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model-index:
  - name: no_model_name_available
    results:
      - dataset:
          config: en-ext
          name: MTEB AmazonCounterfactualClassification (en-ext)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 68.60569715142428
          - type: ap
            value: 19.05710055685074
          - type: ap_weighted
            value: 19.05710055685074
          - type: f1
            value: 56.581673345537695
          - type: f1_weighted
            value: 74.61143344921274
          - type: main_score
            value: 68.60569715142428
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonCounterfactualClassification (en)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 68.56716417910447
          - type: ap
            value: 31.32344301280815
          - type: ap_weighted
            value: 31.32344301280815
          - type: f1
            value: 62.570662383384025
          - type: f1_weighted
            value: 71.61789541976941
          - type: main_score
            value: 68.56716417910447
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB AmazonCounterfactualClassification (de)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 63.276231263383295
          - type: ap
            value: 77.029702826753
          - type: ap_weighted
            value: 77.029702826753
          - type: f1
            value: 61.38234936043525
          - type: f1_weighted
            value: 64.54688276108833
          - type: main_score
            value: 63.276231263383295
        task:
          type: Classification
      - dataset:
          config: ja
          name: MTEB AmazonCounterfactualClassification (ja)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 44.368308351177724
          - type: ap
            value: 10.954835146791183
          - type: ap_weighted
            value: 10.954835146791183
          - type: f1
            value: 36.62906436161906
          - type: f1_weighted
            value: 51.69895802800691
          - type: main_score
            value: 44.368308351177724
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonReviewsClassification (en)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 36.808
          - type: f1
            value: 34.68301166695203
          - type: f1_weighted
            value: 34.68301166695202
          - type: main_score
            value: 36.808
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB AmazonReviewsClassification (de)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 27.057999999999993
          - type: f1
            value: 26.24275950859653
          - type: f1_weighted
            value: 26.242759508596524
          - type: main_score
            value: 27.057999999999993
        task:
          type: Classification
      - dataset:
          config: es
          name: MTEB AmazonReviewsClassification (es)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 31.064000000000004
          - type: f1
            value: 29.708079352003708
          - type: f1_weighted
            value: 29.7080793520037
          - type: main_score
            value: 31.064000000000004
        task:
          type: Classification
      - dataset:
          config: fr
          name: MTEB AmazonReviewsClassification (fr)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 29.43
          - type: f1
            value: 27.94855548400926
          - type: f1_weighted
            value: 27.94855548400926
          - type: main_score
            value: 29.43
        task:
          type: Classification
      - dataset:
          config: ja
          name: MTEB AmazonReviewsClassification (ja)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 20.787999999999997
          - type: f1
            value: 15.135022040282188
          - type: f1_weighted
            value: 15.135022040282188
          - type: main_score
            value: 20.787999999999997
        task:
          type: Classification
      - dataset:
          config: zh
          name: MTEB AmazonReviewsClassification (zh)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 21.914
          - type: f1
            value: 15.895956878609303
          - type: f1_weighted
            value: 15.895956878609303
          - type: main_score
            value: 21.914
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 19.890899955689118
          - type: v_measure
            value: 19.890899955689118
          - type: v_measure_std
            value: 15.234197799081727
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: main_score
            value: 49.123206371254746
          - type: map
            value: 49.123206371254746
          - type: mrr
            value: 62.31862551114629
          - type: nAUC_map_diff1
            value: 10.382490924755208
          - type: nAUC_map_max
            value: 18.748869416562293
          - type: nAUC_map_std
            value: 2.5774869725944383
          - type: nAUC_mrr_diff1
            value: 13.422210021656673
          - type: nAUC_mrr_max
            value: 24.878571083763035
          - type: nAUC_mrr_std
            value: -0.41050314967328677
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB BIOSSES (default)
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
          split: test
          type: mteb/biosses-sts
        metrics:
          - type: cosine_pearson
            value: 54.66661709953381
          - type: cosine_spearman
            value: 61.90442258245585
          - type: euclidean_pearson
            value: 57.802209299685984
          - type: euclidean_spearman
            value: 61.90442258245585
          - type: main_score
            value: 61.90442258245585
          - type: manhattan_pearson
            value: 58.05739954223122
          - type: manhattan_spearman
            value: 62.10683683315609
          - type: pearson
            value: 54.66661709953381
          - type: spearman
            value: 61.90442258245585
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB Banking77Classification (default)
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
          split: test
          type: mteb/banking77
        metrics:
          - type: accuracy
            value: 50.75324675324676
          - type: f1
            value: 50.08833636657759
          - type: f1_weighted
            value: 50.08833636657759
          - type: main_score
            value: 50.75324675324676
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BiorxivClusteringS2S (default)
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
          split: test
          type: mteb/biorxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 19.543768231624547
          - type: v_measure
            value: 19.543768231624547
          - type: v_measure_std
            value: 0.8448669358199523
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB EmotionClassification (default)
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
          split: test
          type: mteb/emotion
        metrics:
          - type: accuracy
            value: 31.465
          - type: f1
            value: 27.518410158786278
          - type: f1_weighted
            value: 32.729446691751605
          - type: main_score
            value: 31.465
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MTOPDomainClassification (en)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 83.66393068855447
          - type: f1
            value: 83.02273407562654
          - type: f1_weighted
            value: 83.66877159114159
          - type: main_score
            value: 83.66393068855447
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB MTOPDomainClassification (de)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 63.97013243167089
          - type: f1
            value: 60.85033241575268
          - type: f1_weighted
            value: 63.82115556806192
          - type: main_score
            value: 63.97013243167089
        task:
          type: Classification
      - dataset:
          config: es
          name: MTEB MTOPDomainClassification (es)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 62.37491661107405
          - type: f1
            value: 60.94290925815502
          - type: f1_weighted
            value: 62.10717598146462
          - type: main_score
            value: 62.37491661107405
        task:
          type: Classification
      - dataset:
          config: fr
          name: MTEB MTOPDomainClassification (fr)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 62.95020357031006
          - type: f1
            value: 60.758971765144224
          - type: f1_weighted
            value: 63.42247920372272
          - type: main_score
            value: 62.95020357031006
        task:
          type: Classification
      - dataset:
          config: hi
          name: MTEB MTOPDomainClassification (hi)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 12.613840086052347
          - type: f1
            value: 6.5750442135283
          - type: f1_weighted
            value: 6.53244904380679
          - type: main_score
            value: 12.613840086052347
        task:
          type: Classification
      - dataset:
          config: th
          name: MTEB MTOPDomainClassification (th)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 14.759493670886076
          - type: f1
            value: 8.12843236923924
          - type: f1_weighted
            value: 8.793246140296032
          - type: main_score
            value: 14.759493670886076
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MTOPIntentClassification (en)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 49.43228454172367
          - type: f1
            value: 34.55112542095168
          - type: f1_weighted
            value: 52.614378484454974
          - type: main_score
            value: 49.43228454172367
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB MTOPIntentClassification (de)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 39.01662440123979
          - type: f1
            value: 23.82791663064076
          - type: f1_weighted
            value: 43.645398141967966
          - type: main_score
            value: 39.01662440123979
        task:
          type: Classification
      - dataset:
          config: es
          name: MTEB MTOPIntentClassification (es)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 37.11140760507005
          - type: f1
            value: 21.935352507756388
          - type: f1_weighted
            value: 39.321275372065685
          - type: main_score
            value: 37.11140760507005
        task:
          type: Classification
      - dataset:
          config: fr
          name: MTEB MTOPIntentClassification (fr)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 33.7770122142186
          - type: f1
            value: 22.220964590376273
          - type: f1_weighted
            value: 37.485286173160986
          - type: main_score
            value: 33.7770122142186
        task:
          type: Classification
      - dataset:
          config: hi
          name: MTEB MTOPIntentClassification (hi)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 5.453567586948727
          - type: f1
            value: 0.7075326300577311
          - type: f1_weighted
            value: 2.3858630958577836
          - type: main_score
            value: 5.453567586948727
        task:
          type: Classification
      - dataset:
          config: th
          name: MTEB MTOPIntentClassification (th)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 5.529837251356239
          - type: f1
            value: 1.2115090491792773
          - type: f1_weighted
            value: 3.498070456864493
          - type: main_score
            value: 5.529837251356239
        task:
          type: Classification
      - dataset:
          config: eng
          name: MTEB MasakhaNEWSClassification (eng)
          revision: 18193f187b92da67168c655c9973a165ed9593dd
          split: test
          type: mteb/masakhanews
        metrics:
          - type: accuracy
            value: 64.5042194092827
          - type: f1
            value: 62.368592308141814
          - type: f1_weighted
            value: 63.90417453510408
          - type: main_score
            value: 64.5042194092827
        task:
          type: Classification
      - dataset:
          config: eng
          name: MTEB MasakhaNEWSClusteringS2S (eng)
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
          split: test
          type: masakhane/masakhanews
        metrics:
          - type: main_score
            value: 24.84564500417387
          - type: v_measure
            value: 24.84564500417387
          - type: v_measure_std
            value: 22.286703004465615
        task:
          type: Clustering
      - dataset:
          config: ta
          name: MTEB MassiveIntentClassification (ta)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.219233355749832
          - type: f1
            value: 0.1932870095686131
          - type: f1_weighted
            value: 0.251235487639337
          - type: main_score
            value: 2.219233355749832
        task:
          type: Classification
      - dataset:
          config: ml
          name: MTEB MassiveIntentClassification (ml)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.2844653665097512
          - type: f1
            value: 0.18710410412943543
          - type: f1_weighted
            value: 0.2739907174462001
          - type: main_score
            value: 1.2844653665097512
        task:
          type: Classification
      - dataset:
          config: af
          name: MTEB MassiveIntentClassification (af)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 32.982515131136516
