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metadata
pipeline_tag: sentence-similarity
language: multilingual
license: apache-2.0
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - transformers
  - mteb
model-index:
  - name: distiluse-base-multilingual-cased-v2
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 71.80597014925372
          - type: ap
            value: 33.70263085714158
          - type: f1
            value: 65.44989712268762
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (de)
          config: de
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 68.13704496788009
          - type: ap
            value: 80.6706553308835
          - type: f1
            value: 66.6468090116337
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en-ext)
          config: en-ext
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 72.96101949025487
          - type: ap
            value: 22.209148737301962
          - type: f1
            value: 60.428775420466906
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (ja)
          config: ja
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 65.38543897216275
          - type: ap
            value: 16.13590032328447
          - type: f1
            value: 53.20720298606364
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 67.9988
          - type: ap
            value: 62.59891275364823
          - type: f1
            value: 67.73408963897285
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 35.454
          - type: f1
            value: 35.01958914240701
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (de)
          config: de
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 35.032000000000004
          - type: f1
            value: 33.93976447064354
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (es)
          config: es
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 36.242000000000004
          - type: f1
            value: 34.98879083946539
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (fr)
          config: fr
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 35.699999999999996
          - type: f1
            value: 34.74911268048424
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (ja)
          config: ja
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 31.075999999999997
          - type: f1
            value: 30.525865114811996
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (zh)
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 33.894000000000005
          - type: f1
            value: 32.63851365829613
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 33.59372253035037
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 53.752292029725815
          - type: mrr
            value: 68.26968737633557
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 79.26094784825986
          - type: cos_sim_spearman
            value: 78.34033925464169
          - type: euclidean_pearson
            value: 77.43607353262966
          - type: euclidean_spearman
            value: 76.77765304536669
          - type: manhattan_pearson
            value: 77.43287991423313
          - type: manhattan_spearman
            value: 76.849341425823
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 71.48051948051949
          - type: f1
            value: 70.45713884617551
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 40.045
          - type: f1
            value: 36.59544493168501
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 61.516799999999996
          - type: ap
            value: 57.302114956239514
          - type: f1
            value: 61.24392423075582
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 91.59142726858185
          - type: f1
            value: 91.16731589297895
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (de)
          config: de
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 86.19047619047619
          - type: f1
            value: 84.42185095665184
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (es)
          config: es
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 87.74516344229485
          - type: f1
            value: 86.89629934160831
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (fr)
          config: fr
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 84.61321641089883
          - type: f1
            value: 83.86194715158408
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (hi)
          config: hi
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 76.4144854786662
          - type: f1
            value: 74.66143814759417
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (th)
          config: th
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 73.61663652802893
          - type: f1
            value: 71.59773512640322
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 66.40218878248974
          - type: f1
            value: 44.0157655128108
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (de)
          config: de
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 59.208227669766124
          - type: f1
            value: 36.59415374962454
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (es)
          config: es
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 57.21147431621081
          - type: f1
            value: 38.46167201793877
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (fr)
          config: fr
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 53.40745380519887
          - type: f1
            value: 36.87813951228687
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (hi)
          config: hi
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 45.54320544998208
          - type: f1
            value: 28.091086881484788
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (th)
          config: th
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 47.732368896925855
          - type: f1
            value: 29.87429451601028
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (af)
          config: af
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 40.02017484868864
          - type: f1
            value: 35.75859698769357
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (am)
          config: am
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 2.347007397444519
          - type: f1
            value: 0.7465390699534603
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ar)
          config: ar
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 43.143913920645595
          - type: f1
            value: 38.85558637592047
