Gitee AI
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元数据

tags:
- feature-extraction
- sentence-similarity
- sentence-transformers
- transformers
- mteb
license: gemma
model-index:
- name: bge-multilingual-gemma2
  results:
  - task:
      type: Retrieval
    dataset:
      type: mteb/nfcorpus
      name: MTEB NFCorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: main_score
      value: 38.11433513284057
    - type: ndcg_at_1
      value: 48.45201238390093
    - type: ndcg_at_3
      value: 44.451438575534574
    - type: ndcg_at_5
      value: 41.13929990797894
    - type: ndcg_at_10
      value: 38.11433513284057
    - type: ndcg_at_100
      value: 35.36065387898559
    - type: ndcg_at_1000
      value: 44.01125752781003
    - type: map_at_1
      value: 5.638004398054564
    - type: map_at_3
      value: 10.375632572339333
    - type: map_at_5
      value: 11.820531148202422
    - type: map_at_10
      value: 14.087436978063389
    - type: map_at_100
      value: 18.25397463114958
    - type: map_at_1000
      value: 19.868440221606203
    - type: precision_at_1
      value: 49.84520123839009
    - type: precision_at_3
      value: 41.89886480908153
    - type: precision_at_5
      value: 35.356037151702814
    - type: precision_at_10
      value: 28.513931888544857
    - type: precision_at_100
      value: 9.337461300309604
    - type: precision_at_1000
      value: 2.210216718266251
    - type: recall_at_1
      value: 5.638004398054564
    - type: recall_at_3
      value: 11.938154656310312
    - type: recall_at_5
      value: 14.06183119422843
    - type: recall_at_10
      value: 18.506397834147705
    - type: recall_at_100
      value: 35.96995569451433
    - type: recall_at_1000
      value: 68.31771509404795
  - task:
      type: Retrieval
    dataset:
      type: mteb/msmarco
      name: MTEB MSMARCO
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: main_score
      value: 45.70688915742828
    - type: ndcg_at_1
      value: 26.002865329512893
    - type: ndcg_at_3
      value: 37.49665652114275
    - type: ndcg_at_5
      value: 41.684045067615834
    - type: ndcg_at_10
      value: 45.70688915742828
    - type: ndcg_at_100
      value: 51.08932609519671
    - type: ndcg_at_1000
      value: 51.98806137292924
    - type: map_at_1
      value: 25.35219675262655
    - type: map_at_3
      value: 34.39549506526583
    - type: map_at_5
      value: 36.74936326010824
    - type: map_at_10
      value: 38.44429852488596
    - type: map_at_100
      value: 39.60260286311527
    - type: map_at_1000
      value: 39.64076154054021
    - type: precision_at_1
      value: 26.002865329512893
    - type: precision_at_3
      value: 15.840496657115954
    - type: precision_at_5
      value: 11.647564469914684
    - type: precision_at_10
      value: 7.1275071633243705
    - type: precision_at_100
      value: 0.9782234957019871
    - type: precision_at_1000
      value: 0.10565902578797497
    - type: recall_at_1
      value: 25.35219675262655
    - type: recall_at_3
      value: 45.78438395415474
    - type: recall_at_5
      value: 55.83213944603631
    - type: recall_at_10
      value: 68.08500477554918
    - type: recall_at_100
      value: 92.55133715377269
    - type: recall_at_1000
      value: 99.29083094555875
  - task:
      type: Retrieval
    dataset:
      type: mteb/fiqa
      name: MTEB FiQA2018
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: main_score
      value: 60.04205769404706
    - type: ndcg_at_1
      value: 59.25925925925925
    - type: ndcg_at_3
      value: 55.96637679199298
    - type: ndcg_at_5
      value: 56.937223390223956
    - type: ndcg_at_10
      value: 60.04205769404706
    - type: ndcg_at_100
      value: 66.01619664462949
    - type: ndcg_at_1000
      value: 67.59651529720728
    - type: map_at_1
      value: 31.5081163692275
    - type: map_at_3
      value: 45.7486689836227
    - type: map_at_5
      value: 48.944906602314
    - type: map_at_10
      value: 51.85427043799874
    - type: map_at_100
      value: 53.92920237379484
    - type: map_at_1000
      value: 54.04694438963671
    - type: precision_at_1
      value: 59.25925925925925
    - type: precision_at_3
      value: 37.44855967078195
    - type: precision_at_5
      value: 26.913580246913547
    - type: precision_at_10
      value: 16.52777777777774
    - type: precision_at_100
      value: 2.2962962962962754
    - type: precision_at_1000
      value: 0.2566358024691334
    - type: recall_at_1
      value: 31.5081163692275
    - type: recall_at_3
      value: 50.71759045138676
    - type: recall_at_5
      value: 57.49321152098932
    - type: recall_at_10
      value: 67.36356750245642
    - type: recall_at_100
      value: 88.67335767798735
    - type: recall_at_1000
      value: 97.83069725199356
  - task:
      type: Retrieval
    dataset:
      type: mteb/scidocs
      name: MTEB SCIDOCS
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: main_score
      value: 26.93150756480961
    - type: ndcg_at_1
      value: 30.8
    - type: ndcg_at_3
      value: 25.048085553386628
    - type: ndcg_at_5
      value: 22.351207380852305
    - type: ndcg_at_10
      value: 26.93150756480961
    - type: ndcg_at_100
      value: 37.965486832874014
    - type: ndcg_at_1000
      value: 43.346046425140244
    - type: map_at_1
      value: 6.238333333333366
    - type: map_at_3
      value: 11.479166666666679
    - type: map_at_5
      value: 14.215999999999983
    - type: map_at_10
      value: 16.774632936507945
    - type: map_at_100
      value: 20.148869158557293
    - type: map_at_1000
      value: 20.528644104490823
    - type: precision_at_1
      value: 30.8
    - type: precision_at_3
      value: 23.466666666666736
    - type: precision_at_5
      value: 19.899999999999967
    - type: precision_at_10
      value: 14.069999999999938
    - type: precision_at_100
      value: 2.9770000000000065
    - type: precision_at_1000
      value: 0.42569999999999486
    - type: recall_at_1
      value: 6.238333333333366
    - type: recall_at_3
      value: 14.29333333333338
    - type: recall_at_5
      value: 20.206666666666628
    - type: recall_at_10
      value: 28.573333333333224
    - type: recall_at_100
      value: 60.43666666666675
    - type: recall_at_1000
      value: 86.3649999999997
  - task:
      type: Retrieval
    dataset:
      type: mteb/fever
      name: MTEB FEVER
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: main_score
      value: 90.38165339181239
    - type: ndcg_at_1
      value: 84.86348634863486
    - type: ndcg_at_3
      value: 88.98667069230609
    - type: ndcg_at_5
      value: 89.86028996734895
    - type: ndcg_at_10
      value: 90.38165339181239
    - type: ndcg_at_100
      value: 90.99655378684439
    - type: ndcg_at_1000
      value: 91.15536362599602
    - type: map_at_1
      value: 78.8556296105801
    - type: map_at_3
      value: 86.24061810942983
    - type: map_at_5
      value: 86.94776680048933
    - type: map_at_10
      value: 87.26956235873007
    - type: map_at_100
      value: 87.47986397174834
    - type: map_at_1000
      value: 87.4897076664281
    - type: precision_at_1
      value: 84.86348634863486
    - type: precision_at_3
      value: 34.02340234023296
    - type: precision_at_5
      value: 21.10411041104359
    - type: precision_at_10
      value: 10.828082808282083
    - type: precision_at_100
      value: 1.1381638163816703
    - type: precision_at_1000
      value: 0.11662166216622569
    - type: recall_at_1
      value: 78.8556296105801
    - type: recall_at_3
      value: 92.34465708475605
    - type: recall_at_5
      value: 94.58010682020583
    - type: recall_at_10
      value: 96.10713452297611
    - type: recall_at_100
      value: 98.31672452959585
    - type: recall_at_1000
      value: 99.25967001462051
  - task:
      type: Retrieval
    dataset:
      type: mteb/arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: main_score
      value: 77.36555747844541
    - type: ndcg_at_1
      value: 57.681365576102415
    - type: ndcg_at_3
      value: 72.01664798084765
    - type: ndcg_at_5
      value: 75.26345973082836
    - type: ndcg_at_10
      value: 77.36555747844541
    - type: ndcg_at_100
      value: 78.15567833673768
    - type: ndcg_at_1000
      value: 78.16528851292641
    - type: map_at_1
      value: 57.681365576102415
    - type: map_at_3
      value: 68.59886201991475
    - type: map_at_5
      value: 70.38051209103858
    - type: map_at_10
      value: 71.26684955632336
    - type: map_at_100
      value: 71.4637216600468
    - type: map_at_1000
      value: 71.46414501573332
    - type: precision_at_1
      value: 57.681365576102415
    - type: precision_at_3
      value: 27.287814129919084
    - type: precision_at_5
      value: 17.965860597439132
    - type: precision_at_10
      value: 9.623044096728066
    - type: precision_at_100
      value: 0.995732574679925
    - type: precision_at_1000
      value: 0.09964438122332549
    - type: recall_at_1
      value: 57.681365576102415
    - type: recall_at_3
      value: 81.86344238975818
    - type: recall_at_5
      value: 89.82930298719772
    - type: recall_at_10
      value: 96.23044096728307
    - type: recall_at_100
      value: 99.57325746799431
    - type: recall_at_1000
      value: 99.6443812233286
  - task:
      type: Retrieval
    dataset:
      type: mteb/scifact
      name: MTEB SciFact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 72.0465439956427
    - type: ndcg_at_1
      value: 58.666666666666664
    - type: ndcg_at_3
      value: 66.84566274610046
    - type: ndcg_at_5
      value: 69.46578881873717
    - type: ndcg_at_10
      value: 72.0465439956427
    - type: ndcg_at_100
      value: 74.25705461923272
    - type: ndcg_at_1000
      value: 74.63689058493014
    - type: map_at_1
      value: 55.59444444444445
    - type: map_at_3
      value: 63.71851851851852
    - type: map_at_5
      value: 65.5362962962963
    - type: map_at_10
      value: 66.84112433862435
    - type: map_at_100
      value: 67.36269426417417
    - type: map_at_1000
      value: 67.37568665562833
    - type: precision_at_1
      value: 58.666666666666664
    - type: precision_at_3
      value: 26.444444444444425
    - type: precision_at_5
      value: 17.66666666666672
    - type: precision_at_10
      value: 9.866666666666706
    - type: precision_at_100
      value: 1.0966666666666596
    - type: precision_at_1000
      value: 0.11266666666666675
    - type: recall_at_1
      value: 55.59444444444445
    - type: recall_at_3
      value: 72.72777777777777
    - type: recall_at_5
      value: 79.31666666666666
    - type: recall_at_10
      value: 86.75
    - type: recall_at_100
      value: 96.66666666666667
    - type: recall_at_1000
      value: 99.66666666666667
  - task:
      type: Retrieval
    dataset:
      type: mteb/trec-covid
      name: MTEB TRECCOVID
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: main_score
      value: 64.26928884606035
    - type: ndcg_at_1
      value: 63.0
    - type: ndcg_at_3
      value: 64.18432764386345
    - type: ndcg_at_5
      value: 64.73235515799435
    - type: ndcg_at_10
      value: 64.26928884606035
    - type: ndcg_at_100
      value: 52.39807133285409
    - type: ndcg_at_1000
      value: 52.19937563361241
    - type: map_at_1
      value: 0.18483494997310454
    - type: map_at_3
      value: 0.5139705769331114
    - type: map_at_5
      value: 0.8245601222717243
    - type: map_at_10
      value: 1.5832530269558573
    - type: map_at_100
      value: 9.664760850102393
    - type: map_at_1000
      value: 25.568347406468334
    - type: precision_at_1
      value: 70.0
    - type: precision_at_3
      value: 71.33333333333333
    - type: precision_at_5
      value: 71.60000000000001
    - type: precision_at_10
      value: 70.99999999999996
    - type: precision_at_100
      value: 55.140000000000015
    - type: precision_at_1000
      value: 23.857999999999997
    - type: recall_at_1
      value: 0.18483494997310454
    - type: recall_at_3
      value: 0.5584287301859913
    - type: recall_at_5
      value: 0.9489025953807098
    - type: recall_at_10
      value: 1.9023711039425688
    - type: recall_at_100
      value: 13.596810701594226
    - type: recall_at_1000
      value: 50.92058432920189
  - task:
      type: Retrieval
    dataset:
      type: mteb/climate-fever
      name: MTEB ClimateFEVER
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: main_score
      value: 39.37204193531481
    - type: ndcg_at_1
      value: 35.11400651465798
    - type: ndcg_at_3
      value: 32.36672790229743
    - type: ndcg_at_5
      value: 34.79369234162357
    - type: ndcg_at_10
      value: 39.37204193531481
    - type: ndcg_at_100
      value: 47.544500439419124
    - type: ndcg_at_1000
      value: 50.305733346049855
    - type: map_at_1
      value: 15.516829533116216
    - type: map_at_3
      value: 23.73669923995656
    - type: map_at_5
      value: 26.43208469055373
    - type: map_at_10
      value: 28.912036175309773
    - type: map_at_100
      value: 31.413762299240894
    - type: map_at_1000
      value: 31.596796093997014
    - type: precision_at_1
      value: 35.11400651465798
    - type: precision_at_3
      value: 24.994571118349487
    - type: precision_at_5
      value: 19.231270358305956
    - type: precision_at_10
      value: 12.690553745928165
    - type: precision_at_100
      value: 2.1576547231270466
    - type: precision_at_1000
      value: 0.2676221498371306
    - type: recall_at_1
      value: 15.516829533116216
    - type: recall_at_3
      value: 29.994571118349512
    - type: recall_at_5
      value: 37.14223669923993
    - type: recall_at_10
      value: 47.29207383279043
    - type: recall_at_100
      value: 74.37133550488598
    - type: recall_at_1000
      value: 89.41585233441913
  - task:
      type: Retrieval
    dataset:
      type: mteb/hotpotqa
      name: MTEB HotpotQA
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: main_score
      value: 83.26282954330777
    - type: ndcg_at_1
      value: 87.5489534098582
    - type: ndcg_at_3
      value: 78.7646435855166
    - type: ndcg_at_5
      value: 81.41629077444277
    - type: ndcg_at_10
      value: 83.26282954330777
    - type: ndcg_at_100
      value: 85.2771369900158
    - type: ndcg_at_1000
      value: 85.77519303747493
    - type: map_at_1
      value: 43.7744767049291
    - type: map_at_3
      value: 73.4661264911093
    - type: map_at_5
      value: 75.7169705154168
    - type: map_at_10
      value: 76.89183627536043
    - type: map_at_100
      value: 77.53680315727078
    - type: map_at_1000
      value: 77.5649311522075
    - type: precision_at_1
      value: 87.5489534098582
    - type: precision_at_3
      value: 51.74881836596788
    - type: precision_at_5
      value: 33.13977042539127
    - type: precision_at_10
      value: 17.492234976369023
    - type: precision_at_100
      value: 1.9030384875084312
    - type: precision_at_1000
      value: 0.19679945982446267
    - type: recall_at_1
      value: 43.7744767049291
    - type: recall_at_3
      value: 77.62322754895341
    - type: recall_at_5
      value: 82.84942606347063
    - type: recall_at_10
      value: 87.4611748818366
    - type: recall_at_100
      value: 95.15192437542201
    - type: recall_at_1000
      value: 98.39972991222147
  - task:
      type: Retrieval
    dataset:
      type: mteb/nq
      name: MTEB NQ
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: main_score
      value: 71.44670934705796
    - type: ndcg_at_1
      value: 54.026651216685984
    - type: ndcg_at_3
      value: 65.1267452491225
    - type: ndcg_at_5
      value: 68.6696802020747
    - type: ndcg_at_10
      value: 71.44670934705796
    - type: ndcg_at_100
      value: 73.74642927386503
    - type: ndcg_at_1000
      value: 73.90908268307331
    - type: map_at_1
      value: 48.50086906141366
    - type: map_at_3
      value: 61.07691193510995
    - type: map_at_5
      value: 63.36580243337187
    - type: map_at_10
