mteb model-index region:us
---
tags:
- mteb
model-index:
- name: no_model_name_available
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    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:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    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:
      name: MTEB AmazonCounterfactualClassification (de)
      type: mteb/amazon_counterfactual
      config: de
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    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:
      name: MTEB AmazonCounterfactualClassification (ja)
      type: mteb/amazon_counterfactual
      config: ja
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    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:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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:
      name: MTEB AmazonReviewsClassification (de)
      type: mteb/amazon_reviews_multi
      config: de
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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:
      name: MTEB AmazonReviewsClassification (es)
      type: mteb/amazon_reviews_multi
      config: es
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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:
      name: MTEB AmazonReviewsClassification (fr)
      type: mteb/amazon_reviews_multi
      config: fr
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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:
      name: MTEB AmazonReviewsClassification (ja)
      type: mteb/amazon_reviews_multi
      config: ja
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    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: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 19.890899955689118
    - type: v_measure
      value: 19.890899955689118
    - type: v_measure_std
      value: 15.234197799081727
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    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: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    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: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    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: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: main_score
      value: 19.543768231624547
    - type: v_measure
      value: 19.543768231624547
    - type: v_measure_std
      value: 0.8448669358199523
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification (default)
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    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:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPDomainClassification (de)
      type: mteb/mtop_domain
      config: de
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPDomainClassification (es)
      type: mteb/mtop_domain
      config: es
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPDomainClassification (hi)
      type: mteb/mtop_domain
      config: hi
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPDomainClassification (th)
      type: mteb/mtop_domain
      config: th
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    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:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MTOPIntentClassification (de)
      type: mteb/mtop_intent
      config: de
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MTOPIntentClassification (es)
      type: mteb/mtop_intent
      config: es
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MTOPIntentClassification (hi)
      type: mteb/mtop_intent
      config: hi
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MTOPIntentClassification (th)
      type: mteb/mtop_intent
      config: th
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    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:
      name: MTEB MasakhaNEWSClassification (eng)
      type: mteb/masakhanews
      config: eng
      split: test
      revision: 18193f187b92da67168c655c9973a165ed9593dd
    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: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringS2S (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: main_score
      value: 24.84564500417387
    - type: v_measure
      value: 24.84564500417387
    - type: v_measure_std
      value: 22.286703004465615
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ta)
      type: mteb/amazon_massive_intent
      config: ta
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ml)
      type: mteb/amazon_massive_intent
      config: ml
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (af)
      type: mteb/amazon_massive_intent
      config: af
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (bn)
      type: mteb/amazon_massive_intent
      config: bn
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (is)
      type: mteb/amazon_massive_intent
      config: is
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (el)
      type: mteb/amazon_massive_intent
      config: el
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (sw)
      type: mteb/amazon_massive_intent
      config: sw
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (cy)
      type: mteb/amazon_massive_intent
      config: cy
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (pt)
      type: mteb/amazon_massive_intent
      config: pt
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (fa)
      type: mteb/amazon_massive_intent
      config: fa
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (mn)
      type: mteb/amazon_massive_intent
      config: mn
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (de)
      type: mteb/amazon_massive_intent
      config: de
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (sl)
      type: mteb/amazon_massive_intent
      config: sl
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (km)
      type: mteb/amazon_massive_intent
      config: km
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (az)
      type: mteb/amazon_massive_intent
      config: az
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (my)
      type: mteb/amazon_massive_intent
      config: my
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (it)
      type: mteb/amazon_massive_intent
      config: it
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (sq)
      type: mteb/amazon_massive_intent
      config: sq
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (da)
      type: mteb/amazon_massive_intent
      config: da
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ka)
      type: mteb/amazon_massive_intent
      config: ka
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (hu)
      type: mteb/amazon_massive_intent
      config: hu
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ms)
      type: mteb/amazon_massive_intent
      config: ms
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (tl)
      type: mteb/amazon_massive_intent
      config: tl
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (th)
      type: mteb/amazon_massive_intent
      config: th
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (fi)
      type: mteb/amazon_massive_intent
      config: fi