          - type: f1
            value: 29.879476335364973
          - type: f1_weighted
            value: 32.59262194412672
          - type: main_score
            value: 32.982515131136516
        task:
          type: Classification
      - dataset:
          config: bn
          name: MTEB MassiveIntentClassification (bn)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.2125084061869535
          - type: f1
            value: 0.5736320148349802
          - type: f1_weighted
            value: 0.7371018417507617
          - type: main_score
            value: 2.2125084061869535
        task:
          type: Classification
      - dataset:
          config: is
          name: MTEB MassiveIntentClassification (is)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 27.165433759246802
          - type: f1
            value: 25.68362075943369
          - type: f1_weighted
            value: 25.71202157696122
          - type: main_score
            value: 27.165433759246802
        task:
          type: Classification
      - dataset:
          config: el
          name: MTEB MassiveIntentClassification (el)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 10.665770006724948
          - type: f1
            value: 5.114611283180833
          - type: f1_weighted
            value: 7.526848175428076
          - type: main_score
            value: 10.665770006724948
        task:
          type: Classification
      - dataset:
          config: sw
          name: MTEB MassiveIntentClassification (sw)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 31.661062542030933
          - type: f1
            value: 31.298953203005986
          - type: f1_weighted
            value: 30.183076634560134
          - type: main_score
            value: 31.661062542030933
        task:
          type: Classification
      - dataset:
          config: cy
          name: MTEB MassiveIntentClassification (cy)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 27.995965030262276
          - type: f1
            value: 25.849404737727465
          - type: f1_weighted
            value: 26.922571545761638
          - type: main_score
            value: 27.995965030262276
        task:
          type: Classification
      - dataset:
          config: pt
          name: MTEB MassiveIntentClassification (pt)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 36.73839946200404
          - type: f1
            value: 35.6799981256784
          - type: f1_weighted
            value: 35.65583276626004
          - type: main_score
            value: 36.73839946200404
        task:
          type: Classification
      - dataset:
          config: fa
          name: MTEB MassiveIntentClassification (fa)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.1062542030934768
          - type: f1
            value: 0.3829753109058956
          - type: f1_weighted
            value: 0.42459533841173747
          - type: main_score
            value: 1.1062542030934768
        task:
          type: Classification
      - dataset:
          config: mn
          name: MTEB MassiveIntentClassification (mn)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.3604572965702753
          - type: f1
            value: 0.9096234324517042
          - type: f1_weighted
            value: 0.9394595549389105
          - type: main_score
            value: 2.3604572965702753
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB MassiveIntentClassification (de)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 32.68997982515132
          - type: f1
            value: 29.986572248952147
          - type: f1_weighted
            value: 32.22231191644284
          - type: main_score
            value: 32.68997982515132
        task:
          type: Classification
      - dataset:
          config: sl
          name: MTEB MassiveIntentClassification (sl)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 36.70477471418964
          - type: f1
            value: 33.50288534893127
          - type: f1_weighted
            value: 34.846130335010265
          - type: main_score
            value: 36.70477471418964
        task:
          type: Classification
      - dataset:
          config: km
          name: MTEB MassiveIntentClassification (km)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.96906523201076
          - type: f1
            value: 0.7797856721437596
          - type: f1_weighted
            value: 0.6236996914225641
          - type: main_score
            value: 2.96906523201076
        task:
          type: Classification
      - dataset:
          config: az
          name: MTEB MassiveIntentClassification (az)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 31.01882985877606
          - type: f1
            value: 29.527835951539323
          - type: f1_weighted
            value: 30.66568514409952
          - type: main_score
            value: 31.01882985877606
        task:
          type: Classification
      - dataset:
          config: my
          name: MTEB MassiveIntentClassification (my)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 3.2178883658372555
          - type: f1
            value: 0.5240681583697773
          - type: f1_weighted
            value: 0.9198214868347652
          - type: main_score
            value: 3.2178883658372555
        task:
          type: Classification
      - dataset:
          config: it
          name: MTEB MassiveIntentClassification (it)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 37.11499663752522
          - type: f1
            value: 36.36396173693096
          - type: f1_weighted
            value: 35.50337761684995
          - type: main_score
            value: 37.11499663752522
        task:
          type: Classification
      - dataset:
          config: sq
          name: MTEB MassiveIntentClassification (sq)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 26.7350369872226
          - type: f1
            value: 25.812896452146234
          - type: f1_weighted
            value: 26.2226872478251
          - type: main_score
            value: 26.7350369872226
        task:
          type: Classification
      - dataset:
          config: da
          name: MTEB MassiveIntentClassification (da)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 34.97982515131137
          - type: f1
            value: 32.92316320729933
          - type: f1_weighted
            value: 33.68424734170567
          - type: main_score
            value: 34.97982515131137
        task:
          type: Classification
      - dataset:
          config: ka
          name: MTEB MassiveIntentClassification (ka)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.546738399462004
          - type: f1
            value: 0.6491922803798055
          - type: f1_weighted
            value: 0.36416059882684426
          - type: main_score
            value: 1.546738399462004
        task:
          type: Classification
      - dataset:
          config: hu
          name: MTEB MassiveIntentClassification (hu)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 25.16476126429052
          - type: f1
            value: 23.67218773633549
          - type: f1_weighted
            value: 23.6371559019449
          - type: main_score
            value: 25.16476126429052
        task:
          type: Classification
      - dataset:
          config: ms
          name: MTEB MassiveIntentClassification (ms)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 33.79959650302623
          - type: f1
            value: 32.51301308582213
          - type: f1_weighted
            value: 32.526479564865305
          - type: main_score
            value: 33.79959650302623
        task:
          type: Classification
      - dataset:
          config: tl
          name: MTEB MassiveIntentClassification (tl)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 29.49226630800269
          - type: f1
            value: 28.94940260858102
          - type: f1_weighted
            value: 28.63948113059682
          - type: main_score
            value: 29.49226630800269
        task:
          type: Classification
      - dataset:
          config: th
          name: MTEB MassiveIntentClassification (th)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.6778749159381305
          - type: f1
            value: 0.9744693901937154
          - type: f1_weighted
            value: 0.691053805319416
          - type: main_score
            value: 1.6778749159381305
        task:
          type: Classification
      - dataset:
          config: fi
          name: MTEB MassiveIntentClassification (fi)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 30.114324142568925
          - type: f1
            value: 29.430743039242152
          - type: f1_weighted
            value: 29.04299307313548
          - type: main_score
            value: 30.114324142568925
        task:
          type: Classification
      - dataset:
          config: hi
          name: MTEB MassiveIntentClassification (hi)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.797579018157364
          - type: f1
            value: 1.144033688398988
          - type: f1_weighted
            value: 1.0884768126381035
          - type: main_score
            value: 2.797579018157364
        task:
          type: Classification
      - dataset:
          config: lv
          name: MTEB MassiveIntentClassification (lv)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 32.54539340954942
          - type: f1
            value: 31.521139537198316
          - type: f1_weighted
            value: 31.530360085026093
          - type: main_score
            value: 32.54539340954942
        task:
          type: Classification
      - dataset:
          config: sv
          name: MTEB MassiveIntentClassification (sv)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 30.783456624075324
          - type: f1
            value: 29.604725003907866
          - type: f1_weighted
            value: 29.685617024715732
          - type: main_score
            value: 30.783456624075324
        task:
          type: Classification
      - dataset:
          config: am
          name: MTEB MassiveIntentClassification (am)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.8426361802286482
          - type: f1
            value: 0.33542666799543247
          - type: f1_weighted
            value: 0.2711276986927232
          - type: main_score
            value: 1.8426361802286482
        task:
          type: Classification
      - dataset:
          config: jv
          name: MTEB MassiveIntentClassification (jv)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 30.178211163416268
          - type: f1
            value: 29.37132431463145
          - type: f1_weighted
            value: 29.494452777308833
          - type: main_score
            value: 30.178211163416268
        task:
          type: Classification
      - dataset:
          config: ru
          name: MTEB MassiveIntentClassification (ru)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.649630127774042
          - type: f1
            value: 1.7505098874789995
          - type: f1_weighted
            value: 1.4639682364635813
          - type: main_score
            value: 2.649630127774042
        task:
          type: Classification
      - dataset:
          config: zh-TW
          name: MTEB MassiveIntentClassification (zh-TW)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 4.468728984532616
          - type: f1
            value: 2.090461109042727
          - type: f1_weighted
            value: 2.7853674561791295
          - type: main_score
            value: 4.468728984532616
        task:
          type: Classification
      - dataset:
          config: fr
          name: MTEB MassiveIntentClassification (fr)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 33.27168796234029
          - type: f1
            value: 32.00481372908824
          - type: f1_weighted
            value: 32.159041657111764
          - type: main_score
            value: 33.27168796234029
        task:
          type: Classification
      - dataset:
          config: zh-CN
          name: MTEB MassiveIntentClassification (zh-CN)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 0.749831876260928
          - type: f1
            value: 0.11432947296104061
          - type: f1_weighted
            value: 0.0764038848837725
          - type: main_score
            value: 0.749831876260928
        task:
          type: Classification
      - dataset:
          config: nb
          name: MTEB MassiveIntentClassification (nb)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 32.125084061869536
          - type: f1
            value: 30.154247947358247
          - type: f1_weighted
            value: 30.87288096360447
          - type: main_score
            value: 32.125084061869536
        task:
          type: Classification
      - dataset:
          config: kn
          name: MTEB MassiveIntentClassification (kn)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.617350369872226
          - type: f1
            value: 0.9905489260231543
          - type: f1_weighted
            value: 0.7953294182207199
          - type: main_score
            value: 1.617350369872226
        task:
          type: Classification
      - dataset:
          config: ja
          name: MTEB MassiveIntentClassification (ja)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 3.806321452589106
          - type: f1
            value: 1.9196646149428953
          - type: f1_weighted
            value: 1.6645242984042585
          - type: main_score
            value: 3.806321452589106
        task:
          type: Classification
      - dataset:
          config: nl
