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	---
	model-index:
	- name: no_model_name_available
	results:
	- dataset:
	config: en-ext
	name: MTEB AmazonCounterfactualClassification (en-ext)
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	split: test
	type: mteb/amazon_counterfactual
	metrics:
	- type: accuracy
	value: 68.60569715142428
	- type: ap
	value: 19.05710055685074
	- type: ap_weighted
	value: 19.05710055685074
	- type: f1
	value: 56.581673345537695
	- type: f1_weighted
	value: 74.61143344921274
	- type: main_score
	value: 68.60569715142428
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB AmazonCounterfactualClassification (en)
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	split: test
	type: mteb/amazon_counterfactual
	metrics:
	- type: accuracy
	value: 68.56716417910447
	- type: ap
	value: 31.32344301280815
	- type: ap_weighted
	value: 31.32344301280815
	- type: f1
	value: 62.570662383384025
	- type: f1_weighted
	value: 71.61789541976941
	- type: main_score
	value: 68.56716417910447
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB AmazonCounterfactualClassification (de)
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	split: test
	type: mteb/amazon_counterfactual
	metrics:
	- type: accuracy
	value: 63.276231263383295
	- type: ap
	value: 77.029702826753
	- type: ap_weighted
	value: 77.029702826753
	- type: f1
	value: 61.38234936043525
	- type: f1_weighted
	value: 64.54688276108833
	- type: main_score
	value: 63.276231263383295
	task:
	type: Classification
	- dataset:
	config: ja
	name: MTEB AmazonCounterfactualClassification (ja)
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	split: test
	type: mteb/amazon_counterfactual
	metrics:
	- type: accuracy
	value: 44.368308351177724
	- type: ap
	value: 10.954835146791183
	- type: ap_weighted
	value: 10.954835146791183
	- type: f1
	value: 36.62906436161906
	- type: f1_weighted
	value: 51.69895802800691
	- type: main_score
	value: 44.368308351177724
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB AmazonReviewsClassification (en)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 36.808
	- type: f1
	value: 34.68301166695203
	- type: f1_weighted
	value: 34.68301166695202
	- type: main_score
	value: 36.808
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB AmazonReviewsClassification (de)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 27.057999999999993
	- type: f1
	value: 26.24275950859653
	- type: f1_weighted
	value: 26.242759508596524
	- type: main_score
	value: 27.057999999999993
	task:
	type: Classification
	- dataset:
	config: es
	name: MTEB AmazonReviewsClassification (es)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 31.064000000000004
	- type: f1
	value: 29.708079352003708
	- type: f1_weighted
	value: 29.7080793520037
	- type: main_score
	value: 31.064000000000004
	task:
	type: Classification
	- dataset:
	config: fr
	name: MTEB AmazonReviewsClassification (fr)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 29.43
	- type: f1
	value: 27.94855548400926
	- type: f1_weighted
	value: 27.94855548400926
	- type: main_score
	value: 29.43
	task:
	type: Classification
	- dataset:
	config: ja
	name: MTEB AmazonReviewsClassification (ja)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 20.787999999999997
	- type: f1
	value: 15.135022040282188
	- type: f1_weighted
	value: 15.135022040282188
	- type: main_score
	value: 20.787999999999997
	task:
	type: Classification
	- dataset:
	config: zh
	name: MTEB AmazonReviewsClassification (zh)
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	split: test
	type: mteb/amazon_reviews_multi
	metrics:
	- type: accuracy
	value: 21.914
	- type: f1
	value: 15.895956878609303
	- type: f1_weighted
	value: 15.895956878609303
	- type: main_score
	value: 21.914
	task:
	type: Classification
	- dataset:
	config: default
	name: MTEB ArxivClusteringS2S (default)
	revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
	split: test
	type: mteb/arxiv-clustering-s2s
	metrics:
	- type: main_score
	value: 19.890899955689118
	- type: v_measure
	value: 19.890899955689118
	- type: v_measure_std
	value: 15.234197799081727
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB AskUbuntuDupQuestions (default)
	revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
	split: test
	type: mteb/askubuntudupquestions-reranking
	metrics:
	- type: main_score
	value: 49.123206371254746
	- type: map
	value: 49.123206371254746
	- type: mrr
	value: 62.31862551114629
	- type: nAUC_map_diff1
	value: 10.382490924755208
	- type: nAUC_map_max
	value: 18.748869416562293
	- type: nAUC_map_std
	value: 2.5774869725944383
	- type: nAUC_mrr_diff1
	value: 13.422210021656673
	- type: nAUC_mrr_max
	value: 24.878571083763035
	- type: nAUC_mrr_std
	value: -0.41050314967328677
	task:
	type: Reranking
	- dataset:
	config: default
	name: MTEB BIOSSES (default)
	revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
	split: test
	type: mteb/biosses-sts
	metrics:
	- type: cosine_pearson
	value: 54.66661709953381
	- type: cosine_spearman
	value: 61.90442258245585
	- type: euclidean_pearson
	value: 57.802209299685984
	- type: euclidean_spearman
	value: 61.90442258245585
	- type: main_score
	value: 61.90442258245585
	- type: manhattan_pearson
	value: 58.05739954223122
	- type: manhattan_spearman
	value: 62.10683683315609
	- type: pearson
	value: 54.66661709953381
	- type: spearman
	value: 61.90442258245585
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB Banking77Classification (default)
	revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
	split: test
	type: mteb/banking77
	metrics:
	- type: accuracy
	value: 50.75324675324676
	- type: f1
	value: 50.08833636657759
	- type: f1_weighted
	value: 50.08833636657759
	- type: main_score
	value: 50.75324675324676
	task:
	type: Classification
	- dataset:
	config: default
	name: MTEB BiorxivClusteringS2S (default)
	revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
	split: test
	type: mteb/biorxiv-clustering-s2s
	metrics:
	- type: main_score
	value: 19.543768231624547
	- type: v_measure
	value: 19.543768231624547
	- type: v_measure_std
	value: 0.8448669358199523
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB EmotionClassification (default)
	revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
	split: test
	type: mteb/emotion
	metrics:
	- type: accuracy
	value: 31.465
	- type: f1
	value: 27.518410158786278
	- type: f1_weighted
	value: 32.729446691751605
	- type: main_score
	value: 31.465
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB MTOPDomainClassification (en)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 83.66393068855447
	- type: f1
	value: 83.02273407562654
	- type: f1_weighted
	value: 83.66877159114159
	- type: main_score
	value: 83.66393068855447
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB MTOPDomainClassification (de)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 63.97013243167089
	- type: f1
	value: 60.85033241575268
	- type: f1_weighted
	value: 63.82115556806192
	- type: main_score
	value: 63.97013243167089
	task:
	type: Classification
	- dataset:
	config: es
	name: MTEB MTOPDomainClassification (es)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 62.37491661107405
	- type: f1
	value: 60.94290925815502
	- type: f1_weighted
	value: 62.10717598146462
	- type: main_score
	value: 62.37491661107405
	task:
	type: Classification
	- dataset:
	config: fr
	name: MTEB MTOPDomainClassification (fr)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 62.95020357031006
	- type: f1
	value: 60.758971765144224
	- type: f1_weighted
	value: 63.42247920372272
	- type: main_score
	value: 62.95020357031006
	task:
	type: Classification
	- dataset:
	config: hi
	name: MTEB MTOPDomainClassification (hi)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 12.613840086052347
	- type: f1
	value: 6.5750442135283
	- type: f1_weighted
	value: 6.53244904380679
	- type: main_score
	value: 12.613840086052347
	task:
	type: Classification
	- dataset:
	config: th
	name: MTEB MTOPDomainClassification (th)
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	split: test
	type: mteb/mtop_domain
	metrics:
	- type: accuracy
	value: 14.759493670886076
	- type: f1
	value: 8.12843236923924
	- type: f1_weighted
	value: 8.793246140296032
	- type: main_score
	value: 14.759493670886076
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB MTOPIntentClassification (en)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 49.43228454172367
	- type: f1
	value: 34.55112542095168
	- type: f1_weighted
	value: 52.614378484454974
	- type: main_score
	value: 49.43228454172367
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB MTOPIntentClassification (de)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 39.01662440123979
	- type: f1
	value: 23.82791663064076
	- type: f1_weighted
	value: 43.645398141967966
	- type: main_score
	value: 39.01662440123979
	task:
	type: Classification
	- dataset:
	config: es
	name: MTEB MTOPIntentClassification (es)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 37.11140760507005
	- type: f1
	value: 21.935352507756388
	- type: f1_weighted
	value: 39.321275372065685
	- type: main_score
	value: 37.11140760507005
	task:
	type: Classification
	- dataset:
	config: fr
	name: MTEB MTOPIntentClassification (fr)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 33.7770122142186
	- type: f1
	value: 22.220964590376273
	- type: f1_weighted
	value: 37.485286173160986
	- type: main_score
	value: 33.7770122142186
	task:
	type: Classification
	- dataset:
	config: hi
	name: MTEB MTOPIntentClassification (hi)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 5.453567586948727
	- type: f1
	value: 0.7075326300577311
	- type: f1_weighted
	value: 2.3858630958577836
	- type: main_score
	value: 5.453567586948727
	task:
	type: Classification
	- dataset:
	config: th
	name: MTEB MTOPIntentClassification (th)
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	split: test
	type: mteb/mtop_intent
	metrics:
	- type: accuracy
	value: 5.529837251356239
	- type: f1
	value: 1.2115090491792773
	- type: f1_weighted
	value: 3.498070456864493
	- type: main_score
	value: 5.529837251356239
	task:
	type: Classification
	- dataset:
	config: eng
	name: MTEB MasakhaNEWSClassification (eng)
	revision: 18193f187b92da67168c655c9973a165ed9593dd
	split: test
	type: mteb/masakhanews
	metrics:
	- type: accuracy
	value: 64.5042194092827
	- type: f1
	value: 62.368592308141814
	- type: f1_weighted
	value: 63.90417453510408
	- type: main_score
	value: 64.5042194092827
	task:
	type: Classification
	- dataset:
	config: eng
	name: MTEB MasakhaNEWSClusteringS2S (eng)
	revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
	split: test
	type: masakhane/masakhanews
	metrics:
	- type: main_score
	value: 24.84564500417387
	- type: v_measure