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (az)
          config: az
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 25.601882985877605
          - type: f1
            value: 25.205774742990254
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (bn)
          config: bn
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 4.84196368527236
          - type: f1
            value: 1.7486302624639154
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (cy)
          config: cy
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 15.43375924680565
          - type: f1
            value: 14.212012285498213
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (da)
          config: da
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 52.33355749831876
          - type: f1
            value: 48.18484932318873
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (de)
          config: de
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 51.573638197713514
          - type: f1
            value: 45.55934579164648
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (el)
          config: el
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 49.65366509751178
          - type: f1
            value: 45.64683808611846
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 66.71149966375253
          - type: f1
            value: 63.78255507050109
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (es)
          config: es
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 56.573638197713514
          - type: f1
            value: 54.98029542986489
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fa)
          config: fa
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 55.35642232683256
          - type: f1
            value: 50.20214626269123
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fi)
          config: fi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 45.71620712844654
          - type: f1
            value: 42.200836560817535
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (fr)
          config: fr
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 57.02084734364491
          - type: f1
            value: 53.910650671151814
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (he)
          config: he
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 46.7350369872226
          - type: f1
            value: 42.509857120773866
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hi)
          config: hi
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 48.55077336919973
          - type: f1
            value: 43.993275443482936
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hu)
          config: hu
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 50.64559515803631
          - type: f1
            value: 45.28464736653043
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (hy)
          config: hy
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 40.79354404841964
          - type: f1
            value: 36.90100598587695
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (id)
          config: id
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 55.99529253530599
          - type: f1
            value: 52.44999289764702
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (is)
          config: is
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 16.079354404841965
          - type: f1
            value: 14.926428149458182
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (it)
          config: it
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 57.64626765299259
          - type: f1
            value: 53.7737970315679
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ja)
          config: ja
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 55.329522528581045
          - type: f1
            value: 50.89055472943818
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (jv)
          config: jv
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 28.164088769334228
          - type: f1
            value: 25.896264320477325
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ka)
          config: ka
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 29.411566913248148
          - type: f1
            value: 26.845594782986996
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (km)
          config: km
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 4.791526563550773
          - type: f1
            value: 1.4491239093711443
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (kn)
          config: kn
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.365837256220579
          - type: f1
            value: 1.3064783225018712
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ko)
          config: ko
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 49.9663752521856
          - type: f1
            value: 46.28463081207797
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (lv)
          config: lv
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 44.31405514458642
          - type: f1
            value: 41.59880687298492
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (ml)
          config: ml
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 3.2447881640887695
          - type: f1
            value: 1.1130430676330432
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        dataset:
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          name: MTEB MassiveScenarioClassification (ru)
          config: ru
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 65.41358439811701
          - type: f1
            value: 64.15512608670188
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sl)
          config: sl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 59.357767316745125
          - type: f1
            value: 58.284479078165106
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sq)
          config: sq
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 62.686617350369865
          - type: f1
            value: 59.49767603465277
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sv)
          config: sv
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 64.35104236718225
          - type: f1
            value: 61.62298238070601
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (sw)
          config: sw
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 25.12104909213181
          - type: f1
            value: 22.063961287382483
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ta)
          config: ta