          name: MTEB MassiveIntentClassification (nl)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 35.77673167451245
          - type: f1
            value: 33.18041618186975
          - type: f1_weighted
            value: 35.833046113268786
          - type: main_score
            value: 35.77673167451245
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MassiveIntentClassification (en)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 53.4969737726967
          - type: f1
            value: 51.88341293441036
          - type: f1_weighted
            value: 53.20514357568628
          - type: main_score
            value: 53.4969737726967
        task:
          type: Classification
      - dataset:
          config: ar
          name: MTEB MassiveIntentClassification (ar)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 4.784801613987895
          - type: f1
            value: 1.969274839533907
          - type: f1_weighted
            value: 2.4942212470758016
          - type: main_score
            value: 4.784801613987895
        task:
          type: Classification
      - dataset:
          config: es
          name: MTEB MassiveIntentClassification (es)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 31.069266980497645
          - type: f1
            value: 31.48265427665997
          - type: f1_weighted
            value: 30.3696521492686
          - type: main_score
            value: 31.069266980497645
        task:
          type: Classification
      - dataset:
          config: he
          name: MTEB MassiveIntentClassification (he)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 1.9670477471418968
          - type: f1
            value: 0.45697365831527426
          - type: f1_weighted
            value: 0.2853963696007572
          - type: main_score
            value: 1.9670477471418968
        task:
          type: Classification
      - dataset:
          config: te
          name: MTEB MassiveIntentClassification (te)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.1015467383994615
          - type: f1
            value: 0.5210481229705188
          - type: f1_weighted
            value: 0.5924944385210995
          - type: main_score
            value: 2.1015467383994615
        task:
          type: Classification
      - dataset:
          config: tr
          name: MTEB MassiveIntentClassification (tr)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 31.318090114324143
          - type: f1
            value: 30.05810538658039
          - type: f1_weighted
            value: 30.360376696442504
          - type: main_score
            value: 31.318090114324143
        task:
          type: Classification
      - dataset:
          config: vi
          name: MTEB MassiveIntentClassification (vi)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 19.078681909885677
          - type: f1
            value: 18.360818504390085
          - type: f1_weighted
            value: 18.15470646878023
          - type: main_score
            value: 19.078681909885677
        task:
          type: Classification
      - dataset:
          config: id
          name: MTEB MassiveIntentClassification (id)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 35.564895763281775
          - type: f1
            value: 35.587064959631185
          - type: f1_weighted
            value: 34.4349962874478
          - type: main_score
            value: 35.564895763281775
        task:
          type: Classification
      - dataset:
          config: ko
          name: MTEB MassiveIntentClassification (ko)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 3.2111634162743776
          - type: f1
            value: 1.4524341197394974
          - type: f1_weighted
            value: 1.3395307357797508
          - type: main_score
            value: 3.2111634162743776
        task:
          type: Classification
      - dataset:
          config: ro
          name: MTEB MassiveIntentClassification (ro)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 33.99798251513114
          - type: f1
            value: 32.69281167233965
          - type: f1_weighted
            value: 32.22827641327085
          - type: main_score
            value: 33.99798251513114
        task:
          type: Classification
      - dataset:
          config: pl
          name: MTEB MassiveIntentClassification (pl)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 29.660390047074646
          - type: f1
            value: 28.090771859451536
          - type: f1_weighted
            value: 29.50058846849659
          - type: main_score
            value: 29.660390047074646
        task:
          type: Classification
      - dataset:
          config: ur
          name: MTEB MassiveIntentClassification (ur)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.118359112306658
          - type: f1
            value: 1.0794128790274702
          - type: f1_weighted
            value: 1.0149237288074577
          - type: main_score
            value: 2.118359112306658
        task:
          type: Classification
      - dataset:
          config: hy
          name: MTEB MassiveIntentClassification (hy)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 2.242770679219906
          - type: f1
            value: 0.6772746623940161
          - type: f1_weighted
            value: 0.5935033259869644
          - type: main_score
            value: 2.242770679219906
        task:
          type: Classification
      - dataset:
          config: ta
          name: MTEB MassiveScenarioClassification (ta)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 4.7679892400807
          - type: f1
            value: 0.6958635242707644
          - type: f1_weighted
            value: 0.7383116540131966
          - type: main_score
            value: 4.7679892400807
        task:
          type: Classification
      - dataset:
          config: ml
          name: MTEB MassiveScenarioClassification (ml)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 4.599865501008742
          - type: f1
            value: 0.8680195452904774
          - type: f1_weighted
            value: 1.3022709162006496
          - type: main_score
            value: 4.599865501008742
        task:
          type: Classification
      - dataset:
          config: af
          name: MTEB MassiveScenarioClassification (af)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 45.80026899798251
          - type: f1
            value: 42.09162084904855
          - type: f1_weighted
            value: 45.937899984554896
          - type: main_score
            value: 45.80026899798251
        task:
          type: Classification
      - dataset:
          config: bn
          name: MTEB MassiveScenarioClassification (bn)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 7.935440484196368
          - type: f1
            value: 2.054473625082069
          - type: f1_weighted
            value: 2.331310360179839
          - type: main_score
            value: 7.935440484196368
        task:
          type: Classification
      - dataset:
          config: is
          name: MTEB MassiveScenarioClassification (is)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 39.525891055817084
          - type: f1
            value: 35.64315129468117
          - type: f1_weighted
            value: 38.873288696604064
          - type: main_score
            value: 39.525891055817084
        task:
          type: Classification
      - dataset:
          config: el
          name: MTEB MassiveScenarioClassification (el)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 16.822461331540016
          - type: f1
            value: 9.528868617590787
          - type: f1_weighted
            value: 12.052833175443745
          - type: main_score
            value: 16.822461331540016
        task:
          type: Classification
      - dataset:
          config: sw
          name: MTEB MassiveScenarioClassification (sw)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 41.44922663080027
          - type: f1
            value: 38.29694592816531
          - type: f1_weighted
            value: 40.494682049238065
          - type: main_score
            value: 41.44922663080027
        task:
          type: Classification
      - dataset:
          config: cy
          name: MTEB MassiveScenarioClassification (cy)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 36.37525218560861
          - type: f1
            value: 32.742079476295714
          - type: f1_weighted
            value: 36.41453434396975
          - type: main_score
            value: 36.37525218560861
        task:
          type: Classification
      - dataset:
          config: pt
          name: MTEB MassiveScenarioClassification (pt)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 43.79959650302623
          - type: f1
            value: 41.74604131799107
          - type: f1_weighted
            value: 41.89697637112924
          - type: main_score
            value: 43.79959650302623
        task:
          type: Classification
      - dataset:
          config: fa
          name: MTEB MassiveScenarioClassification (fa)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 6.2844653665097505
          - type: f1
            value: 1.1363404526147562
          - type: f1_weighted
            value: 1.507290141564863
          - type: main_score
            value: 6.2844653665097505
        task:
          type: Classification
      - dataset:
          config: mn
          name: MTEB MassiveScenarioClassification (mn)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 5.406859448554135
          - type: f1
            value: 2.560817113707556
          - type: f1_weighted
            value: 2.408341973383642
          - type: main_score
            value: 5.406859448554135
        task:
          type: Classification
      - dataset:
          config: de
          name: MTEB MassiveScenarioClassification (de)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 43.08002689979825
          - type: f1
            value: 39.31491179400749
          - type: f1_weighted
            value: 42.387701010649735
          - type: main_score
            value: 43.08002689979825
        task:
          type: Classification
      - dataset:
          config: sl
          name: MTEB MassiveScenarioClassification (sl)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 46.30127774041695
          - type: f1
            value: 43.177548916667774
          - type: f1_weighted
            value: 46.02641155529322
          - type: main_score
            value: 46.30127774041695
        task:
          type: Classification
      - dataset:
          config: km
          name: MTEB MassiveScenarioClassification (km)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 5.968392737054471
          - type: f1
            value: 1.558644350101979
          - type: f1_weighted
            value: 2.184277748991485
          - type: main_score
            value: 5.968392737054471
        task:
          type: Classification
      - dataset:
          config: az
          name: MTEB MassiveScenarioClassification (az)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 39.08204438466712
          - type: f1
            value: 37.19465931596499
          - type: f1_weighted
            value: 37.92508333682256
          - type: main_score
            value: 39.08204438466712
        task:
          type: Classification
      - dataset:
          config: my
          name: MTEB MassiveScenarioClassification (my)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 5.712844653665098
          - type: f1
            value: 2.3513952725160445
          - type: f1_weighted
            value: 2.591355133449796
          - type: main_score
            value: 5.712844653665098
        task:
          type: Classification
      - dataset:
          config: it
          name: MTEB MassiveScenarioClassification (it)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 44.79488903833221
          - type: f1
            value: 42.216456011086514
          - type: f1_weighted
            value: 43.63836497077992
          - type: main_score
            value: 44.79488903833221
        task:
          type: Classification
      - dataset:
          config: sq
          name: MTEB MassiveScenarioClassification (sq)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 38.91055817081372
          - type: f1
            value: 36.658118919837705
          - type: f1_weighted
            value: 38.285047658406185
          - type: main_score
            value: 38.91055817081372
        task:
          type: Classification
      - dataset:
          config: da
          name: MTEB MassiveScenarioClassification (da)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 42.82447881640888
          - type: f1
            value: 39.71183576580626
          - type: f1_weighted
            value: 42.99955794883917
          - type: main_score
            value: 42.82447881640888
        task:
          type: Classification
      - dataset:
          config: ka
          name: MTEB MassiveScenarioClassification (ka)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 6.9569603227975785
          - type: f1
            value: 1.3249507928345723
          - type: f1_weighted
            value: 2.1526435195273512
          - type: main_score
            value: 6.9569603227975785
        task:
          type: Classification
      - dataset:
          config: hu
          name: MTEB MassiveScenarioClassification (hu)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 35.47747141896436
          - type: f1
            value: 32.68368628376791
          - type: f1_weighted
            value: 34.486227854192805