	value: 24.84564500417387
	- type: v_measure_std
	value: 22.286703004465615
	task:
	type: Clustering
	- dataset:
	config: ta
	name: MTEB MassiveIntentClassification (ta)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.219233355749832
	- type: f1
	value: 0.1932870095686131
	- type: f1_weighted
	value: 0.251235487639337
	- type: main_score
	value: 2.219233355749832
	task:
	type: Classification
	- dataset:
	config: ml
	name: MTEB MassiveIntentClassification (ml)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.2844653665097512
	- type: f1
	value: 0.18710410412943543
	- type: f1_weighted
	value: 0.2739907174462001
	- type: main_score
	value: 1.2844653665097512
	task:
	type: Classification
	- dataset:
	config: af
	name: MTEB MassiveIntentClassification (af)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 32.982515131136516
	- type: f1
	value: 29.879476335364973
	- type: f1_weighted
	value: 32.59262194412672
	- type: main_score
	value: 32.982515131136516
	task:
	type: Classification
	- dataset:
	config: bn
	name: MTEB MassiveIntentClassification (bn)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.2125084061869535
	- type: f1
	value: 0.5736320148349802
	- type: f1_weighted
	value: 0.7371018417507617
	- type: main_score
	value: 2.2125084061869535
	task:
	type: Classification
	- dataset:
	config: is
	name: MTEB MassiveIntentClassification (is)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 27.165433759246802
	- type: f1
	value: 25.68362075943369
	- type: f1_weighted
	value: 25.71202157696122
	- type: main_score
	value: 27.165433759246802
	task:
	type: Classification
	- dataset:
	config: el
	name: MTEB MassiveIntentClassification (el)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 10.665770006724948
	- type: f1
	value: 5.114611283180833
	- type: f1_weighted
	value: 7.526848175428076
	- type: main_score
	value: 10.665770006724948
	task:
	type: Classification
	- dataset:
	config: sw
	name: MTEB MassiveIntentClassification (sw)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 31.661062542030933
	- type: f1
	value: 31.298953203005986
	- type: f1_weighted
	value: 30.183076634560134
	- type: main_score
	value: 31.661062542030933
	task:
	type: Classification
	- dataset:
	config: cy
	name: MTEB MassiveIntentClassification (cy)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 27.995965030262276
	- type: f1
	value: 25.849404737727465
	- type: f1_weighted
	value: 26.922571545761638
	- type: main_score
	value: 27.995965030262276
	task:
	type: Classification
	- dataset:
	config: pt
	name: MTEB MassiveIntentClassification (pt)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 36.73839946200404
	- type: f1
	value: 35.6799981256784
	- type: f1_weighted
	value: 35.65583276626004
	- type: main_score
	value: 36.73839946200404
	task:
	type: Classification
	- dataset:
	config: fa
	name: MTEB MassiveIntentClassification (fa)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.1062542030934768
	- type: f1
	value: 0.3829753109058956
	- type: f1_weighted
	value: 0.42459533841173747
	- type: main_score
	value: 1.1062542030934768
	task:
	type: Classification
	- dataset:
	config: mn
	name: MTEB MassiveIntentClassification (mn)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.3604572965702753
	- type: f1
	value: 0.9096234324517042
	- type: f1_weighted
	value: 0.9394595549389105
	- type: main_score
	value: 2.3604572965702753
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB MassiveIntentClassification (de)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 32.68997982515132
	- type: f1
	value: 29.986572248952147
	- type: f1_weighted
	value: 32.22231191644284
	- type: main_score
	value: 32.68997982515132
	task:
	type: Classification
	- dataset:
	config: sl
	name: MTEB MassiveIntentClassification (sl)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 36.70477471418964
	- type: f1
	value: 33.50288534893127
	- type: f1_weighted
	value: 34.846130335010265
	- type: main_score
	value: 36.70477471418964
	task:
	type: Classification
	- dataset:
	config: km
	name: MTEB MassiveIntentClassification (km)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.96906523201076
	- type: f1
	value: 0.7797856721437596
	- type: f1_weighted
	value: 0.6236996914225641
	- type: main_score
	value: 2.96906523201076
	task:
	type: Classification
	- dataset:
	config: az
	name: MTEB MassiveIntentClassification (az)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 31.01882985877606
	- type: f1
	value: 29.527835951539323
	- type: f1_weighted
	value: 30.66568514409952
	- type: main_score
	value: 31.01882985877606
	task:
	type: Classification
	- dataset:
	config: my
	name: MTEB MassiveIntentClassification (my)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 3.2178883658372555
	- type: f1
	value: 0.5240681583697773
	- type: f1_weighted
	value: 0.9198214868347652
	- type: main_score
	value: 3.2178883658372555
	task:
	type: Classification
	- dataset:
	config: it
	name: MTEB MassiveIntentClassification (it)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 37.11499663752522
	- type: f1
	value: 36.36396173693096
	- type: f1_weighted
	value: 35.50337761684995
	- type: main_score
	value: 37.11499663752522
	task:
	type: Classification
	- dataset:
	config: sq
	name: MTEB MassiveIntentClassification (sq)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 26.7350369872226
	- type: f1
	value: 25.812896452146234
	- type: f1_weighted
	value: 26.2226872478251
	- type: main_score
	value: 26.7350369872226
	task:
	type: Classification
	- dataset:
	config: da
	name: MTEB MassiveIntentClassification (da)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 34.97982515131137
	- type: f1
	value: 32.92316320729933
	- type: f1_weighted
	value: 33.68424734170567
	- type: main_score
	value: 34.97982515131137
	task:
	type: Classification
	- dataset:
	config: ka
	name: MTEB MassiveIntentClassification (ka)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.546738399462004
	- type: f1
	value: 0.6491922803798055
	- type: f1_weighted
	value: 0.36416059882684426
	- type: main_score
	value: 1.546738399462004
	task:
	type: Classification
	- dataset:
	config: hu
	name: MTEB MassiveIntentClassification (hu)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 25.16476126429052
	- type: f1
	value: 23.67218773633549
	- type: f1_weighted
	value: 23.6371559019449
	- type: main_score
	value: 25.16476126429052
	task:
	type: Classification
	- dataset:
	config: ms
	name: MTEB MassiveIntentClassification (ms)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 33.79959650302623
	- type: f1
	value: 32.51301308582213
	- type: f1_weighted
	value: 32.526479564865305
	- type: main_score
	value: 33.79959650302623
	task:
	type: Classification
	- dataset:
	config: tl
	name: MTEB MassiveIntentClassification (tl)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 29.49226630800269
	- type: f1
	value: 28.94940260858102
	- type: f1_weighted
	value: 28.63948113059682
	- type: main_score
	value: 29.49226630800269
	task:
	type: Classification
	- dataset:
	config: th
	name: MTEB MassiveIntentClassification (th)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.6778749159381305
	- type: f1
	value: 0.9744693901937154
	- type: f1_weighted
	value: 0.691053805319416
	- type: main_score
	value: 1.6778749159381305
	task:
	type: Classification
	- dataset:
	config: fi
	name: MTEB MassiveIntentClassification (fi)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 30.114324142568925
	- type: f1
	value: 29.430743039242152
	- type: f1_weighted
	value: 29.04299307313548
	- type: main_score
	value: 30.114324142568925
	task:
	type: Classification
	- dataset:
	config: hi
	name: MTEB MassiveIntentClassification (hi)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.797579018157364
	- type: f1
	value: 1.144033688398988
	- type: f1_weighted
	value: 1.0884768126381035
	- type: main_score
	value: 2.797579018157364
	task:
	type: Classification
	- dataset:
	config: lv
	name: MTEB MassiveIntentClassification (lv)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 32.54539340954942
	- type: f1
	value: 31.521139537198316
	- type: f1_weighted
	value: 31.530360085026093
	- type: main_score
	value: 32.54539340954942
	task:
	type: Classification
	- dataset:
	config: sv
	name: MTEB MassiveIntentClassification (sv)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 30.783456624075324
	- type: f1
	value: 29.604725003907866
	- type: f1_weighted
	value: 29.685617024715732
	- type: main_score
	value: 30.783456624075324
	task:
	type: Classification
	- dataset:
	config: am
	name: MTEB MassiveIntentClassification (am)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.8426361802286482
	- type: f1
	value: 0.33542666799543247
	- type: f1_weighted
	value: 0.2711276986927232
	- type: main_score
	value: 1.8426361802286482
	task:
	type: Classification
	- dataset:
	config: jv
	name: MTEB MassiveIntentClassification (jv)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 30.178211163416268
	- type: f1
	value: 29.37132431463145
	- type: f1_weighted
	value: 29.494452777308833
	- type: main_score
	value: 30.178211163416268
	task:
	type: Classification
	- dataset:
	config: ru
	name: MTEB MassiveIntentClassification (ru)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.649630127774042
	- type: f1
	value: 1.7505098874789995
	- type: f1_weighted
	value: 1.4639682364635813
	- type: main_score
	value: 2.649630127774042
	task:
	type: Classification
	- dataset:
	config: zh-TW
	name: MTEB MassiveIntentClassification (zh-TW)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 4.468728984532616
	- type: f1
	value: 2.090461109042727
	- type: f1_weighted
	value: 2.7853674561791295
	- type: main_score
	value: 4.468728984532616
	task:
	type: Classification
	- dataset:
	config: fr
	name: MTEB MassiveIntentClassification (fr)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 33.27168796234029
	- type: f1
	value: 32.00481372908824
	- type: f1_weighted
	value: 32.159041657111764
	- type: main_score
	value: 33.27168796234029
	task:
	type: Classification
	- dataset:
	config: zh-CN
	name: MTEB MassiveIntentClassification (zh-CN)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 0.749831876260928
	- type: f1
	value: 0.11432947296104061
	- type: f1_weighted
	value: 0.0764038848837725
	- type: main_score
	value: 0.749831876260928
	task:
	type: Classification
	- dataset:
	config: nb
	name: MTEB MassiveIntentClassification (nb)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 32.125084061869536
	- type: f1
	value: 30.154247947358247
	- type: f1_weighted
	value: 30.87288096360447
	- type: main_score
	value: 32.125084061869536
	task:
	type: Classification
	- dataset:
	config: kn
	name: MTEB MassiveIntentClassification (kn)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.617350369872226
	- type: f1
