg_at_3
	value: 76.173
	- type: ndcg_at_5
	value: 75.264
	- type: precision_at_1
	value: 86.0
	- type: precision_at_10
	value: 76.4
	- type: precision_at_100
	value: 55.50000000000001
	- type: precision_at_1000
	value: 21.802
	- type: precision_at_3
	value: 81.333
	- type: precision_at_5
	value: 80.4
	- type: recall_at_1
	value: 0.22
	- type: recall_at_10
	value: 1.925
	- type: recall_at_100
	value: 12.762
	- type: recall_at_1000
	value: 44.946000000000005
	- type: recall_at_3
	value: 0.634
	- type: recall_at_5
	value: 1.051
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (sqi-eng)
	type: mteb/tatoeba-bitext-mining
	config: sqi-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 91.0
	- type: f1
	value: 88.55666666666666
	- type: precision
	value: 87.46166666666667
	- type: recall
	value: 91.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (fry-eng)
	type: mteb/tatoeba-bitext-mining
	config: fry-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 57.22543352601156
	- type: f1
	value: 51.03220478943021
	- type: precision
	value: 48.8150289017341
	- type: recall
	value: 57.22543352601156
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kur-eng)
	type: mteb/tatoeba-bitext-mining
	config: kur-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 46.58536585365854
	- type: f1
	value: 39.66870798578116
	- type: precision
	value: 37.416085946573745
	- type: recall
	value: 46.58536585365854
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tur-eng)
	type: mteb/tatoeba-bitext-mining
	config: tur-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 89.7
	- type: f1
	value: 86.77999999999999
	- type: precision
	value: 85.45333333333332
	- type: recall
	value: 89.7
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (deu-eng)
	type: mteb/tatoeba-bitext-mining
	config: deu-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 97.39999999999999
	- type: f1
	value: 96.58333333333331
	- type: precision
	value: 96.2
	- type: recall
	value: 97.39999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (nld-eng)
	type: mteb/tatoeba-bitext-mining
	config: nld-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 92.4
	- type: f1
	value: 90.3
	- type: precision
	value: 89.31666666666668
	- type: recall
	value: 92.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ron-eng)
	type: mteb/tatoeba-bitext-mining
	config: ron-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 86.9
	- type: f1
	value: 83.67190476190476
	- type: precision
	value: 82.23333333333332
	- type: recall
	value: 86.9
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ang-eng)
	type: mteb/tatoeba-bitext-mining
	config: ang-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 50.0
	- type: f1
	value: 42.23229092632078
	- type: precision
	value: 39.851634683724235
	- type: recall
	value: 50.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ido-eng)
	type: mteb/tatoeba-bitext-mining
	config: ido-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 76.3
	- type: f1
	value: 70.86190476190477
	- type: precision
	value: 68.68777777777777
	- type: recall
	value: 76.3
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (jav-eng)
	type: mteb/tatoeba-bitext-mining
	config: jav-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 57.073170731707314
	- type: f1
	value: 50.658958927251604
	- type: precision
	value: 48.26480836236933
	- type: recall
	value: 57.073170731707314
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (isl-eng)
	type: mteb/tatoeba-bitext-mining
	config: isl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 68.2
	- type: f1
	value: 62.156507936507936
	- type: precision
	value: 59.84964285714286
	- type: recall
	value: 68.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (slv-eng)
	type: mteb/tatoeba-bitext-mining
	config: slv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 77.52126366950182
	- type: f1
	value: 72.8496210148701
	- type: precision
	value: 70.92171498003819
	- type: recall
	value: 77.52126366950182
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cym-eng)
	type: mteb/tatoeba-bitext-mining
	config: cym-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 70.78260869565217
	- type: f1
	value: 65.32422360248447
	- type: precision
	value: 63.063067367415194
	- type: recall
	value: 70.78260869565217
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kaz-eng)
	type: mteb/tatoeba-bitext-mining
	config: kaz-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 78.43478260869566
	- type: f1
	value: 73.02608695652172
	- type: precision
	value: 70.63768115942028
	- type: recall
	value: 78.43478260869566
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (est-eng)
	type: mteb/tatoeba-bitext-mining
	config: est-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 60.9
	- type: f1
	value: 55.309753694581275