          - type: main_score
            value: 35.47747141896436
        task:
          type: Classification
      - dataset:
          config: ms
          name: MTEB MassiveScenarioClassification (ms)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 44.20645595158036
          - type: f1
            value: 40.46275245484104
          - type: f1_weighted
            value: 43.07451372640555
          - type: main_score
            value: 44.20645595158036
        task:
          type: Classification
      - dataset:
          config: tl
          name: MTEB MassiveScenarioClassification (tl)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 37.565568258238066
          - type: f1
            value: 34.34228491467635
          - type: f1_weighted
            value: 36.715470304700304
          - type: main_score
            value: 37.565568258238066
        task:
          type: Classification
      - dataset:
          config: th
          name: MTEB MassiveScenarioClassification (th)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 4.428379287155346
          - type: f1
            value: 2.118733356397359
          - type: f1_weighted
            value: 1.6597464958411214
          - type: main_score
            value: 4.428379287155346
        task:
          type: Classification
      - dataset:
          config: fi
          name: MTEB MassiveScenarioClassification (fi)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 34.67720242098184
          - type: f1
            value: 31.648714845929625
          - type: f1_weighted
            value: 34.62782835061803
          - type: main_score
            value: 34.67720242098184
        task:
          type: Classification
      - dataset:
          config: hi
          name: MTEB MassiveScenarioClassification (hi)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 8.006052454606591
          - type: f1
            value: 2.1079480174137237
          - type: f1_weighted
            value: 2.1631918405037758
          - type: main_score
            value: 8.006052454606591
        task:
          type: Classification
      - dataset:
          config: lv
          name: MTEB MassiveScenarioClassification (lv)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 39.22999327505043
          - type: f1
            value: 37.16721131021293
          - type: f1_weighted
            value: 39.397613949853735
          - type: main_score
            value: 39.22999327505043
        task:
          type: Classification
      - dataset:
          config: sv
          name: MTEB MassiveScenarioClassification (sv)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 41.55010087424344
          - type: f1
            value: 38.32223910141539
          - type: f1_weighted
            value: 41.72498846160742
          - type: main_score
            value: 41.55010087424344
        task:
          type: Classification
      - dataset:
          config: am
          name: MTEB MassiveScenarioClassification (am)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 3.0363147276395432
          - type: f1
            value: 0.4951111891349476
          - type: f1_weighted
            value: 0.4456347917226148
          - type: main_score
            value: 3.0363147276395432
        task:
          type: Classification
      - dataset:
          config: jv
          name: MTEB MassiveScenarioClassification (jv)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 42.84801613987895
          - type: f1
            value: 40.77209890733345
          - type: f1_weighted
            value: 42.29511181907119
          - type: main_score
            value: 42.84801613987895
        task:
          type: Classification
      - dataset:
          config: ru
          name: MTEB MassiveScenarioClassification (ru)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 8.140551445864155
          - type: f1
            value: 3.088889182397252
          - type: f1_weighted
            value: 3.382529160821981
          - type: main_score
            value: 8.140551445864155
        task:
          type: Classification
      - dataset:
          config: zh-TW
          name: MTEB MassiveScenarioClassification (zh-TW)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 10.063887020847343
          - type: f1
            value: 4.3953906298120415
          - type: f1_weighted
            value: 6.1030360630370675
          - type: main_score
            value: 10.063887020847343
        task:
          type: Classification
      - dataset:
          config: fr
          name: MTEB MassiveScenarioClassification (fr)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 40.86079354404843
          - type: f1
            value: 38.12848430733589
          - type: f1_weighted
            value: 39.61399818207077
          - type: main_score
            value: 40.86079354404843
        task:
          type: Classification
      - dataset:
          config: zh-CN
          name: MTEB MassiveScenarioClassification (zh-CN)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 3.1809011432414254
          - type: f1
            value: 0.6663078501713696
          - type: f1_weighted
            value: 0.6161504543566888
          - type: main_score
            value: 3.1809011432414254
        task:
          type: Classification
      - dataset:
          config: nb
          name: MTEB MassiveScenarioClassification (nb)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 38.991257565568255
          - type: f1
            value: 35.8711142606479
          - type: f1_weighted
            value: 39.27058914996822
          - type: main_score
            value: 38.991257565568255
        task:
          type: Classification
      - dataset:
          config: kn
          name: MTEB MassiveScenarioClassification (kn)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 7.5117686617350365
          - type: f1
            value: 2.730333236177
          - type: f1_weighted
            value: 2.476626926704587
          - type: main_score
            value: 7.5117686617350365
        task:
          type: Classification
      - dataset:
          config: ja
          name: MTEB MassiveScenarioClassification (ja)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 8.32548755884331
          - type: f1
            value: 3.0996007067176996
          - type: f1_weighted
            value: 3.0676442629069967
          - type: main_score
            value: 8.32548755884331
        task:
          type: Classification
      - dataset:
          config: nl
          name: MTEB MassiveScenarioClassification (nl)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 47.57901815736382
          - type: f1
            value: 43.47365742357309
          - type: f1_weighted
            value: 47.581511497169764
          - type: main_score
            value: 47.57901815736382
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MassiveScenarioClassification (en)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 63.84330867518494
          - type: f1
            value: 61.80623184800081
          - type: f1_weighted
            value: 63.66823920852459
          - type: main_score
            value: 63.84330867518494
        task:
          type: Classification
      - dataset:
          config: ar
          name: MTEB MassiveScenarioClassification (ar)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 10.060524546065905
          - type: f1
            value: 4.697788726183898
          - type: f1_weighted
            value: 8.0688374518688
          - type: main_score
            value: 10.060524546065905
        task:
          type: Classification
      - dataset:
          config: es
          name: MTEB MassiveScenarioClassification (es)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 39.02824478816409
          - type: f1
            value: 37.25613303442762
          - type: f1_weighted
            value: 38.22861284484312
          - type: main_score
            value: 39.02824478816409
        task:
          type: Classification
      - dataset:
          config: he
          name: MTEB MassiveScenarioClassification (he)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 5.0638870208473445
          - type: f1
            value: 1.0753261358276471
          - type: f1_weighted
            value: 1.0802883978030118
          - type: main_score
            value: 5.0638870208473445
        task:
          type: Classification
      - dataset:
          config: te
          name: MTEB MassiveScenarioClassification (te)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 6.321452589105584
          - type: f1
            value: 1.5829376262790664
          - type: f1_weighted
            value: 2.232184358298365
          - type: main_score
            value: 6.321452589105584
        task:
          type: Classification
      - dataset:
          config: tr
          name: MTEB MassiveScenarioClassification (tr)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 37.21923335574983
          - type: f1
            value: 36.993268170979576
          - type: f1_weighted
            value: 35.67645464322424
          - type: main_score
            value: 37.21923335574983
        task:
          type: Classification
      - dataset:
          config: vi
          name: MTEB MassiveScenarioClassification (vi)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 25.934767989240076
          - type: f1
            value: 24.616943306685748
          - type: f1_weighted
            value: 24.74309285569417
          - type: main_score
            value: 25.934767989240076
        task:
          type: Classification
      - dataset:
          config: id
          name: MTEB MassiveScenarioClassification (id)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 44.69401479488904
          - type: f1
            value: 42.41464498194295
          - type: f1_weighted
            value: 44.26134318268762
          - type: main_score
            value: 44.69401479488904
        task:
          type: Classification
      - dataset:
          config: ko
          name: MTEB MassiveScenarioClassification (ko)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 8.47343644922663
          - type: f1
            value: 2.9718553546241506
          - type: f1_weighted
            value: 3.9449930229420818
          - type: main_score
            value: 8.47343644922663
        task:
          type: Classification
      - dataset:
          config: ro
          name: MTEB MassiveScenarioClassification (ro)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 42.92199058507061
          - type: f1
            value: 40.00185738475351
          - type: f1_weighted
            value: 42.53838435113089
          - type: main_score
            value: 42.92199058507061
        task:
          type: Classification
      - dataset:
          config: pl
          name: MTEB MassiveScenarioClassification (pl)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 36.856086079354405
          - type: f1
            value: 35.85809216604705
          - type: f1_weighted
            value: 36.503220372495356
          - type: main_score
            value: 36.856086079354405
        task:
          type: Classification
      - dataset:
          config: ur
          name: MTEB MassiveScenarioClassification (ur)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 7.427706792199058
          - type: f1
            value: 2.355649221281433
          - type: f1_weighted
            value: 2.3635737714890097
          - type: main_score
            value: 7.427706792199058
        task:
          type: Classification
      - dataset:
          config: hy
          name: MTEB MassiveScenarioClassification (hy)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 7.2494956287827845
          - type: f1
            value: 3.0267066892790786
          - type: f1_weighted
            value: 2.228737132597149
          - type: main_score
            value: 7.2494956287827845
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB MedrxivClusteringS2S (default)
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
          split: test
          type: mteb/medrxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 22.3149940028344
          - type: v_measure
            value: 22.3149940028344
          - type: v_measure_std
            value: 1.184495521159966
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB MindSmallReranking (default)
          revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
          split: test
          type: mteb/mind_small
        metrics:
          - type: main_score
            value: 26.874241404290856
          - type: map
            value: 26.874241404290856
          - type: mrr
            value: 27.50127374810197
          - type: nAUC_map_diff1
            value: 20.72193125860396
          - type: nAUC_map_max
            value: -21.181361650744908
          - type: nAUC_map_std
            value: -21.136143423992458
          - type: nAUC_mrr_diff1
            value: 18.217458666186445
          - type: nAUC_mrr_max
            value: -14.657975701378914
          - type: nAUC_mrr_std
            value: -17.948245474413323
        task:
          type: Reranking
      - dataset:
          config: de
          name: MTEB OpusparcusPC (de)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.90448901623687
          - type: cosine_accuracy_threshold
            value: 32.084010045061795
          - type: cosine_ap
            value: 100
          - type: cosine_f1
            value: 99.95222169135212
          - type: cosine_f1_threshold
            value: 32.084010045061795
          - type: cosine_precision
            value: 100
          - type: cosine_recall