      value: 64.74485498782997
    - type: map_at_100
      value: 65.34329174534082
    - type: map_at_1000
      value: 65.35107870745652
    - type: precision_at_1
      value: 54.026651216685984
    - type: precision_at_3
      value: 28.437620702974996
    - type: precision_at_5
      value: 19.20625724217861
    - type: precision_at_10
      value: 10.67207415990753
    - type: precision_at_100
      value: 1.1987253765932955
    - type: precision_at_1000
      value: 0.12143684820393259
    - type: recall_at_1
      value: 48.50086906141366
    - type: recall_at_3
      value: 73.19428350714561
    - type: recall_at_5
      value: 81.19689069138664
    - type: recall_at_10
      value: 89.04741212823485
    - type: recall_at_100
      value: 98.58053302433372
    - type: recall_at_1000
      value: 99.75376593279258
  - task:
      type: Retrieval
    dataset:
      type: mteb/quora
      name: MTEB QuoraRetrieval
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: main_score
      value: 90.03760323006117
    - type: ndcg_at_1
      value: 83.53
    - type: ndcg_at_3
      value: 87.53800795646302
    - type: ndcg_at_5
      value: 88.92909168525203
    - type: ndcg_at_10
      value: 90.03760323006117
    - type: ndcg_at_100
      value: 91.08558507332712
    - type: ndcg_at_1000
      value: 91.1430039358834
    - type: map_at_1
      value: 72.61760432018744
    - type: map_at_3
      value: 83.8457060028347
    - type: map_at_5
      value: 85.6228412692169
    - type: map_at_10
      value: 86.67700531365115
    - type: map_at_100
      value: 87.29851728827602
    - type: map_at_1000
      value: 87.31014621733333
    - type: precision_at_1
      value: 83.53
    - type: precision_at_3
      value: 38.33666666667159
    - type: precision_at_5
      value: 25.12599999999881
    - type: precision_at_10
      value: 13.629999999998683
    - type: precision_at_100
      value: 1.5431999999999773
    - type: precision_at_1000
      value: 0.15671999999997974
    - type: recall_at_1
      value: 72.61760432018744
    - type: recall_at_3
      value: 89.06736052932686
    - type: recall_at_5
      value: 93.09634203522849
    - type: recall_at_10
      value: 96.35128012894234
    - type: recall_at_100
      value: 99.7740237858541
    - type: recall_at_1000
      value: 99.99690476190477
  - task:
      type: Retrieval
    dataset:
      type: mteb/webis-touche2020
      name: MTEB Touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: main_score
      value: 30.2563523019649
    - type: ndcg_at_1
      value: 37.755102040816325
    - type: ndcg_at_3
      value: 34.45349994459905
    - type: ndcg_at_5
      value: 32.508805919063086
    - type: ndcg_at_10
      value: 30.2563523019649
    - type: ndcg_at_100
      value: 40.538336664503746
    - type: ndcg_at_1000
      value: 52.2066951614923
    - type: map_at_1
      value: 2.75537988273998
    - type: map_at_3
      value: 6.011397290504469
    - type: map_at_5
      value: 8.666495836494098
    - type: map_at_10
      value: 12.17701515007822
    - type: map_at_100
      value: 18.789086471205852
    - type: map_at_1000
      value: 20.42972375502502
    - type: precision_at_1
      value: 40.816326530612244
    - type: precision_at_3
      value: 35.37414965986394
    - type: precision_at_5
      value: 32.244897959183675
    - type: precision_at_10
      value: 26.93877551020408
    - type: precision_at_100
      value: 8.163265306122451
    - type: precision_at_1000
      value: 1.5979591836734703
    - type: recall_at_1
      value: 2.75537988273998
    - type: recall_at_3
      value: 7.254270324385098
    - type: recall_at_5
      value: 11.580137100328589
    - type: recall_at_10
      value: 18.745232816450553
    - type: recall_at_100
      value: 50.196809658622755
    - type: recall_at_1000
      value: 85.87317364148332
  - task:
      type: Retrieval
    dataset:
      type: mteb/dbpedia
      name: MTEB DBPedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: main_score
      value: 51.36940792375597
    - type: ndcg_at_1
      value: 65.125
    - type: ndcg_at_3
      value: 55.3967569049025
    - type: ndcg_at_5
      value: 53.09668587926677
    - type: ndcg_at_10
      value: 51.36940792375597
    - type: ndcg_at_100
      value: 56.69623269243084
    - type: ndcg_at_1000
      value: 63.481061270842
    - type: map_at_1
      value: 10.265595545755545
    - type: map_at_3
      value: 16.776544233350698
    - type: map_at_5
      value: 20.184523605272798
    - type: map_at_10
      value: 24.772797659849264
    - type: map_at_100
      value: 36.72689012514183
    - type: map_at_1000
      value: 38.73869985105569
    - type: precision_at_1
      value: 77.5
    - type: precision_at_3
      value: 59.75000000000003
    - type: precision_at_5
      value: 52.849999999999994
    - type: precision_at_10
      value: 42.47499999999995
    - type: precision_at_100
      value: 13.614999999999993
    - type: precision_at_1000
      value: 2.500749999999998
    - type: recall_at_1
      value: 10.265595545755545
    - type: recall_at_3
      value: 17.819804963534246
    - type: recall_at_5
      value: 22.46124219601634
    - type: recall_at_10
      value: 30.44583516613163
    - type: recall_at_100
      value: 63.84118006287797
    - type: recall_at_1000
      value: 85.06450356093833
  - task:
      type: Retrieval
    dataset:
      type: BeIR/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: main_score
      value: 47.93921415959017
    - type: ndcg_at_1
      value: 36.526219490536015
    - type: ndcg_at_3
      value: 42.35099043224295
    - type: ndcg_at_5
      value: 44.989685312964156
    - type: ndcg_at_10
      value: 47.93921415959017
    - type: ndcg_at_100
      value: 53.05390282389675
    - type: ndcg_at_1000
      value: 54.776052731794266
    - type: map_at_1
      value: 30.818605279548184
    - type: map_at_3
      value: 38.363350019087974
    - type: map_at_5
      value: 40.295203936887226
    - type: map_at_10
      value: 41.81978941662592
    - type: map_at_100
      value: 43.13300727554278
    - type: map_at_1000
      value: 43.2351061120207
    - type: precision_at_1
      value: 36.526219490536015
    - type: precision_at_3
      value: 19.550515857206346
    - type: precision_at_5
      value: 13.958783060831967
    - type: precision_at_10
      value: 8.498592395773393
    - type: precision_at_100
      value: 1.3024888941713948
    - type: precision_at_1000
      value: 0.1630253057414617
    - type: recall_at_1
      value: 30.818605279548184
    - type: recall_at_3
      value: 45.9132085981904
    - type: recall_at_5
      value: 52.6851323959227
    - type: recall_at_10
      value: 61.39718618970463
    - type: recall_at_100
      value: 83.30757187969981
    - type: recall_at_1000
      value: 94.9192024147964
  - dataset:
      config: en
      name: MTEB AmazonCounterfactualClassification (en)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 89.47761194029852
    - type: accuracy_stderr
      value: 1.6502495811564162
    - type: ap
      value: 62.20813715457866
    - type: ap_stderr
      value: 3.7902166647587854
    - type: f1
      value: 84.91493292274734
    - type: f1_stderr
      value: 1.9572239640276208
    - type: main_score
      value: 89.47761194029852
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AmazonPolarityClassification
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      split: test
      type: mteb/amazon_polarity
    metrics:
    - type: accuracy
      value: 96.89569999999999
    - type: accuracy_stderr
      value: 0.6886368582206464
    - type: ap
      value: 95.38531339207739
    - type: ap_stderr
      value: 0.9009257949898158
    - type: f1
      value: 96.8941935264779
    - type: f1_stderr
      value: 0.6908609132985931
    - type: main_score
      value: 96.89569999999999
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonReviewsClassification (en)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 61.602000000000004
    - type: accuracy_stderr
      value: 1.4532019818318436
    - type: f1
      value: 60.96100449021481
    - type: f1_stderr
      value: 1.8031398419765765
    - type: main_score
      value: 61.602000000000004
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 54.906319409992
    - type: v_measure
      value: 54.906319409992
    - type: v_measure_std
      value: 14.382682652951683
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 50.27779516565727
    - type: v_measure
      value: 50.27779516565727
    - type: v_measure_std
      value: 14.463711418590636
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: map
      value: 64.59457317979604
    - type: mrr
      value: 78.05214791364376
    - type: main_score
      value: 64.59457317979604
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB BIOSSES
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
      split: test
      type: mteb/biosses-sts
    metrics:
    - type: cosine_pearson
      value: 86.5833945335644
    - type: cosine_spearman
      value: 85.74472483606
    - type: manhattan_pearson
      value: 85.07748703871708
    - type: manhattan_spearman
      value: 85.1459160110718
    - type: euclidean_pearson
      value: 85.14704290043478
    - type: euclidean_spearman
      value: 85.10073425868336
    - type: main_score
      value: 85.74472483606
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Banking77Classification
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      split: test
      type: mteb/banking77
    metrics:
    - type: accuracy
      value: 92.53246753246755
    - type: accuracy_stderr
      value: 0.5488837781559508
    - type: f1
      value: 92.5143182074032
    - type: f1_stderr
      value: 0.5657577980223147
    - type: main_score
      value: 92.53246753246755
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 52.64099497480452
    - type: v_measure
      value: 52.64099497480452
    - type: v_measure_std
      value: 1.081892399559334
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 49.1972734308178
    - type: v_measure
      value: 49.1972734308178
    - type: v_measure_std
      value: 0.9081245477708283
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB EmotionClassification
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
      split: test
      type: mteb/emotion
    metrics:
    - type: accuracy
      value: 92.975
    - type: accuracy_stderr
      value: 0.5287958017987677
    - type: f1
      value: 89.29755895896542
    - type: f1_stderr
      value: 0.6485027046025079
    - type: main_score
      value: 92.975
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ImdbClassification
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      split: test
      type: mteb/imdb
    metrics:
    - type: accuracy
      value: 96.66480000000001
    - type: accuracy_stderr
      value: 0.45673204398202666
    - type: ap
      value: 95.33843919456118
    - type: ap_stderr
      value: 0.6449846039754393
    - type: f1
      value: 96.6637668164617
    - type: f1_stderr
      value: 0.45793673051468287
    - type: main_score
      value: 96.66480000000001
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPDomainClassification (en)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 98.61149110807114
    - type: accuracy_stderr
      value: 0.469748178253266
    - type: f1
      value: 98.4685511007568
    - type: f1_stderr
      value: 0.51636776728259
    - type: main_score
      value: 98.61149110807114
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPIntentClassification (en)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 95.51299589603283
    - type: accuracy_stderr
      value: 0.3591676911539482
    - type: f1
      value: 85.2464691439773
    - type: f1_stderr
      value: 0.9234502856695337
    - type: main_score
      value: 95.51299589603283
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveIntentClassification (en)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 82.04774714189644
    - type: accuracy_stderr
      value: 0.7288818520309376
    - type: f1
      value: 79.28060657840692
    - type: f1_stderr
      value: 0.6872008571781982
    - type: main_score
      value: 82.04774714189644
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveScenarioClassification (en)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 84.40147948890383
    - type: accuracy_stderr
      value: 1.2939587629143627
    - type: f1
      value: 83.97779287582267
    - type: f1_stderr
      value: 0.9970599222060901
    - type: main_score
      value: 84.40147948890383
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedrxivClusteringP2P
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
      split: test
      type: mteb/medrxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 45.80879120838561
    - type: v_measure
      value: 45.80879120838561
    - type: v_measure_std
      value: 1.257800489264564
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MedrxivClusteringS2S
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
      split: test
      type: mteb/medrxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 44.106849261042505
    - type: v_measure
      value: 44.106849261042505
    - type: v_measure_std
      value: 1.4347344477874981
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MindSmallReranking
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
      split: test
      type: mteb/mind_small
    metrics:
    - type: map
      value: 31.794062752995345
    - type: mrr
      value: 32.98581714772614
    - type: main_score
      value: 31.794062752995345
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB RedditClustering
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
      split: test
      type: mteb/reddit-clustering
    metrics:
    - type: main_score
      value: 56.03342473834434
    - type: v_measure
      value: 56.03342473834434
    - type: v_measure_std
      value: 5.972192613803461
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB RedditClusteringP2P
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
      split: test
      type: mteb/reddit-clustering-p2p
    metrics:
    - type: main_score
      value: 65.83156688381274
    - type: v_measure
      value: 65.83156688381274
    - type: v_measure_std
      value: 14.180225112120162
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB SICK-R
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: cosine_pearson
      value: 84.15759544348467
    - type: cosine_spearman
      value: 82.66085892322664
    - type: manhattan_pearson
      value: 82.27257241990692
    - type: manhattan_spearman
      value: 82.57752467555896
    - type: euclidean_pearson
      value: 82.20795646456065
    - type: euclidean_spearman
      value: 82.51008729416401
    - type: main_score
      value: 82.66085892322664
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: cosine_pearson
      value: 84.3406321391237
    - type: cosine_spearman
      value: 77.71091257651071
    - type: manhattan_pearson
      value: 81.25784268400994
    - type: manhattan_spearman
      value: 77.98426383345507
    - type: euclidean_pearson
      value: 81.25641851462917
    - type: euclidean_spearman
      value: 77.93254971878063
    - type: main_score
      value: 77.71091257651071
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: cosine_pearson
      value: 86.1528398894769
    - type: cosine_spearman
      value: 87.44662352358895
    - type: manhattan_pearson
      value: 86.92164570802663
    - type: manhattan_spearman
      value: 86.9132692625668
    - type: euclidean_pearson
      value: 87.00156426580821
    - type: euclidean_spearman
      value: 86.98750068631274
    - type: main_score
      value: 87.44662352358895
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: cosine_pearson
      value: 83.32782491176253
    - type: cosine_spearman
      value: 83.48313793311584
    - type: manhattan_pearson
      value: 82.60528063429948
    - type: manhattan_spearman