	- type: precision
	value: 53.130476190476195
	- type: recall
	value: 60.9
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (heb-eng)
	type: mteb/tatoeba-bitext-mining
	config: heb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 72.89999999999999
	- type: f1
	value: 67.92023809523809
	- type: precision
	value: 65.82595238095237
	- type: recall
	value: 72.89999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (gla-eng)
	type: mteb/tatoeba-bitext-mining
	config: gla-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 46.80337756332931
	- type: f1
	value: 39.42174900558496
	- type: precision
	value: 36.97101116280851
	- type: recall
	value: 46.80337756332931
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (mar-eng)
	type: mteb/tatoeba-bitext-mining
	config: mar-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 89.8
	- type: f1
	value: 86.79
	- type: precision
	value: 85.375
	- type: recall
	value: 89.8
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (lat-eng)
	type: mteb/tatoeba-bitext-mining
	config: lat-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 47.199999999999996
	- type: f1
	value: 39.95484348984349
	- type: precision
	value: 37.561071428571424
	- type: recall
	value: 47.199999999999996
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (bel-eng)
	type: mteb/tatoeba-bitext-mining
	config: bel-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 87.8
	- type: f1
	value: 84.68190476190475
	- type: precision
	value: 83.275
	- type: recall
	value: 87.8
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (pms-eng)
	type: mteb/tatoeba-bitext-mining
	config: pms-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 48.76190476190476
	- type: f1
	value: 42.14965986394558
	- type: precision
	value: 39.96743626743626
	- type: recall
	value: 48.76190476190476
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (gle-eng)
	type: mteb/tatoeba-bitext-mining
	config: gle-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 66.10000000000001
	- type: f1
	value: 59.58580086580086
	- type: precision
	value: 57.150238095238095
	- type: recall
	value: 66.10000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (pes-eng)
	type: mteb/tatoeba-bitext-mining
	config: pes-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 87.3
	- type: f1
	value: 84.0
	- type: precision
	value: 82.48666666666666
	- type: recall
	value: 87.3
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (nob-eng)
	type: mteb/tatoeba-bitext-mining
	config: nob-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 90.4
	- type: f1
	value: 87.79523809523809
	- type: precision
	value: 86.6
	- type: recall
	value: 90.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (bul-eng)
	type: mteb/tatoeba-bitext-mining
	config: bul-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 87.0
	- type: f1
	value: 83.81
	- type: precision
	value: 82.36666666666666
	- type: recall
	value: 87.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cbk-eng)
	type: mteb/tatoeba-bitext-mining
	config: cbk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 63.9
	- type: f1
	value: 57.76533189033189
	- type: precision
	value: 55.50595238095239
	- type: recall
	value: 63.9
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (hun-eng)
	type: mteb/tatoeba-bitext-mining
	config: hun-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 76.1
	- type: f1
	value: 71.83690476190478
	- type: precision
	value: 70.04928571428573
	- type: recall
	value: 76.1
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (uig-eng)
	type: mteb/tatoeba-bitext-mining
	config: uig-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 66.3
	- type: f1
	value: 59.32626984126984
	- type: precision
	value: 56.62535714285713
	- type: recall
	value: 66.3
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (rus-eng)
	type: mteb/tatoeba-bitext-mining
	config: rus-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 90.60000000000001
	- type: f1
	value: 87.96333333333334
	- type: precision
	value: 86.73333333333333
	- type: recall
	value: 90.60000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (spa-eng)
	type: mteb/tatoeba-bitext-mining
	config: spa-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 93.10000000000001
	- type: f1
	value: 91.10000000000001
	- type: precision
	value: 90.16666666666666
	- type: recall
	value: 93.10000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (hye-eng)
	type: mteb/tatoeba-bitext-mining
	config: hye-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 85.71428571428571
	- type: f1
	value: 82.29142600436403
	- type: precision
	value: 80.8076626877166
	- type: recall
	value: 85.71428571428571
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tel-eng)
	type: mteb/tatoeba-bitext-mining
	config: tel-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.88888888888889