            value: 99.90448901623687
          - type: dot_accuracy
            value: 99.90448901623687
          - type: dot_accuracy_threshold
            value: 14.194202811836867
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.95222169135212
          - type: dot_f1_threshold
            value: 14.194202811836867
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.90448901623687
          - type: euclidean_accuracy
            value: 99.90448901623687
          - type: euclidean_accuracy_threshold
            value: 116.50380181599331
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.95222169135212
          - type: euclidean_f1_threshold
            value: 116.50380181599331
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.90448901623687
          - type: main_score
            value: 100
          - type: manhattan_accuracy
            value: 99.90448901623687
          - type: manhattan_accuracy_threshold
            value: 5994.10849076798
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.95222169135212
          - type: manhattan_f1_threshold
            value: 5994.10849076798
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.90448901623687
          - type: max_accuracy
            value: 99.90448901623687
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.95222169135212
          - type: max_precision
            value: 100
          - type: max_recall
            value: 99.90448901623687
          - type: similarity_accuracy
            value: 99.90448901623687
          - type: similarity_accuracy_threshold
            value: 32.084010045061795
          - type: similarity_ap
            value: 100
          - type: similarity_f1
            value: 99.95222169135212
          - type: similarity_f1_threshold
            value: 32.084010045061795
          - type: similarity_precision
            value: 100
          - type: similarity_recall
            value: 99.90448901623687
        task:
          type: PairClassification
      - dataset:
          config: en
          name: MTEB OpusparcusPC (en)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.89816700610999
          - type: cosine_accuracy_threshold
            value: 40.08682069986206
          - type: cosine_ap
            value: 100
          - type: cosine_f1
            value: 99.9490575649516
          - type: cosine_f1_threshold
            value: 40.08682069986206
          - type: cosine_precision
            value: 100
          - type: cosine_recall
            value: 99.89816700610999
          - type: dot_accuracy
            value: 99.89816700610999
          - type: dot_accuracy_threshold
            value: 40.08682068226012
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.9490575649516
          - type: dot_f1_threshold
            value: 40.08682068226012
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.89816700610999
          - type: euclidean_accuracy
            value: 99.89816700610999
          - type: euclidean_accuracy_threshold
            value: 109.46519126990579
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.9490575649516
          - type: euclidean_f1_threshold
            value: 109.46519126990579
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.89816700610999
          - type: main_score
            value: 100
          - type: manhattan_accuracy
            value: 99.89816700610999
          - type: manhattan_accuracy_threshold
            value: 5586.837509625999
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.9490575649516
          - type: manhattan_f1_threshold
            value: 5586.837509625999
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.89816700610999
          - type: max_accuracy
            value: 99.89816700610999
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.9490575649516
          - type: max_precision
            value: 100
          - type: max_recall
            value: 99.89816700610999
          - type: similarity_accuracy
            value: 99.89816700610999
          - type: similarity_accuracy_threshold
            value: 40.08682069986206
          - type: similarity_ap
            value: 100
          - type: similarity_f1
            value: 99.9490575649516
          - type: similarity_f1_threshold
            value: 40.08682069986206
          - type: similarity_precision
            value: 100
          - type: similarity_recall
            value: 99.89816700610999
        task:
          type: PairClassification
      - dataset:
          config: fi
          name: MTEB OpusparcusPC (fi)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.89561586638831
          - type: cosine_accuracy_threshold
            value: -22.557142663724193
          - type: cosine_ap
            value: 99.99999999999999
          - type: cosine_f1
            value: 99.94778067885117
          - type: cosine_f1_threshold
            value: -22.557142663724193
          - type: cosine_precision
            value: 100
          - 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
          - 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
          - 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
          - 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
          - 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
          - type: similarity_recall
            value: 99.89561586638831
        task:
          type: PairClassification
      - dataset:
          config: fr
          name: MTEB OpusparcusPC (fr)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.90069513406156
          - type: cosine_accuracy_threshold
            value: 4.276752354307001
          - type: cosine_ap
            value: 100
          - type: cosine_f1
            value: 99.95032290114257
          - type: cosine_f1_threshold
            value: 4.276752354307001
          - type: cosine_precision
            value: 100
          - type: cosine_recall
            value: 99.90069513406156
          - type: dot_accuracy
            value: 99.90069513406156
          - type: dot_accuracy_threshold
            value: 4.276752351391649
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.95032290114257
          - type: dot_f1_threshold
            value: 4.276752351391649
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.90069513406156
          - type: euclidean_accuracy
            value: 99.90069513406156
          - type: euclidean_accuracy_threshold
            value: 136.9020176878726
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.95032290114257
          - type: euclidean_f1_threshold
            value: 136.9020176878726
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.90069513406156
          - type: main_score
            value: 100
          - type: manhattan_accuracy
            value: 99.90069513406156
          - type: manhattan_accuracy_threshold
            value: 7063.200709566871
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.95032290114257
          - type: manhattan_f1_threshold
            value: 7063.200709566871
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.90069513406156
          - type: max_accuracy
            value: 99.90069513406156
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.95032290114257
          - type: max_precision
            value: 100
          - type: max_recall
            value: 99.90069513406156
          - type: similarity_accuracy
            value: 99.90069513406156
          - type: similarity_accuracy_threshold
            value: 4.276752354307001
          - type: similarity_ap
            value: 100
          - type: similarity_f1
            value: 99.95032290114257
          - type: similarity_f1_threshold
            value: 4.276752354307001
          - type: similarity_precision
            value: 100
          - type: similarity_recall
            value: 99.90069513406156
        task:
          type: PairClassification
      - dataset:
          config: ru
          name: MTEB OpusparcusPC (ru)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.90636704119851
          - type: cosine_accuracy_threshold
            value: 7.132103928293631
          - type: cosine_ap
            value: 100
          - type: cosine_f1
            value: 99.95316159250585
          - type: cosine_f1_threshold
            value: 7.132103928293631
          - type: cosine_precision
            value: 100
          - type: cosine_recall
            value: 99.90636704119851
          - type: dot_accuracy
            value: 99.90636704119851
          - type: dot_accuracy_threshold
            value: -13.447421954803113
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.95316159250585
          - type: dot_f1_threshold
            value: -13.447421954803113
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.90636704119851
          - type: euclidean_accuracy
            value: 99.90636704119851
          - type: euclidean_accuracy_threshold
            value: 133.89453353967028
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.95316159250585
          - type: euclidean_f1_threshold
            value: 133.89453353967028
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.90636704119851
          - type: main_score
            value: 100
          - type: manhattan_accuracy
            value: 99.90636704119851
          - type: manhattan_accuracy_threshold
            value: 7020.097656622158
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.95316159250585
          - type: manhattan_f1_threshold
            value: 7020.097656622158
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.90636704119851
          - type: max_accuracy
            value: 99.90636704119851
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.95316159250585
          - type: max_precision
            value: 100
          - type: max_recall
            value: 99.90636704119851
          - type: similarity_accuracy
            value: 99.90636704119851
          - type: similarity_accuracy_threshold
            value: 7.132103928293631
          - type: similarity_ap
            value: 100
          - type: similarity_f1
            value: 99.95316159250585
          - type: similarity_f1_threshold
            value: 7.132103928293631
          - type: similarity_precision
            value: 100
          - type: similarity_recall
            value: 99.90636704119851
        task:
          type: PairClassification
      - dataset:
          config: sv
          name: MTEB OpusparcusPC (sv)
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
          split: test
          type: GEM/opusparcus
        metrics:
          - type: cosine_accuracy
            value: 99.89440337909187
          - type: cosine_accuracy_threshold
            value: 0.2529676444121498
          - type: cosine_ap
            value: 100
          - type: cosine_f1
            value: 99.9471737982039
          - type: cosine_f1_threshold
            value: 0.2529676444121498
          - type: cosine_precision
            value: 100
          - 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
          - type: dot_recall
            value: 99.89440337909187
          - type: euclidean_accuracy
            value: 99.89440337909187
          - type: euclidean_accuracy_threshold
            value: 139.80163412046423
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.9471737982039
          - type: euclidean_f1_threshold
            value: 139.80163412046423
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.89440337909187
          - type: main_score
            value: 100
          - type: manhattan_accuracy
            value: 99.89440337909187
          - type: manhattan_accuracy_threshold
            value: 7259.639697084279
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.9471737982039
          - type: manhattan_f1_threshold
            value: 7259.639697084279
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.89440337909187
          - type: max_accuracy
            value: 99.89440337909187
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.9471737982039
          - type: max_precision
            value: 100
          - type: max_recall
            value: 99.89440337909187
          - type: similarity_accuracy
            value: 99.89440337909187
          - type: similarity_accuracy_threshold
            value: 0.2529676444121498
          - type: similarity_ap
            value: 100
          - type: similarity_f1
            value: 99.9471737982039
          - type: similarity_f1_threshold
            value: 0.2529676444121498
          - type: similarity_precision
            value: 100
          - type: similarity_recall
            value: 99.89440337909187
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB QuoraRetrieval (default)
          revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
          split: test
          type: mteb/quora
        metrics:
          - type: main_score
            value: 68.73
          - type: map_at_1
            value: 53.492
          - type: map_at_10
            value: 64.086
          - type: map_at_100
            value: 64.832
          - type: map_at_1000
            value: 64.88199999999999
          - type: map_at_20
            value: 64.537
          - type: map_at_3
            value: 61.592
          - type: map_at_5
            value: 63.113
          - type: mrr_at_1
            value: 61.56
          - type: mrr_at_10
            value: 68.92823412698384
          - type: mrr_at_100
            value: 69.28307943909826
          - type: mrr_at_1000
            value: 69.30426854775237
          - type: mrr_at_20
            value: 69.15371761666225
          - type: mrr_at_3
            value: 67.3866666666664
          - type: mrr_at_5
            value: 68.36666666666618