      value: 83.10434862310481
    - type: euclidean_pearson
      value: 82.68016090104034
    - type: euclidean_spearman
      value: 83.14418662406631
    - type: main_score
      value: 83.48313793311584
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: cosine_pearson
      value: 86.31535441436343
    - type: cosine_spearman
      value: 87.63145141246594
    - type: manhattan_pearson
      value: 86.95972711389149
    - type: manhattan_spearman
      value: 86.9849824463052
    - type: euclidean_pearson
      value: 86.95391575487379
    - type: euclidean_spearman
      value: 86.97613682266213
    - type: main_score
      value: 87.63145141246594
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: cosine_pearson
      value: 83.43854397443079
    - type: cosine_spearman
      value: 86.70176531845136
    - type: manhattan_pearson
      value: 85.82302317064868
    - type: manhattan_spearman
      value: 86.36561734213241
    - type: euclidean_pearson
      value: 85.80127366135169
    - type: euclidean_spearman
      value: 86.34803859754834
    - type: main_score
      value: 86.70176531845136
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 90.38940955877999
    - type: cosine_spearman
      value: 91.18282119920893
    - type: manhattan_pearson
      value: 91.31823663739615
    - type: manhattan_spearman
      value: 90.67257321731341
    - type: euclidean_pearson
      value: 91.30318753138528
    - type: euclidean_spearman
      value: 90.69044765693836
    - type: main_score
      value: 91.18282119920893
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 69.33936467780947
    - type: cosine_spearman
      value: 69.02345807358802
    - type: manhattan_pearson
      value: 70.11799452953082
    - type: manhattan_spearman
      value: 68.55450923481405
    - type: euclidean_pearson
      value: 70.10857680491809
    - type: euclidean_spearman
      value: 68.44610245708984
    - type: main_score
      value: 69.02345807358802
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: cosine_pearson
      value: 85.97288135509513
    - type: cosine_spearman
      value: 87.25208310840168
    - type: manhattan_pearson
      value: 86.3786471501451
    - type: manhattan_spearman
      value: 86.71177136523868
    - type: euclidean_pearson
      value: 86.40522339296625
    - type: euclidean_spearman
      value: 86.73930576508816
    - type: main_score
      value: 87.25208310840168
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: map
      value: 87.60324164489178
    - type: mrr
      value: 96.30331904841708
    - type: main_score
      value: 87.60324164489178
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SprintDuplicateQuestions
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
    metrics:
    - type: cos_sim_accuracy
      value: 99.6920792079208
    - type: cos_sim_accuracy_threshold
      value: 90.36337347155474
    - type: cos_sim_ap
      value: 90.93952679056765
    - type: cos_sim_f1
      value: 83.10700706137968
    - type: cos_sim_f1_threshold
      value: 90.36337347155474
    - type: cos_sim_precision
      value: 90.96313912009512
    - type: cos_sim_recall
      value: 76.5
    - type: dot_accuracy
      value: 99.54554455445545
    - type: dot_accuracy_threshold
      value: 2876800.0
    - type: dot_ap
      value: 84.01112287735286
    - type: dot_f1
      value: 75.7622739018088
    - type: dot_f1_threshold
      value: 2820800.0
    - type: dot_precision
      value: 78.39572192513369
    - type: dot_recall
      value: 73.3
    - type: euclidean_accuracy
      value: 99.6930693069307
    - type: euclidean_accuracy_threshold
      value: 7718.054017089397
    - type: euclidean_ap
      value: 91.1257568881301
    - type: euclidean_f1
      value: 83.09022150189087
    - type: euclidean_f1_threshold
      value: 7817.08324628535
    - type: euclidean_precision
      value: 90.36427732079906
    - type: euclidean_recall
      value: 76.9
    - type: manhattan_accuracy
      value: 99.6920792079208
    - type: manhattan_accuracy_threshold
      value: 364735.19654273987
    - type: manhattan_ap
      value: 91.2326885940691
    - type: manhattan_f1
      value: 83.36008560727663
    - type: manhattan_f1_threshold
      value: 375395.8945572376
    - type: manhattan_precision
      value: 89.64326812428078
    - type: manhattan_recall
      value: 77.9
    - type: max_accuracy
      value: 99.6930693069307
    - type: max_ap
      value: 91.2326885940691
    - type: max_f1
      value: 83.36008560727663
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB StackExchangeClustering
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
      split: test
      type: mteb/stackexchange-clustering
    metrics:
    - type: main_score
      value: 66.2095300942637
    - type: v_measure
      value: 66.2095300942637
    - type: v_measure_std
      value: 3.214369679617631
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackExchangeClusteringP2P
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
      split: test
      type: mteb/stackexchange-clustering-p2p
    metrics:
    - type: main_score
      value: 45.74307000935057
    - type: v_measure
      value: 45.74307000935057
    - type: v_measure_std
      value: 1.5352466748569888
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackOverflowDupQuestions
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
    metrics:
    - type: map
      value: 54.90337951829123
    - type: mrr
      value: 56.12889663441134
    - type: main_score
      value: 54.90337951829123
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SummEval
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
      split: test
      type: mteb/summeval
    metrics:
    - type: cosine_pearson
      value: 31.0669308484832
    - type: cosine_spearman
      value: 31.19637421540861
    - type: dot_pearson
      value: 30.62326176666765
    - type: dot_spearman
      value: 30.42135737502967
    - type: main_score
      value: 31.19637421540861
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB ToxicConversationsClassification
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
      split: test
      type: mteb/toxic_conversations_50k
    metrics:
    - type: accuracy
      value: 87.34339999999999
    - type: accuracy_stderr
      value: 1.838245696309393
    - type: ap
      value: 33.536584790435406
    - type: ap_stderr
      value: 2.276373512492581
    - type: f1
      value: 72.47307082324448
    - type: f1_stderr
      value: 1.9964640292072542
    - type: main_score
      value: 87.34339999999999
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TweetSentimentExtractionClassification
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
      split: test
      type: mteb/tweet_sentiment_extraction
    metrics:
    - type: accuracy
      value: 78.86247877758915
    - type: accuracy_stderr
      value: 1.1273253738982443
    - type: f1
      value: 79.14666244848874
    - type: f1_stderr
      value: 1.1532640958036497
    - type: main_score
      value: 78.86247877758915
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TwentyNewsgroupsClustering
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
      split: test
      type: mteb/twentynewsgroups-clustering
    metrics:
    - type: main_score
      value: 70.44270836680788
    - type: v_measure
      value: 70.44270836680788
    - type: v_measure_std
      value: 1.5185423698266132
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: cos_sim_accuracy
      value: 87.74512725755498
    - type: cos_sim_accuracy_threshold
      value: 82.34941560483547
    - type: cos_sim_ap
      value: 79.6389274210382
    - type: cos_sim_f1
      value: 71.76319176319176
    - type: cos_sim_f1_threshold
      value: 80.1523829249257
    - type: cos_sim_precision
      value: 70.0502512562814
    - type: cos_sim_recall
      value: 73.56200527704485
    - type: dot_accuracy
      value: 85.13441020444657
    - type: dot_accuracy_threshold
      value: 2220800.0
    - type: dot_ap
      value: 71.67080150823449
    - type: dot_f1
      value: 66.18984119287187
    - type: dot_f1_threshold
      value: 2086400.0
    - type: dot_precision
      value: 61.224489795918366
    - type: dot_recall
      value: 72.0316622691293
    - type: euclidean_accuracy
      value: 87.69148238660071
    - type: euclidean_accuracy_threshold
      value: 9221.50036619459
    - type: euclidean_ap
      value: 79.65326151280289
    - type: euclidean_f1
      value: 71.7903489983621
    - type: euclidean_f1_threshold
      value: 10313.528386219872
    - type: euclidean_precision
      value: 68.70026525198939
    - type: euclidean_recall
      value: 75.17150395778364
    - type: manhattan_accuracy
      value: 87.74512725755498
    - type: manhattan_accuracy_threshold
      value: 444289.1119837761
    - type: manhattan_ap
      value: 79.67744645365104
    - type: manhattan_f1
      value: 71.94423699278066
    - type: manhattan_f1_threshold
      value: 491676.24004781246
    - type: manhattan_precision
      value: 68.0961357210179
    - type: manhattan_recall
      value: 76.2532981530343
    - type: max_accuracy
      value: 87.74512725755498
    - type: max_ap
      value: 79.67744645365104
    - type: max_f1
      value: 71.94423699278066
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: cos_sim_accuracy
      value: 89.5544688943222
    - type: cos_sim_accuracy_threshold
      value: 81.58909533293946
    - type: cos_sim_ap
      value: 86.95174990178396
    - type: cos_sim_f1
      value: 79.1543756145526
    - type: cos_sim_f1_threshold
      value: 80.08573448087095
    - type: cos_sim_precision
      value: 77.78355879292404
    - type: cos_sim_recall
      value: 80.5743763473976
    - type: dot_accuracy
      value: 88.60752124810804
    - type: dot_accuracy_threshold
      value: 2136000.0
    - type: dot_ap
      value: 84.26724775947629
    - type: dot_f1
      value: 77.67666146985243
    - type: dot_f1_threshold
      value: 2064000.0
    - type: dot_precision
      value: 73.40505721921468
    - type: dot_recall
      value: 82.47613181398214
    - type: euclidean_accuracy
      value: 89.5370046959289
    - type: euclidean_accuracy_threshold
      value: 9750.113991666478
    - type: euclidean_ap
      value: 86.99393092403776
    - type: euclidean_f1
      value: 79.07167337207571
    - type: euclidean_f1_threshold
      value: 10338.095928500366
    - type: euclidean_precision
      value: 76.59497690531177
    - type: euclidean_recall
      value: 81.71388974437943
    - type: manhattan_accuracy
      value: 89.57581402569178
    - type: manhattan_accuracy_threshold
      value: 463812.92815208435
    - type: manhattan_ap
      value: 87.00849868076658
    - type: manhattan_f1
      value: 79.08583576933297
    - type: manhattan_f1_threshold
      value: 482453.35128605366
    - type: manhattan_precision
      value: 78.00494270950348
    - type: manhattan_recall
      value: 80.19710502001848
    - type: max_accuracy
      value: 89.57581402569178
    - type: max_ap
      value: 87.00849868076658
    - type: max_f1
      value: 79.1543756145526
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB AFQMC
      revision: b44c3b011063adb25877c13823db83bb193913c4
      split: validation
      type: C-MTEB/AFQMC
    metrics:
    - type: cosine_pearson
      value: 45.108559635369325
    - type: cosine_spearman
      value: 47.172833128216176
    - type: manhattan_pearson
      value: 45.75443077564791
    - type: manhattan_spearman
      value: 47.13974146235398
    - type: euclidean_pearson
      value: 45.78921257223492
    - type: euclidean_spearman
      value: 47.177095238278625
    - type: main_score
      value: 47.172833128216176
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB ATEC
      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
      split: test
      type: C-MTEB/ATEC
    metrics:
    - type: cosine_pearson
      value: 48.304409578388466
    - type: cosine_spearman
      value: 50.75006977697012
    - type: manhattan_pearson
      value: 52.688818756177035
    - type: manhattan_spearman
      value: 50.739214155741095
    - type: euclidean_pearson
      value: 52.71788557204978
    - type: euclidean_spearman
      value: 50.77895730336448
    - type: main_score
      value: 50.75006977697012
    task:
      type: STS
  - dataset:
      config: zh
      name: MTEB AmazonReviewsClassification (zh)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 54.339999999999996
    - type: accuracy_stderr
      value: 1.6518837731511269
    - type: f1
      value: 53.37316538790502
    - type: f1_stderr
      value: 1.6112926272861336
    - type: main_score
      value: 54.339999999999996
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BQ
      revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
      split: test
      type: C-MTEB/BQ
    metrics:
    - type: cosine_pearson
      value: 59.62831218167518
    - type: cosine_spearman
      value: 62.02213472473759
    - type: manhattan_pearson
      value: 61.122261197018176
    - type: manhattan_spearman
      value: 62.208780520694454
    - type: euclidean_pearson
      value: 61.17827629627213
    - type: euclidean_spearman
      value: 62.266859648664244
    - type: main_score
      value: 62.02213472473759
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB CLSClusteringP2P
      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
      split: test
      type: C-MTEB/CLSClusteringP2P
    metrics:
    - type: main_score
      value: 54.64518394835408
    - type: v_measure
      value: 54.64518394835408
    - type: v_measure_std
      value: 1.2745946640208072
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CLSClusteringS2S
      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
      split: test
      type: C-MTEB/CLSClusteringS2S
    metrics:
    - type: main_score
      value: 63.68323477729556
    - type: v_measure
      value: 63.68323477729556
    - type: v_measure_std
      value: 1.740918833098302
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CMedQAv1
      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
      split: test
      type: C-MTEB/CMedQAv1-reranking
    metrics:
    - type: map
      value: 84.61500884703916
    - type: mrr
      value: 87.01424603174604
    - type: main_score
      value: 84.61500884703916
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB CMedQAv2
      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
      split: test
      type: C-MTEB/CMedQAv2-reranking
    metrics:
    - type: map
      value: 85.60137988993483
    - type: mrr
      value: 87.96857142857142
    - type: main_score
      value: 85.60137988993483
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB CmedqaRetrieval
      revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
      split: dev
      type: C-MTEB/CmedqaRetrieval
    metrics:
    - type: map_at_1
      value: 24.191
    - type: map_at_10
      value: 35.819
    - type: map_at_100
      value: 37.639
    - type: map_at_1000
      value: 37.775
    - type: map_at_3
      value: 32.045
    - type: map_at_5
      value: 34.008
    - type: mrr_at_1
      value: 36.684
    - type: mrr_at_10
      value: 44.769
    - type: mrr_at_100
      value: 45.754
    - type: mrr_at_1000
      value: 45.809
    - type: mrr_at_3
      value: 42.465
    - type: mrr_at_5
      value: 43.696
    - type: ndcg_at_1
      value: 36.834
    - type: ndcg_at_10
      value: 42.208
    - type: ndcg_at_100
      value: 49.507
    - type: ndcg_at_1000
      value: 51.834
    - type: ndcg_at_3
      value: 37.416
    - type: ndcg_at_5
      value: 39.152
    - type: precision_at_1
      value: 36.834
    - type: precision_at_10
      value: 9.357
    - type: precision_at_100
      value: 1.5310000000000001
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 21.08
    - type: precision_at_5
      value: 15.068999999999999
    - type: recall_at_1
      value: 24.191
    - type: recall_at_10