	value: 0.9905489260231543
	- type: f1_weighted
	value: 0.7953294182207199
	- type: main_score
	value: 1.617350369872226
	task:
	type: Classification
	- dataset:
	config: ja
	name: MTEB MassiveIntentClassification (ja)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 3.806321452589106
	- type: f1
	value: 1.9196646149428953
	- type: f1_weighted
	value: 1.6645242984042585
	- type: main_score
	value: 3.806321452589106
	task:
	type: Classification
	- dataset:
	config: nl
	name: MTEB MassiveIntentClassification (nl)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 35.77673167451245
	- type: f1
	value: 33.18041618186975
	- type: f1_weighted
	value: 35.833046113268786
	- type: main_score
	value: 35.77673167451245
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB MassiveIntentClassification (en)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 53.4969737726967
	- type: f1
	value: 51.88341293441036
	- type: f1_weighted
	value: 53.20514357568628
	- type: main_score
	value: 53.4969737726967
	task:
	type: Classification
	- dataset:
	config: ar
	name: MTEB MassiveIntentClassification (ar)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 4.784801613987895
	- type: f1
	value: 1.969274839533907
	- type: f1_weighted
	value: 2.4942212470758016
	- type: main_score
	value: 4.784801613987895
	task:
	type: Classification
	- dataset:
	config: es
	name: MTEB MassiveIntentClassification (es)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 31.069266980497645
	- type: f1
	value: 31.48265427665997
	- type: f1_weighted
	value: 30.3696521492686
	- type: main_score
	value: 31.069266980497645
	task:
	type: Classification
	- dataset:
	config: he
	name: MTEB MassiveIntentClassification (he)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 1.9670477471418968
	- type: f1
	value: 0.45697365831527426
	- type: f1_weighted
	value: 0.2853963696007572
	- type: main_score
	value: 1.9670477471418968
	task:
	type: Classification
	- dataset:
	config: te
	name: MTEB MassiveIntentClassification (te)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.1015467383994615
	- type: f1
	value: 0.5210481229705188
	- type: f1_weighted
	value: 0.5924944385210995
	- type: main_score
	value: 2.1015467383994615
	task:
	type: Classification
	- dataset:
	config: tr
	name: MTEB MassiveIntentClassification (tr)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 31.318090114324143
	- type: f1
	value: 30.05810538658039
	- type: f1_weighted
	value: 30.360376696442504
	- type: main_score
	value: 31.318090114324143
	task:
	type: Classification
	- dataset:
	config: vi
	name: MTEB MassiveIntentClassification (vi)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 19.078681909885677
	- type: f1
	value: 18.360818504390085
	- type: f1_weighted
	value: 18.15470646878023
	- type: main_score
	value: 19.078681909885677
	task:
	type: Classification
	- dataset:
	config: id
	name: MTEB MassiveIntentClassification (id)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 35.564895763281775
	- type: f1
	value: 35.587064959631185
	- type: f1_weighted
	value: 34.4349962874478
	- type: main_score
	value: 35.564895763281775
	task:
	type: Classification
	- dataset:
	config: ko
	name: MTEB MassiveIntentClassification (ko)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 3.2111634162743776
	- type: f1
	value: 1.4524341197394974
	- type: f1_weighted
	value: 1.3395307357797508
	- type: main_score
	value: 3.2111634162743776
	task:
	type: Classification
	- dataset:
	config: ro
	name: MTEB MassiveIntentClassification (ro)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 33.99798251513114
	- type: f1
	value: 32.69281167233965
	- type: f1_weighted
	value: 32.22827641327085
	- type: main_score
	value: 33.99798251513114
	task:
	type: Classification
	- dataset:
	config: pl
	name: MTEB MassiveIntentClassification (pl)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 29.660390047074646
	- type: f1
	value: 28.090771859451536
	- type: f1_weighted
	value: 29.50058846849659
	- type: main_score
	value: 29.660390047074646
	task:
	type: Classification
	- dataset:
	config: ur
	name: MTEB MassiveIntentClassification (ur)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.118359112306658
	- type: f1
	value: 1.0794128790274702
	- type: f1_weighted
	value: 1.0149237288074577
	- type: main_score
	value: 2.118359112306658
	task:
	type: Classification
	- dataset:
	config: hy
	name: MTEB MassiveIntentClassification (hy)
	revision: 4672e20407010da34463acc759c162ca9734bca6
	split: test
	type: mteb/amazon_massive_intent
	metrics:
	- type: accuracy
	value: 2.242770679219906
	- type: f1
	value: 0.6772746623940161
	- type: f1_weighted
	value: 0.5935033259869644
	- type: main_score
	value: 2.242770679219906
	task:
	type: Classification
	- dataset:
	config: ta
	name: MTEB MassiveScenarioClassification (ta)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 4.7679892400807
	- type: f1
	value: 0.6958635242707644
	- type: f1_weighted
	value: 0.7383116540131966
	- type: main_score
	value: 4.7679892400807
	task:
	type: Classification
	- dataset:
	config: ml
	name: MTEB MassiveScenarioClassification (ml)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 4.599865501008742
	- type: f1
	value: 0.8680195452904774
	- type: f1_weighted
	value: 1.3022709162006496
	- type: main_score
	value: 4.599865501008742
	task:
	type: Classification
	- dataset:
	config: af
	name: MTEB MassiveScenarioClassification (af)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 45.80026899798251
	- type: f1
	value: 42.09162084904855
	- type: f1_weighted
	value: 45.937899984554896
	- type: main_score
	value: 45.80026899798251
	task:
	type: Classification
	- dataset:
	config: bn
	name: MTEB MassiveScenarioClassification (bn)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 7.935440484196368
	- type: f1
	value: 2.054473625082069
	- type: f1_weighted
	value: 2.331310360179839
	- type: main_score
	value: 7.935440484196368
	task:
	type: Classification
	- dataset:
	config: is
	name: MTEB MassiveScenarioClassification (is)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 39.525891055817084
	- type: f1
	value: 35.64315129468117
	- type: f1_weighted
	value: 38.873288696604064
	- type: main_score
	value: 39.525891055817084
	task:
	type: Classification
	- dataset:
	config: el
	name: MTEB MassiveScenarioClassification (el)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 16.822461331540016
	- type: f1
	value: 9.528868617590787
	- type: f1_weighted
	value: 12.052833175443745
	- type: main_score
	value: 16.822461331540016
	task:
	type: Classification
	- dataset:
	config: sw
	name: MTEB MassiveScenarioClassification (sw)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 41.44922663080027
	- type: f1
	value: 38.29694592816531
	- type: f1_weighted
	value: 40.494682049238065
	- type: main_score
	value: 41.44922663080027
	task:
	type: Classification
	- dataset:
	config: cy
	name: MTEB MassiveScenarioClassification (cy)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 36.37525218560861
	- type: f1
	value: 32.742079476295714
	- type: f1_weighted
	value: 36.41453434396975
	- type: main_score
	value: 36.37525218560861
	task:
	type: Classification
	- dataset:
	config: pt
	name: MTEB MassiveScenarioClassification (pt)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 43.79959650302623
	- type: f1
	value: 41.74604131799107
	- type: f1_weighted
	value: 41.89697637112924
	- type: main_score
	value: 43.79959650302623
	task:
	type: Classification
	- dataset:
	config: fa
	name: MTEB MassiveScenarioClassification (fa)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 6.2844653665097505
	- type: f1
	value: 1.1363404526147562
	- type: f1_weighted
	value: 1.507290141564863
	- type: main_score
	value: 6.2844653665097505
	task:
	type: Classification
	- dataset:
	config: mn
	name: MTEB MassiveScenarioClassification (mn)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 5.406859448554135
	- type: f1
	value: 2.560817113707556
	- type: f1_weighted
	value: 2.408341973383642
	- type: main_score
	value: 5.406859448554135
	task:
	type: Classification
	- dataset:
	config: de
	name: MTEB MassiveScenarioClassification (de)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 43.08002689979825
	- type: f1
	value: 39.31491179400749
	- type: f1_weighted
	value: 42.387701010649735
	- type: main_score
	value: 43.08002689979825
	task:
	type: Classification
	- dataset:
	config: sl
	name: MTEB MassiveScenarioClassification (sl)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 46.30127774041695
	- type: f1
	value: 43.177548916667774
	- type: f1_weighted
	value: 46.02641155529322
	- type: main_score
	value: 46.30127774041695
	task:
	type: Classification
	- dataset:
	config: km
	name: MTEB MassiveScenarioClassification (km)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 5.968392737054471
	- type: f1
	value: 1.558644350101979
	- type: f1_weighted
	value: 2.184277748991485
	- type: main_score
	value: 5.968392737054471
	task:
	type: Classification
	- dataset:
	config: az
	name: MTEB MassiveScenarioClassification (az)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 39.08204438466712
	- type: f1
	value: 37.19465931596499
	- type: f1_weighted
	value: 37.92508333682256
	- type: main_score
	value: 39.08204438466712
	task:
	type: Classification
	- dataset:
	config: my
	name: MTEB MassiveScenarioClassification (my)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 5.712844653665098
	- type: f1
	value: 2.3513952725160445
	- type: f1_weighted
	value: 2.591355133449796
	- type: main_score
	value: 5.712844653665098
	task:
	type: Classification
	- dataset:
	config: it
	name: MTEB MassiveScenarioClassification (it)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 44.79488903833221
	- type: f1
	value: 42.216456011086514
	- type: f1_weighted
	value: 43.63836497077992
	- type: main_score
	value: 44.79488903833221
	task:
	type: Classification
	- dataset:
	config: sq
	name: MTEB MassiveScenarioClassification (sq)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 38.91055817081372
	- type: f1
	value: 36.658118919837705
	- type: f1_weighted
	value: 38.285047658406185
	- type: main_score
	value: 38.91055817081372
	task:
	type: Classification
	- dataset:
	config: da
	name: MTEB MassiveScenarioClassification (da)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 42.82447881640888
	- type: f1
	value: 39.71183576580626
	- type: f1_weighted
	value: 42.99955794883917
	- type: main_score
	value: 42.82447881640888
	task:
	type: Classification
	- dataset:
	config: ka
	name: MTEB MassiveScenarioClassification (ka)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 6.9569603227975785
	- type: f1
	value: 1.3249507928345723
	- type: f1_weighted
	value: 2.1526435195273512
	- type: main_score
	value: 6.9569603227975785
	task:
	type: Classification
	- dataset:
	config: hu
	name: MTEB MassiveScenarioClassification (hu)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 35.47747141896436
	- type: f1
	value: 32.68368628376791
	- type: f1_weighted
	value: 34.486227854192805
	- type: main_score
	value: 35.47747141896436
	task:
	type: Classification
	- dataset:
	config: ms
	name: MTEB MassiveScenarioClassification (ms)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 44.20645595158036
	- type: f1
	value: 40.46275245484104
	- type: f1_weighted
	value: 43.07451372640555
	- type: main_score
	value: 44.20645595158036
	task:
	type: Classification
	- dataset:
	config: tl
	name: MTEB MassiveScenarioClassification (tl)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 37.565568258238066
	- type: f1
	value: 34.34228491467635
	- type: f1_weighted
	value: 36.715470304700304
	- type: main_score
	value: 37.565568258238066
	task:
	type: Classification
	- dataset:
	config: th
	name: MTEB MassiveScenarioClassification (th)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 4.428379287155346
	- type: f1
	value: 2.118733356397359
	- type: f1_weighted
	value: 1.6597464958411214
	- type: main_score
	value: 4.428379287155346
	task:
	type: Classification
	- dataset:
	config: fi
	name: MTEB MassiveScenarioClassification (fi)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 34.67720242098184
	- type: f1
	value: 31.648714845929625
	- type: f1_weighted
	value: 34.62782835061803
	- type: main_score
	value: 34.67720242098184
	task:
	type: Classification
	- dataset:
	config: hi
	name: MTEB MassiveScenarioClassification (hi)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 8.006052454606591
	- type: f1
	value: 2.1079480174137237
	- type: f1_weighted
	value: 2.1631918405037758
	- type: main_score
	value: 8.006052454606591
	task:
	type: Classification
	- dataset:
	config: lv
	name: MTEB MassiveScenarioClassification (lv)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 39.22999327505043
	- type: f1
	value: 37.16721131021293
	- type: f1_weighted
	value: 39.397613949853735
	- type: main_score
	value: 39.22999327505043
	task:
	type: Classification
	- dataset:
	config: sv
	name: MTEB MassiveScenarioClassification (sv)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 41.55010087424344
	- type: f1
	value: 38.32223910141539
	- type: f1_weighted
	value: 41.72498846160742
	- type: main_score
	value: 41.55010087424344
	task:
	type: Classification
	- dataset:
	config: am
	name: MTEB MassiveScenarioClassification (am)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 3.0363147276395432
	- type: f1
	value: 0.4951111891349476
	- type: f1_weighted
	value: 0.4456347917226148
	- type: main_score
	value: 3.0363147276395432
	task:
	type: Classification
	- dataset:
	config: jv
	name: MTEB MassiveScenarioClassification (jv)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 42.84801613987895
	- type: f1
	value: 40.77209890733345
	- type: f1_weighted
	value: 42.29511181907119
	- type: main_score
	value: 42.84801613987895
	task:
	type: Classification
	- dataset:
	config: ru
	name: MTEB MassiveScenarioClassification (ru)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 8.140551445864155
	- type: f1
	value: 3.088889182397252
	- type: f1_weighted
	value: 3.382529160821981
	- type: main_score
	value: 8.140551445864155
	task:
	type: Classification
	- dataset:
	config: zh-TW
	name: MTEB MassiveScenarioClassification (zh-TW)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 10.063887020847343
	- type: f1
	value: 4.3953906298120415
	- type: f1_weighted
	value: 6.1030360630370675
	- type: main_score
	value: 10.063887020847343
	task:
	type: Classification
	- dataset:
	config: fr
	name: MTEB MassiveScenarioClassification (fr)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 40.86079354404843
	- type: f1
	value: 38.12848430733589
	- type: f1_weighted
	value: 39.61399818207077
	- type: main_score
	value: 40.86079354404843
	task:
	type: Classification
	- dataset:
	config: zh-CN
	name: MTEB MassiveScenarioClassification (zh-CN)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 3.1809011432414254
	- type: f1
	value: 0.6663078501713696
	- type: f1_weighted
	value: 0.6161504543566888
	- type: main_score
	value: 3.1809011432414254
	task:
	type: Classification
	- dataset:
	config: nb
	name: MTEB MassiveScenarioClassification (nb)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 38.991257565568255
	- type: f1
	value: 35.8711142606479
	- type: f1_weighted
	value: 39.27058914996822
	- type: main_score
	value: 38.991257565568255
	task:
	type: Classification
	- dataset:
	config: kn
	name: MTEB MassiveScenarioClassification (kn)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 7.5117686617350365
	- type: f1
	value: 2.730333236177
	- type: f1_weighted
	value: 2.476626926704587
	- type: main_score
	value: 7.5117686617350365
	task:
	type: Classification
	- dataset:
	config: ja
	name: MTEB MassiveScenarioClassification (ja)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 8.32548755884331
	- type: f1
	value: 3.0996007067176996
	- type: f1_weighted
	value: 3.0676442629069967
	- type: main_score
	value: 8.32548755884331
	task:
	type: Classification
	- dataset:
	config: nl
	name: MTEB MassiveScenarioClassification (nl)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 47.57901815736382
	- type: f1
	value: 43.47365742357309
	- type: f1_weighted
	value: 47.581511497169764
	- type: main_score
	value: 47.57901815736382
	task:
	type: Classification
	- dataset:
	config: en
	name: MTEB MassiveScenarioClassification (en)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 63.84330867518494
	- type: f1
	value: 61.80623184800081
	- type: f1_weighted
	value: 63.66823920852459
	- type: main_score
	value: 63.84330867518494
	task:
	type: Classification
	- dataset:
	config: ar
	name: MTEB MassiveScenarioClassification (ar)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 10.060524546065905
	- type: f1
	value: 4.697788726183898
	- type: f1_weighted
	value: 8.0688374518688
	- type: main_score
	value: 10.060524546065905
	task:
	type: Classification
	- dataset:
	config: es
	name: MTEB MassiveScenarioClassification (es)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 39.02824478816409
	- type: f1
	value: 37.25613303442762
	- type: f1_weighted
	value: 38.22861284484312
	- type: main_score
	value: 39.02824478816409
	task:
	type: Classification
	- dataset:
	config: he
	name: MTEB MassiveScenarioClassification (he)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 5.0638870208473445
	- type: f1
	value: 1.0753261358276471
	- type: f1_weighted
	value: 1.0802883978030118
	- type: main_score
	value: 5.0638870208473445
	task:
	type: Classification
	- dataset:
	config: te
	name: MTEB MassiveScenarioClassification (te)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 6.321452589105584
	- type: f1
	value: 1.5829376262790664
	- type: f1_weighted
	value: 2.232184358298365
	- type: main_score
	value: 6.321452589105584
	task:
	type: Classification
	- dataset:
	config: tr
	name: MTEB MassiveScenarioClassification (tr)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 37.21923335574983
	- type: f1
	value: 36.993268170979576
	- type: f1_weighted
	value: 35.67645464322424
	- type: main_score
	value: 37.21923335574983
	task:
	type: Classification
	- dataset:
	config: vi
	name: MTEB MassiveScenarioClassification (vi)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 25.934767989240076
	- type: f1
	value: 24.616943306685748
	- type: f1_weighted
	value: 24.74309285569417
	- type: main_score
	value: 25.934767989240076
	task:
	type: Classification
	- dataset:
	config: id
	name: MTEB MassiveScenarioClassification (id)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 44.69401479488904
	- type: f1
	value: 42.41464498194295
	- type: f1_weighted
	value: 44.26134318268762
	- type: main_score
	value: 44.69401479488904
	task:
	type: Classification
	- dataset:
	config: ko
	name: MTEB MassiveScenarioClassification (ko)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 8.47343644922663
	- type: f1
	value: 2.9718553546241506
	- type: f1_weighted
	value: 3.9449930229420818
	- type: main_score
	value: 8.47343644922663
	task:
	type: Classification
	- dataset:
	config: ro
	name: MTEB MassiveScenarioClassification (ro)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 42.92199058507061
	- type: f1
	value: 40.00185738475351
	- type: f1_weighted
	value: 42.53838435113089
	- type: main_score
	value: 42.92199058507061
	task:
	type: Classification
	- dataset:
	config: pl
	name: MTEB MassiveScenarioClassification (pl)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 36.856086079354405
	- type: f1
	value: 35.85809216604705
	- type: f1_weighted
	value: 36.503220372495356
	- type: main_score
	value: 36.856086079354405
	task:
	type: Classification
	- dataset:
	config: ur
	name: MTEB MassiveScenarioClassification (ur)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 7.427706792199058
	- type: f1
	value: 2.355649221281433
	- type: f1_weighted
	value: 2.3635737714890097
	- type: main_score
	value: 7.427706792199058
	task:
	type: Classification
	- dataset:
	config: hy
	name: MTEB MassiveScenarioClassification (hy)
	revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
	split: test
	type: mteb/amazon_massive_scenario
	metrics:
	- type: accuracy
	value: 7.2494956287827845
	- type: f1
	value: 3.0267066892790786
	- type: f1_weighted
	value: 2.228737132597149
	- type: main_score
	value: 7.2494956287827845
	task:
	type: Classification
	- dataset:
	config: default
	name: MTEB MedrxivClusteringS2S (default)
	revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
	split: test
	type: mteb/medrxiv-clustering-s2s
	metrics:
	- type: main_score
	value: 22.3149940028344
	- type: v_measure
	value: 22.3149940028344
	- type: v_measure_std
	value: 1.184495521159966
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB MindSmallReranking (default)
	revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
	split: test
	type: mteb/mind_small
	metrics:
	- type: main_score
	value: 26.874241404290856
	- type: map
	value: 26.874241404290856
	- type: mrr
	value: 27.50127374810197
	- type: nAUC_map_diff1
	value: 20.72193125860396
	- type: nAUC_map_max
	value: -21.181361650744908
	- type: nAUC_map_std
	value: -21.136143423992458
	- type: nAUC_mrr_diff1
	value: 18.217458666186445
	- type: nAUC_mrr_max
	value: -14.657975701378914
	- type: nAUC_mrr_std
	value: -17.948245474413323
	task:
	type: Reranking
	- dataset:
	config: de
	name: MTEB OpusparcusPC (de)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.90448901623687
	- type: cosine_accuracy_threshold
	value: 32.084010045061795
	- type: cosine_ap
	value: 100.0
	- type: cosine_f1
	value: 99.95222169135212
	- type: cosine_f1_threshold
	value: 32.084010045061795