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 8.671822461331539
          - type: f1
            value: 4.160922973001201
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (te)
          config: te
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 7.821116341627439
          - type: f1
            value: 3.59600077788794
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (th)
          config: th
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 54.64694014794888
          - type: f1
            value: 51.591586777977504
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tl)
          config: tl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 36.08607935440485
          - type: f1
            value: 32.46731674317254
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (tr)
          config: tr
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 60.89441829186282
          - type: f1
            value: 60.11999627480401
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (ur)
          config: ur
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 54.707464694014796
          - type: f1
            value: 52.46709289947395
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (vi)
          config: vi
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 55.1546738399462
          - type: f1
            value: 54.110902262235584
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-CN)
          config: zh-CN
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 66.4357767316745
          - type: f1
            value: 64.94684758602547
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (zh-TW)
          config: zh-TW
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 62.88836583725623
          - type: f1
            value: 61.7106895387137
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 30.389522323606887
          - type: mrr
            value: 31.507198662637208
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 81.18466748223793
          - type: cos_sim_spearman
            value: 75.24738784985722
          - type: euclidean_pearson
            value: 78.51159752223624
          - type: euclidean_spearman
            value: 75.46087065937311
          - type: manhattan_pearson
            value: 77.16743820738003
          - type: manhattan_spearman
            value: 73.49433694282183
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 79.35237266605724
          - type: cos_sim_spearman
            value: 72.95904349793416
          - type: euclidean_pearson
            value: 73.07895490202789
          - type: euclidean_spearman
            value: 71.66451640969629
          - type: manhattan_pearson
            value: 73.08359981539324
          - type: manhattan_spearman
            value: 71.91126963073746
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 68.26126180159085
          - type: cos_sim_spearman
            value: 70.5821267642011
          - type: euclidean_pearson
            value: 69.32005598610408
          - type: euclidean_spearman
            value: 69.91767420734864
          - type: manhattan_pearson
            value: 69.65574245013867
          - type: manhattan_spearman
            value: 70.22188522513176
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 73.8304467062826
          - type: cos_sim_spearman
            value: 70.28565248557119
          - type: euclidean_pearson
            value: 72.80361711138981
          - type: euclidean_spearman
            value: 70.63777081958187
          - type: manhattan_pearson
            value: 72.88892597106383
          - type: manhattan_spearman
            value: 70.86449280993048
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 81.41478503988436
          - type: cos_sim_spearman
            value: 81.94087130039843
          - type: euclidean_pearson
            value: 81.23351470401855
          - type: euclidean_spearman
            value: 81.43266713211875
          - type: manhattan_pearson
            value: 81.16667353510842
          - type: manhattan_spearman
            value: 81.24163241523068
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 75.08475719822
          - type: cos_sim_spearman
            value: 76.80438358515593
          - type: euclidean_pearson
            value: 75.90649123881406
          - type: euclidean_spearman
            value: 75.9482319164023
          - type: manhattan_pearson
            value: 75.64396465387331
          - type: manhattan_spearman
            value: 75.56185817375638
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (ko-ko)
          config: ko-ko
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 76.57756740555968
          - type: cos_sim_spearman
            value: 76.39843364267264
          - type: euclidean_pearson
            value: 75.40424583472578
          - type: euclidean_spearman
            value: 75.31307938562327
          - type: manhattan_pearson
            value: 74.73109587053861
          - type: manhattan_spearman
            value: 74.54667368714956
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (ar-ar)
          config: ar-ar
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 76.54105158056127
          - type: cos_sim_spearman
            value: 77.34104635434048
          - type: euclidean_pearson
            value: 75.28125389103582
          - type: euclidean_spearman
            value: 75.42418151345
          - type: manhattan_pearson
            value: 74.2691880967768
          - type: manhattan_spearman
            value: 74.14253657856801
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-ar)
          config: en-ar
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 77.02928931510961
          - type: cos_sim_spearman
            value: 77.45907270306685
          - type: euclidean_pearson
            value: 77.47937379735676
          - type: euclidean_spearman
            value: 77.21301895586583
          - type: manhattan_pearson
            value: 76.6676288138473
          - type: manhattan_spearman
            value: 76.7187203876331
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-de)
          config: en-de
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 79.85147526701459
          - type: cos_sim_spearman
            value: 80.24439450219447
          - type: euclidean_pearson
            value: 80.16905693851314
          - type: euclidean_spearman
            value: 79.30869641757035
          - type: manhattan_pearson
            value: 79.4830024429918
          - type: manhattan_spearman
            value: 78.64845690144578