      value: 52.078
    - type: recall_at_100
      value: 82.548
    - type: recall_at_1000
      value: 98.017
    - type: recall_at_3
      value: 37.484
    - type: recall_at_5
      value: 43.187
    - type: main_score
      value: 42.208
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB Cmnli
      revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
      split: validation
      type: C-MTEB/CMNLI
    metrics:
    - type: cos_sim_accuracy
      value: 81.98436560432953
    - type: cos_sim_accuracy_threshold
      value: 67.33228049687503
    - type: cos_sim_ap
      value: 90.13312662430796
    - type: cos_sim_f1
      value: 83.2163938077737
    - type: cos_sim_f1_threshold
      value: 64.44945196171463
    - type: cos_sim_precision
      value: 79.45555082943429
    - type: cos_sim_recall
      value: 87.350946925415
    - type: dot_accuracy
      value: 80.50511124473843
    - type: dot_accuracy_threshold
      value: 1736000.0
    - type: dot_ap
      value: 88.76136186445322
    - type: dot_f1
      value: 81.75838631878973
    - type: dot_f1_threshold
      value: 1681600.0
    - type: dot_precision
      value: 76.96594427244582
    - type: dot_recall
      value: 87.18728080430208
    - type: euclidean_accuracy
      value: 82.21286831028262
    - type: euclidean_accuracy_threshold
      value: 13240.938473272565
    - type: euclidean_ap
      value: 90.14863232280865
    - type: euclidean_f1
      value: 83.277292086976
    - type: euclidean_f1_threshold
      value: 13667.852165734186
    - type: euclidean_precision
      value: 79.97847147470398
    - type: euclidean_recall
      value: 86.85994856207621
    - type: manhattan_accuracy
      value: 82.21286831028262
    - type: manhattan_accuracy_threshold
      value: 629412.1389746666
    - type: manhattan_ap
      value: 90.03868533208357
    - type: manhattan_f1
      value: 83.15683870248579
    - type: manhattan_f1_threshold
      value: 649621.3114321232
    - type: manhattan_precision
      value: 79.46314443971026
    - type: manhattan_recall
      value: 87.21066167874679
    - type: max_accuracy
      value: 82.21286831028262
    - type: max_ap
      value: 90.14863232280865
    - type: max_f1
      value: 83.277292086976
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB CovidRetrieval
      revision: 1271c7809071a13532e05f25fb53511ffce77117
      split: dev
      type: C-MTEB/CovidRetrieval
    metrics:
    - type: map_at_1
      value: 65.595
    - type: map_at_10
      value: 73.717
    - type: map_at_100
      value: 74.134
    - type: map_at_1000
      value: 74.143
    - type: map_at_3
      value: 71.97
    - type: map_at_5
      value: 73.11800000000001
    - type: mrr_at_1
      value: 65.648
    - type: mrr_at_10
      value: 73.618
    - type: mrr_at_100
      value: 74.02499999999999
    - type: mrr_at_1000
      value: 74.033
    - type: mrr_at_3
      value: 71.865
    - type: mrr_at_5
      value: 73.04
    - type: ndcg_at_1
      value: 65.753
    - type: ndcg_at_10
      value: 77.458
    - type: ndcg_at_100
      value: 79.46
    - type: ndcg_at_1000
      value: 79.666
    - type: ndcg_at_3
      value: 73.988
    - type: ndcg_at_5
      value: 76.038
    - type: precision_at_1
      value: 65.753
    - type: precision_at_10
      value: 8.999
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 26.765
    - type: precision_at_5
      value: 17.092
    - type: recall_at_1
      value: 65.595
    - type: recall_at_10
      value: 89.041
    - type: recall_at_100
      value: 98.31400000000001
    - type: recall_at_1000
      value: 99.895
    - type: recall_at_3
      value: 79.768
    - type: recall_at_5
      value: 84.66799999999999
    - type: main_score
      value: 77.458
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB DuRetrieval
      revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
      split: dev
      type: C-MTEB/DuRetrieval
    metrics:
    - type: map_at_1
      value: 27.248
    - type: map_at_10
      value: 84.303
    - type: map_at_100
      value: 86.866
    - type: map_at_1000
      value: 86.888
    - type: map_at_3
      value: 58.658
    - type: map_at_5
      value: 74.265
    - type: mrr_at_1
      value: 92.2
    - type: mrr_at_10
      value: 94.733
    - type: mrr_at_100
      value: 94.767
    - type: mrr_at_1000
      value: 94.768
    - type: mrr_at_3
      value: 94.492
    - type: mrr_at_5
      value: 94.627
    - type: ndcg_at_1
      value: 92.2
    - type: ndcg_at_10
      value: 90.462
    - type: ndcg_at_100
      value: 92.562
    - type: ndcg_at_1000
      value: 92.757
    - type: ndcg_at_3
      value: 89.44800000000001
    - type: ndcg_at_5
      value: 88.683
    - type: precision_at_1
      value: 92.2
    - type: precision_at_10
      value: 42.980000000000004
    - type: precision_at_100
      value: 4.851
    - type: precision_at_1000
      value: 0.49
    - type: precision_at_3
      value: 80.233
    - type: precision_at_5
      value: 67.95
    - type: recall_at_1
      value: 27.248
    - type: recall_at_10
      value: 91.46600000000001
    - type: recall_at_100
      value: 98.566
    - type: recall_at_1000
      value: 99.557
    - type: recall_at_3
      value: 60.671
    - type: recall_at_5
      value: 78.363
    - type: main_score
      value: 90.462
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB EcomRetrieval
      revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
      split: dev
      type: C-MTEB/EcomRetrieval
    metrics:
    - type: map_at_1
      value: 54.7
    - type: map_at_10
      value: 64.574
    - type: map_at_100
      value: 65.144
    - type: map_at_1000
      value: 65.156
    - type: map_at_3
      value: 62.333000000000006
    - type: map_at_5
      value: 63.63799999999999
    - type: mrr_at_1
      value: 54.7
    - type: mrr_at_10
      value: 64.603
    - type: mrr_at_100
      value: 65.172
    - type: mrr_at_1000
      value: 65.184
    - type: mrr_at_3
      value: 62.383
    - type: mrr_at_5
      value: 63.683
    - type: ndcg_at_1
      value: 54.7
    - type: ndcg_at_10
      value: 69.298
    - type: ndcg_at_100
      value: 71.81
    - type: ndcg_at_1000
      value: 72.117
    - type: ndcg_at_3
      value: 64.72099999999999
    - type: ndcg_at_5
      value: 67.071
    - type: precision_at_1
      value: 54.7
    - type: precision_at_10
      value: 8.41
    - type: precision_at_100
      value: 0.9530000000000001
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 23.867
    - type: precision_at_5
      value: 15.459999999999999
    - type: recall_at_1
      value: 54.7
    - type: recall_at_10
      value: 84.1
    - type: recall_at_100
      value: 95.3
    - type: recall_at_1000
      value: 97.7
    - type: recall_at_3
      value: 71.6
    - type: recall_at_5
      value: 77.3
    - type: main_score
      value: 69.298
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB IFlyTek
      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
      split: validation
      type: C-MTEB/IFlyTek-classification
    metrics:
    - type: accuracy
      value: 49.942285494420936
    - type: accuracy_stderr
      value: 0.9218275144833329
    - type: f1
      value: 41.32381790374152
    - type: f1_stderr
      value: 0.8291507105327707
    - type: main_score
      value: 49.942285494420936
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB JDReview
      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
      split: test
      type: C-MTEB/JDReview-classification
    metrics:
    - type: accuracy
      value: 88.91181988742964
    - type: accuracy_stderr
      value: 1.952391767940518
    - type: ap
      value: 60.18509628974178
    - type: ap_stderr
      value: 4.273060966573582
    - type: f1
      value: 84.02722221827027
    - type: f1_stderr
      value: 2.238197243395083
    - type: main_score
      value: 88.91181988742964
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB LCQMC
      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
      split: test
      type: C-MTEB/LCQMC
    metrics:
    - type: cosine_pearson
      value: 68.32691294171383
    - type: cosine_spearman
      value: 75.95458618586729
    - type: manhattan_pearson
      value: 74.37198807732018
    - type: manhattan_spearman
      value: 75.99352157963375
    - type: euclidean_pearson
      value: 74.36294627886716
    - type: euclidean_spearman
      value: 75.98632511635132
    - type: main_score
      value: 75.95458618586729
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB MMarcoReranking
      revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
      split: dev
      type: C-MTEB/Mmarco-reranking
    metrics:
    - type: map
      value: 35.4327533126161
    - type: mrr
      value: 34.61507936507937
    - type: main_score
      value: 35.4327533126161
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB MMarcoRetrieval
      revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
      split: dev
      type: C-MTEB/MMarcoRetrieval
    metrics:
    - type: map_at_1
      value: 72.652
    - type: map_at_10
      value: 81.396
    - type: map_at_100
      value: 81.597
    - type: map_at_1000
      value: 81.60300000000001
    - type: map_at_3
      value: 79.757
    - type: map_at_5
      value: 80.798
    - type: mrr_at_1
      value: 75.01400000000001
    - type: mrr_at_10
      value: 81.842
    - type: mrr_at_100
      value: 82.025
    - type: mrr_at_1000
      value: 82.03099999999999
    - type: mrr_at_3
      value: 80.45400000000001
    - type: mrr_at_5
      value: 81.345
    - type: ndcg_at_1
      value: 74.98599999999999
    - type: ndcg_at_10
      value: 84.70100000000001
    - type: ndcg_at_100
      value: 85.568
    - type: ndcg_at_1000
      value: 85.721
    - type: ndcg_at_3
      value: 81.64099999999999
    - type: ndcg_at_5
      value: 83.375
    - type: precision_at_1
      value: 74.98599999999999
    - type: precision_at_10
      value: 10.049
    - type: precision_at_100
      value: 1.047
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 30.458000000000002
    - type: precision_at_5
      value: 19.206
    - type: recall_at_1
      value: 72.652
    - type: recall_at_10
      value: 94.40899999999999
    - type: recall_at_100
      value: 98.241
    - type: recall_at_1000
      value: 99.42
    - type: recall_at_3
      value: 86.354
    - type: recall_at_5
      value: 90.472
    - type: main_score
      value: 84.70100000000001
    task:
      type: Retrieval
  - dataset:
      config: zh-CN
      name: MTEB MassiveIntentClassification (zh-CN)
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 78.19098856758575
    - type: accuracy_stderr
      value: 0.6325028678427684
    - type: f1
      value: 74.80611425574001
    - type: f1_stderr
      value: 0.9021806207904779
    - type: main_score
      value: 78.19098856758575
    task:
      type: Classification
  - dataset:
      config: zh-CN
      name: MTEB MassiveScenarioClassification (zh-CN)
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 82.58238063214526
    - type: accuracy_stderr
      value: 1.0999970213165273
    - type: f1
      value: 81.94734854057064
    - type: f1_stderr
      value: 1.248633855872851
    - type: main_score
      value: 82.58238063214526
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedicalRetrieval
      revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
      split: dev
      type: C-MTEB/MedicalRetrieval
    metrics:
    - type: map_at_1
      value: 53.7
    - type: map_at_10
      value: 59.184000000000005
    - type: map_at_100
      value: 59.754
    - type: map_at_1000
      value: 59.8
    - type: map_at_3
      value: 57.833
    - type: map_at_5
      value: 58.548
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 59.352000000000004
    - type: mrr_at_100
      value: 59.926
    - type: mrr_at_1000
      value: 59.971
    - type: mrr_at_3
      value: 57.99999999999999
    - type: mrr_at_5
      value: 58.714999999999996
    - type: ndcg_at_1
      value: 53.7
    - type: ndcg_at_10
      value: 62.022
    - type: ndcg_at_100
      value: 65.038
    - type: ndcg_at_1000
      value: 66.366
    - type: ndcg_at_3
      value: 59.209
    - type: ndcg_at_5
      value: 60.51299999999999
    - type: precision_at_1
      value: 53.7
    - type: precision_at_10
      value: 7.1
    - type: precision_at_100
      value: 0.856
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 21.067
    - type: precision_at_5
      value: 13.28
    - type: recall_at_1
      value: 53.7
    - type: recall_at_10
      value: 71.0
    - type: recall_at_100
      value: 85.6
    - type: recall_at_1000
      value: 96.3
    - type: recall_at_3
      value: 63.2
    - type: recall_at_5
      value: 66.4
    - type: main_score
      value: 62.022
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB MultilingualSentiment
      revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
      split: validation
      type: C-MTEB/MultilingualSentiment-classification
    metrics:
    - type: accuracy
      value: 78.91333333333334
    - type: accuracy_stderr
      value: 1.0834307648494321
    - type: f1
      value: 78.881433228092
    - type: f1_stderr
      value: 1.122457277013712
    - type: main_score
      value: 78.91333333333334
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB Ocnli
      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
      split: validation
      type: C-MTEB/OCNLI
    metrics:
    - type: cos_sim_accuracy
      value: 76.39415268002165
    - type: cos_sim_accuracy_threshold
      value: 68.98242139321592
    - type: cos_sim_ap
      value: 83.20687440058073
    - type: cos_sim_f1
      value: 78.4351145038168
    - type: cos_sim_f1_threshold
      value: 65.47409929698304
    - type: cos_sim_precision
      value: 71.54046997389034
    - type: cos_sim_recall
      value: 86.80042238648363
    - type: dot_accuracy
      value: 74.60747157552788
    - type: dot_accuracy_threshold
      value: 1737600.0
    - type: dot_ap
      value: 79.78938545919723
    - type: dot_f1
      value: 76.92307692307692
    - type: dot_f1_threshold
      value: 1652800.0
    - type: dot_precision
      value: 67.90622473726758
    - type: dot_recall
      value: 88.70116156283
    - type: euclidean_accuracy
      value: 76.34001082837032
    - type: euclidean_accuracy_threshold
      value: 12597.299662420446
    - type: euclidean_ap
      value: 83.60222701792158
    - type: euclidean_f1
      value: 78.77947295423024
    - type: euclidean_f1_threshold
      value: 13639.653702639469
    - type: euclidean_precision
      value: 70.06578947368422
    - type: euclidean_recall
      value: 89.96832101372756
    - type: manhattan_accuracy
      value: 76.23172712506768
    - type: manhattan_accuracy_threshold
      value: 587601.2824743986
    - type: manhattan_ap
      value: 83.51813426548178
    - type: manhattan_f1
      value: 78.6654135338346
    - type: manhattan_f1_threshold
      value: 639711.1931562424
    - type: manhattan_precision
      value: 70.87214225232854
    - type: manhattan_recall
      value: 88.3843717001056
    - type: max_accuracy
      value: 76.39415268002165
    - type: max_ap
      value: 83.60222701792158
    - type: max_f1
      value: 78.77947295423024
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB OnlineShopping
      revision: e610f2ebd179a8fda30ae534c3878750a96db120
      split: test
      type: C-MTEB/OnlineShopping-classification
    metrics:
    - type: accuracy
      value: 94.59
    - type: accuracy_stderr
      value: 0.8971621926942733
    - type: ap
      value: 93.01229797205905
    - type: ap_stderr
      value: 1.0519542956523058
    - type: f1
      value: 94.58077736915268
    - type: f1_stderr
      value: 0.8954928292768671
    - type: main_score
      value: 94.59
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PAWSX
      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
      split: test
      type: C-MTEB/PAWSX
    metrics:
    - type: cosine_pearson