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.90448901623687
	- type: dot_accuracy
	value: 99.90448901623687
	- type: dot_accuracy_threshold
	value: 14.194202811836867
	- type: dot_ap
	value: 100.0
	- type: dot_f1
	value: 99.95222169135212
	- type: dot_f1_threshold
	value: 14.194202811836867
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.90448901623687
	- type: euclidean_accuracy
	value: 99.90448901623687
	- type: euclidean_accuracy_threshold
	value: 116.50380181599331
	- type: euclidean_ap
	value: 100.0
	- type: euclidean_f1
	value: 99.95222169135212
	- type: euclidean_f1_threshold
	value: 116.50380181599331
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.90448901623687
	- type: main_score
	value: 100.0
	- type: manhattan_accuracy
	value: 99.90448901623687
	- type: manhattan_accuracy_threshold
	value: 5994.10849076798
	- type: manhattan_ap
	value: 100.0
	- type: manhattan_f1
	value: 99.95222169135212
	- type: manhattan_f1_threshold
	value: 5994.10849076798
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.90448901623687
	- type: max_accuracy
	value: 99.90448901623687
	- type: max_ap
	value: 100.0
	- type: max_f1
	value: 99.95222169135212
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.90448901623687
	- type: similarity_accuracy
	value: 99.90448901623687
	- type: similarity_accuracy_threshold
	value: 32.084010045061795
	- type: similarity_ap
	value: 100.0
	- type: similarity_f1
	value: 99.95222169135212
	- type: similarity_f1_threshold
	value: 32.084010045061795
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.90448901623687
	task:
	type: PairClassification
	- dataset:
	config: en
	name: MTEB OpusparcusPC (en)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.89816700610999
	- type: cosine_accuracy_threshold
	value: 40.08682069986206
	- type: cosine_ap
	value: 100.0
	- type: cosine_f1
	value: 99.9490575649516
	- type: cosine_f1_threshold
	value: 40.08682069986206
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.89816700610999
	- type: dot_accuracy
	value: 99.89816700610999
	- type: dot_accuracy_threshold
	value: 40.08682068226012
	- type: dot_ap
	value: 100.0
	- type: dot_f1
	value: 99.9490575649516
	- type: dot_f1_threshold
	value: 40.08682068226012
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.89816700610999
	- type: euclidean_accuracy
	value: 99.89816700610999
	- type: euclidean_accuracy_threshold
	value: 109.46519126990579
	- type: euclidean_ap
	value: 100.0
	- type: euclidean_f1
	value: 99.9490575649516
	- type: euclidean_f1_threshold
	value: 109.46519126990579
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.89816700610999
	- type: main_score
	value: 100.0
	- type: manhattan_accuracy
	value: 99.89816700610999
	- type: manhattan_accuracy_threshold
	value: 5586.837509625999
	- type: manhattan_ap
	value: 100.0
	- type: manhattan_f1
	value: 99.9490575649516
	- type: manhattan_f1_threshold
	value: 5586.837509625999
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.89816700610999
	- type: max_accuracy
	value: 99.89816700610999
	- type: max_ap
	value: 100.0
	- type: max_f1
	value: 99.9490575649516
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.89816700610999
	- type: similarity_accuracy
	value: 99.89816700610999
	- type: similarity_accuracy_threshold
	value: 40.08682069986206
	- type: similarity_ap
	value: 100.0
	- type: similarity_f1
	value: 99.9490575649516
	- type: similarity_f1_threshold
	value: 40.08682069986206
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.89816700610999
	task:
	type: PairClassification
	- dataset:
	config: fi
	name: MTEB OpusparcusPC (fi)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.89561586638831
	- type: cosine_accuracy_threshold
	value: -22.557142663724193
	- type: cosine_ap
	value: 99.99999999999999
	- type: cosine_f1
	value: 99.94778067885117
	- type: cosine_f1_threshold
	value: -22.557142663724193
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.89561586638831
	- type: dot_accuracy
	value: 99.89561586638831
	- type: dot_accuracy_threshold
	value: -22.55714265463469
	- type: dot_ap
	value: 99.99999999999999
	- type: dot_f1
	value: 99.94778067885117
	- type: dot_f1_threshold
	value: -22.55714265463469
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.89561586638831
	- type: euclidean_accuracy
	value: 99.89561586638831
	- type: euclidean_accuracy_threshold
	value: 156.13722151560276
	- type: euclidean_ap
	value: 99.99999999999999
	- type: euclidean_f1
	value: 99.94778067885117
	- type: euclidean_f1_threshold
	value: 156.13722151560276
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.89561586638831
	- type: main_score
	value: 99.99999999999999
	- type: manhattan_accuracy
	value: 99.89561586638831
	- type: manhattan_accuracy_threshold
	value: 8123.721240822417
	- type: manhattan_ap
	value: 99.99999999999999
	- type: manhattan_f1
	value: 99.94778067885117
	- type: manhattan_f1_threshold
	value: 8123.721240822417
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.89561586638831
	- type: max_accuracy
	value: 99.89561586638831
	- type: max_ap
	value: 99.99999999999999
	- type: max_f1
	value: 99.94778067885117
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.89561586638831
	- type: similarity_accuracy
	value: 99.89561586638831
	- type: similarity_accuracy_threshold
	value: -22.557142663724193
	- type: similarity_ap
	value: 99.99999999999999
	- type: similarity_f1
	value: 99.94778067885117
	- type: similarity_f1_threshold
	value: -22.557142663724193
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.89561586638831
	task:
	type: PairClassification
	- dataset:
	config: fr
	name: MTEB OpusparcusPC (fr)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.90069513406156
	- type: cosine_accuracy_threshold
	value: 4.276752354307001
	- type: cosine_ap
	value: 100.0
	- type: cosine_f1
	value: 99.95032290114257
	- type: cosine_f1_threshold
	value: 4.276752354307001
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.90069513406156
	- type: dot_accuracy
	value: 99.90069513406156
	- type: dot_accuracy_threshold
	value: 4.276752351391649
	- type: dot_ap
	value: 100.0
	- type: dot_f1
	value: 99.95032290114257
	- type: dot_f1_threshold
	value: 4.276752351391649
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.90069513406156
	- type: euclidean_accuracy
	value: 99.90069513406156
	- type: euclidean_accuracy_threshold
	value: 136.9020176878726
	- type: euclidean_ap
	value: 100.0
	- type: euclidean_f1
	value: 99.95032290114257
	- type: euclidean_f1_threshold
	value: 136.9020176878726
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.90069513406156
	- type: main_score
	value: 100.0
	- type: manhattan_accuracy
	value: 99.90069513406156
	- type: manhattan_accuracy_threshold
	value: 7063.200709566871
	- type: manhattan_ap
	value: 100.0
	- type: manhattan_f1
	value: 99.95032290114257
	- type: manhattan_f1_threshold
	value: 7063.200709566871
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.90069513406156
	- type: max_accuracy
	value: 99.90069513406156
	- type: max_ap
	value: 100.0
	- type: max_f1
	value: 99.95032290114257
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.90069513406156
	- type: similarity_accuracy
	value: 99.90069513406156
	- type: similarity_accuracy_threshold
	value: 4.276752354307001
	- type: similarity_ap
	value: 100.0
	- type: similarity_f1
	value: 99.95032290114257
	- type: similarity_f1_threshold
	value: 4.276752354307001
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.90069513406156
	task:
	type: PairClassification
	- dataset:
	config: ru
	name: MTEB OpusparcusPC (ru)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.90636704119851
	- type: cosine_accuracy_threshold
	value: 7.132103928293631
	- type: cosine_ap
	value: 100.0
	- type: cosine_f1
	value: 99.95316159250585
	- type: cosine_f1_threshold
	value: 7.132103928293631
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.90636704119851
	- type: dot_accuracy
	value: 99.90636704119851
	- type: dot_accuracy_threshold
	value: -13.447421954803113
	- type: dot_ap
	value: 100.0
	- type: dot_f1
	value: 99.95316159250585
	- type: dot_f1_threshold
	value: -13.447421954803113
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.90636704119851
	- type: euclidean_accuracy
	value: 99.90636704119851
	- type: euclidean_accuracy_threshold
	value: 133.89453353967028
	- type: euclidean_ap
	value: 100.0
	- type: euclidean_f1
	value: 99.95316159250585
	- type: euclidean_f1_threshold
	value: 133.89453353967028
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.90636704119851
	- type: main_score
	value: 100.0
	- type: manhattan_accuracy
	value: 99.90636704119851
	- type: manhattan_accuracy_threshold
	value: 7020.097656622158
	- type: manhattan_ap
	value: 100.0
	- type: manhattan_f1
	value: 99.95316159250585
	- type: manhattan_f1_threshold
	value: 7020.097656622158
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.90636704119851
	- type: max_accuracy
	value: 99.90636704119851
	- type: max_ap
	value: 100.0
	- type: max_f1
	value: 99.95316159250585
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.90636704119851
	- type: similarity_accuracy
	value: 99.90636704119851
	- type: similarity_accuracy_threshold
	value: 7.132103928293631
	- type: similarity_ap
	value: 100.0
	- type: similarity_f1
	value: 99.95316159250585
	- type: similarity_f1_threshold
	value: 7.132103928293631
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.90636704119851
	task:
	type: PairClassification
	- dataset:
	config: sv
	name: MTEB OpusparcusPC (sv)
	revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
	split: test
	type: GEM/opusparcus
	metrics:
	- type: cosine_accuracy
	value: 99.89440337909187
	- type: cosine_accuracy_threshold
	value: 0.2529676444121498
	- type: cosine_ap
	value: 100.0
	- type: cosine_f1
	value: 99.9471737982039
	- type: cosine_f1_threshold
	value: 0.2529676444121498
	- type: cosine_precision
	value: 100.0
	- type: cosine_recall
	value: 99.89440337909187
	- type: dot_accuracy
	value: 99.89440337909187
	- type: dot_accuracy_threshold
	value: -13.939213532311562
	- type: dot_ap
	value: 99.99999999999999
	- type: dot_f1
	value: 99.9471737982039
	- type: dot_f1_threshold
	value: -13.939213532311562
	- type: dot_precision
	value: 100.0
	- type: dot_recall
	value: 99.89440337909187
	- type: euclidean_accuracy
	value: 99.89440337909187
	- type: euclidean_accuracy_threshold
	value: 139.80163412046423
	- type: euclidean_ap
	value: 100.0
	- type: euclidean_f1
	value: 99.9471737982039
	- type: euclidean_f1_threshold
	value: 139.80163412046423
	- type: euclidean_precision
	value: 100.0
	- type: euclidean_recall
	value: 99.89440337909187
	- type: main_score
	value: 100.0
	- type: manhattan_accuracy
	value: 99.89440337909187
	- type: manhattan_accuracy_threshold
	value: 7259.639697084279
	- type: manhattan_ap
	value: 100.0