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-en)
          config: en-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 85.23328074603815
          - type: cos_sim_spearman
            value: 86.18847213007086
          - type: euclidean_pearson
            value: 85.91331577309407
          - type: euclidean_spearman
            value: 85.89967500124904
          - type: manhattan_pearson
            value: 85.13857617716477
          - type: manhattan_spearman
            value: 84.82259586513993
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (en-tr)
          config: en-tr
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 75.38182956463326
          - type: cos_sim_spearman
            value: 74.34143229429068
          - type: euclidean_pearson
            value: 76.66151217728661
          - type: euclidean_spearman
            value: 75.68846427284615
          - type: manhattan_pearson
            value: 75.55942040372382
          - type: manhattan_spearman
            value: 74.67284614447757
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (es-en)
          config: es-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 76.94108940753875
          - type: cos_sim_spearman
            value: 77.39619379750977
          - type: euclidean_pearson
            value: 76.7736720732895
          - type: euclidean_spearman
            value: 76.29160645031078
          - type: manhattan_pearson
            value: 74.69337188827635
          - type: manhattan_spearman
            value: 74.47874230344613
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (es-es)
          config: es-es
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 83.99450399002905
          - type: cos_sim_spearman
            value: 83.71182297187157
          - type: euclidean_pearson
            value: 85.14304799861979
          - type: euclidean_spearman
            value: 83.69127569618827
          - type: manhattan_pearson
            value: 84.90116866712872
          - type: manhattan_spearman
            value: 83.31690582990805
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (fr-en)
          config: fr-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 79.12525161262887
          - type: cos_sim_spearman
            value: 79.27905944348255
          - type: euclidean_pearson
            value: 80.37847361563627
          - type: euclidean_spearman
            value: 79.45430583111714
          - type: manhattan_pearson
            value: 79.39311209355259
          - type: manhattan_spearman
            value: 78.35224091918822
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (it-en)
          config: it-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 80.35229136945712
          - type: cos_sim_spearman
            value: 80.82110464777067
          - type: euclidean_pearson
            value: 80.8820546236635
          - type: euclidean_spearman
            value: 80.52608029482144
          - type: manhattan_pearson
            value: 79.87881836256757
          - type: manhattan_spearman
            value: 79.21409642635105
      - task:
          type: STS
        dataset:
          type: mteb/sts17-crosslingual-sts
          name: MTEB STS17 (nl-en)
          config: nl-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 80.08711291606406
          - type: cos_sim_spearman
            value: 80.50747550174945
          - type: euclidean_pearson
            value: 80.19128295947303
          - type: euclidean_spearman
            value: 79.80068556328985
          - type: manhattan_pearson
            value: 79.2805531467
          - type: manhattan_spearman
            value: 78.67459586691882
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (en)
          config: en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 63.749476793187654
          - type: cos_sim_spearman
            value: 62.87618960301087
          - type: euclidean_pearson
            value: 62.00259194547161
          - type: euclidean_spearman
            value: 60.14134804263504
          - type: manhattan_pearson
            value: 61.85663435862556
          - type: manhattan_spearman
            value: 60.49194043559385
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (de)
          config: de
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 30.728588031668387
          - type: cos_sim_spearman
            value: 35.72910641917946
          - type: euclidean_pearson
            value: 27.727483814940634
          - type: euclidean_spearman
            value: 36.697908777201874
          - type: manhattan_pearson
            value: 26.887457740598375
          - type: manhattan_spearman
            value: 35.65193589164902
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (es)
          config: es
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 58.515732517017895
          - type: cos_sim_spearman
            value: 59.34352724163223
          - type: euclidean_pearson
            value: 59.37822334487575
          - type: euclidean_spearman
            value: 59.952966536792296
          - type: manhattan_pearson
            value: 59.34905346132589
          - type: manhattan_spearman
            value: 59.58363163864109
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (pl)
          config: pl
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 26.73251862968695
          - type: cos_sim_spearman
            value: 34.57702083368428
          - type: euclidean_pearson
            value: 11.555722679629111
          - type: euclidean_spearman
            value: 33.83302978677857
          - type: manhattan_pearson
            value: 11.30958607896797
          - type: manhattan_spearman
            value: 33.45113736058396
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (tr)
          config: tr
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 50.59069907623683
          - type: cos_sim_spearman
            value: 54.07437321160808
          - type: euclidean_pearson
            value: 55.31327716542195
          - type: euclidean_spearman
            value: 55.862881519289
          - type: manhattan_pearson
            value: 55.76874086920313
          - type: manhattan_spearman
            value: 56.389207939925434
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (ar)
          config: ar
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 43.19525519197726
          - type: cos_sim_spearman
            value: 49.04013064287781
          - type: euclidean_pearson
            value: 41.51101650799975
          - type: euclidean_spearman
            value: 45.69491981920255