      value: 24.341872875292857
    - type: cosine_spearman
      value: 30.570037022875436
    - type: manhattan_pearson
      value: 31.41015320258418
    - type: manhattan_spearman
      value: 30.604526098895114
    - type: euclidean_pearson
      value: 31.400038084432175
    - type: euclidean_spearman
      value: 30.61062265273698
    - type: main_score
      value: 30.570037022875436
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB QBQTC
      revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
      split: test
      type: C-MTEB/QBQTC
    metrics:
    - type: cosine_pearson
      value: 36.61757468091905
    - type: cosine_spearman
      value: 38.981417359835504
    - type: manhattan_pearson
      value: 37.971127169578764
    - type: manhattan_spearman
      value: 39.55028286687854
    - type: euclidean_pearson
      value: 37.96983777648438
    - type: euclidean_spearman
      value: 39.542856511171784
    - type: main_score
      value: 38.981417359835504
    task:
      type: STS
  - dataset:
      config: zh
      name: MTEB STS22 (zh)
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 68.29834902017382
    - type: cosine_spearman
      value: 68.6823378297782
    - type: manhattan_pearson
      value: 68.47336169904406
    - type: manhattan_spearman
      value: 69.08033223619941
    - type: euclidean_pearson
      value: 68.38785956191622
    - type: euclidean_spearman
      value: 68.97973814449657
    - type: main_score
      value: 68.6823378297782
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSB
      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
      split: test
      type: C-MTEB/STSB
    metrics:
    - type: cosine_pearson
      value: 80.60572958563593
    - type: cosine_spearman
      value: 80.87063761195603
    - type: manhattan_pearson
      value: 79.30174059269083
    - type: manhattan_spearman
      value: 80.02203618135883
    - type: euclidean_pearson
      value: 79.3314553444783
    - type: euclidean_spearman
      value: 80.04556415585255
    - type: main_score
      value: 80.87063761195603
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB T2Reranking
      revision: 76631901a18387f85eaa53e5450019b87ad58ef9
      split: dev
      type: C-MTEB/T2Reranking
    metrics:
    - type: map
      value: 67.47921173708028
    - type: mrr
      value: 77.9396513739777
    - type: main_score
      value: 67.47921173708028
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB T2Retrieval
      revision: 8731a845f1bf500a4f111cf1070785c793d10e64
      split: dev
      type: C-MTEB/T2Retrieval
    metrics:
    - type: map_at_1
      value: 28.021
    - type: map_at_10
      value: 79.149
    - type: map_at_100
      value: 82.613
    - type: map_at_1000
      value: 82.67099999999999
    - type: map_at_3
      value: 55.665
    - type: map_at_5
      value: 68.46900000000001
    - type: mrr_at_1
      value: 91.106
    - type: mrr_at_10
      value: 93.372
    - type: mrr_at_100
      value: 93.44200000000001
    - type: mrr_at_1000
      value: 93.445
    - type: mrr_at_3
      value: 92.99300000000001
    - type: mrr_at_5
      value: 93.24900000000001
    - type: ndcg_at_1
      value: 91.106
    - type: ndcg_at_10
      value: 86.259
    - type: ndcg_at_100
      value: 89.46600000000001
    - type: ndcg_at_1000
      value: 90.012
    - type: ndcg_at_3
      value: 87.574
    - type: ndcg_at_5
      value: 86.283
    - type: precision_at_1
      value: 91.106
    - type: precision_at_10
      value: 42.742999999999995
    - type: precision_at_100
      value: 5.029999999999999
    - type: precision_at_1000
      value: 0.516
    - type: precision_at_3
      value: 76.593
    - type: precision_at_5
      value: 64.243
    - type: recall_at_1
      value: 28.021
    - type: recall_at_10
      value: 85.184
    - type: recall_at_100
      value: 95.79299999999999
    - type: recall_at_1000
      value: 98.547
    - type: recall_at_3
      value: 57.233000000000004
    - type: recall_at_5
      value: 71.628
    - type: main_score
      value: 86.259
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB TNews
      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
      split: validation
      type: C-MTEB/TNews-classification
    metrics:
    - type: accuracy
      value: 50.255
    - type: accuracy_stderr
      value: 0.9341868121526873
    - type: f1
      value: 48.65080322457893
    - type: f1_stderr
      value: 0.9391547591179161
    - type: main_score
      value: 50.255
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ThuNewsClusteringP2P
      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
      split: test
      type: C-MTEB/ThuNewsClusteringP2P
    metrics:
    - type: main_score
      value: 64.32076022871308
    - type: v_measure
      value: 64.32076022871308
    - type: v_measure_std
      value: 0.7190996709617924
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ThuNewsClusteringS2S
      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
      split: test
      type: C-MTEB/ThuNewsClusteringS2S
    metrics:
    - type: main_score
      value: 54.57080911705562
    - type: v_measure
      value: 54.57080911705562
    - type: v_measure_std
      value: 1.5185826402845883
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB VideoRetrieval
      revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
      split: dev
      type: C-MTEB/VideoRetrieval
    metrics:
    - type: map_at_1
      value: 63.1
    - type: map_at_10
      value: 73.137
    - type: map_at_100
      value: 73.539
    - type: map_at_1000
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      value: 72.552
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    task:
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  - dataset:
      config: default
      name: MTEB Waimai
      revision: 339287def212450dcaa9df8c22bf93e9980c7023
      split: test
      type: C-MTEB/waimai-classification
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    task:
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  - dataset:
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      name: MTEB AlloProfClusteringP2P
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
      split: test
      type: lyon-nlp/alloprof
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    task:
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  - dataset:
      config: default
      name: MTEB AlloProfClusteringS2S
      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
      split: test
      type: lyon-nlp/alloprof
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  - dataset:
      config: default
      name: MTEB AlloprofReranking
      revision: 65393d0d7a08a10b4e348135e824f385d420b0fd
      split: test
      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
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    task:
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  - dataset:
      config: default
      name: MTEB AlloprofRetrieval
      revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
      split: test
      type: lyon-nlp/alloprof
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    - type: recall_at_1
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    task:
      type: Retrieval
  - dataset:
      config: fr
      name: MTEB AmazonReviewsClassification (fr)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
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      value: 54.46705535013317
    - type: main_score
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    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BSARDRetrieval
      revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
      split: test
      type: maastrichtlawtech/bsard
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      value: 28.358433127289974
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      value: 18.889080152631095
    - type: nauc_recall_at_5_std
      value: 12.221319698087767
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    - type: ndcg_at_10
      value: 28.524
    - type: ndcg_at_100
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    - type: ndcg_at_1000
      value: 36.012
    - type: ndcg_at_20
      value: 30.820999999999998
    - type: ndcg_at_3
      value: 22.721
    - type: ndcg_at_5
      value: 26.596999999999998
    - type: precision_at_1
      value: 17.116999999999997
    - type: precision_at_10
      value: 4.234
    - type: precision_at_100
      value: 0.658
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_20
      value: 2.568
    - type: precision_at_3
      value: 9.009
    - type: precision_at_5
      value: 7.297
    - type: recall_at_1
      value: 17.116999999999997
    - type: recall_at_10
      value: 42.342
    - type: recall_at_100
      value: 65.766
    - type: recall_at_1000
      value: 86.036
    - type: recall_at_20
      value: 51.351
    - type: recall_at_3
      value: 27.027
    - type: recall_at_5
      value: 36.486000000000004
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB HALClusteringS2S
      revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
      split: test
      type: lyon-nlp/clustering-hal-s2s
    metrics:
    - type: main_score
      value: 28.18744772954557
    - type: v_measure
      value: 28.18744772954557
    - type: v_measure_std
      value: 3.239838057506439
    task:
      type: Clustering
  - dataset:
      config: fr
      name: MTEB MLSUMClusteringP2P (fr)
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
      split: test
      type: reciTAL/mlsum
    metrics:
    - type: main_score
      value: 47.75009059283003
    - type: v_measure
      value: 47.75009059283003
    - type: v_measure_std
      value: 2.009277732690298
    task:
      type: Clustering
  - dataset:
      config: fr
      name: MTEB MLSUMClusteringS2S (fr)
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
      split: test
      type: reciTAL/mlsum
    metrics:
    - type: main_score
      value: 47.46091989113078
    - type: v_measure
      value: 47.46091989113078
    - type: v_measure_std
      value: 2.604802270948194
    task:
      type: Clustering
  - dataset:
      config: fr
      name: MTEB MTOPDomainClassification (fr)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 97.20325712496086
    - type: f1
      value: 97.05991090368462
    - type: f1_weighted
      value: 97.20748006323807
    - type: main_score
      value: 97.20325712496086
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MTOPIntentClassification (fr)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 93.07234575634199
    - type: f1
      value: 76.54521288506878
    - type: f1_weighted
      value: 93.6903586431893
    - type: main_score
      value: 93.07234575634199
    task:
      type: Classification
  - dataset:
      config: fra
      name: MTEB MasakhaNEWSClassification (fra)
      revision: 18193f187b92da67168c655c9973a165ed9593dd
      split: test
      type: mteb/masakhanews
    metrics:
    - type: accuracy
      value: 82.48815165876778
    - type: f1
      value: 78.71164464238117
    - type: f1_weighted
      value: 82.38927389376973
    - type: main_score
      value: 82.48815165876778
    task:
      type: Classification
  - dataset:
      config: fra
      name: MTEB MasakhaNEWSClusteringP2P (fra)
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
      split: test
      type: masakhane/masakhanews
    metrics:
    - type: main_score
      value: 73.85712952800003
    - type: v_measure
      value: 73.85712952800003
    - type: v_measure_std
      value: 22.471668299794416
    task:
      type: Clustering
  - dataset:
      config: fra
      name: MTEB MasakhaNEWSClusteringS2S (fra)
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
      split: test
      type: masakhane/masakhanews
    metrics:
    - type: main_score
      value: 67.23960512566751
    - type: v_measure
      value: 67.23960512566751
    - type: v_measure_std
      value: 24.65079601360142
    task:
      type: Clustering
  - dataset:
      config: fr
      name: MTEB MassiveIntentClassification (fr)
      revision: 4672e20407010da34463acc759c162ca9734bca6
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 79.59986550100874
    - type: f1
      value: 76.0439154517916
    - type: f1_weighted
      value: 79.48538292013761
    - type: main_score
      value: 79.59986550100874
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MassiveScenarioClassification (fr)
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 82.182246133154
    - type: f1
      value: 81.68006668655397
    - type: f1_weighted
      value: 81.94775072858566
    - type: main_score
      value: 82.182246133154
    task:
      type: Classification
  - dataset:
      config: fr
      name: MTEB MintakaRetrieval (fr)
      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
      split: test
      type: jinaai/mintakaqa
    metrics:
    - type: main_score
      value: 62.532
    - type: map_at_1
      value: 45.823
    - type: map_at_10
      value: 57.174
    - type: map_at_100
      value: 57.735
    - type: map_at_1000
      value: 57.767
    - type: map_at_20
      value: 57.53
    - type: map_at_3
      value: 54.716
    - type: map_at_5
      value: 56.227000000000004
    - type: mrr_at_1
      value: 45.82309582309582
    - type: mrr_at_10
      value: 57.17958217958217
    - type: mrr_at_100
      value: 57.744059413627866
    - type: mrr_at_1000
      value: 57.776651992832605
    - type: mrr_at_20
      value: 57.53890924556554
    - type: mrr_at_3
      value: 54.716079716079676
    - type: mrr_at_5
      value: 56.227136227136256
    - type: nauc_map_at_1000_diff1
      value: 39.48401851944296
    - type: nauc_map_at_1000_max
      value: 36.55276875160682
    - type: nauc_map_at_1000_std
      value: 3.9173787361040913
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      value: 3.9506714061766557
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      value: 39.31548009319837
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      value: 36.75711871602276
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      value: 3.782911249250981
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      value: 44.190649439568766
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      value: 31.017419446234317
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      value: 0.5544388561183956
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      value: 39.443640617310585
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      value: 36.63799366674228
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      value: 3.934276303386171
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      value: 40.30871768246873
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      value: 36.944169455458656
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      value: 2.9847330185694556
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      value: 39.590461060438095
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      value: 36.998781454405574
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      value: 3.532693606637119
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      value: 36.56900606103558
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      value: 3.972436075561705
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      value: 39.43269261665982
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      value: 36.574081599242014
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      value: 4.006374171904806
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      value: 39.29970560564493
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      value: 36.778388879484716
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      value: 3.8335456201567206
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      value: 31.017419446234317
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      value: 0.5544388561183956