	- type: manhattan_f1
	value: 99.9471737982039
	- type: manhattan_f1_threshold
	value: 7259.639697084279
	- type: manhattan_precision
	value: 100.0
	- type: manhattan_recall
	value: 99.89440337909187
	- type: max_accuracy
	value: 99.89440337909187
	- type: max_ap
	value: 100.0
	- type: max_f1
	value: 99.9471737982039
	- type: max_precision
	value: 100.0
	- type: max_recall
	value: 99.89440337909187
	- type: similarity_accuracy
	value: 99.89440337909187
	- type: similarity_accuracy_threshold
	value: 0.2529676444121498
	- type: similarity_ap
	value: 100.0
	- type: similarity_f1
	value: 99.9471737982039
	- type: similarity_f1_threshold
	value: 0.2529676444121498
	- type: similarity_precision
	value: 100.0
	- type: similarity_recall
	value: 99.89440337909187
	task:
	type: PairClassification
	- dataset:
	config: default
	name: MTEB QuoraRetrieval (default)
	revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
	split: test
	type: mteb/quora
	metrics:
	- type: main_score
	value: 68.73
	- type: map_at_1
	value: 53.492
	- type: map_at_10
	value: 64.086
	- type: map_at_100
	value: 64.832
	- type: map_at_1000
	value: 64.88199999999999
	- type: map_at_20
	value: 64.537
	- type: map_at_3
	value: 61.592
	- type: map_at_5
	value: 63.113
	- type: mrr_at_1
	value: 61.56
	- type: mrr_at_10
	value: 68.92823412698384
	- type: mrr_at_100
	value: 69.28307943909826
	- type: mrr_at_1000
	value: 69.30426854775237
	- type: mrr_at_20
	value: 69.15371761666225
	- type: mrr_at_3
	value: 67.3866666666664
	- type: mrr_at_5
	value: 68.36666666666618
	- type: nauc_map_at_1000_diff1
	value: 67.15642759814821
	- type: nauc_map_at_1000_max
	value: 45.055780376792974
	- type: nauc_map_at_1000_std
	value: -9.604334727421541
	- type: nauc_map_at_100_diff1
	value: 67.15173583169253
	- type: nauc_map_at_100_max
	value: 45.04159938681548
	- type: nauc_map_at_100_std
	value: -9.621105481487115
	- type: nauc_map_at_10_diff1
	value: 67.21904799567723
	- type: nauc_map_at_10_max
	value: 44.64598524589752
	- type: nauc_map_at_10_std
	value: -10.240236577363671
	- type: nauc_map_at_1_diff1
	value: 69.75325378909568
	- type: nauc_map_at_1_max
	value: 39.57437605382559
	- type: nauc_map_at_1_std
	value: -13.560013524667186
	- type: nauc_map_at_20_diff1
	value: 67.18218534766027
	- type: nauc_map_at_20_max
	value: 44.898145457359036
	- type: nauc_map_at_20_std
	value: -9.853291926035132
	- type: nauc_map_at_3_diff1
	value: 67.33579825697572
	- type: nauc_map_at_3_max
	value: 43.434634746776254
	- type: nauc_map_at_3_std
	value: -11.533963319404025
	- type: nauc_map_at_5_diff1
	value: 67.29212861119778
	- type: nauc_map_at_5_max
	value: 44.149577446190584
	- type: nauc_map_at_5_std
	value: -10.846590188540638
	- type: nauc_mrr_at_1000_diff1
	value: 68.43853101345768
	- type: nauc_mrr_at_1000_max
	value: 48.23642231569019
	- type: nauc_mrr_at_1000_std
	value: -8.164139622888774
	- type: nauc_mrr_at_100_diff1
	value: 68.43230932580869
	- type: nauc_mrr_at_100_max
	value: 48.2366506280321
	- type: nauc_mrr_at_100_std
	value: -8.15719155689163
	- type: nauc_mrr_at_10_diff1
	value: 68.40804119736147
	- type: nauc_mrr_at_10_max
	value: 48.2668711810203
	- type: nauc_mrr_at_10_std
	value: -8.28336977621905
	- type: nauc_mrr_at_1_diff1
	value: 70.8152113865952
	- type: nauc_mrr_at_1_max
	value: 47.0802377233158
	- type: nauc_mrr_at_1_std
	value: -11.195273246909617
	- type: nauc_mrr_at_20_diff1
	value: 68.42041452964153
	- type: nauc_mrr_at_20_max
	value: 48.22983590171867
	- type: nauc_mrr_at_20_std
	value: -8.20351261044932
	- type: nauc_mrr_at_3_diff1
	value: 68.44729044448252
	- type: nauc_mrr_at_3_max
	value: 48.16311095038692
	- type: nauc_mrr_at_3_std
	value: -8.78728757717942
	- type: nauc_mrr_at_5_diff1
	value: 68.38338463498374
	- type: nauc_mrr_at_5_max
	value: 48.268101599089846
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	- type: nauc_ndcg_at_3_diff1
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	- type: nauc_ndcg_at_5_diff1
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	- type: nauc_recall_at_1000_diff1
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	- type: nauc_recall_at_1000_std
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	- type: nauc_recall_at_100_max
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	value: 13.253969225652396
	- type: nauc_recall_at_10_diff1
	value: 60.22299195797645
	- type: nauc_recall_at_10_max
	value: 43.85065064759132
	- type: nauc_recall_at_10_std
	value: -3.125491914491259
	- type: nauc_recall_at_1_diff1
	value: 69.75325378909568
	- type: nauc_recall_at_1_max
	value: 39.57437605382559
	- type: nauc_recall_at_1_std
	value: -13.560013524667186
	- type: nauc_recall_at_20_diff1
	value: 59.1680127262332
	- type: nauc_recall_at_20_max
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	- type: nauc_recall_at_20_std
	value: 1.7610688570268762
	- type: nauc_recall_at_3_diff1
	value: 62.75286406178069
	- type: nauc_recall_at_3_max
	value: 42.40300188251299
	- type: nauc_recall_at_3_std
	value: -8.94270893049646
	- type: nauc_recall_at_5_diff1
	value: 61.57224817120582
	- type: nauc_recall_at_5_max
	value: 43.2469875881082
	- type: nauc_recall_at_5_std
	value: -6.712607605292967
	- type: ndcg_at_1
	value: 61.61
	- type: ndcg_at_10
	value: 68.73
	- type: ndcg_at_100
	value: 71.281
	- type: ndcg_at_1000
	value: 72.209
	- type: ndcg_at_20
	value: 69.862
	- type: ndcg_at_3
	value: 65.35
	- type: ndcg_at_5
	value: 67.099
	- type: precision_at_1
	value: 61.61
	- type: precision_at_10
	value: 10.295
	- type: precision_at_100
	value: 1.2670000000000001
	- type: precision_at_1000
	value: 0.14100000000000001
	- type: precision_at_20
	value: 5.583
	- type: precision_at_3
	value: 28.157
	- type: precision_at_5
	value: 18.644
	- type: recall_at_1
	value: 53.492
	- type: recall_at_10
	value: 77.395
	- type: recall_at_100
	value: 87.822
	- type: recall_at_1000
	value: 94.039
	- type: recall_at_20
	value: 81.381
	- type: recall_at_3
	value: 67.657
	- type: recall_at_5
	value: 72.494
	task:
	type: Retrieval
	- dataset:
	config: default
	name: MTEB RedditClustering (default)
	revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
	split: test
	type: mteb/reddit-clustering
	metrics:
	- type: main_score
	value: 22.18693423438157
	- type: v_measure
	value: 22.18693423438157
	- type: v_measure_std
	value: 3.362608784471836
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB SICK-R (default)
	revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
	split: test
	type: mteb/sickr-sts
	metrics:
	- type: cosine_pearson
	value: 74.25579384618342
	- type: cosine_spearman
	value: 67.31903429944056
	- type: euclidean_pearson
	value: 71.84781550612432
	- type: euclidean_spearman
	value: 67.31913348808827
	- type: main_score
	value: 67.31903429944056
	- type: manhattan_pearson
	value: 71.93525335001107
	- type: manhattan_spearman
	value: 67.44731252485444
	- type: pearson
	value: 74.25579384618342
	- type: spearman
	value: 67.31903429944056
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STS12 (default)
	revision: a0d554a64d88156834ff5ae9920b964011b16384
	split: test
	type: mteb/sts12-sts
	metrics:
	- type: cosine_pearson
	value: 70.45282392047417
	- type: cosine_spearman
	value: 57.66176503826067
	- type: euclidean_pearson
	value: 68.20476513300197
	- type: euclidean_spearman
	value: 57.662984752186595
	- type: main_score
	value: 57.66176503826067
	- type: manhattan_pearson
	value: 68.35595302570229
	- type: manhattan_spearman
	value: 57.78214901099006
	- type: pearson
	value: 70.45282392047417
	- type: spearman
	value: 57.66176503826067
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STS13 (default)
	revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
	split: test
	type: mteb/sts13-sts
	metrics:
	- type: cosine_pearson
	value: 66.72224934737348
	- type: cosine_spearman
	value: 71.89696855506867
	- type: euclidean_pearson
	value: 70.4712630269631
	- type: euclidean_spearman
	value: 71.89698079206684
	- type: main_score
	value: 71.89696855506867
	- type: manhattan_pearson
	value: 70.45860743861545
	- type: manhattan_spearman
	value: 71.91608445555363
	- type: pearson
	value: 66.72224934737348
	- type: spearman
	value: 71.89696855506867
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STS14 (default)
	revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
	split: test
	type: mteb/sts14-sts
	metrics:
	- type: cosine_pearson
	value: 70.34249555730298
	- type: cosine_spearman
	value: 69.53679034910807
	- type: euclidean_pearson
	value: 71.56701694057745
	- type: euclidean_spearman
	value: 69.5367806640627
	- type: main_score
	value: 69.53679034910807
	- type: manhattan_pearson
	value: 71.53194206589868
	- type: manhattan_spearman
	value: 69.52240262783113
	- type: pearson
	value: 70.34249555730298
	- type: spearman
	value: 69.53679034910807
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STS15 (default)
	revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
	split: test
	type: mteb/sts15-sts
	metrics:
	- type: cosine_pearson
	value: 68.33547250158846
	- type: cosine_spearman
	value: 73.96543736110634
	- type: euclidean_pearson
	value: 72.63926797717605
	- type: euclidean_spearman
	value: 73.96543799049243
	- type: main_score
	value: 73.96543736110634
	- type: manhattan_pearson
	value: 72.6308651035737
	- type: manhattan_spearman
	value: 73.99784893840472
	- type: pearson
	value: 68.33547250158846
	- type: spearman
	value: 73.96543736110634
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STS16 (default)
	revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
	split: test
	type: mteb/sts16-sts
	metrics:
	- type: cosine_pearson
	value: 62.50064232309498
	- type: cosine_spearman
	value: 69.99690285087063
	- type: euclidean_pearson
	value: 67.7773080753282
	- type: euclidean_spearman
	value: 69.99717504340504
	- type: main_score
	value: 69.99690285087063
	- type: manhattan_pearson
	value: 67.77737269625732
	- type: manhattan_spearman
	value: 70.05662507231811
	- type: pearson
	value: 62.50064232309498
	- type: spearman
	value: 69.99690285087063
	task:
	type: STS
	- dataset:
	config: en-de
	name: MTEB STS17 (en-de)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -4.639974351143124
	- type: cosine_spearman
	value: -5.70963417137641
	- type: euclidean_pearson
	value: -4.671269689471623
	- type: euclidean_spearman
	value: -5.70963417137641
	- type: main_score
	value: -5.70963417137641
	- type: manhattan_pearson
	value: -4.822356012695697
	- type: manhattan_spearman
	value: -5.805771748799997
	- type: pearson
	value: -4.639974351143124
	- type: spearman
	value: -5.70963417137641
	task:
	type: STS
	- dataset:
	config: en-en
	name: MTEB STS17 (en-en)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: 75.07706637430398
	- type: cosine_spearman
	value: 78.81834383119009