          - type: manhattan_pearson
            value: 41.798306097489686
          - type: manhattan_spearman
            value: 45.88969916327865
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (ru)
          config: ru
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 46.72887212606245
          - type: cos_sim_spearman
            value: 52.40251410115027
          - type: euclidean_pearson
            value: 42.61087105318375
          - type: euclidean_spearman
            value: 49.31647979068464
          - type: manhattan_pearson
            value: 41.971488569524226
          - type: manhattan_spearman
            value: 48.603948080104416
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (zh)
          config: zh
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 50.282899703556204
          - type: cos_sim_spearman
            value: 54.31518993723914
          - type: euclidean_pearson
            value: 46.92686134587321
          - type: euclidean_spearman
            value: 50.4258942374202
          - type: manhattan_pearson
            value: 47.119373335384516
          - type: manhattan_spearman
            value: 50.290545214030644
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (fr)
          config: fr
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 76.6695578258507
          - type: cos_sim_spearman
            value: 76.41254265129491
          - type: euclidean_pearson
            value: 68.10573760855496
          - type: euclidean_spearman
            value: 71.53756176277794
          - type: manhattan_pearson
            value: 67.71247571269289
          - type: manhattan_spearman
            value: 71.52537846395397
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (de-en)
          config: de-en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 52.39033873441029
          - type: cos_sim_spearman
            value: 47.50888019756861
          - type: euclidean_pearson
            value: 54.09329593694967
          - type: euclidean_spearman
            value: 46.745911343795036
          - type: manhattan_pearson
            value: 55.071517962875795
          - type: manhattan_spearman
            value: 47.82505012490346
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (es-en)
          config: es-en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 66.22856680218524
          - type: cos_sim_spearman
            value: 68.9583551854743
          - type: euclidean_pearson
            value: 69.45990476537347
          - type: euclidean_spearman
            value: 69.51326488176926
          - type: manhattan_pearson
            value: 69.2654378415376
          - type: manhattan_spearman
            value: 69.25549968332008
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (it)
          config: it
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 63.86370050619784
          - type: cos_sim_spearman
            value: 65.10152541505573
          - type: euclidean_pearson
            value: 61.23738658178195
          - type: euclidean_spearman
            value: 62.77231926242124
          - type: manhattan_pearson
            value: 61.20141239111747
          - type: manhattan_spearman
            value: 62.58683030963466
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (pl-en)
          config: pl-en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 70.24310112698741
          - type: cos_sim_spearman
            value: 71.32608389737901
          - type: euclidean_pearson
            value: 69.53167907457565
          - type: euclidean_spearman
            value: 69.24756304760876
          - type: manhattan_pearson
            value: 69.4432001214127
          - type: manhattan_spearman
            value: 69.92998467998946
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (zh-en)
          config: zh-en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 62.96457033320131
          - type: cos_sim_spearman
            value: 61.750627475845285
          - type: euclidean_pearson
            value: 59.58377101704754
          - type: euclidean_spearman
            value: 55.91175172327044
          - type: manhattan_pearson
            value: 59.64672089274813
          - type: manhattan_spearman
            value: 55.93114256617111
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (es-it)
          config: es-it
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 60.54093974085284
          - type: cos_sim_spearman
            value: 63.277246213501634
          - type: euclidean_pearson
            value: 59.21790717375445
          - type: euclidean_spearman
            value: 60.77632900198518
          - type: manhattan_pearson
            value: 59.572573245502824
          - type: manhattan_spearman
            value: 60.86391917522135
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (de-fr)
          config: de-fr
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 56.2735220514599
          - type: cos_sim_spearman
            value: 60.76242915296164
          - type: euclidean_pearson
            value: 54.73358313453174
          - type: euclidean_spearman
            value: 59.01153256838316
          - type: manhattan_pearson
            value: 53.30971466711619
          - type: manhattan_spearman
            value: 57.427602926148516
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (de-pl)
          config: de-pl
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 33.210422466959244
          - type: cos_sim_spearman
            value: 36.09068930156353
          - type: euclidean_pearson
            value: 36.72425141682268
          - type: euclidean_spearman
            value: 33.3808081935963
          - type: manhattan_pearson
            value: 35.47249118003641
          - type: manhattan_spearman
            value: 31.964279432613434
      - task:
          type: STS
        dataset:
          type: mteb/sts22-crosslingual-sts
          name: MTEB STS22 (fr-pl)
          config: fr-pl
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 62.721710627517034
          - type: cos_sim_spearman
            value: 61.97797868009122
          - type: euclidean_pearson
            value: 63.59898515445168
          - type: euclidean_spearman
            value: 84.51542547285167
          - type: manhattan_pearson
            value: 62.15380605376377
          - type: manhattan_spearman
            value: 73.24670207647144
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 81.6839488629375
          - type: cos_sim_spearman
            value: 80.75478754676419