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      value: 39.42091158484574
    - type: nauc_mrr_at_20_max
      value: 36.65421566061936
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      value: 3.988695948848555
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      value: 40.313976315898195
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      value: 36.960483501441985
    - type: nauc_mrr_at_3_std
      value: 3.0112756156560394
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      value: 39.56386294620379
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      value: 37.02119815939672
    - type: nauc_mrr_at_5_std
      value: 3.6118004205573184
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      value: 37.41178875860201
    - type: nauc_ndcg_at_1000_std
      value: 5.525420555163393
    - type: nauc_ndcg_at_100_diff1
      value: 37.18408005856676
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      value: 37.617851212997685
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      value: 6.871461890669446
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      value: 36.624444841382484
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      value: 38.62100324849529
    - type: nauc_ndcg_at_10_std
      value: 6.027810657475449
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      value: 44.190649439568766
    - type: nauc_ndcg_at_1_max
      value: 31.017419446234317
    - type: nauc_ndcg_at_1_std
      value: 0.5544388561183956
    - type: nauc_ndcg_at_20_diff1
      value: 37.057047514121564
    - type: nauc_ndcg_at_20_max
      value: 38.19839331454421
    - type: nauc_ndcg_at_20_std
      value: 6.770369938343684
    - type: nauc_ndcg_at_3_diff1
      value: 38.95821428563954
    - type: nauc_ndcg_at_3_max
      value: 38.87440219376017
    - type: nauc_ndcg_at_3_std
      value: 4.097498274708613
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      value: 37.515589837182034
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      value: 39.165561493023276
    - type: nauc_ndcg_at_5_std
      value: 5.291512124344874
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      value: -13.365474882749279
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      value: 50.68568417959442
    - type: nauc_precision_at_1000_std
      value: 37.847145129019054
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      value: 12.081443207482383
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      value: 43.67561356191485
    - type: nauc_precision_at_100_std
      value: 44.64523987759538
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      value: 23.20358204183261
    - type: nauc_precision_at_10_max
      value: 46.93706139285088
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      value: 17.36243956517301
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      value: 44.190649439568766
    - type: nauc_precision_at_1_max
      value: 31.017419446234317
    - type: nauc_precision_at_1_std
      value: 0.5544388561183956
    - type: nauc_precision_at_20_diff1
      value: 22.42836999246196
    - type: nauc_precision_at_20_max
      value: 46.29381413041759
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      value: 26.126609401922696
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      value: 34.503018704702484
    - type: nauc_precision_at_3_max
      value: 45.194775358016095
    - type: nauc_precision_at_3_std
      value: 7.864444241838433
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      value: 29.494641243672138
    - type: nauc_precision_at_5_max
      value: 47.326071718857484
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      value: 12.273738036245172
    - type: nauc_recall_at_1000_diff1
      value: -13.365474882756335
    - type: nauc_recall_at_1000_max
      value: 50.68568417959348
    - type: nauc_recall_at_1000_std
      value: 37.8471451290128
    - type: nauc_recall_at_100_diff1
      value: 12.08144320748251
    - type: nauc_recall_at_100_max
      value: 43.675613561914986
    - type: nauc_recall_at_100_std
      value: 44.645239877595564
    - type: nauc_recall_at_10_diff1
      value: 23.203582041832526
    - type: nauc_recall_at_10_max
      value: 46.9370613928509
    - type: nauc_recall_at_10_std
      value: 17.36243956517297
    - type: nauc_recall_at_1_diff1
      value: 44.190649439568766
    - type: nauc_recall_at_1_max
      value: 31.017419446234317
    - type: nauc_recall_at_1_std
      value: 0.5544388561183956
    - type: nauc_recall_at_20_diff1
      value: 22.42836999246212
    - type: nauc_recall_at_20_max
      value: 46.29381413041773
    - type: nauc_recall_at_20_std
      value: 26.12660940192268
    - type: nauc_recall_at_3_diff1
      value: 34.50301870470248
    - type: nauc_recall_at_3_max
      value: 45.19477535801611
    - type: nauc_recall_at_3_std
      value: 7.8644442418384335
    - type: nauc_recall_at_5_diff1
      value: 29.494641243672216
    - type: nauc_recall_at_5_max
      value: 47.32607171885759
    - type: nauc_recall_at_5_std
      value: 12.273738036245142
    - type: ndcg_at_1
      value: 45.823
    - type: ndcg_at_10
      value: 62.532
    - type: ndcg_at_100
      value: 65.298
    - type: ndcg_at_1000
      value: 66.214
    - type: ndcg_at_20
      value: 63.82600000000001
    - type: ndcg_at_3
      value: 57.528999999999996
    - type: ndcg_at_5
      value: 60.24
    - type: precision_at_1
      value: 45.823
    - type: precision_at_10
      value: 7.928
    - type: precision_at_100
      value: 0.923
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.22
    - type: precision_at_3
      value: 21.881
    - type: precision_at_5
      value: 14.438999999999998
    - type: recall_at_1
      value: 45.823
    - type: recall_at_10
      value: 79.279
    - type: recall_at_100
      value: 92.301
    - type: recall_at_1000
      value: 99.631
    - type: recall_at_20
      value: 84.398
    - type: recall_at_3
      value: 65.643
    - type: recall_at_5
      value: 72.195
    task:
      type: Retrieval
  - dataset:
      config: fr
      name: MTEB OpusparcusPC (fr)
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
      split: test
      type: GEM/opusparcus
    metrics:
    - type: cosine_accuracy
      value: 99.90069513406156
    - type: cosine_accuracy_threshold
      value: 54.45001207375879
    - type: cosine_ap
      value: 100.0
    - type: cosine_f1
      value: 99.95032290114257
    - type: cosine_f1_threshold
      value: 54.45001207375879
    - type: cosine_precision
      value: 100.0
    - type: cosine_recall
      value: 99.90069513406156
    - type: dot_accuracy
      value: 99.90069513406156
    - type: dot_accuracy_threshold
      value: 1312800.0
    - type: dot_ap
      value: 100.0
    - type: dot_f1
      value: 99.95032290114257
    - type: dot_f1_threshold
      value: 1312800.0
    - type: dot_precision
      value: 100.0
    - type: dot_recall
      value: 99.90069513406156
    - type: euclidean_accuracy
      value: 99.90069513406156
    - type: euclidean_accuracy_threshold
      value: 15150.791732002876
    - type: euclidean_ap
      value: 100.0
    - type: euclidean_f1
      value: 99.95032290114257
    - type: euclidean_f1_threshold
      value: 15150.791732002876
    - type: euclidean_precision
      value: 100.0
    - type: euclidean_recall
      value: 99.90069513406156
    - type: main_score
      value: 100.0
    - type: manhattan_accuracy
      value: 99.90069513406156
    - type: manhattan_accuracy_threshold
      value: 717903.2791554928
    - type: manhattan_ap
      value: 100.0
    - type: manhattan_f1
      value: 99.95032290114257
    - type: manhattan_f1_threshold
      value: 717903.2791554928
    - type: manhattan_precision
      value: 100.0
    - type: manhattan_recall
      value: 99.90069513406156
    - type: max_ap
      value: 100.0
    - type: max_f1
      value: 99.95032290114257
    - type: max_precision
      value: 100.0
    - type: max_recall
      value: 99.90069513406156
    - type: similarity_accuracy
      value: 99.90069513406156
    - type: similarity_accuracy_threshold
      value: 54.45001207375879
    - type: similarity_ap
      value: 100.0
    - type: similarity_f1
      value: 99.95032290114257
    - type: similarity_f1_threshold
      value: 54.45001207375879
    - type: similarity_precision
      value: 100.0
    - type: similarity_recall
      value: 99.90069513406156
    task:
      type: PairClassification
  - dataset:
      config: fr
      name: MTEB PawsXPairClassification (fr)
      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
      split: test
      type: google-research-datasets/paws-x
    metrics:
    - type: cosine_accuracy
      value: 67.95
    - type: cosine_accuracy_threshold
      value: 97.36901285947026
    - type: cosine_ap
      value: 70.14158727060726
    - type: cosine_f1
      value: 65.38108356290174
    - type: cosine_f1_threshold
      value: 94.90683744884689
    - type: cosine_precision
      value: 55.84313725490196
    - type: cosine_recall
      value: 78.8482834994463
    - type: dot_accuracy
      value: 60.5
    - type: dot_accuracy_threshold
      value: 2606400.0
    - type: dot_ap
      value: 57.0114505567262
    - type: dot_f1
      value: 63.29394387001477
    - type: dot_f1_threshold
      value: 2345600.0
    - type: dot_precision
      value: 47.4792243767313
    - type: dot_recall
      value: 94.90586932447398
    - type: euclidean_accuracy
      value: 68.05
    - type: euclidean_accuracy_threshold
      value: 3824.99743197985
    - type: euclidean_ap
      value: 70.01158306654237
    - type: euclidean_f1
      value: 65.21939953810623
    - type: euclidean_f1_threshold
      value: 5187.47968966464
    - type: euclidean_precision
      value: 55.942947702060216
    - type: euclidean_recall
      value: 78.18383167220377
    - type: main_score
      value: 70.14158727060726
    - type: manhattan_accuracy
      value: 68.05
    - type: manhattan_accuracy_threshold
      value: 191852.34832763672
    - type: manhattan_ap
      value: 70.01670033904287
    - type: manhattan_f1
      value: 65.2854511970534
    - type: manhattan_f1_threshold
      value: 246807.1710705757
    - type: manhattan_precision
      value: 55.87076438140268
    - type: manhattan_recall
      value: 78.51605758582502
    - type: max_ap
      value: 70.14158727060726
    - type: max_f1
      value: 65.38108356290174
    - type: max_precision
      value: 55.942947702060216
    - type: max_recall
      value: 94.90586932447398
    - type: similarity_accuracy
      value: 67.95
    - type: similarity_accuracy_threshold
      value: 97.36901285947026
    - type: similarity_ap
      value: 70.14158727060726
    - type: similarity_f1
      value: 65.38108356290174
    - type: similarity_f1_threshold
      value: 94.90683744884689
    - type: similarity_precision
      value: 55.84313725490196
    - type: similarity_recall
      value: 78.8482834994463
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB SICKFr
      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
      split: test
      type: Lajavaness/SICK-fr
    metrics:
    - type: cosine_pearson
      value: 79.79861486027
    - type: cosine_spearman
      value: 79.3918786992987
    - type: euclidean_pearson
      value: 77.73226212475764
    - type: euclidean_spearman
      value: 79.08856888397014
    - type: main_score
      value: 79.3918786992987
    - type: manhattan_pearson
      value: 77.8002206650809
    - type: manhattan_spearman
      value: 79.15284532531264
    - type: pearson
      value: 79.79861486027
    - type: spearman
      value: 79.3918786992987
    task:
      type: STS
  - dataset:
      config: fr
      name: MTEB STS22 (fr)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 83.32314025534286
    - type: cosine_spearman
      value: 83.2806004701507
    - type: euclidean_pearson
      value: 81.88040500817269
    - type: euclidean_spearman
      value: 82.73179823676206
    - type: main_score
      value: 83.2806004701507
    - type: manhattan_pearson
      value: 82.0438174605579
    - type: manhattan_spearman
      value: 83.0253049811576
    - type: pearson
      value: 83.32314025534286
    - type: spearman
      value: 83.2806004701507
    task:
      type: STS
  - dataset:
      config: fr
      name: MTEB STSBenchmarkMultilingualSTS (fr)
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
      split: test
      type: mteb/stsb_multi_mt
    metrics:
    - type: cosine_pearson
      value: 84.56723075054445
    - type: cosine_spearman
      value: 85.08759191551403
    - type: euclidean_pearson
      value: 83.186096744725
    - type: euclidean_spearman
      value: 84.36958569816491
    - type: main_score
      value: 85.08759191551403
    - type: manhattan_pearson
      value: 83.1405072165467
    - type: manhattan_spearman
      value: 84.34227830781155
    - type: pearson
      value: 84.56723075054445
    - type: spearman
      value: 85.08759191551403
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SummEvalFr
      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
      split: test
      type: lyon-nlp/summarization-summeval-fr-p2p
    metrics:
    - type: cosine_pearson
      value: 31.921764332449115
    - type: cosine_spearman
      value: 31.260442997631806
    - type: dot_pearson
      value: 31.585578707631406
    - type: dot_spearman
      value: 31.479238746310028
    - type: main_score
      value: 31.260442997631806
    - type: pearson
      value: 31.921764332449115
    - type: spearman
      value: 31.260442997631806
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB SyntecReranking
      revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
      split: test
      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
    metrics:
    - type: main_score
      value: 91.83333333333333
    - type: map
      value: 91.83333333333333
    - type: mrr
      value: 92.0
    - type: nAUC_map_diff1
      value: 53.97793263646914
    - type: nAUC_map_max
      value: 44.264158743282195
    - type: nAUC_map_std
      value: 14.692218350754885
    - type: nAUC_mrr_diff1
      value: 54.36926882239366
    - type: nAUC_mrr_max
      value: 46.43108510296003
    - type: nAUC_mrr_std
      value: 17.48914092664096
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SyntecRetrieval
      revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
      split: test
      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
    metrics:
    - type: main_score
      value: 90.36699999999999
    - type: map_at_1
      value: 79.0
    - type: map_at_10
      value: 87.18599999999999
    - type: map_at_100
      value: 87.18599999999999
    - type: map_at_1000
      value: 87.18599999999999
    - type: map_at_20
      value: 87.18599999999999
    - type: map_at_3
      value: 86.0
    - type: map_at_5
      value: 86.95
    - type: mrr_at_1
      value: 79.0
    - type: mrr_at_10
      value: 87.18611111111112
    - type: mrr_at_100
      value: 87.18611111111112
    - type: mrr_at_1000
      value: 87.18611111111112
    - type: mrr_at_20
      value: 87.18611111111112
    - type: mrr_at_3
      value: 86.0
    - type: mrr_at_5
      value: 86.95
    - type: nauc_map_at_1000_diff1
      value: 63.05539428169271
    - type: nauc_map_at_1000_max
      value: 45.428107132447124
    - type: nauc_map_at_1000_std
      value: 13.94507583970834
    - type: nauc_map_at_100_diff1
      value: 63.05539428169271
    - type: nauc_map_at_100_max
      value: 45.428107132447124
    - type: nauc_map_at_100_std
      value: 13.94507583970834
    - type: nauc_map_at_10_diff1
      value: 63.05539428169271
    - type: nauc_map_at_10_max
      value: 45.428107132447124
    - type: nauc_map_at_10_std
      value: 13.94507583970834
    - type: nauc_map_at_1_diff1
      value: 64.24122923028831
    - type: nauc_map_at_1_max
      value: 44.34077957053877
    - type: nauc_map_at_1_std