	- type: euclidean_pearson
	value: 78.33040815719426
	- type: euclidean_spearman
	value: 78.81922098296683
	- type: main_score
	value: 78.81834383119009
	- type: manhattan_pearson
	value: 78.25386282376627
	- type: manhattan_spearman
	value: 78.73096351789457
	- type: pearson
	value: 75.07706637430398
	- type: spearman
	value: 78.81834383119009
	task:
	type: STS
	- dataset:
	config: it-en
	name: MTEB STS17 (it-en)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -8.034513096828757
	- type: cosine_spearman
	value: -8.94071782108332
	- type: euclidean_pearson
	value: -8.362035046748408
	- type: euclidean_spearman
	value: -8.94071782108332
	- type: main_score
	value: -8.94071782108332
	- type: manhattan_pearson
	value: -8.58384659065939
	- type: manhattan_spearman
	value: -9.022478967496742
	- type: pearson
	value: -8.034513096828757
	- type: spearman
	value: -8.94071782108332
	task:
	type: STS
	- dataset:
	config: es-en
	name: MTEB STS17 (es-en)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -9.309746585888194
	- type: cosine_spearman
	value: -9.989532291941243
	- type: euclidean_pearson
	value: -9.113663493693515
	- type: euclidean_spearman
	value: -9.989532291941243
	- type: main_score
	value: -9.989532291941243
	- type: manhattan_pearson
	value: -9.123108445100232
	- type: manhattan_spearman
	value: -10.02555353386953
	- type: pearson
	value: -9.309746585888194
	- type: spearman
	value: -9.989532291941243
	task:
	type: STS
	- dataset:
	config: es-es
	name: MTEB STS17 (es-es)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: 49.203212653579534
	- type: cosine_spearman
	value: 62.17745071362616
	- type: euclidean_pearson
	value: 60.12172084869311
	- type: euclidean_spearman
	value: 62.17745071362616
	- type: main_score
	value: 62.17745071362616
	- type: manhattan_pearson
	value: 60.03123674358504
	- type: manhattan_spearman
	value: 62.08054980165127
	- type: pearson
	value: 49.203212653579534
	- type: spearman
	value: 62.17745071362616
	task:
	type: STS
	- dataset:
	config: fr-en
	name: MTEB STS17 (fr-en)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -3.796131822561097
	- type: cosine_spearman
	value: -3.6829417954942962
	- type: euclidean_pearson
	value: -3.9617579449787215
	- type: euclidean_spearman
	value: -3.6829417954942962
	- type: main_score
	value: -3.6829417954942962
	- type: manhattan_pearson
	value: -4.229917664747983
	- type: manhattan_spearman
	value: -3.8304347521413575
	- type: pearson
	value: -3.796131822561097
	- type: spearman
	value: -3.6829417954942962
	task:
	type: STS
	- dataset:
	config: ko-ko
	name: MTEB STS17 (ko-ko)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: 9.70401307418669
	- type: cosine_spearman
	value: 7.125994342518046
	- type: euclidean_pearson
	value: 8.692865519584803
	- type: euclidean_spearman
	value: 7.086314063560257
	- type: main_score
	value: 7.125994342518046
	- type: manhattan_pearson
	value: 8.688214277742162
	- type: manhattan_spearman
	value: 6.951151829297476
	- type: pearson
	value: 9.70401307418669
	- type: spearman
	value: 7.125994342518046
	task:
	type: STS
	- dataset:
	config: en-tr
	name: MTEB STS17 (en-tr)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -12.59835322441286
	- type: cosine_spearman
	value: -17.99707926594973
	- type: euclidean_pearson
	value: -14.34931127125891
	- type: euclidean_spearman
	value: -17.99707926594973
	- type: main_score
	value: -17.99707926594973
	- type: manhattan_pearson
	value: -14.599702365227513
	- type: manhattan_spearman
	value: -18.256327942493844
	- type: pearson
	value: -12.59835322441286
	- type: spearman
	value: -17.99707926594973
	task:
	type: STS
	- dataset:
	config: nl-en
	name: MTEB STS17 (nl-en)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -0.06664551245524106
	- type: cosine_spearman
	value: -0.891108084699552
	- type: euclidean_pearson
	value: 0.2657845183657392
	- type: euclidean_spearman
	value: -0.891108084699552
	- type: main_score
	value: -0.891108084699552
	- type: manhattan_pearson
	value: 0.120752189864216
	- type: manhattan_spearman
	value: -0.8531297054534491
	- type: pearson
	value: -0.06664551245524106
	- type: spearman
	value: -0.891108084699552
	task:
	type: STS
	- dataset:
	config: ar-ar
	name: MTEB STS17 (ar-ar)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: 9.587866133715462
	- type: cosine_spearman
	value: 10.240476793789082
	- type: euclidean_pearson
	value: 9.587866133709937
	- type: euclidean_spearman
	value: 10.299853867377841
	- type: main_score
	value: 10.240476793789082
	- type: manhattan_pearson
	value: 9.587479080379996
	- type: manhattan_spearman
	value: 10.289638886132417
	- type: pearson
	value: 9.587866133715462
	- type: spearman
	value: 10.240476793789082
	task:
	type: STS
	- dataset:
	config: en-ar
	name: MTEB STS17 (en-ar)
	revision: faeb762787bd10488a50c8b5be4a3b82e411949c
	split: test
	type: mteb/sts17-crosslingual-sts
	metrics:
	- type: cosine_pearson
	value: -11.455833153778357
	- type: cosine_spearman
	value: -12.120168687487281
	- type: euclidean_pearson
	value: -4.8404233986021
	- type: euclidean_spearman
	value: -5.629445269503656
	- type: main_score
	value: -12.120168687487281
	- type: manhattan_pearson
	value: -5.802510530492165
	- type: manhattan_spearman
	value: -4.129636012427943
	- type: pearson
	value: -11.455833153778357
	- type: spearman
	value: -12.120168687487281
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB STSBenchmark (default)
	revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
	split: test
	type: mteb/stsbenchmark-sts
	metrics:
	- type: cosine_pearson
	value: 67.09018720017058
	- type: cosine_spearman
	value: 67.6086401236391
	- type: euclidean_pearson
	value: 69.37492911426406
	- type: euclidean_spearman
	value: 67.60865860108962
	- type: main_score
	value: 67.6086401236391
	- type: manhattan_pearson
	value: 69.34659483682688
	- type: manhattan_spearman
	value: 67.592012200863
	- type: pearson
	value: 67.09018720017058
	- type: spearman
	value: 67.6086401236391
	task:
	type: STS
	- dataset:
	config: it
	name: MTEB STSBenchmarkMultilingualSTS (it)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 44.27233827248044
	- type: cosine_spearman
	value: 49.47510261384346
	- type: euclidean_pearson
	value: 49.40398312290145
	- type: euclidean_spearman
	value: 49.47500131889738
	- type: main_score
	value: 49.47510261384346
	- type: manhattan_pearson
	value: 49.341548618895466
	- type: manhattan_spearman
	value: 49.4424887001277
	- type: pearson
	value: 44.27233827248044
	- type: spearman
	value: 49.47510261384346
	task:
	type: STS
	- dataset:
	config: nl
	name: MTEB STSBenchmarkMultilingualSTS (nl)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 44.79696340221503
	- type: cosine_spearman
	value: 48.84897104878986
	- type: euclidean_pearson
	value: 49.324260285317855
	- type: euclidean_spearman
	value: 48.848924358139364
	- type: main_score
	value: 48.84897104878986
	- type: manhattan_pearson
	value: 49.33647165074528
	- type: manhattan_spearman
	value: 48.88344266774654
	- type: pearson
	value: 44.79696340221503
	- type: spearman
	value: 48.84897104878986
	task:
	type: STS
	- dataset:
	config: en
	name: MTEB STSBenchmarkMultilingualSTS (en)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 67.09018713920469
	- type: cosine_spearman
	value: 67.6086401236391
	- type: euclidean_pearson
	value: 69.37492906687476
	- type: euclidean_spearman
	value: 67.60865860108962
	- type: main_score
	value: 67.6086401236391
	- type: manhattan_pearson
	value: 69.34659479129859
	- type: manhattan_spearman
	value: 67.592012200863
	- type: pearson
	value: 67.09018713920469
	- type: spearman
	value: 67.6086401236391
	task:
	type: STS
	- dataset:
	config: es
	name: MTEB STSBenchmarkMultilingualSTS (es)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 42.895339590180996
	- type: cosine_spearman
	value: 52.21235147253785
	- type: euclidean_pearson
	value: 49.413874942919264
	- type: euclidean_spearman
	value: 52.21203780406665
	- type: main_score
	value: 52.21235147253785
	- type: manhattan_pearson
	value: 49.276873027104855
	- type: manhattan_spearman
	value: 52.16409604469493
	- type: pearson
	value: 42.895339590180996
	- type: spearman
	value: 52.21235147253785
	task:
	type: STS
	- dataset:
	config: ru
	name: MTEB STSBenchmarkMultilingualSTS (ru)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 10.389925450857834
	- type: cosine_spearman
	value: 8.908138291052701
	- type: euclidean_pearson
	value: 9.890367033199064
	- type: euclidean_spearman
	value: 8.770978113601167
	- type: main_score
	value: 8.908138291052701
	- type: manhattan_pearson
	value: 9.899760056143247
	- type: manhattan_spearman
	value: 9.030970134574098
	- type: pearson
	value: 10.389925450857834
	- type: spearman
	value: 8.908138291052701
	task:
	type: STS
	- dataset:
	config: zh
	name: MTEB STSBenchmarkMultilingualSTS (zh)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 3.2165863331249414
	- type: cosine_spearman
	value: 0.7975692702633864
	- type: euclidean_pearson
	value: 2.0618436826186066
	- type: euclidean_spearman
	value: 0.5027230247162311
	- type: main_score
	value: 0.7975692702633864
	- type: manhattan_pearson
	value: 2.0514189695530325
	- type: manhattan_spearman
	value: 0.39577079994867403
	- type: pearson
	value: 3.2165863331249414
	- type: spearman
	value: 0.7975692702633864
	task:
	type: STS
	- dataset:
	config: fr
	name: MTEB STSBenchmarkMultilingualSTS (fr)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 46.17508747479316
	- type: cosine_spearman
	value: 51.086872268140816
	- type: euclidean_pearson
	value: 51.41891364659744
	- type: euclidean_spearman
	value: 51.08665283035928
	- type: main_score
	value: 51.086872268140816
	- type: manhattan_pearson
	value: 51.361372778247606
	- type: manhattan_spearman
	value: 51.045873818882924
	- type: pearson
	value: 46.17508747479316
	- type: spearman
	value: 51.086872268140816
	task:
	type: STS
	- dataset:
	config: pt
	name: MTEB STSBenchmarkMultilingualSTS (pt)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 40.639680830613514
	- type: cosine_spearman
	value: 47.99664145034049
	- type: euclidean_pearson
	value: 46.61505913234052
	- type: euclidean_spearman
	value: 47.99654723025848
	- type: main_score
	value: 47.99664145034049
	- type: manhattan_pearson
	value: 46.594310151466146
	- type: manhattan_spearman
	value: 47.96444879548329
	- type: pearson
	value: 40.639680830613514
	- type: spearman
	value: 47.99664145034049
	task:
	type: STS
	- dataset:
	config: pl
	name: MTEB STSBenchmarkMultilingualSTS (pl)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 46.72373117676612
	- type: cosine_spearman
	value: 52.865236864827345
	- type: euclidean_pearson
	value: 52.45181901546032
	- type: euclidean_spearman
	value: 52.86458795625298
	- type: main_score