          - type: euclidean_pearson
            value: 80.67588249670365
          - type: euclidean_spearman
            value: 80.2296669116562
          - type: manhattan_pearson
            value: 79.79275882752755
          - type: manhattan_spearman
            value: 79.41562131296504
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 69.21586199162861
          - type: mrr
            value: 88.86282290694054
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.62079207920792
          - type: cos_sim_ap
            value: 87.14976457350163
          - type: cos_sim_f1
            value: 81.07317073170732
          - type: cos_sim_precision
            value: 79.14285714285715
          - type: cos_sim_recall
            value: 83.1
          - type: dot_accuracy
            value: 99.57722772277228
          - type: dot_ap
            value: 84.07833605976549
          - type: dot_f1
            value: 77.88461538461539
          - type: dot_precision
            value: 75
          - type: dot_recall
            value: 81
          - type: euclidean_accuracy
            value: 99.61287128712871
          - type: euclidean_ap
            value: 86.94165408325189
          - type: euclidean_f1
            value: 80.33596837944663
          - type: euclidean_precision
            value: 79.39453125
          - type: euclidean_recall
            value: 81.3
          - type: manhattan_accuracy
            value: 99.64653465346535
          - type: manhattan_ap
            value: 88.43495903247096
          - type: manhattan_f1
            value: 81.7193675889328
          - type: manhattan_precision
            value: 80.76171875
          - type: manhattan_recall
            value: 82.69999999999999
          - type: max_accuracy
            value: 99.64653465346535
          - type: max_ap
            value: 88.43495903247096
          - type: max_f1
            value: 81.7193675889328
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 41.92031499253617
          - type: mrr
            value: 42.11711389101095
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 69.0936
          - type: ap
            value: 13.464419132094955
          - type: f1
            value: 53.17756829624628
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 59.968873797396704
          - type: f1
            value: 60.23697658216021
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 82.7978780473267
          - type: cos_sim_ap
            value: 61.669291081213906
          - type: cos_sim_f1
            value: 57.68693665100927
          - type: cos_sim_precision
            value: 55.59089796917054
          - type: cos_sim_recall
            value: 59.94722955145119
          - type: dot_accuracy
            value: 81.68921738093819
          - type: dot_ap
            value: 57.39705387908134
          - type: dot_f1
            value: 54.72479298587434
          - type: dot_precision
            value: 50.814111261872455
          - type: dot_recall
            value: 59.287598944591025
          - type: euclidean_accuracy
            value: 82.85152291828098
          - type: euclidean_ap
            value: 62.456817170822255
          - type: euclidean_f1
            value: 58.32305795314425
          - type: euclidean_precision
            value: 54.745370370370374
          - type: euclidean_recall
            value: 62.401055408970976
          - type: manhattan_accuracy
            value: 82.76807534124099
          - type: manhattan_ap
            value: 61.85267667234618
          - type: manhattan_f1
            value: 57.62629336579428
          - type: manhattan_precision
            value: 53.49152542372882
          - type: manhattan_recall
            value: 62.45382585751978
          - type: max_accuracy
            value: 82.85152291828098
          - type: max_ap
            value: 62.456817170822255
          - type: max_f1
            value: 58.32305795314425
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.03896456708192
          - type: cos_sim_ap
            value: 84.0249558879327
          - type: cos_sim_f1
            value: 76.26290458870642
          - type: cos_sim_precision
            value: 72.93233082706767
          - type: cos_sim_recall
            value: 79.91222667077302
          - type: dot_accuracy
            value: 87.87402491558971
          - type: dot_ap
            value: 83.20076543059169
          - type: dot_f1
            value: 76.02826329490517
          - type: dot_precision
            value: 73.52898863472882
          - type: dot_recall
            value: 78.70341854019095
          - type: euclidean_accuracy
            value: 87.96328637404433
          - type: euclidean_ap
            value: 83.78378095020464
          - type: euclidean_f1
            value: 75.94917787742901
          - type: euclidean_precision
            value: 73.78739471391229
          - type: euclidean_recall
            value: 78.24145364952264
          - type: manhattan_accuracy
            value: 87.99239337136648
          - type: manhattan_ap
            value: 83.72045889779073
          - type: manhattan_f1
            value: 75.93527315914488
          - type: manhattan_precision
            value: 73.30180567497851
          - type: manhattan_recall
            value: 78.76501385894672
          - type: max_accuracy
            value: 88.03896456708192
          - type: max_ap
            value: 84.0249558879327
          - type: max_f1
            value: 76.26290458870642

sentence-transformers/distiluse-base-multilingual-cased-v2

This is a sentence-transformers model: It maps sentences & paragraphs to a 512 dimensional dense vector space and can be used for tasks like clustering or semantic search.

Usage (Sentence-Transformers)

Using this model becomes easy when you have sentence-transformers installed:

pip install -U sentence-transformers

Then you can use the model like this:

from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('sentence-transformers/distiluse-base-multilingual-cased-v2')
embeddings = model.encode(sentences)
print(embeddings)

Evaluation Results

For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: DistilBertModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
  (2): Dense({'in_features': 768, 'out_features': 512, 'bias': True, 'activation_function': 'torch.nn.modules.activation.Tanh'})
)

Citing & Authors

This model was trained by sentence-transformers.

If you find this model helpful, feel free to cite our publication Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks:

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}