	- type: f1
	value: 85.7834757834758
	- type: precision
	value: 84.43732193732193
	- type: recall
	value: 88.88888888888889
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (afr-eng)
	type: mteb/tatoeba-bitext-mining
	config: afr-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.5
	- type: f1
	value: 85.67190476190476
	- type: precision
	value: 84.43333333333332
	- type: recall
	value: 88.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (mon-eng)
	type: mteb/tatoeba-bitext-mining
	config: mon-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 82.72727272727273
	- type: f1
	value: 78.21969696969695
	- type: precision
	value: 76.18181818181819
	- type: recall
	value: 82.72727272727273
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (arz-eng)
	type: mteb/tatoeba-bitext-mining
	config: arz-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 61.0062893081761
	- type: f1
	value: 55.13976240391334
	- type: precision
	value: 52.92112499659669
	- type: recall
	value: 61.0062893081761
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (hrv-eng)
	type: mteb/tatoeba-bitext-mining
	config: hrv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 89.5
	- type: f1
	value: 86.86666666666666
	- type: precision
	value: 85.69166666666668
	- type: recall
	value: 89.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (nov-eng)
	type: mteb/tatoeba-bitext-mining
	config: nov-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 73.54085603112841
	- type: f1
	value: 68.56031128404669
	- type: precision
	value: 66.53047989623866
	- type: recall
	value: 73.54085603112841
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (gsw-eng)
	type: mteb/tatoeba-bitext-mining
	config: gsw-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 43.58974358974359
	- type: f1
	value: 36.45299145299145
	- type: precision
	value: 33.81155881155882
	- type: recall
	value: 43.58974358974359
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (nds-eng)
	type: mteb/tatoeba-bitext-mining
	config: nds-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 59.599999999999994
	- type: f1
	value: 53.264689754689755
	- type: precision
	value: 50.869166666666665
	- type: recall
	value: 59.599999999999994
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ukr-eng)
	type: mteb/tatoeba-bitext-mining
	config: ukr-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 85.2
	- type: f1
	value: 81.61666666666665
	- type: precision
	value: 80.02833333333335
	- type: recall
	value: 85.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (uzb-eng)
	type: mteb/tatoeba-bitext-mining
	config: uzb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 63.78504672897196
	- type: f1
	value: 58.00029669188548
	- type: precision
	value: 55.815809968847354
	- type: recall
	value: 63.78504672897196
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (lit-eng)
	type: mteb/tatoeba-bitext-mining
	config: lit-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 66.5
	- type: f1
	value: 61.518333333333345
	- type: precision
	value: 59.622363699102834
	- type: recall
	value: 66.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ina-eng)
	type: mteb/tatoeba-bitext-mining
	config: ina-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.6
	- type: f1
	value: 85.60222222222221
	- type: precision
	value: 84.27916666666665
	- type: recall
	value: 88.6
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (lfn-eng)
	type: mteb/tatoeba-bitext-mining
	config: lfn-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 58.699999999999996
	- type: f1
	value: 52.732375957375965
	- type: precision
	value: 50.63214035964035
	- type: recall
	value: 58.699999999999996
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (zsm-eng)
	type: mteb/tatoeba-bitext-mining
	config: zsm-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 92.10000000000001
	- type: f1
	value: 89.99666666666667
	- type: precision
	value: 89.03333333333333
	- type: recall
	value: 92.10000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ita-eng)
	type: mteb/tatoeba-bitext-mining
	config: ita-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 90.10000000000001
	- type: f1
	value: 87.55666666666667
	- type: precision
	value: 86.36166666666668
	- type: recall
	value: 90.10000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cmn-eng)
	type: mteb/tatoeba-bitext-mining
	config: cmn-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 91.4
	- type: f1
	value: 88.89000000000001
	- type: precision
	value: 87.71166666666666
	- type: recall
	value: 91.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (lvs-eng)
	type: mteb/tatoeba-bitext-mining
	config: lvs-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 65.7
	- type: f1
	value: 60.67427750410509
	- type: precision
