---
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
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (mn)
      config: mn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 40.36650975117687
    - type: f1
      value: 36.405182949755556
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ms)
      config: ms
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 47.969065232010756
    - type: f1
      value: 43.564724873023735
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (my)
      config: my
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 38.483523873570945
    - type: f1
      value: 33.325537301233815
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (nb)
      config: nb
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 46.008742434431745
    - type: f1
      value: 43.1074675107609
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (nl)
      config: nl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.29186281102891
    - type: f1
      value: 53.383269502572276
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (pl)
      config: pl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 53.10020174848689
    - type: f1
      value: 48.491009241597
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (pt)
      config: pt
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.62811028917283
    - type: f1
      value: 56.39037901287144
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ro)
      config: ro
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 50.632145258910555
    - type: f1
      value: 47.52272047301657
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ru)
      config: ru
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 57.95897780766644
    - type: f1
      value: 53.79707075942384
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (sl)
      config: sl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 50.65904505716207
    - type: f1
      value: 48.69839976207718
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (sq)
      config: sq
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 50.25218560860794
    - type: f1
      value: 46.925456055473525
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (sv)
      config: sv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 52.410894418291875
    - type: f1
      value: 47.64228703598475
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (sw)
      config: sw
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 19.293880295897782
    - type: f1
      value: 17.66502971829105
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ta)
      config: ta
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 3.7861466039004705
    - type: f1
      value: 1.2869466371674323
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (te)
      config: te
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 3.3591123066577
    - type: f1
      value: 1.3191646312270082
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (th)
      config: th
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 45.279085406859444
    - type: f1
      value: 42.5424265903176
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (tl)
      config: tl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 28.43981170141224
    - type: f1
      value: 25.283226291015392
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (tr)
      config: tr
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 50.474108944182916
    - type: f1
      value: 47.186574797430794
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (ur)
      config: ur
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 46.02891728312038
    - type: f1
      value: 41.42008348263186
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (vi)
      config: vi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 45.252185608607945
    - type: f1
      value: 41.69045540062304
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (zh-CN)
      config: zh-CN
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 59.21990585070611
    - type: f1
      value: 56.214011316092495
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (zh-TW)
      config: zh-TW
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 54.96301277740416
    - type: f1
      value: 53.020268356293045
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (af)
      config: af
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 53.665097511768664
    - type: f1
      value: 48.81662825721646
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (am)
      config: am
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 7.720242098184263
    - type: f1
      value: 3.0172360162047553
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ar)
      config: ar
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 52.188971082716876
    - type: f1
      value: 52.360668734058116
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (az)
      config: az
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 34.74781439139206
    - type: f1
      value: 32.55953852645334
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (bn)
      config: bn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 10.652320107599191
    - type: f1
      value: 6.439785272600618
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (cy)
      config: cy
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 21.237390719569603
    - type: f1
      value: 18.428497244325158
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (da)
      config: da
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 62.54875588433087
    - type: f1
      value: 60.69001958508912
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (de)
      config: de
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 61.40215198386013
    - type: f1
      value: 58.07492599013545
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (el)
      config: el
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 60.67585743106927
    - type: f1
      value: 58.055827627792056
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 74.00470746469401
    - type: f1
      value: 72.22931856264793
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (es)
      config: es
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.6133154001345
    - type: f1
      value: 63.345907502958184
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (fa)
      config: fa
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 59.2434431741762
    - type: f1
      value: 57.40580117369346
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (fi)
      config: fi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 54.660390047074635
    - type: f1
      value: 51.45432689446743
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (fr)
      config: fr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.19502353732346
    - type: f1
      value: 63.50200684075783
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (he)
      config: he
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 54.744451916610636
    - type: f1
      value: 52.621508448089294
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (hi)
      config: hi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 55.985205110961665
    - type: f1
      value: 53.70079438430524
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (hu)
      config: hu
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 61.20040349697378
    - type: f1
      value: 58.5060672562612
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (hy)
      config: hy
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 49.63349024882314
    - type: f1
      value: 47.39478501763526
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (id)
      config: id
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.25218560860793
    - type: f1
      value: 63.45266636240826
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (is)
      config: is
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 22.599193006052456
    - type: f1
      value: 21.93829297740852
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (it)
      config: it
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.63349024882314
    - type: f1
      value: 63.15345402734339
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ja)
      config: ja
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 62.32010759919301
    - type: f1
      value: 60.02914271738089
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (jv)
      config: jv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 35.76664425016812
    - type: f1
      value: 33.52830525064859
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ka)
      config: ka
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 39.08204438466712
    - type: f1
      value: 37.312566552928736
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (km)
      config: km
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 9.236718224613314
    - type: f1
      value: 3.41684484979606
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (kn)
      config: kn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 8.278412911903162
    - type: f1
      value: 3.9418094806677426
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ko)
      config: ko
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 57.595830531271005
    - type: f1
      value: 56.42188880877947
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (lv)
      config: lv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 51.72158708809683
    - type: f1
      value: 49.903136843275256
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ml)
      config: ml
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 8.254875588433089
    - type: f1
      value: 4.06813409809564
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (mn)
      config: mn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 47.20914593140552
    - type: f1
      value: 44.780121017940225
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ms)
      config: ms
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 55.64559515803632
    - type: f1
      value: 53.10457083056076
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (my)
      config: my
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 43.308675184936114
    - type: f1
      value: 40.40654924373442
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (nb)
      config: nb
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 54.983187626092814
    - type: f1
      value: 54.22408282419106
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (nl)
      config: nl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.4915938130464
    - type: f1
      value: 64.66608521628295
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (pl)
      config: pl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 61.28782784129119
    - type: f1
      value: 59.364955179296544
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (pt)
      config: pt
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.26361802286483
    - type: f1
      value: 63.01306314842478
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (ro)
      config: ro
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 58.02622730329523
    - type: f1
      value: 55.8928740774695
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      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: 75.0
    - type: dot_recall
      value: 81.0
    - 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](https://www.SBERT.net) 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](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
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](https://seb.sbert.net?model_name=sentence-transformers/distiluse-base-multilingual-cased-v2)



## 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](https://www.sbert.net/). 
        
If you find this model helpful, feel free to cite our publication [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://arxiv.org/abs/1908.10084):
```bibtex 
@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",
}
```