      value: 9.594344386466878
    - type: nauc_map_at_20_diff1
      value: 63.05539428169271
    - type: nauc_map_at_20_max
      value: 45.428107132447124
    - type: nauc_map_at_20_std
      value: 13.94507583970834
    - type: nauc_map_at_3_diff1
      value: 62.30831315577075
    - type: nauc_map_at_3_max
      value: 47.33980193586779
    - type: nauc_map_at_3_std
      value: 16.132624025733
    - type: nauc_map_at_5_diff1
      value: 63.079622378971834
    - type: nauc_map_at_5_max
      value: 45.13424437707254
    - type: nauc_map_at_5_std
      value: 13.730785051570013
    - type: nauc_mrr_at_1000_diff1
      value: 63.05539428169271
    - type: nauc_mrr_at_1000_max
      value: 45.428107132447124
    - type: nauc_mrr_at_1000_std
      value: 13.94507583970834
    - type: nauc_mrr_at_100_diff1
      value: 63.05539428169271
    - type: nauc_mrr_at_100_max
      value: 45.428107132447124
    - type: nauc_mrr_at_100_std
      value: 13.94507583970834
    - type: nauc_mrr_at_10_diff1
      value: 63.05539428169271
    - type: nauc_mrr_at_10_max
      value: 45.428107132447124
    - type: nauc_mrr_at_10_std
      value: 13.94507583970834
    - type: nauc_mrr_at_1_diff1
      value: 64.24122923028831
    - type: nauc_mrr_at_1_max
      value: 44.34077957053877
    - type: nauc_mrr_at_1_std
      value: 9.594344386466878
    - type: nauc_mrr_at_20_diff1
      value: 63.05539428169271
    - type: nauc_mrr_at_20_max
      value: 45.428107132447124
    - type: nauc_mrr_at_20_std
      value: 13.94507583970834
    - type: nauc_mrr_at_3_diff1
      value: 62.30831315577075
    - type: nauc_mrr_at_3_max
      value: 47.33980193586779
    - type: nauc_mrr_at_3_std
      value: 16.132624025733
    - type: nauc_mrr_at_5_diff1
      value: 63.079622378971834
    - type: nauc_mrr_at_5_max
      value: 45.13424437707254
    - type: nauc_mrr_at_5_std
      value: 13.730785051570013
    - type: nauc_ndcg_at_1000_diff1
      value: 62.97376441474187
    - type: nauc_ndcg_at_1000_max
      value: 45.457846840130586
    - type: nauc_ndcg_at_1000_std
      value: 14.17695491254452
    - type: nauc_ndcg_at_100_diff1
      value: 62.97376441474187
    - type: nauc_ndcg_at_100_max
      value: 45.457846840130586
    - type: nauc_ndcg_at_100_std
      value: 14.17695491254452
    - type: nauc_ndcg_at_10_diff1
      value: 62.97376441474187
    - type: nauc_ndcg_at_10_max
      value: 45.457846840130586
    - type: nauc_ndcg_at_10_std
      value: 14.17695491254452
    - type: nauc_ndcg_at_1_diff1
      value: 64.24122923028831
    - type: nauc_ndcg_at_1_max
      value: 44.34077957053877
    - type: nauc_ndcg_at_1_std
      value: 9.594344386466878
    - type: nauc_ndcg_at_20_diff1
      value: 62.97376441474187
    - type: nauc_ndcg_at_20_max
      value: 45.457846840130586
    - type: nauc_ndcg_at_20_std
      value: 14.17695491254452
    - type: nauc_ndcg_at_3_diff1
      value: 61.47043349797183
    - type: nauc_ndcg_at_3_max
      value: 49.12165820225059
    - type: nauc_ndcg_at_3_std
      value: 18.525396343409568
    - type: nauc_ndcg_at_5_diff1
      value: 63.04022063936115
    - type: nauc_ndcg_at_5_max
      value: 44.381937619091765
    - type: nauc_ndcg_at_5_std
      value: 13.3263412698325
    - type: nauc_precision_at_1000_diff1
      value: .nan
    - type: nauc_precision_at_1000_max
      value: .nan
    - type: nauc_precision_at_1000_std
      value: .nan
    - type: nauc_precision_at_100_diff1
      value: .nan
    - type: nauc_precision_at_100_max
      value: .nan
    - type: nauc_precision_at_100_std
      value: .nan
    - type: nauc_precision_at_10_diff1
      value: 100.0
    - type: nauc_precision_at_10_max
      value: 100.0
    - type: nauc_precision_at_10_std
      value: 100.0
    - type: nauc_precision_at_1_diff1
      value: 64.24122923028831
    - type: nauc_precision_at_1_max
      value: 44.34077957053877
    - type: nauc_precision_at_1_std
      value: 9.594344386466878
    - type: nauc_precision_at_20_diff1
      value: 100.0
    - type: nauc_precision_at_20_max
      value: 100.0
    - type: nauc_precision_at_20_std
      value: 100.0
    - type: nauc_precision_at_3_diff1
      value: 56.27917833800158
    - type: nauc_precision_at_3_max
      value: 60.51976346093969
    - type: nauc_precision_at_3_std
      value: 33.02209772798002
    - type: nauc_precision_at_5_diff1
      value: 63.81886087768404
    - type: nauc_precision_at_5_max
      value: 27.544351073763345
    - type: nauc_precision_at_5_std
      value: -0.4668534080301362
    - type: nauc_recall_at_1000_diff1
      value: .nan
    - type: nauc_recall_at_1000_max
      value: .nan
    - type: nauc_recall_at_1000_std
      value: .nan
    - type: nauc_recall_at_100_diff1
      value: .nan
    - type: nauc_recall_at_100_max
      value: .nan
    - type: nauc_recall_at_100_std
      value: .nan
    - type: nauc_recall_at_10_diff1
      value: .nan
    - type: nauc_recall_at_10_max
      value: .nan
    - type: nauc_recall_at_10_std
      value: .nan
    - type: nauc_recall_at_1_diff1
      value: 64.24122923028831
    - type: nauc_recall_at_1_max
      value: 44.34077957053877
    - type: nauc_recall_at_1_std
      value: 9.594344386466878
    - type: nauc_recall_at_20_diff1
      value: .nan
    - type: nauc_recall_at_20_max
      value: .nan
    - type: nauc_recall_at_20_std
      value: .nan
    - type: nauc_recall_at_3_diff1
      value: 56.27917833800187
    - type: nauc_recall_at_3_max
      value: 60.51976346094
    - type: nauc_recall_at_3_std
      value: 33.022097727980125
    - type: nauc_recall_at_5_diff1
      value: 63.81886087768457
    - type: nauc_recall_at_5_max
      value: 27.544351073763107
    - type: nauc_recall_at_5_std
      value: -0.46685340803013775
    - type: ndcg_at_1
      value: 79.0
    - type: ndcg_at_10
      value: 90.36699999999999
    - type: ndcg_at_100
      value: 90.36699999999999
    - type: ndcg_at_1000
      value: 90.36699999999999
    - type: ndcg_at_20
      value: 90.36699999999999
    - type: ndcg_at_3
      value: 88.071
    - type: ndcg_at_5
      value: 89.75
    - type: precision_at_1
      value: 79.0
    - type: precision_at_10
      value: 10.0
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 5.0
    - type: precision_at_3
      value: 31.333
    - type: precision_at_5
      value: 19.6
    - type: recall_at_1
      value: 79.0
    - type: recall_at_10
      value: 100.0
    - type: recall_at_100
      value: 100.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 100.0
    - type: recall_at_3
      value: 94.0
    - type: recall_at_5
      value: 98.0
    task:
      type: Retrieval
  - dataset:
      config: fra-fra
      name: MTEB XPQARetrieval (fr)
      revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
      split: test
      type: jinaai/xpqa
    metrics:
    - type: main_score
      value: 77.425
    - type: map_at_1
      value: 46.749
    - type: map_at_10
      value: 72.108
    - type: map_at_100
      value: 73.32499999999999
    - type: map_at_1000
      value: 73.341
    - type: map_at_20
      value: 72.991
    - type: map_at_3
      value: 65.09
    - type: map_at_5
      value: 70.137
    - type: mrr_at_1
      value: 71.82910547396529
    - type: mrr_at_10
      value: 78.63357492529722
    - type: mrr_at_100
      value: 78.97374961354801
    - type: mrr_at_1000
      value: 78.97840549855806
    - type: mrr_at_20
      value: 78.86005025292395
    - type: mrr_at_3
      value: 77.28081886960389
    - type: mrr_at_5
      value: 78.0551846906987
    - type: nauc_map_at_1000_diff1
      value: 57.508397030020156
    - type: nauc_map_at_1000_max
      value: 43.80251983780665
    - type: nauc_map_at_1000_std
      value: -16.231491160419434
    - type: nauc_map_at_100_diff1
      value: 57.48614844875469
    - type: nauc_map_at_100_max
      value: 43.797011627763055
    - type: nauc_map_at_100_std
      value: -16.239303348969592
    - type: nauc_map_at_10_diff1
      value: 57.254064849553934
    - type: nauc_map_at_10_max
      value: 42.765535577219026
    - type: nauc_map_at_10_std
      value: -17.255606315997156
    - type: nauc_map_at_1_diff1
      value: 65.04324659040175
    - type: nauc_map_at_1_max
      value: 17.852220653388855
    - type: nauc_map_at_1_std
      value: -14.257753661018779
    - type: nauc_map_at_20_diff1
      value: 57.48367588324867
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      value: 43.680084254814425
    - type: nauc_map_at_20_std
      value: -16.59381108810359
    - type: nauc_map_at_3_diff1
      value: 58.328817274958276
    - type: nauc_map_at_3_max
      value: 34.603370607250675
    - type: nauc_map_at_3_std
      value: -15.326569334165047
    - type: nauc_map_at_5_diff1
      value: 57.544271139796365
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      value: 41.58159814532708
    - type: nauc_map_at_5_std
      value: -17.035562345654515
    - type: nauc_mrr_at_1000_diff1
      value: 67.23053035385993
    - type: nauc_mrr_at_1000_max
      value: 53.982556981667095
    - type: nauc_mrr_at_1000_std
      value: -12.015571062417035
    - type: nauc_mrr_at_100_diff1
      value: 67.23047293440347
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      value: 53.97931489747768
    - type: nauc_mrr_at_100_std
      value: -12.026957248146365
    - type: nauc_mrr_at_10_diff1
      value: 67.25927907237941
    - type: nauc_mrr_at_10_max
      value: 53.99647347811833
    - type: nauc_mrr_at_10_std
      value: -12.356365137919108
    - type: nauc_mrr_at_1_diff1
      value: 67.80552098159194
    - type: nauc_mrr_at_1_max
      value: 52.34740974885752
    - type: nauc_mrr_at_1_std
      value: -9.009347371853096
    - type: nauc_mrr_at_20_diff1
      value: 67.22472566769486
    - type: nauc_mrr_at_20_max
      value: 54.03480374123263
    - type: nauc_mrr_at_20_std
      value: -12.129416933895373
    - type: nauc_mrr_at_3_diff1
      value: 66.86636026044627
    - type: nauc_mrr_at_3_max
      value: 53.84675762408544
    - type: nauc_mrr_at_3_std
      value: -12.318414220208327
    - type: nauc_mrr_at_5_diff1
      value: 67.16713697443882
    - type: nauc_mrr_at_5_max
      value: 54.174275682276765
    - type: nauc_mrr_at_5_std
      value: -12.382704200660772
    - type: nauc_ndcg_at_1000_diff1
      value: 60.076768803793875
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    task:
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  - dataset:
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      revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6
      split: test
      type: PL-MTEB/allegro-reviews
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    - type: main_score
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    task:
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  - dataset:
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      revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
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      type: clarin-knext/arguana-pl
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    - type: recall_at_3
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    task:
      type: Retrieval
  - dataset:
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      revision: 36ddb419bcffe6a5374c3891957912892916f28d
      split: test
      type: PL-MTEB/cbd
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    task:
      type: Classification
  - dataset:
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      revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d
      split: test
      type: PL-MTEB/cdsce-pairclassification
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    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB CDSC-R
      revision: 1cd6abbb00df7d14be3dbd76a7dcc64b3a79a7cd
      split: test
      type: PL-MTEB/cdscr-sts
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    task:
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  - dataset:
      config: default
      name: MTEB DBPedia-PL
      revision: 76afe41d9af165cc40999fcaa92312b8b012064a
      split: test
      type: clarin-knext/dbpedia-pl
    metrics:
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      value: 43.189
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  - dataset:
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  - dataset:
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      type: clarin-knext/nfcorpus-pl
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    task:
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  - dataset:
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    - type: recall_at_3
      value: 57.484
    - type: recall_at_5
      value: 66.476
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB PAC
      revision: None
      split: test
      type: laugustyniak/abusive-clauses-pl
    metrics:
    - type: accuracy
      value: 67.24297712134376
    - type: accuracy_stderr
      value: 4.77558207347837
    - type: ap
      value: 77.38171975466854
    - type: ap_stderr
      value: 2.5801970175320394
    - type: f1
      value: 65.21823897814332
    - type: f1_stderr
      value: 4.317111734308895
    - type: main_score
      value: 67.24297712134376
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PSC
      revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
      split: test
      type: PL-MTEB/psc-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 97.95918367346938
    - type: cosine_accuracy_threshold
      value: 59.87724328133361
    - type: cosine_ap
      value: 99.24498625606927
    - type: cosine_f1
      value: 96.6867469879518
    - type: cosine_f1_threshold
      value: 59.87724328133361
    - type: cosine_precision
      value: 95.53571428571429
    - type: cosine_recall
      value: 97.86585365853658
    - type: dot_accuracy
      value: 98.51576994434137
    - type: dot_accuracy_threshold
      value: 1574400.0
    - type: dot_ap
      value: 99.28566232682996
    - type: dot_f1
      value: 97.57575757575758
    - type: dot_f1_threshold
      value: 1564800.0
    - type: dot_precision
      value: 96.98795180722891
    - type: dot_recall
      value: 98.17073170731707
    - type: euclidean_accuracy
      value: 97.6808905380334
    - type: euclidean_accuracy_threshold
      value: 14418.957939643331
    - type: euclidean_ap
      value: 99.0876340868033
    - type: euclidean_f1
      value: 96.24060150375941
    - type: euclidean_f1_threshold
      value: 14442.183182634264
    - type: euclidean_precision
      value: 94.95548961424333
    - type: euclidean_recall
      value: 97.5609756097561
    - type: main_score
      value: 99.28566232682996
    - type: manhattan_accuracy
      value: 97.86641929499072
    - type: manhattan_accuracy_threshold
      value: 681802.1857857704
    - type: manhattan_ap
      value: 99.08465290287205
    - type: manhattan_f1
      value: 96.52042360060513
    - type: manhattan_f1_threshold
      value: 681802.1857857704
    - type: manhattan_precision
      value: 95.7957957957958
    - type: manhattan_recall
      value: 97.2560975609756
    - type: max_ap
      value: 99.28566232682996
    - type: max_f1
      value: 97.57575757575758
    - type: max_precision
      value: 96.98795180722891
    - type: max_recall
      value: 98.17073170731707
    - type: similarity_accuracy
      value: 97.95918367346938
    - type: similarity_accuracy_threshold
      value: 59.87724328133361
    - type: similarity_ap
      value: 99.24498625606927
    - type: similarity_f1
      value: 96.6867469879518
    - type: similarity_f1_threshold
      value: 59.87724328133361
    - type: similarity_precision
      value: 95.53571428571429
    - type: similarity_recall
      value: 97.86585365853658
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB PolEmo2.0-IN
      revision: d90724373c70959f17d2331ad51fb60c71176b03
      split: test
      type: PL-MTEB/polemo2_in
    metrics:
    - type: accuracy
      value: 90.41551246537396
    - type: f1
      value: 89.15361039614409