	value: 58.71785714285714
	- type: recall
	value: 65.7
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (glg-eng)
	type: mteb/tatoeba-bitext-mining
	config: glg-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 85.39999999999999
	- type: f1
	value: 81.93190476190475
	- type: precision
	value: 80.37833333333333
	- type: recall
	value: 85.39999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ceb-eng)
	type: mteb/tatoeba-bitext-mining
	config: ceb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 47.833333333333336
	- type: f1
	value: 42.006625781625786
	- type: precision
	value: 40.077380952380956
	- type: recall
	value: 47.833333333333336
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (bre-eng)
	type: mteb/tatoeba-bitext-mining
	config: bre-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 10.4
	- type: f1
	value: 8.24465007215007
	- type: precision
	value: 7.664597069597071
	- type: recall
	value: 10.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ben-eng)
	type: mteb/tatoeba-bitext-mining
	config: ben-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 82.6
	- type: f1
	value: 77.76333333333334
	- type: precision
	value: 75.57833333333332
	- type: recall
	value: 82.6
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (swg-eng)
	type: mteb/tatoeba-bitext-mining
	config: swg-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 52.67857142857143
	- type: f1
	value: 44.302721088435376
	- type: precision
	value: 41.49801587301587
	- type: recall
	value: 52.67857142857143
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (arq-eng)
	type: mteb/tatoeba-bitext-mining
	config: arq-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 28.3205268935236
	- type: f1
	value: 22.426666605171157
	- type: precision
	value: 20.685900116470915
	- type: recall
	value: 28.3205268935236
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kab-eng)
	type: mteb/tatoeba-bitext-mining
	config: kab-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 22.7
	- type: f1
	value: 17.833970473970474
	- type: precision
	value: 16.407335164835164
	- type: recall
	value: 22.7
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (fra-eng)
	type: mteb/tatoeba-bitext-mining
	config: fra-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 92.2
	- type: f1
	value: 89.92999999999999
	- type: precision
	value: 88.87
	- type: recall
	value: 92.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (por-eng)
	type: mteb/tatoeba-bitext-mining
	config: por-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 91.4
	- type: f1
	value: 89.25
	- type: precision
	value: 88.21666666666667
	- type: recall
	value: 91.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tat-eng)
	type: mteb/tatoeba-bitext-mining
	config: tat-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 69.19999999999999
	- type: f1
	value: 63.38269841269841
	- type: precision
	value: 61.14773809523809
	- type: recall
	value: 69.19999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (oci-eng)
	type: mteb/tatoeba-bitext-mining
	config: oci-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 48.8
	- type: f1
	value: 42.839915639915645
	- type: precision
	value: 40.770287114845935
	- type: recall
	value: 48.8
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (pol-eng)
	type: mteb/tatoeba-bitext-mining
	config: pol-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.8
	- type: f1
	value: 85.90666666666668
	- type: precision
	value: 84.54166666666666
	- type: recall
	value: 88.8
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (war-eng)
	type: mteb/tatoeba-bitext-mining
	config: war-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 46.6
	- type: f1
	value: 40.85892920804686
	- type: precision
	value: 38.838223114604695
	- type: recall
	value: 46.6
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (aze-eng)
	type: mteb/tatoeba-bitext-mining
	config: aze-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 84.0
	- type: f1
	value: 80.14190476190475
	- type: precision
	value: 78.45333333333333
	- type: recall
	value: 84.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (vie-eng)
	type: mteb/tatoeba-bitext-mining
	config: vie-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 90.5
	- type: f1
	value: 87.78333333333333
	- type: precision
	value: 86.5
	- type: recall
	value: 90.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (nno-eng)
	type: mteb/tatoeba-bitext-mining
	config: nno-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 74.5
	- type: f1
	value: 69.48397546897547
	- type: precision
	value: 67.51869047619049
	- type: recall
	value: 74.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cha-eng)
	type: mteb/tatoeba-bitext-mining
	config: cha-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 32.846715328467155
	- type: f1