	value: 52.865236864827345
	- type: manhattan_pearson
	value: 52.44185889658423
	- type: manhattan_spearman
	value: 52.78491169411964
	- type: pearson
	value: 46.72373117676612
	- type: spearman
	value: 52.865236864827345
	task:
	type: STS
	- dataset:
	config: de
	name: MTEB STSBenchmarkMultilingualSTS (de)
	revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
	split: test
	type: mteb/stsb_multi_mt
	metrics:
	- type: cosine_pearson
	value: 48.138397241162444
	- type: cosine_spearman
	value: 51.285304430536335
	- type: euclidean_pearson
	value: 51.803064906612896
	- type: euclidean_spearman
	value: 51.28542208854524
	- type: main_score
	value: 51.285304430536335
	- type: manhattan_pearson
	value: 51.819864335986956
	- type: manhattan_spearman
	value: 51.32840976987932
	- type: pearson
	value: 48.138397241162444
	- type: spearman
	value: 51.285304430536335
	task:
	type: STS
	- dataset:
	config: default
	name: MTEB SciDocsRR (default)
	revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
	split: test
	type: mteb/scidocs-reranking
	metrics:
	- type: main_score
	value: 60.74844680566163
	- type: map
	value: 60.74844680566163
	- type: mrr
	value: 84.68450485607349
	- type: nAUC_map_diff1
	value: 13.078055417971749
	- type: nAUC_map_max
	value: 47.937301739074215
	- type: nAUC_map_std
	value: 34.26921463872339
	- type: nAUC_mrr_diff1
	value: 42.90446482292105
	- type: nAUC_mrr_max
	value: 59.75684998106037
	- type: nAUC_mrr_std
	value: 30.107306162191268
	task:
	type: Reranking
	- dataset:
	config: default
	name: MTEB SprintDuplicateQuestions (default)
	revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
	split: test
	type: mteb/sprintduplicatequestions-pairclassification
	metrics:
	- type: cosine_accuracy
	value: 99.44851485148514
	- type: cosine_accuracy_threshold
	value: 95.47240059357654
	- type: cosine_ap
	value: 68.22522420879186
	- type: cosine_f1
	value: 65.92635885447106
	- type: cosine_f1_threshold
	value: 94.98664208777299
	- type: cosine_precision
	value: 79.32489451476793
	- type: cosine_recall
	value: 56.39999999999999
	- type: dot_accuracy
	value: 99.44851485148514
	- type: dot_accuracy_threshold
	value: 95.47240056095825
	- type: dot_ap
	value: 68.22522420879186
	- type: dot_f1
	value: 65.92635885447106
	- type: dot_f1_threshold
	value: 94.98664205438727
	- type: dot_precision
	value: 79.32489451476793
	- type: dot_recall
	value: 56.39999999999999
	- type: euclidean_accuracy
	value: 99.44851485148514
	- type: euclidean_accuracy_threshold
	value: 30.091857225199625
	- type: euclidean_ap
	value: 68.22522420879186
	- type: euclidean_f1
	value: 65.92635885447106
	- type: euclidean_f1_threshold
	value: 31.664989847761138
	- type: euclidean_precision
	value: 79.32489451476793
	- type: euclidean_recall
	value: 56.39999999999999
	- type: main_score
	value: 68.28159512609737
	- type: manhattan_accuracy
	value: 99.44851485148514
	- type: manhattan_accuracy_threshold
	value: 1519.5971755477553
	- type: manhattan_ap
	value: 68.28159512609737
	- type: manhattan_f1
	value: 66.05818596691385
	- type: manhattan_f1_threshold
	value: 1628.6210010065347
	- type: manhattan_precision
	value: 76.89243027888446
	- type: manhattan_recall
	value: 57.9
	- type: max_accuracy
	value: 99.44851485148514
	- type: max_ap
	value: 68.28159512609737
	- type: max_f1
	value: 66.05818596691385
	- type: max_precision
	value: 79.32489451476793
	- type: max_recall
	value: 57.9
	- type: similarity_accuracy
	value: 99.44851485148514
	- type: similarity_accuracy_threshold
	value: 95.47240059357654
	- type: similarity_ap
	value: 68.22522420879186
	- type: similarity_f1
	value: 65.92635885447106
	- type: similarity_f1_threshold
	value: 94.98664208777299
	- type: similarity_precision
	value: 79.32489451476793
	- type: similarity_recall
	value: 56.39999999999999
	task:
	type: PairClassification
	- dataset:
	config: default
	name: MTEB StackExchangeClustering (default)
	revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
	split: test
	type: mteb/stackexchange-clustering
	metrics:
	- type: main_score
	value: 29.30513928170411
	- type: v_measure
	value: 29.30513928170411
	- type: v_measure_std
	value: 4.167908098359504
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB StackOverflowDupQuestions (default)
	revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
	split: test
	type: mteb/stackoverflowdupquestions-reranking
	metrics:
	- type: main_score
	value: 41.60577705014483
	- type: map
	value: 41.60577705014483
	- type: mrr
	value: 42.046595153212806
	- type: nAUC_map_diff1
	value: 29.435613304703427
	- type: nAUC_map_max
	value: 23.041089610073772
	- type: nAUC_map_std
	value: 4.187983544965867
	- type: nAUC_mrr_diff1
	value: 28.24912241668722
	- type: nAUC_mrr_max
	value: 23.844594928925574
	- type: nAUC_mrr_std
	value: 5.300127051350153
	task:
	type: Reranking
	- dataset:
	config: default
	name: MTEB ToxicConversationsClassification (default)
	revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
	split: test
	type: mteb/toxic_conversations_50k
	metrics:
	- type: accuracy
	value: 61.03515625
	- type: ap
	value: 10.357109818250033
	- type: ap_weighted
	value: 10.357109818250033
	- type: f1
	value: 46.79659702416427
	- type: f1_weighted
	value: 69.34093343990779
	- type: main_score
	value: 61.03515625
	task:
	type: Classification
	- dataset:
	config: default
	name: MTEB TweetSentimentExtractionClassification (default)
	revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
	split: test
	type: mteb/tweet_sentiment_extraction
	metrics:
	- type: accuracy
	value: 54.88964346349745
	- type: f1
	value: 54.88849570146398
	- type: f1_weighted
	value: 54.0202173220827
	- type: main_score
	value: 54.88964346349745
	task:
	type: Classification
	- dataset:
	config: default
	name: MTEB TwentyNewsgroupsClustering (default)
	revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
	split: test
	type: mteb/twentynewsgroups-clustering
	metrics:
	- type: main_score
	value: 25.77793337013197
	- type: v_measure
	value: 25.77793337013197
	- type: v_measure_std
	value: 1.7036625620777253
	task:
	type: Clustering
	- dataset:
	config: default
	name: MTEB TwitterSemEval2015 (default)
	revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
	split: test
	type: mteb/twittersemeval2015-pairclassification
	metrics:
	- type: cosine_accuracy
	value: 83.50718245216666
	- type: cosine_accuracy_threshold
	value: 92.85797990005872
	- type: cosine_ap
	value: 64.57501485077721
	- type: cosine_f1
	value: 61.107669433775236
	- type: cosine_f1_threshold
	value: 90.91770372653797
	- type: cosine_precision
	value: 57.60336370007008
	- type: cosine_recall
	value: 65.06596306068602
	- type: dot_accuracy
	value: 83.50718245216666
	- type: dot_accuracy_threshold
	value: 92.85797986316105
	- type: dot_ap
	value: 64.57501485077721
	- type: dot_f1
	value: 61.107669433775236
	- type: dot_f1_threshold
	value: 90.91770369108825
	- type: dot_precision
	value: 57.60336370007008
	- type: dot_recall
	value: 65.06596306068602
	- type: euclidean_accuracy
	value: 83.50718245216666
	- type: euclidean_accuracy_threshold
	value: 37.794231852628414
	- type: euclidean_ap
	value: 64.57501485077721
	- type: euclidean_f1
	value: 61.107669433775236
	- type: euclidean_f1_threshold
	value: 42.61993960299444
	- type: euclidean_precision
	value: 57.60336370007008
	- type: euclidean_recall
	value: 65.06596306068602
	- type: main_score
	value: 64.57501485077721
	- type: manhattan_accuracy
	value: 83.48930082851524
	- type: manhattan_accuracy_threshold
	value: 1897.2244120282544
	- type: manhattan_ap
	value: 64.55099351854031
	- type: manhattan_f1
	value: 61.062609129458714
	- type: manhattan_f1_threshold
	value: 2160.535839208718
	- type: manhattan_precision
	value: 57.89971617786187
	- type: manhattan_recall
	value: 64.5910290237467
	- type: max_accuracy
	value: 83.50718245216666
	- type: max_ap
	value: 64.57501485077721
	- type: max_f1
	value: 61.107669433775236
	- type: max_precision
	value: 57.89971617786187
	- type: max_recall
	value: 65.06596306068602
	- type: similarity_accuracy
	value: 83.50718245216666
	- type: similarity_accuracy_threshold
	value: 92.85797990005872
	- type: similarity_ap
	value: 64.57501485077721
	- type: similarity_f1
	value: 61.107669433775236
	- type: similarity_f1_threshold
	value: 90.91770372653797
	- type: similarity_precision
	value: 57.60336370007008
	- type: similarity_recall
	value: 65.06596306068602
	task:
	type: PairClassification
	- dataset:
	config: default
	name: MTEB TwitterURLCorpus (default)
	revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
	split: test
	type: mteb/twitterurlcorpus-pairclassification
	metrics:
	- type: cosine_accuracy
	value: 86.35463965537315
	- type: cosine_accuracy_threshold
	value: 93.93182168113243
	- type: cosine_ap
	value: 79.17988590079685
	- type: cosine_f1
	value: 71.77413258749716
	- type: cosine_f1_threshold
	value: 92.7978491290961
	- type: cosine_precision
	value: 70.48997772828508
	- type: cosine_recall
	value: 73.10594394825993
	- type: dot_accuracy
	value: 86.35463965537315
	- type: dot_accuracy_threshold
	value: 93.9318216501234
	- type: dot_ap
	value: 79.17988590079685
	- type: dot_f1
	value: 71.77413258749716
	- type: dot_f1_threshold
	value: 92.79784909821515
	- type: dot_precision
	value: 70.48997772828508
	- type: dot_recall
	value: 73.10594394825993
	- type: euclidean_accuracy
	value: 86.35463965537315
	- type: euclidean_accuracy_threshold
	value: 34.837274051981524
	- type: euclidean_ap
	value: 79.17988575609482
	- type: euclidean_f1
	value: 71.77413258749716
	- type: euclidean_f1_threshold
	value: 37.95299953339363
	- type: euclidean_precision
	value: 70.48997772828508
	- type: euclidean_recall
	value: 73.10594394825993
	- type: main_score
	value: 79.17988590079685
	- type: manhattan_accuracy
	value: 86.36046105483757
	- type: manhattan_accuracy_threshold
	value: 1771.5702122947137
	- type: manhattan_ap
	value: 79.16559289648251
	- type: manhattan_f1
	value: 71.8502354427472
	- type: manhattan_f1_threshold
	value: 1912.7281549009595
	- type: manhattan_precision
	value: 71.45359019264448
	- type: manhattan_recall
	value: 72.25130890052355
	- type: max_accuracy
	value: 86.36046105483757
	- type: max_ap
	value: 79.17988590079685
	- type: max_f1
	value: 71.8502354427472
	- type: max_precision
	value: 71.45359019264448
	- type: max_recall
	value: 73.10594394825993
	- type: similarity_accuracy
	value: 86.35463965537315
	- type: similarity_accuracy_threshold
	value: 93.93182168113243
	- type: similarity_ap
	value: 79.17988590079685
	- type: similarity_f1
	value: 71.77413258749716
	- type: similarity_f1_threshold
	value: 92.7978491290961
	- type: similarity_precision
	value: 70.48997772828508
	- type: similarity_recall
	value: 73.10594394825993
	task:
	type: PairClassification
	tags:
	- mteb
	---