          - type: nauc_map_at_1000_diff1
            value: 67.15642759814821
          - type: nauc_map_at_1000_max
            value: 45.055780376792974
          - type: nauc_map_at_1000_std
            value: -9.604334727421541
          - type: nauc_map_at_100_diff1
            value: 67.15173583169253
          - type: nauc_map_at_100_max
            value: 45.04159938681548
          - type: nauc_map_at_100_std
            value: -9.621105481487115
          - type: nauc_map_at_10_diff1
            value: 67.21904799567723
          - type: nauc_map_at_10_max
            value: 44.64598524589752
          - type: nauc_map_at_10_std
            value: -10.240236577363671
          - type: nauc_map_at_1_diff1
            value: 69.75325378909568
          - type: nauc_map_at_1_max
            value: 39.57437605382559
          - type: nauc_map_at_1_std
            value: -13.560013524667186
          - type: nauc_map_at_20_diff1
            value: 67.18218534766027
          - type: nauc_map_at_20_max
            value: 44.898145457359036
          - type: nauc_map_at_20_std
            value: -9.853291926035132
          - type: nauc_map_at_3_diff1
            value: 67.33579825697572
          - type: nauc_map_at_3_max
            value: 43.434634746776254
          - type: nauc_map_at_3_std
            value: -11.533963319404025
          - type: nauc_map_at_5_diff1
            value: 67.29212861119778
          - type: nauc_map_at_5_max
            value: 44.149577446190584
          - type: nauc_map_at_5_std
            value: -10.846590188540638
          - type: nauc_mrr_at_1000_diff1
            value: 68.43853101345768
          - type: nauc_mrr_at_1000_max
            value: 48.23642231569019
          - type: nauc_mrr_at_1000_std
            value: -8.164139622888774
          - type: nauc_mrr_at_100_diff1
            value: 68.43230932580869
          - type: nauc_mrr_at_100_max
            value: 48.2366506280321
          - type: nauc_mrr_at_100_std
            value: -8.15719155689163
          - type: nauc_mrr_at_10_diff1
            value: 68.40804119736147
          - type: nauc_mrr_at_10_max
            value: 48.2668711810203
          - type: nauc_mrr_at_10_std
            value: -8.28336977621905
          - type: nauc_mrr_at_1_diff1
            value: 70.8152113865952
          - type: nauc_mrr_at_1_max
            value: 47.0802377233158
          - type: nauc_mrr_at_1_std
            value: -11.195273246909617
          - type: nauc_mrr_at_20_diff1
            value: 68.42041452964153
          - type: nauc_mrr_at_20_max
            value: 48.22983590171867
          - type: nauc_mrr_at_20_std
            value: -8.20351261044932
          - type: nauc_mrr_at_3_diff1
            value: 68.44729044448252
          - type: nauc_mrr_at_3_max
            value: 48.16311095038692
          - type: nauc_mrr_at_3_std
            value: -8.78728757717942
          - type: nauc_mrr_at_5_diff1
            value: 68.38338463498374
          - type: nauc_mrr_at_5_max
            value: 48.268101599089846
          - type: nauc_mrr_at_5_std
            value: -8.477703392514476
          - type: nauc_ndcg_at_1000_diff1
            value: 66.78555692495787
          - type: nauc_ndcg_at_1000_max
            value: 46.769939711081044
          - type: nauc_ndcg_at_1000_std
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          - type: nauc_ndcg_at_100_diff1
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          - type: nauc_recall_at_1000_diff1
            value: 57.196928991569266
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            value: 46.153589753933446
          - type: nauc_recall_at_1000_std
            value: 30.748423976943613
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            value: 57.976992158794886
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            value: 45.79893337773414
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            value: 13.253969225652396
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            value: 60.22299195797645
          - type: nauc_recall_at_10_max
            value: 43.85065064759132
          - type: nauc_recall_at_10_std
            value: -3.125491914491259
          - type: nauc_recall_at_1_diff1
            value: 69.75325378909568
          - type: nauc_recall_at_1_max
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          - type: nauc_recall_at_1_std
            value: -13.560013524667186
          - type: nauc_recall_at_20_diff1
            value: 59.1680127262332
          - type: nauc_recall_at_20_max
            value: 44.06962727874914
          - type: nauc_recall_at_20_std
            value: 1.7610688570268762
          - type: nauc_recall_at_3_diff1
            value: 62.75286406178069
          - type: nauc_recall_at_3_max
            value: 42.40300188251299
          - type: nauc_recall_at_3_std
            value: -8.94270893049646
          - type: nauc_recall_at_5_diff1
            value: 61.57224817120582
          - type: nauc_recall_at_5_max
            value: 43.2469875881082
          - type: nauc_recall_at_5_std
            value: -6.712607605292967
          - type: ndcg_at_1
            value: 61.61
          - type: ndcg_at_10
            value: 68.73
          - type: ndcg_at_100
            value: 71.281
          - type: ndcg_at_1000
            value: 72.209
          - type: ndcg_at_20
            value: 69.862
          - type: ndcg_at_3
            value: 65.35
          - type: ndcg_at_5
            value: 67.099
          - type: precision_at_1
            value: 61.61
          - type: precision_at_10
            value: 10.295
          - type: precision_at_100
            value: 1.2670000000000001
          - type: precision_at_1000
            value: 0.14100000000000001
          - type: precision_at_20
            value: 5.583
          - type: precision_at_3
            value: 28.157
          - type: precision_at_5
            value: 18.644
          - type: recall_at_1
            value: 53.492
          - type: recall_at_10
            value: 77.395
          - type: recall_at_100
            value: 87.822
          - type: recall_at_1000
            value: 94.039
          - type: recall_at_20
            value: 81.381
          - type: recall_at_3
            value: 67.657
          - type: recall_at_5
            value: 72.494
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB RedditClustering (default)
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
          split: test
          type: mteb/reddit-clustering
        metrics:
          - type: main_score
            value: 22.18693423438157
          - type: v_measure
            value: 22.18693423438157
          - type: v_measure_std
            value: 3.362608784471836
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB SICK-R (default)
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
          split: test
          type: mteb/sickr-sts
        metrics:
          - type: cosine_pearson
            value: 74.25579384618342
          - type: cosine_spearman
            value: 67.31903429944056
          - type: euclidean_pearson
            value: 71.84781550612432
          - type: euclidean_spearman
            value: 67.31913348808827
          - type: main_score
            value: 67.31903429944056
          - type: manhattan_pearson
            value: 71.93525335001107
          - type: manhattan_spearman
            value: 67.44731252485444
          - type: pearson
            value: 74.25579384618342
          - type: spearman
            value: 67.31903429944056
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS12 (default)
          revision: a0d554a64d88156834ff5ae9920b964011b16384
          split: test
          type: mteb/sts12-sts
        metrics:
          - type: cosine_pearson
            value: 70.45282392047417
          - type: cosine_spearman
            value: 57.66176503826067
          - type: euclidean_pearson
            value: 68.20476513300197
          - type: euclidean_spearman
            value: 57.662984752186595
          - type: main_score
            value: 57.66176503826067
          - type: manhattan_pearson
            value: 68.35595302570229
          - type: manhattan_spearman
            value: 57.78214901099006
          - type: pearson
            value: 70.45282392047417
          - type: spearman
            value: 57.66176503826067
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS13 (default)
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
          split: test
          type: mteb/sts13-sts
        metrics:
          - type: cosine_pearson
            value: 66.72224934737348
          - type: cosine_spearman
            value: 71.89696855506867
          - type: euclidean_pearson
            value: 70.4712630269631
          - type: euclidean_spearman
            value: 71.89698079206684
          - type: main_score
            value: 71.89696855506867
          - type: manhattan_pearson
            value: 70.45860743861545
          - type: manhattan_spearman
            value: 71.91608445555363
          - type: pearson
            value: 66.72224934737348
          - type: spearman
            value: 71.89696855506867
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS14 (default)
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
          split: test
          type: mteb/sts14-sts
        metrics:
          - type: cosine_pearson
            value: 70.34249555730298
          - type: cosine_spearman
            value: 69.53679034910807
          - type: euclidean_pearson
            value: 71.56701694057745
          - type: euclidean_spearman
            value: 69.5367806640627
          - type: main_score
            value: 69.53679034910807
          - type: manhattan_pearson
            value: 71.53194206589868
          - type: manhattan_spearman
            value: 69.52240262783113
          - type: pearson
            value: 70.34249555730298
          - type: spearman
            value: 69.53679034910807
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS15 (default)
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
          split: test
          type: mteb/sts15-sts
        metrics:
          - type: cosine_pearson
            value: 68.33547250158846
          - type: cosine_spearman
            value: 73.96543736110634
          - type: euclidean_pearson
            value: 72.63926797717605
          - type: euclidean_spearman
            value: 73.96543799049243
          - type: main_score
            value: 73.96543736110634
          - type: manhattan_pearson
            value: 72.6308651035737
          - type: manhattan_spearman
            value: 73.99784893840472
          - type: pearson
            value: 68.33547250158846
          - type: spearman
            value: 73.96543736110634
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS16 (default)
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
          split: test
          type: mteb/sts16-sts
        metrics:
          - type: cosine_pearson
            value: 62.50064232309498
          - type: cosine_spearman
            value: 69.99690285087063
          - type: euclidean_pearson
            value: 67.7773080753282
          - type: euclidean_spearman
            value: 69.99717504340504
          - type: main_score
            value: 69.99690285087063
          - type: manhattan_pearson
            value: 67.77737269625732
          - type: manhattan_spearman
            value: 70.05662507231811
          - type: pearson
            value: 62.50064232309498
          - type: spearman
            value: 69.99690285087063
        task:
          type: STS
      - dataset:
          config: en-de
          name: MTEB STS17 (en-de)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -4.639974351143124
          - type: cosine_spearman
            value: -5.70963417137641
          - type: euclidean_pearson
            value: -4.671269689471623
          - type: euclidean_spearman
            value: -5.70963417137641
          - type: main_score
            value: -5.70963417137641
          - type: manhattan_pearson
            value: -4.822356012695697
          - type: manhattan_spearman
            value: -5.805771748799997
          - type: pearson
            value: -4.639974351143124
          - type: spearman
            value: -5.70963417137641
        task:
          type: STS
      - dataset:
          config: en-en
          name: MTEB STS17 (en-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 75.07706637430398
          - type: cosine_spearman
            value: 78.81834383119009
          - type: euclidean_pearson
            value: 78.33040815719426
          - type: euclidean_spearman
            value: 78.81922098296683
          - type: main_score
            value: 78.81834383119009
          - type: manhattan_pearson
            value: 78.25386282376627
          - type: manhattan_spearman
            value: 78.73096351789457
          - type: pearson
            value: 75.07706637430398
          - type: spearman
            value: 78.81834383119009
        task:
          type: STS
      - dataset:
          config: it-en
          name: MTEB STS17 (it-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -8.034513096828757
          - type: cosine_spearman
            value: -8.94071782108332
          - type: euclidean_pearson
            value: -8.362035046748408
          - type: euclidean_spearman
            value: -8.94071782108332
          - type: main_score
            value: -8.94071782108332
          - type: manhattan_pearson
            value: -8.58384659065939
          - type: manhattan_spearman
            value: -9.022478967496742
          - type: pearson