	value: 27.828177499710343
	- type: precision
	value: 26.63451511991658
	- type: recall
	value: 32.846715328467155
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (mhr-eng)
	type: mteb/tatoeba-bitext-mining
	config: mhr-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 8.0
	- type: f1
	value: 6.07664116764988
	- type: precision
	value: 5.544177607179943
	- type: recall
	value: 8.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (dan-eng)
	type: mteb/tatoeba-bitext-mining
	config: dan-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 87.6
	- type: f1
	value: 84.38555555555554
	- type: precision
	value: 82.91583333333334
	- type: recall
	value: 87.6
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ell-eng)
	type: mteb/tatoeba-bitext-mining
	config: ell-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 87.5
	- type: f1
	value: 84.08333333333331
	- type: precision
	value: 82.47333333333333
	- type: recall
	value: 87.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (amh-eng)
	type: mteb/tatoeba-bitext-mining
	config: amh-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 80.95238095238095
	- type: f1
	value: 76.13095238095238
	- type: precision
	value: 74.05753968253967
	- type: recall
	value: 80.95238095238095
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (pam-eng)
	type: mteb/tatoeba-bitext-mining
	config: pam-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 8.799999999999999
	- type: f1
	value: 6.971422975172975
	- type: precision
	value: 6.557814916172301
	- type: recall
	value: 8.799999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (hsb-eng)
	type: mteb/tatoeba-bitext-mining
	config: hsb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 44.099378881987576
	- type: f1
	value: 37.01649742022413
	- type: precision
	value: 34.69420618488942
	- type: recall
	value: 44.099378881987576
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (srp-eng)
	type: mteb/tatoeba-bitext-mining
	config: srp-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 84.3
	- type: f1
	value: 80.32666666666667
	- type: precision
	value: 78.60666666666665
	- type: recall
	value: 84.3
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (epo-eng)
	type: mteb/tatoeba-bitext-mining
	config: epo-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 92.5
	- type: f1
	value: 90.49666666666666
	- type: precision
	value: 89.56666666666668
	- type: recall
	value: 92.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kzj-eng)
	type: mteb/tatoeba-bitext-mining
	config: kzj-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 10.0
	- type: f1
	value: 8.268423529875141
	- type: precision
	value: 7.878118605532398
	- type: recall
	value: 10.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (awa-eng)
	type: mteb/tatoeba-bitext-mining
	config: awa-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 79.22077922077922
	- type: f1
	value: 74.27128427128426
	- type: precision
	value: 72.28715728715729
	- type: recall
	value: 79.22077922077922
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (fao-eng)
	type: mteb/tatoeba-bitext-mining
	config: fao-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 65.64885496183206
	- type: f1
	value: 58.87495456197747
	- type: precision
	value: 55.992366412213734
	- type: recall
	value: 65.64885496183206
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (mal-eng)
	type: mteb/tatoeba-bitext-mining
	config: mal-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 96.06986899563319
	- type: f1
	value: 94.78408539543909
	- type: precision
	value: 94.15332362930616
	- type: recall
	value: 96.06986899563319
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ile-eng)
	type: mteb/tatoeba-bitext-mining
	config: ile-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 77.2
	- type: f1
	value: 71.72571428571428
	- type: precision
	value: 69.41000000000001
	- type: recall
	value: 77.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (bos-eng)
	type: mteb/tatoeba-bitext-mining
	config: bos-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 86.4406779661017
	- type: f1
	value: 83.2391713747646
	- type: precision
	value: 81.74199623352166
	- type: recall
	value: 86.4406779661017
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cor-eng)
	type: mteb/tatoeba-bitext-mining
	config: cor-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 8.4
	- type: f1
	value: 6.017828743398003
	- type: precision
	value: 5.4829865484756795
	- type: recall
	value: 8.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (cat-eng)
	type: mteb/tatoeba-bitext-mining
	config: cat-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 83.5
	- type: f1
	value: 79.74833333333333
	- type: precision
	value: 78.04837662337664
	- type: recall
	value: 83.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (eus-eng)