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (hi)
      type: mteb/amazon_massive_intent
      config: hi
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (lv)
      type: mteb/amazon_massive_intent
      config: lv
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (sv)
      type: mteb/amazon_massive_intent
      config: sv
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (am)
      type: mteb/amazon_massive_intent
      config: am
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (jv)
      type: mteb/amazon_massive_intent
      config: jv
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ru)
      type: mteb/amazon_massive_intent
      config: ru
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (zh-TW)
      type: mteb/amazon_massive_intent
      config: zh-TW
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (zh-CN)
      type: mteb/amazon_massive_intent
      config: zh-CN
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (nb)
      type: mteb/amazon_massive_intent
      config: nb
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (kn)
      type: mteb/amazon_massive_intent
      config: kn
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ja)
      type: mteb/amazon_massive_intent
      config: ja
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (nl)
      type: mteb/amazon_massive_intent
      config: nl
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ar)
      type: mteb/amazon_massive_intent
      config: ar
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (es)
      type: mteb/amazon_massive_intent
      config: es
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (he)
      type: mteb/amazon_massive_intent
      config: he
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (te)
      type: mteb/amazon_massive_intent
      config: te
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (tr)
      type: mteb/amazon_massive_intent
      config: tr
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (vi)
      type: mteb/amazon_massive_intent
      config: vi
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (id)
      type: mteb/amazon_massive_intent
      config: id
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ko)
      type: mteb/amazon_massive_intent
      config: ko
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ro)
      type: mteb/amazon_massive_intent
      config: ro
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (pl)
      type: mteb/amazon_massive_intent
      config: pl
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (ur)
      type: mteb/amazon_massive_intent
      config: ur
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveIntentClassification (hy)
      type: mteb/amazon_massive_intent
      config: hy
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    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:
      name: MTEB MassiveScenarioClassification (ta)
      type: mteb/amazon_massive_scenario
      config: ta
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ml)
      type: mteb/amazon_massive_scenario
      config: ml
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (af)
      type: mteb/amazon_massive_scenario
      config: af
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (bn)
      type: mteb/amazon_massive_scenario
      config: bn
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (is)
      type: mteb/amazon_massive_scenario
      config: is
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (el)
      type: mteb/amazon_massive_scenario
      config: el
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (sw)
      type: mteb/amazon_massive_scenario
      config: sw
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (cy)
      type: mteb/amazon_massive_scenario
      config: cy
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (pt)
      type: mteb/amazon_massive_scenario
      config: pt
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (fa)
      type: mteb/amazon_massive_scenario
      config: fa
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (mn)
      type: mteb/amazon_massive_scenario
      config: mn
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (de)
      type: mteb/amazon_massive_scenario
      config: de
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (sl)
      type: mteb/amazon_massive_scenario
      config: sl
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (km)
      type: mteb/amazon_massive_scenario
      config: km
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (az)
      type: mteb/amazon_massive_scenario
      config: az
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (my)
      type: mteb/amazon_massive_scenario
      config: my
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (it)
      type: mteb/amazon_massive_scenario
      config: it
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (sq)
      type: mteb/amazon_massive_scenario
      config: sq
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (da)
      type: mteb/amazon_massive_scenario
      config: da
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ka)
      type: mteb/amazon_massive_scenario
      config: ka
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (hu)
      type: mteb/amazon_massive_scenario
      config: hu
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ms)
      type: mteb/amazon_massive_scenario
      config: ms
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (tl)
      type: mteb/amazon_massive_scenario
      config: tl
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (th)
      type: mteb/amazon_massive_scenario
      config: th
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (fi)
      type: mteb/amazon_massive_scenario
      config: fi
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (hi)
      type: mteb/amazon_massive_scenario
      config: hi
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (lv)
      type: mteb/amazon_massive_scenario
      config: lv
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (sv)
      type: mteb/amazon_massive_scenario
      config: sv
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (am)
      type: mteb/amazon_massive_scenario
      config: am
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (jv)
      type: mteb/amazon_massive_scenario
      config: jv
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ru)
      type: mteb/amazon_massive_scenario
      config: ru
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (zh-TW)
      type: mteb/amazon_massive_scenario
      config: zh-TW
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (fr)
      type: mteb/amazon_massive_scenario
      config: fr
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (nb)
      type: mteb/amazon_massive_scenario
      config: nb
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (kn)
      type: mteb/amazon_massive_scenario
      config: kn
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ja)
      type: mteb/amazon_massive_scenario
      config: ja
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (nl)
      type: mteb/amazon_massive_scenario
      config: nl
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ar)
      type: mteb/amazon_massive_scenario