            value: -8.034513096828757
          - type: spearman
            value: -8.94071782108332
        task:
          type: STS
      - dataset:
          config: es-en
          name: MTEB STS17 (es-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -9.309746585888194
          - type: cosine_spearman
            value: -9.989532291941243
          - type: euclidean_pearson
            value: -9.113663493693515
          - type: euclidean_spearman
            value: -9.989532291941243
          - type: main_score
            value: -9.989532291941243
          - type: manhattan_pearson
            value: -9.123108445100232
          - type: manhattan_spearman
            value: -10.02555353386953
          - type: pearson
            value: -9.309746585888194
          - type: spearman
            value: -9.989532291941243
        task:
          type: STS
      - dataset:
          config: es-es
          name: MTEB STS17 (es-es)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 49.203212653579534
          - type: cosine_spearman
            value: 62.17745071362616
          - type: euclidean_pearson
            value: 60.12172084869311
          - type: euclidean_spearman
            value: 62.17745071362616
          - type: main_score
            value: 62.17745071362616
          - type: manhattan_pearson
            value: 60.03123674358504
          - type: manhattan_spearman
            value: 62.08054980165127
          - type: pearson
            value: 49.203212653579534
          - type: spearman
            value: 62.17745071362616
        task:
          type: STS
      - dataset:
          config: fr-en
          name: MTEB STS17 (fr-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -3.796131822561097
          - type: cosine_spearman
            value: -3.6829417954942962
          - type: euclidean_pearson
            value: -3.9617579449787215
          - type: euclidean_spearman
            value: -3.6829417954942962
          - type: main_score
            value: -3.6829417954942962
          - type: manhattan_pearson
            value: -4.229917664747983
          - type: manhattan_spearman
            value: -3.8304347521413575
          - type: pearson
            value: -3.796131822561097
          - type: spearman
            value: -3.6829417954942962
        task:
          type: STS
      - dataset:
          config: ko-ko
          name: MTEB STS17 (ko-ko)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 9.70401307418669
          - type: cosine_spearman
            value: 7.125994342518046
          - type: euclidean_pearson
            value: 8.692865519584803
          - type: euclidean_spearman
            value: 7.086314063560257
          - type: main_score
            value: 7.125994342518046
          - type: manhattan_pearson
            value: 8.688214277742162
          - type: manhattan_spearman
            value: 6.951151829297476
          - type: pearson
            value: 9.70401307418669
          - type: spearman
            value: 7.125994342518046
        task:
          type: STS
      - dataset:
          config: en-tr
          name: MTEB STS17 (en-tr)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -12.59835322441286
          - type: cosine_spearman
            value: -17.99707926594973
          - type: euclidean_pearson
            value: -14.34931127125891
          - type: euclidean_spearman
            value: -17.99707926594973
          - type: main_score
            value: -17.99707926594973
          - type: manhattan_pearson
            value: -14.599702365227513
          - type: manhattan_spearman
            value: -18.256327942493844
          - type: pearson
            value: -12.59835322441286
          - type: spearman
            value: -17.99707926594973
        task:
          type: STS
      - dataset:
          config: nl-en
          name: MTEB STS17 (nl-en)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -0.06664551245524106
          - type: cosine_spearman
            value: -0.891108084699552
          - type: euclidean_pearson
            value: 0.2657845183657392
          - type: euclidean_spearman
            value: -0.891108084699552
          - type: main_score
            value: -0.891108084699552
          - type: manhattan_pearson
            value: 0.120752189864216
          - type: manhattan_spearman
            value: -0.8531297054534491
          - type: pearson
            value: -0.06664551245524106
          - type: spearman
            value: -0.891108084699552
        task:
          type: STS
      - dataset:
          config: ar-ar
          name: MTEB STS17 (ar-ar)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 9.587866133715462
          - type: cosine_spearman
            value: 10.240476793789082
          - type: euclidean_pearson
            value: 9.587866133709937
          - type: euclidean_spearman
            value: 10.299853867377841
          - type: main_score
            value: 10.240476793789082
          - type: manhattan_pearson
            value: 9.587479080379996
          - type: manhattan_spearman
            value: 10.289638886132417
          - type: pearson
            value: 9.587866133715462
          - type: spearman
            value: 10.240476793789082
        task:
          type: STS
      - dataset:
          config: en-ar
          name: MTEB STS17 (en-ar)
          revision: faeb762787bd10488a50c8b5be4a3b82e411949c
          split: test
          type: mteb/sts17-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: -11.455833153778357
          - type: cosine_spearman
            value: -12.120168687487281
          - type: euclidean_pearson
            value: -4.8404233986021
          - type: euclidean_spearman
            value: -5.629445269503656
          - type: main_score
            value: -12.120168687487281
          - type: manhattan_pearson
            value: -5.802510530492165
          - type: manhattan_spearman
            value: -4.129636012427943
          - type: pearson
            value: -11.455833153778357
          - type: spearman
            value: -12.120168687487281
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STSBenchmark (default)
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
          split: test
          type: mteb/stsbenchmark-sts
        metrics:
          - type: cosine_pearson
            value: 67.09018720017058
          - type: cosine_spearman
            value: 67.6086401236391
          - type: euclidean_pearson
            value: 69.37492911426406
          - type: euclidean_spearman
            value: 67.60865860108962
          - type: main_score
            value: 67.6086401236391
          - type: manhattan_pearson
            value: 69.34659483682688
          - type: manhattan_spearman
            value: 67.592012200863
          - type: pearson
            value: 67.09018720017058
          - type: spearman
            value: 67.6086401236391
        task:
          type: STS
      - dataset:
          config: it
          name: MTEB STSBenchmarkMultilingualSTS (it)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 44.27233827248044
          - type: cosine_spearman
            value: 49.47510261384346
          - type: euclidean_pearson
            value: 49.40398312290145
          - type: euclidean_spearman
            value: 49.47500131889738
          - type: main_score
            value: 49.47510261384346
          - type: manhattan_pearson
            value: 49.341548618895466
          - type: manhattan_spearman
            value: 49.4424887001277
          - type: pearson
            value: 44.27233827248044
          - type: spearman
            value: 49.47510261384346
        task:
          type: STS
      - dataset:
          config: nl
          name: MTEB STSBenchmarkMultilingualSTS (nl)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 44.79696340221503
          - type: cosine_spearman
            value: 48.84897104878986
          - type: euclidean_pearson
            value: 49.324260285317855
          - type: euclidean_spearman
            value: 48.848924358139364
          - type: main_score
            value: 48.84897104878986
          - type: manhattan_pearson
            value: 49.33647165074528
          - type: manhattan_spearman
            value: 48.88344266774654
          - type: pearson
            value: 44.79696340221503
          - type: spearman
            value: 48.84897104878986
        task:
          type: STS
      - dataset:
          config: en
          name: MTEB STSBenchmarkMultilingualSTS (en)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 67.09018713920469
          - type: cosine_spearman
            value: 67.6086401236391
          - type: euclidean_pearson
            value: 69.37492906687476
          - type: euclidean_spearman
            value: 67.60865860108962
          - type: main_score
            value: 67.6086401236391
          - type: manhattan_pearson
            value: 69.34659479129859
          - type: manhattan_spearman
            value: 67.592012200863
          - type: pearson
            value: 67.09018713920469
          - type: spearman
            value: 67.6086401236391
        task:
          type: STS
      - dataset:
          config: es
          name: MTEB STSBenchmarkMultilingualSTS (es)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 42.895339590180996
          - type: cosine_spearman
            value: 52.21235147253785
          - type: euclidean_pearson
            value: 49.413874942919264
          - type: euclidean_spearman
            value: 52.21203780406665
          - type: main_score
            value: 52.21235147253785
          - type: manhattan_pearson
            value: 49.276873027104855
          - type: manhattan_spearman
            value: 52.16409604469493
          - type: pearson
            value: 42.895339590180996
          - type: spearman
            value: 52.21235147253785
        task:
          type: STS
      - dataset:
          config: ru
          name: MTEB STSBenchmarkMultilingualSTS (ru)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 10.389925450857834
          - type: cosine_spearman
            value: 8.908138291052701
          - type: euclidean_pearson
            value: 9.890367033199064
          - type: euclidean_spearman
            value: 8.770978113601167
          - type: main_score
            value: 8.908138291052701
          - type: manhattan_pearson
            value: 9.899760056143247
          - type: manhattan_spearman
            value: 9.030970134574098
          - type: pearson
            value: 10.389925450857834
          - type: spearman
            value: 8.908138291052701
        task:
          type: STS
      - dataset:
          config: zh
          name: MTEB STSBenchmarkMultilingualSTS (zh)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 3.2165863331249414
          - type: cosine_spearman
            value: 0.7975692702633864
          - type: euclidean_pearson
            value: 2.0618436826186066
          - type: euclidean_spearman
            value: 0.5027230247162311
          - type: main_score
            value: 0.7975692702633864
          - type: manhattan_pearson
            value: 2.0514189695530325
          - type: manhattan_spearman
            value: 0.39577079994867403
          - type: pearson
            value: 3.2165863331249414
          - type: spearman
            value: 0.7975692702633864
        task:
          type: STS
      - dataset:
          config: fr
          name: MTEB STSBenchmarkMultilingualSTS (fr)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 46.17508747479316
          - type: cosine_spearman
            value: 51.086872268140816
          - type: euclidean_pearson
            value: 51.41891364659744
          - type: euclidean_spearman
            value: 51.08665283035928
          - type: main_score
            value: 51.086872268140816
          - type: manhattan_pearson
            value: 51.361372778247606
          - type: manhattan_spearman
            value: 51.045873818882924
          - type: pearson
            value: 46.17508747479316
          - type: spearman
            value: 51.086872268140816
        task:
          type: STS
      - dataset:
          config: pt
          name: MTEB STSBenchmarkMultilingualSTS (pt)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 40.639680830613514
          - type: cosine_spearman
            value: 47.99664145034049
          - type: euclidean_pearson
            value: 46.61505913234052
          - type: euclidean_spearman
            value: 47.99654723025848
          - type: main_score
            value: 47.99664145034049
          - type: manhattan_pearson
            value: 46.594310151466146
          - type: manhattan_spearman
            value: 47.96444879548329
          - type: pearson
            value: 40.639680830613514
          - type: spearman
            value: 47.99664145034049
        task:
          type: STS
      - dataset:
          config: pl
          name: MTEB STSBenchmarkMultilingualSTS (pl)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 46.72373117676612
          - type: cosine_spearman
            value: 52.865236864827345
          - type: euclidean_pearson
            value: 52.45181901546032
          - type: euclidean_spearman
            value: 52.86458795625298
          - type: main_score
            value: 52.865236864827345
          - type: manhattan_pearson
            value: 52.44185889658423
          - type: manhattan_spearman
            value: 52.78491169411964
          - type: pearson
            value: 46.72373117676612
          - type: spearman
            value: 52.865236864827345
        task:
          type: STS