	type: mteb/tatoeba-bitext-mining
	config: eus-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 60.4
	- type: f1
	value: 54.467301587301584
	- type: precision
	value: 52.23242424242424
	- type: recall
	value: 60.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (yue-eng)
	type: mteb/tatoeba-bitext-mining
	config: yue-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 74.9
	- type: f1
	value: 69.68699134199134
	- type: precision
	value: 67.59873015873016
	- type: recall
	value: 74.9
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (swe-eng)
	type: mteb/tatoeba-bitext-mining
	config: swe-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.0
	- type: f1
	value: 84.9652380952381
	- type: precision
	value: 83.66166666666666
	- type: recall
	value: 88.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (dtp-eng)
	type: mteb/tatoeba-bitext-mining
	config: dtp-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 9.1
	- type: f1
	value: 7.681244588744588
	- type: precision
	value: 7.370043290043291
	- type: recall
	value: 9.1
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kat-eng)
	type: mteb/tatoeba-bitext-mining
	config: kat-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 80.9651474530831
	- type: f1
	value: 76.84220605132133
	- type: precision
	value: 75.19606398962966
	- type: recall
	value: 80.9651474530831
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (jpn-eng)
	type: mteb/tatoeba-bitext-mining
	config: jpn-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 86.9
	- type: f1
	value: 83.705
	- type: precision
	value: 82.3120634920635
	- type: recall
	value: 86.9
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (csb-eng)
	type: mteb/tatoeba-bitext-mining
	config: csb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 29.64426877470356
	- type: f1
	value: 23.98763072676116
	- type: precision
	value: 22.506399397703746
	- type: recall
	value: 29.64426877470356
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (xho-eng)
	type: mteb/tatoeba-bitext-mining
	config: xho-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 70.4225352112676
	- type: f1
	value: 62.84037558685445
	- type: precision
	value: 59.56572769953053
	- type: recall
	value: 70.4225352112676
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (orv-eng)
	type: mteb/tatoeba-bitext-mining
	config: orv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 19.64071856287425
	- type: f1
	value: 15.125271011207756
	- type: precision
	value: 13.865019261197494
	- type: recall
	value: 19.64071856287425
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ind-eng)
	type: mteb/tatoeba-bitext-mining
	config: ind-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 90.2
	- type: f1
	value: 87.80666666666666
	- type: precision
	value: 86.70833333333331
	- type: recall
	value: 90.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tuk-eng)
	type: mteb/tatoeba-bitext-mining
	config: tuk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 23.15270935960591
	- type: f1
	value: 18.407224958949097
	- type: precision
	value: 16.982385430661292
	- type: recall
	value: 23.15270935960591
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (max-eng)
	type: mteb/tatoeba-bitext-mining
	config: max-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 55.98591549295775
	- type: f1
	value: 49.94718309859154
	- type: precision
	value: 47.77864154624717
	- type: recall
	value: 55.98591549295775
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (swh-eng)
	type: mteb/tatoeba-bitext-mining
	config: swh-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 73.07692307692307
	- type: f1
	value: 66.74358974358974
	- type: precision
	value: 64.06837606837607
	- type: recall
	value: 73.07692307692307
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (hin-eng)
	type: mteb/tatoeba-bitext-mining
	config: hin-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 94.89999999999999
	- type: f1
	value: 93.25
	- type: precision
	value: 92.43333333333332
	- type: recall
	value: 94.89999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (dsb-eng)
	type: mteb/tatoeba-bitext-mining
	config: dsb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 37.78705636743215
	- type: f1
	value: 31.63899658680452
	- type: precision
	value: 29.72264397629742
	- type: recall
	value: 37.78705636743215
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ber-eng)
	type: mteb/tatoeba-bitext-mining
	config: ber-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 21.6
	- type: f1
	value: 16.91697302697303
	- type: precision
	value: 15.71225147075147
	- type: recall
	value: 21.6
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tam-eng)
	type: mteb/tatoeba-bitext-mining
	config: tam-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 85.01628664495115