      config: ar
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (es)
      type: mteb/amazon_massive_scenario
      config: es
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (he)
      type: mteb/amazon_massive_scenario
      config: he
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (te)
      type: mteb/amazon_massive_scenario
      config: te
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (tr)
      type: mteb/amazon_massive_scenario
      config: tr
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (vi)
      type: mteb/amazon_massive_scenario
      config: vi
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (id)
      type: mteb/amazon_massive_scenario
      config: id
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ko)
      type: mteb/amazon_massive_scenario
      config: ko
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ro)
      type: mteb/amazon_massive_scenario
      config: ro
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (pl)
      type: mteb/amazon_massive_scenario
      config: pl
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (ur)
      type: mteb/amazon_massive_scenario
      config: ur
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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:
      name: MTEB MassiveScenarioClassification (hy)
      type: mteb/amazon_massive_scenario
      config: hy
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    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: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: main_score
      value: 22.3149940028344
    - type: v_measure
      value: 22.3149940028344
    - type: v_measure_std
      value: 1.184495521159966
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    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: PairClassification
    dataset:
      name: MTEB OpusparcusPC (de)
      type: GEM/opusparcus
      config: de
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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:
      name: MTEB OpusparcusPC (en)
      type: GEM/opusparcus
      config: en
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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:
      name: MTEB OpusparcusPC (fi)
      type: GEM/opusparcus
      config: fi
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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:
      name: MTEB OpusparcusPC (fr)
      type: GEM/opusparcus
      config: fr
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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:
      name: MTEB OpusparcusPC (ru)
      type: GEM/opusparcus
      config: ru
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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:
      name: MTEB OpusparcusPC (sv)
      type: GEM/opusparcus
      config: sv
      split: test
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    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: Retrieval
    dataset:
      name: MTEB QuoraRetrieval (default)
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    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_recall_at_10_std
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    - type: nauc_recall_at_3_diff1
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    - type: nauc_recall_at_3_max
      value: 42.40300188251299
    - type: nauc_recall_at_3_std
      value: -8.94270893049646
    - type: nauc_recall_at_5_diff1
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    - 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: Clustering
    dataset:
      name: MTEB RedditClustering (default)
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: main_score
      value: 22.18693423438157
    - type: v_measure
      value: 22.18693423438157
    - type: v_measure_std
      value: 3.362608784471836
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    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:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    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:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    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:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    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:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    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:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    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:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    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:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    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:
      name: MTEB STSBenchmarkMultilingualSTS (it)
      type: mteb/stsb_multi_mt
      config: it
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (nl)
      type: mteb/stsb_multi_mt
      config: nl
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (en)
      type: mteb/stsb_multi_mt
      config: en
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (es)
      type: mteb/stsb_multi_mt
      config: es
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (ru)
      type: mteb/stsb_multi_mt
      config: ru
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (zh)
      type: mteb/stsb_multi_mt
      config: zh
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      type: mteb/stsb_multi_mt
      config: fr
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (pt)
      type: mteb/stsb_multi_mt
      config: pt
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (pl)
      type: mteb/stsb_multi_mt
      config: pl
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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:
      name: MTEB STSBenchmarkMultilingualSTS (de)
      type: mteb/stsb_multi_mt
      config: de
      split: test
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    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: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    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: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    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: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: main_score
      value: 29.30513928170411
    - type: v_measure
      value: 29.30513928170411
    - type: v_measure_std
      value: 4.167908098359504
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    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: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    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:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    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: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 25.77793337013197
    - type: v_measure
      value: 25.77793337013197
    - type: v_measure_std
      value: 1.7036625620777253
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    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:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    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
---