      - dataset:
          config: de
          name: MTEB STSBenchmarkMultilingualSTS (de)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
        metrics:
          - type: cosine_pearson
            value: 48.138397241162444
          - type: cosine_spearman
            value: 51.285304430536335
          - type: euclidean_pearson
            value: 51.803064906612896
          - type: euclidean_spearman
            value: 51.28542208854524
          - type: main_score
            value: 51.285304430536335
          - type: manhattan_pearson
            value: 51.819864335986956
          - type: manhattan_spearman
            value: 51.32840976987932
          - type: pearson
            value: 48.138397241162444
          - type: spearman
            value: 51.285304430536335
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB SciDocsRR (default)
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
          split: test
          type: mteb/scidocs-reranking
        metrics:
          - type: main_score
            value: 60.74844680566163
          - type: map
            value: 60.74844680566163
          - type: mrr
            value: 84.68450485607349
          - type: nAUC_map_diff1
            value: 13.078055417971749
          - type: nAUC_map_max
            value: 47.937301739074215
          - type: nAUC_map_std
            value: 34.26921463872339
          - type: nAUC_mrr_diff1
            value: 42.90446482292105
          - type: nAUC_mrr_max
            value: 59.75684998106037
          - type: nAUC_mrr_std
            value: 30.107306162191268
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SprintDuplicateQuestions (default)
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
          split: test
          type: mteb/sprintduplicatequestions-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 99.44851485148514
          - type: cosine_accuracy_threshold
            value: 95.47240059357654
          - type: cosine_ap
            value: 68.22522420879186
          - type: cosine_f1
            value: 65.92635885447106
          - type: cosine_f1_threshold
            value: 94.98664208777299
          - type: cosine_precision
            value: 79.32489451476793
          - type: cosine_recall
            value: 56.39999999999999
          - type: dot_accuracy
            value: 99.44851485148514
          - type: dot_accuracy_threshold
            value: 95.47240056095825
          - type: dot_ap
            value: 68.22522420879186
          - type: dot_f1
            value: 65.92635885447106
          - type: dot_f1_threshold
            value: 94.98664205438727
          - type: dot_precision
            value: 79.32489451476793
          - type: dot_recall
            value: 56.39999999999999
          - type: euclidean_accuracy
            value: 99.44851485148514
          - type: euclidean_accuracy_threshold
            value: 30.091857225199625
          - type: euclidean_ap
            value: 68.22522420879186
          - type: euclidean_f1
            value: 65.92635885447106
          - type: euclidean_f1_threshold
            value: 31.664989847761138
          - type: euclidean_precision
            value: 79.32489451476793
          - type: euclidean_recall
            value: 56.39999999999999
          - type: main_score
            value: 68.28159512609737
          - type: manhattan_accuracy
            value: 99.44851485148514
          - type: manhattan_accuracy_threshold
            value: 1519.5971755477553
          - type: manhattan_ap
            value: 68.28159512609737
          - type: manhattan_f1
            value: 66.05818596691385
          - type: manhattan_f1_threshold
            value: 1628.6210010065347
          - type: manhattan_precision
            value: 76.89243027888446
          - type: manhattan_recall
            value: 57.9
          - type: max_accuracy
            value: 99.44851485148514
          - type: max_ap
            value: 68.28159512609737
          - type: max_f1
            value: 66.05818596691385
          - type: max_precision
            value: 79.32489451476793
          - type: max_recall
            value: 57.9
          - type: similarity_accuracy
            value: 99.44851485148514
          - type: similarity_accuracy_threshold
            value: 95.47240059357654
          - type: similarity_ap
            value: 68.22522420879186
          - type: similarity_f1
            value: 65.92635885447106
          - type: similarity_f1_threshold
            value: 94.98664208777299
          - type: similarity_precision
            value: 79.32489451476793
          - type: similarity_recall
            value: 56.39999999999999
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB StackExchangeClustering (default)
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
          split: test
          type: mteb/stackexchange-clustering
        metrics:
          - type: main_score
            value: 29.30513928170411
          - type: v_measure
            value: 29.30513928170411
          - type: v_measure_std
            value: 4.167908098359504
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackOverflowDupQuestions (default)
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
          split: test
          type: mteb/stackoverflowdupquestions-reranking
        metrics:
          - type: main_score
            value: 41.60577705014483
          - type: map
            value: 41.60577705014483
          - type: mrr
            value: 42.046595153212806
          - type: nAUC_map_diff1
            value: 29.435613304703427
          - type: nAUC_map_max
            value: 23.041089610073772
          - type: nAUC_map_std
            value: 4.187983544965867
          - type: nAUC_mrr_diff1
            value: 28.24912241668722
          - type: nAUC_mrr_max
            value: 23.844594928925574
          - type: nAUC_mrr_std
            value: 5.300127051350153
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB ToxicConversationsClassification (default)
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
          split: test
          type: mteb/toxic_conversations_50k
        metrics:
          - type: accuracy
            value: 61.03515625
          - type: ap
            value: 10.357109818250033
          - type: ap_weighted
            value: 10.357109818250033
          - type: f1
            value: 46.79659702416427
          - type: f1_weighted
            value: 69.34093343990779
          - type: main_score
            value: 61.03515625
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TweetSentimentExtractionClassification (default)
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
          split: test
          type: mteb/tweet_sentiment_extraction
        metrics:
          - type: accuracy
            value: 54.88964346349745
          - type: f1
            value: 54.88849570146398
          - type: f1_weighted
            value: 54.0202173220827
          - type: main_score
            value: 54.88964346349745
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TwentyNewsgroupsClustering (default)
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
          split: test
          type: mteb/twentynewsgroups-clustering
        metrics:
          - type: main_score
            value: 25.77793337013197
          - type: v_measure
            value: 25.77793337013197
          - type: v_measure_std
            value: 1.7036625620777253
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB TwitterSemEval2015 (default)
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
          split: test
          type: mteb/twittersemeval2015-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 83.50718245216666
          - type: cosine_accuracy_threshold
            value: 92.85797990005872
          - type: cosine_ap
            value: 64.57501485077721
          - type: cosine_f1
            value: 61.107669433775236
          - type: cosine_f1_threshold
            value: 90.91770372653797
          - type: cosine_precision
            value: 57.60336370007008
          - type: cosine_recall
            value: 65.06596306068602
          - type: dot_accuracy
            value: 83.50718245216666
          - type: dot_accuracy_threshold
            value: 92.85797986316105
          - type: dot_ap
            value: 64.57501485077721
          - type: dot_f1
            value: 61.107669433775236
          - type: dot_f1_threshold
            value: 90.91770369108825
          - type: dot_precision
            value: 57.60336370007008
          - type: dot_recall
            value: 65.06596306068602
          - type: euclidean_accuracy
            value: 83.50718245216666
          - type: euclidean_accuracy_threshold
            value: 37.794231852628414
          - type: euclidean_ap
            value: 64.57501485077721
          - type: euclidean_f1
            value: 61.107669433775236
          - type: euclidean_f1_threshold
            value: 42.61993960299444
          - type: euclidean_precision
            value: 57.60336370007008
          - type: euclidean_recall
            value: 65.06596306068602
          - type: main_score
            value: 64.57501485077721
          - type: manhattan_accuracy
            value: 83.48930082851524
          - type: manhattan_accuracy_threshold
            value: 1897.2244120282544
          - type: manhattan_ap
            value: 64.55099351854031
          - type: manhattan_f1
            value: 61.062609129458714
          - type: manhattan_f1_threshold
            value: 2160.535839208718
          - type: manhattan_precision
            value: 57.89971617786187
          - type: manhattan_recall
            value: 64.5910290237467
          - type: max_accuracy
            value: 83.50718245216666
          - type: max_ap
            value: 64.57501485077721
          - type: max_f1
            value: 61.107669433775236
          - type: max_precision
            value: 57.89971617786187
          - type: max_recall
            value: 65.06596306068602
          - type: similarity_accuracy
            value: 83.50718245216666
          - type: similarity_accuracy_threshold
            value: 92.85797990005872
          - type: similarity_ap
            value: 64.57501485077721
          - type: similarity_f1
            value: 61.107669433775236
          - type: similarity_f1_threshold
            value: 90.91770372653797
          - type: similarity_precision
            value: 57.60336370007008
          - type: similarity_recall
            value: 65.06596306068602
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB TwitterURLCorpus (default)
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
          split: test
          type: mteb/twitterurlcorpus-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 86.35463965537315
          - type: cosine_accuracy_threshold
            value: 93.93182168113243
          - type: cosine_ap
            value: 79.17988590079685
          - type: cosine_f1
            value: 71.77413258749716
          - type: cosine_f1_threshold
            value: 92.7978491290961
          - type: cosine_precision
            value: 70.48997772828508
          - type: cosine_recall
            value: 73.10594394825993
          - type: dot_accuracy
            value: 86.35463965537315
          - type: dot_accuracy_threshold
            value: 93.9318216501234
          - type: dot_ap
            value: 79.17988590079685
          - type: dot_f1
            value: 71.77413258749716
          - type: dot_f1_threshold
            value: 92.79784909821515
          - type: dot_precision
            value: 70.48997772828508
          - type: dot_recall
            value: 73.10594394825993
          - type: euclidean_accuracy
            value: 86.35463965537315
          - type: euclidean_accuracy_threshold
            value: 34.837274051981524
          - type: euclidean_ap
            value: 79.17988575609482
          - type: euclidean_f1
            value: 71.77413258749716
          - type: euclidean_f1_threshold
            value: 37.95299953339363
          - type: euclidean_precision
            value: 70.48997772828508
          - type: euclidean_recall
            value: 73.10594394825993
          - type: main_score
            value: 79.17988590079685
          - type: manhattan_accuracy
            value: 86.36046105483757
          - type: manhattan_accuracy_threshold
            value: 1771.5702122947137
          - type: manhattan_ap
            value: 79.16559289648251
          - type: manhattan_f1
            value: 71.8502354427472
          - type: manhattan_f1_threshold
            value: 1912.7281549009595
          - type: manhattan_precision
            value: 71.45359019264448
          - type: manhattan_recall
            value: 72.25130890052355
          - type: max_accuracy
            value: 86.36046105483757
          - type: max_ap
            value: 79.17988590079685
          - type: max_f1
            value: 71.8502354427472
          - type: max_precision
            value: 71.45359019264448
          - type: max_recall
            value: 73.10594394825993
          - type: similarity_accuracy
            value: 86.35463965537315
          - type: similarity_accuracy_threshold
            value: 93.93182168113243
          - type: similarity_ap
            value: 79.17988590079685
          - type: similarity_f1
            value: 71.77413258749716
          - type: similarity_f1_threshold
            value: 92.7978491290961
          - type: similarity_precision
            value: 70.48997772828508
          - type: similarity_recall
            value: 73.10594394825993
        task:
          type: PairClassification
tags:
  - mteb