	- type: f1
	value: 81.38514037536838
	- type: precision
	value: 79.83170466883823
	- type: recall
	value: 85.01628664495115
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (slk-eng)
	type: mteb/tatoeba-bitext-mining
	config: slk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 83.39999999999999
	- type: f1
	value: 79.96380952380952
	- type: precision
	value: 78.48333333333333
	- type: recall
	value: 83.39999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tgl-eng)
	type: mteb/tatoeba-bitext-mining
	config: tgl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 83.2
	- type: f1
	value: 79.26190476190476
	- type: precision
	value: 77.58833333333334
	- type: recall
	value: 83.2
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ast-eng)
	type: mteb/tatoeba-bitext-mining
	config: ast-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 75.59055118110236
	- type: f1
	value: 71.66854143232096
	- type: precision
	value: 70.30183727034121
	- type: recall
	value: 75.59055118110236
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (mkd-eng)
	type: mteb/tatoeba-bitext-mining
	config: mkd-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 65.5
	- type: f1
	value: 59.26095238095238
	- type: precision
	value: 56.81909090909092
	- type: recall
	value: 65.5
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (khm-eng)
	type: mteb/tatoeba-bitext-mining
	config: khm-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 55.26315789473685
	- type: f1
	value: 47.986523325858506
	- type: precision
	value: 45.33950006595436
	- type: recall
	value: 55.26315789473685
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ces-eng)
	type: mteb/tatoeba-bitext-mining
	config: ces-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 82.89999999999999
	- type: f1
	value: 78.835
	- type: precision
	value: 77.04761904761905
	- type: recall
	value: 82.89999999999999
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tzl-eng)
	type: mteb/tatoeba-bitext-mining
	config: tzl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 43.269230769230774
	- type: f1
	value: 36.20421245421245
	- type: precision
	value: 33.57371794871795
	- type: recall
	value: 43.269230769230774
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (urd-eng)
	type: mteb/tatoeba-bitext-mining
	config: urd-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 88.0
	- type: f1
	value: 84.70666666666666
	- type: precision
	value: 83.23166666666665
	- type: recall
	value: 88.0
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (ara-eng)
	type: mteb/tatoeba-bitext-mining
	config: ara-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 77.4
	- type: f1
	value: 72.54666666666667
	- type: precision
	value: 70.54318181818181
	- type: recall
	value: 77.4
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (kor-eng)
	type: mteb/tatoeba-bitext-mining
	config: kor-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 78.60000000000001
	- type: f1
	value: 74.1588888888889
	- type: precision
	value: 72.30250000000001
	- type: recall
	value: 78.60000000000001
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (yid-eng)
	type: mteb/tatoeba-bitext-mining
	config: yid-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 72.40566037735849
	- type: f1
	value: 66.82587328813744
	- type: precision
	value: 64.75039308176099
	- type: recall
	value: 72.40566037735849
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (fin-eng)
	type: mteb/tatoeba-bitext-mining
	config: fin-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 73.8
	- type: f1
	value: 68.56357142857144
	- type: precision
	value: 66.3178822055138
	- type: recall
	value: 73.8
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (tha-eng)
	type: mteb/tatoeba-bitext-mining
	config: tha-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 91.78832116788321
	- type: f1
	value: 89.3552311435523
	- type: precision
	value: 88.20559610705597
	- type: recall
	value: 91.78832116788321
	- task:
	type: BitextMining
	dataset:
	name: MTEB Tatoeba (wuu-eng)
	type: mteb/tatoeba-bitext-mining
	config: wuu-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 74.3
	- type: f1
	value: 69.05085581085581
	- type: precision
	value: 66.955
	- type: recall
	value: 74.3
	- task:
	type: Retrieval
	dataset:
	name: MTEB Touche2020
	type: webis-touche2020
	config: default
	split: test
	revision: None
	metrics:
	- type: map_at_1
	value: 2.896
	- type: map_at_10
	value: 8.993
	- type: map_at_100
	value: 14.133999999999999
	- type: map_at_1000
	value: 15.668000000000001
	- type: map_at_3
	value: 5.862
	- type: map_at_5
	value: 7.17
	- type: mrr_at_1
	value: 34.694
	- type: mrr_at_10
	value: 42.931000000000004
	- type: mrr_at_100
	value: 44.81
	- type: mrr_at_1000
	value: 44.81
	- type: mrr_at_3
	value: 38.435
	- type: mrr_at_5
	value: 41.701
	- type: ndcg_at_1
	value: 31.633
	- type: ndcg_at_10
	value: 21.163
	- type: ndcg_at_100
	value: 33.306000000000004
	- type: ndcg_at_1000
	value: 45.275999999999996
	- type: ndcg_at_3
	value: 25.685999999999996
	- type: ndcg_at_5
	value: 23.732
	- type: precision_at_1
	value: 34.694
	- type: precision_at_10
	value: 17.755000000000003
	- type: precision_at_100
	value: 6.938999999999999
	- type: precision_at_1000
	value: 1.48
	- type: precision_at_3
	value: 25.85
	- type: precision_at_5
	value: 23.265
	- type: recall_at_1
	value: 2.896
	- type: recall_at_10
	value: 13.333999999999998
	- type: recall_at_100
	value: 43.517
	- type: recall_at_1000
	value: 79.836
	- type: recall_at_3
	value: 6.306000000000001
	- type: recall_at_5
	value: 8.825
	- task:
	type: Classification
	dataset:
	name: MTEB ToxicConversationsClassification
	type: mteb/toxic_conversations_50k
	config: default
	split: test
	revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
	metrics:
	- type: accuracy
	value: 69.3874
	- type: ap
	value: 13.829909072469423
	- type: f1
	value: 53.54534203543492
	- task:
	type: Classification
	dataset:
	name: MTEB TweetSentimentExtractionClassification
	type: mteb/tweet_sentiment_extraction
	config: default
	split: test
	revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
	metrics:
	- type: accuracy
	value: 62.62026032823995
	- type: f1
	value: 62.85251350485221
	- task:
	type: Clustering
	dataset:
	name: MTEB TwentyNewsgroupsClustering
	type: mteb/twentynewsgroups-clustering
	config: default
	split: test
	revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
	metrics:
	- type: v_measure
	value: 33.21527881409797
	- task:
	type: PairClassification
	dataset:
	name: MTEB TwitterSemEval2015
	type: mteb/twittersemeval2015-pairclassification
	config: default
	split: test
	revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
	metrics:
	- type: cos_sim_accuracy
	value: 84.97943613280086
	- type: cos_sim_ap
	value: 70.75454316885921
	- type: cos_sim_f1
	value: 65.38274012676743
	- type: cos_sim_precision
	value: 60.761214318078835
	- type: cos_sim_recall
	value: 70.76517150395777
	- type: dot_accuracy
	value: 79.0546581629612
	- type: dot_ap
	value: 47.3197121792147
	- type: dot_f1
	value: 49.20106524633821
	- type: dot_precision
	value: 42.45499808502489
	- type: dot_recall
	value: 58.49604221635884
	- type: euclidean_accuracy
	value: 85.08076533349228
	- type: euclidean_ap
	value: 70.95016106374474
	- type: euclidean_f1
	value: 65.43987900176455
	- type: euclidean_precision
	value: 62.64478764478765
	- type: euclidean_recall
	value: 68.49604221635884
	- type: manhattan_accuracy
	value: 84.93771234428085
	- type: manhattan_ap
	value: 70.63668388755362
	- type: manhattan_f1
	value: 65.23895401262398
	- type: manhattan_precision
	value: 56.946084218811485
	- type: manhattan_recall
	value: 76.35883905013192
	- type: max_accuracy
	value: 85.08076533349228
	- type: max_ap
	value: 70.95016106374474
	- type: max_f1
	value: 65.43987900176455
	- task:
	type: PairClassification
	dataset:
	name: MTEB TwitterURLCorpus
	type: mteb/twitterurlcorpus-pairclassification
	config: default
	split: test
	revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
	metrics:
	- type: cos_sim_accuracy
	value: 88.69096130709822
	- type: cos_sim_ap
	value: 84.82526278228542
	- type: cos_sim_f1
	value: 77.65485060585536
	- type: cos_sim_precision
	value: 75.94582658619167
	- type: cos_sim_recall
	value: 79.44256236526024
	- type: dot_accuracy
	value: 80.97954748321496
	- type: dot_ap
	value: 64.81642914145866
	- type: dot_f1
	value: 60.631996987229975
	- type: dot_precision
	value: 54.5897293631712
	- type: dot_recall
	value: 68.17831844779796
	- type: euclidean_accuracy
	value: 88.6987231730508
	- type: euclidean_ap
	value: 84.80003825477253
	- type: euclidean_f1
	value: 77.67194179854496
	- type: euclidean_precision
	value: 75.7128235122094
	- type: euclidean_recall
	value: 79.73514012935017
	- type: manhattan_accuracy
	value: 88.62692591298949
	- type: manhattan_ap
	value: 84.80451408255276
	- type: manhattan_f1
	value: 77.69888949572183
	- type: manhattan_precision
	value: 73.70311528631622
	- type: manhattan_recall
	value: 82.15275639051433
	- type: max_accuracy
	value: 88.6987231730508
	- type: max_ap
	value: 84.82526278228542
	- type: max_f1
	value: 77.69888949572183
	---

	# multilingual-e5-small-mlx
	This model was converted to MLX format from [`intfloat/multilingual-e5-small`]().
	Refer to the [original model card](https://huggingface.co/intfloat/multilingual-e5-small) for more details on the model.
	## Use with mlx
	```bash
	pip install mlx
	git clone https://github.com/ml-explore/mlx-examples.git
	cd mlx-examples/llms/hf_llm
	python generate.py --model mlx-community/multilingual-e5-small-mlx --prompt "My name is"
	```