    - type: f1_weighted
      value: 90.69893050097603
    - type: main_score
      value: 90.41551246537396
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PolEmo2.0-OUT
      revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4
      split: test
      type: PL-MTEB/polemo2_out
    metrics:
    - type: accuracy
      value: 77.77327935222672
    - type: f1
      value: 61.238079022455636
    - type: f1_weighted
      value: 80.58753601509183
    - type: main_score
      value: 77.77327935222672
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB PPC
      revision: None
      split: test
      type: PL-MTEB/ppc-pairclassification
    metrics:
    - type: cos_sim_accuracy
      value: 87.2
    - type: cos_sim_accuracy_threshold
      value: 83.69773167092553
    - type: cos_sim_ap
      value: 95.43345251568122
    - type: cos_sim_f1
      value: 89.82785602503913
    - type: cos_sim_f1_threshold
      value: 81.2116503074739
    - type: cos_sim_precision
      value: 85.16320474777447
    - type: cos_sim_recall
      value: 95.03311258278146
    - type: dot_accuracy
      value: 85.9
    - type: dot_accuracy_threshold
      value: 2177600.0
    - type: dot_ap
      value: 92.4192102018206
    - type: dot_f1
      value: 88.9238020424195
    - type: dot_f1_threshold
      value: 2163200.0
    - type: dot_precision
      value: 84.60388639760838
    - type: dot_recall
      value: 93.70860927152319
    - type: euclidean_accuracy
      value: 87.5
    - type: euclidean_accuracy_threshold
      value: 9325.450203438862
    - type: euclidean_ap
      value: 95.42730698295347
    - type: euclidean_f1
      value: 89.92747784045125
    - type: euclidean_f1_threshold
      value: 9325.450203438862
    - type: euclidean_precision
      value: 87.59811616954474
    - type: euclidean_recall
      value: 92.3841059602649
    - type: manhattan_accuracy
      value: 87.5
    - type: manhattan_accuracy_threshold
      value: 441412.88244724274
    - type: manhattan_ap
      value: 95.4277447451651
    - type: manhattan_f1
      value: 89.92747784045125
    - type: manhattan_f1_threshold
      value: 441412.88244724274
    - type: manhattan_precision
      value: 87.59811616954474
    - type: manhattan_recall
      value: 92.3841059602649
    - type: max_accuracy
      value: 87.5
    - type: max_ap
      value: 95.43345251568122
    - type: max_f1
      value: 89.92747784045125
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB Quora-PL
      revision: 0be27e93455051e531182b85e85e425aba12e9d4
      split: test
      type: clarin-knext/quora-pl
    metrics:
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      value: 84.47099999999999
    - type: map_at_1
      value: 65.892
    - type: map_at_10
      value: 80.11500000000001
    - type: map_at_100
      value: 80.861
    - type: map_at_1000
      value: 80.879
    - type: map_at_20
      value: 80.604
    - type: map_at_3
      value: 76.97
    - type: map_at_5
      value: 78.926
    - type: mrr_at_1
      value: 75.83
    - type: mrr_at_10
      value: 83.2125238095233
    - type: mrr_at_100
      value: 83.38714262504709
    - type: mrr_at_1000
      value: 83.38942088013238
    - type: mrr_at_20
      value: 83.34284466299037
    - type: mrr_at_3
      value: 81.95333333333281
    - type: mrr_at_5
      value: 82.78533333333272
    - type: nauc_map_at_1000_diff1
      value: 73.95721764018812
    - type: nauc_map_at_1000_max
      value: 9.653675847999432
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      value: -42.35408133902171
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      value: 73.96621756991526
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      value: 9.618124708373092
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      value: -42.41429680546156
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      value: 74.20643666348498
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      value: 9.056688996919677
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      value: -44.13396437616006
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      value: 77.18196114257519
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      value: 7.840648640771136
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      value: -39.84395715001256
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      value: 74.03475632514551
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      value: 9.385795565805118
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      value: -43.160299598965466
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      value: 74.43855921599284
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      value: 7.574218825911361
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      value: -46.1476276122436
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      value: 74.38688915461512
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      value: 8.557764506539128
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      value: -45.53897898458085
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      value: 74.0311045258841
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      value: 11.885448379701055
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      value: -38.16008409213179
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      value: 11.886356221882725
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      value: -38.159139191997795
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      value: 73.99521522874129
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      value: 11.77749620520773
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      value: -38.266295250166635
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      value: 12.979267595721275
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      value: -36.634066084632785
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      value: 74.01273934757484
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      value: 11.887566738728225
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      value: -38.169250252410485
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      value: 73.6073534511043
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      value: 11.450856365709727
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      value: -38.767141663073964
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      value: 73.84950218235583
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      value: 11.787394554048813
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      value: -38.57240589862417
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      value: 10.72929244202152
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      value: -39.92813917654933
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      value: 73.53904136553481
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      value: 10.569310211635521
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      value: -40.12206261908318
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      value: 73.55958917204208
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      value: 9.255791947077263
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      value: -42.7856138240991
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      value: 75.34289960079188
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      value: 13.499789436258705
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      value: -35.91483904818284
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      value: 73.48070745481307
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      value: 9.92427572953505
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      value: -41.55653404596579
    - type: nauc_ndcg_at_3_diff1
      value: 72.72072901275445
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      value: 8.303708237302729
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      value: -43.618531107389344
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      value: 73.30060059269601
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      value: 8.915386932153249
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      value: -44.088053429661
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      value: 42.39482890919027
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      value: 41.30693233869549
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      value: 13.499789436258705
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      value: -35.91483904818284
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      value: -36.75164419452007
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      value: 5.440757182282365
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      value: 33.08928025809355
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      value: 5.156636102003736
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      value: -0.9779263105110453
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      value: -19.92133198420086
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      value: 5.432766335564369
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      value: 11.417736295996392
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      value: 56.57663068186203
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      value: 25.80329039728696
    - type: nauc_recall_at_1000_std
      value: 57.82937604195464
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      value: 6.879939694351325
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      value: -30.098258041087096
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      value: 68.00694154421653
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      value: 0.7226814903576098
    - type: nauc_recall_at_10_std
      value: -52.980002751088215
    - type: nauc_recall_at_1_diff1
      value: 77.18196114257519
    - type: nauc_recall_at_1_max
      value: 7.840648640771136
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      value: -39.84395715001256
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      value: 69.83247207081557
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      value: 2.395588418833963
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      value: -52.11119790224493
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      value: 2.9185552604991716
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    - type: ndcg_at_1
      value: 75.92
    - type: ndcg_at_10
      value: 84.47099999999999
    - type: ndcg_at_100
      value: 86.11999999999999
    - type: ndcg_at_1000
      value: 86.276
    - type: ndcg_at_20
      value: 85.37599999999999
    - type: ndcg_at_3
      value: 81.0
    - type: ndcg_at_5
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    - type: precision_at_1
      value: 75.92
    - type: precision_at_10
      value: 12.987000000000002
    - type: precision_at_100
      value: 1.5190000000000001
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_20
      value: 6.977
    - type: precision_at_3
      value: 35.573
    - type: precision_at_5
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    - type: recall_at_1
      value: 65.892
    - type: recall_at_10
      value: 93.318
    - type: recall_at_100
      value: 99.124
    - type: recall_at_1000
      value: 99.92699999999999
    - type: recall_at_20
      value: 96.256
    - type: recall_at_3
      value: 83.69
    - type: recall_at_5
      value: 88.783
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SCIDOCS-PL
      revision: 45452b03f05560207ef19149545f168e596c9337
      split: test
      type: clarin-knext/scidocs-pl
    metrics:
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      value: 4.5280000000000005
    - type: map_at_10
      value: 11.649
    - type: map_at_100
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    - type: map_at_1000
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    - type: map_at_20
      value: 12.866
    - type: map_at_3
      value: 8.35
    - type: map_at_5
      value: 9.84
    - type: mrr_at_1
      value: 22.3
    - type: mrr_at_10
      value: 32.690039682539656
    - type: mrr_at_100
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    - type: mrr_at_1000
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    - type: mrr_at_3
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    - type: mrr_at_5
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    - type: nauc_map_at_1000_diff1
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    - type: precision_at_1
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    - type: recall_at_1
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    - type: recall_at_1000
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    - type: recall_at_20
      value: 28.28
    - type: recall_at_3
      value: 10.558
    - type: recall_at_5
      value: 14.148
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SICK-E-PL
      revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9
      split: test
      type: PL-MTEB/sicke-pl-pairclassification
    metrics:
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    - type: cosine_accuracy_threshold
      value: 89.01510631979949
    - type: cosine_ap
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    - type: cosine_f1_threshold
      value: 87.10908804245841
    - type: cosine_precision
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    - type: cosine_recall
      value: 79.77207977207978
    - type: dot_accuracy
      value: 83.9380350591113
    - type: dot_accuracy_threshold
      value: 2292800.0
    - type: dot_ap
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    - type: dot_f1
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    - type: dot_f1_threshold
      value: 2190400.0
    - type: dot_precision
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    - type: dot_recall
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    - type: euclidean_accuracy
      value: 87.89237668161435
    - type: euclidean_accuracy_threshold
      value: 7497.701400069587
    - type: euclidean_ap
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    - type: euclidean_f1_threshold
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    - type: euclidean_precision
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    - type: euclidean_recall
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    - type: manhattan_accuracy_threshold
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    - type: manhattan_f1_threshold
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    - type: manhattan_precision
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    - type: manhattan_recall
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    - type: max_ap
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    - type: max_f1
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    - type: max_precision
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    - type: max_recall
      value: 82.4074074074074
    - type: similarity_accuracy
      value: 87.50509580105992
    - type: similarity_accuracy_threshold
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    - type: similarity_ap
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    - type: similarity_f1
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    - type: similarity_f1_threshold
      value: 87.10908804245841
    - type: similarity_precision
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    - type: similarity_recall
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    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB SICK-R-PL
      revision: fd5c2441b7eeff8676768036142af4cfa42c1339
      split: test
      type: PL-MTEB/sickr-pl-sts
    metrics:
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    - type: cosine_spearman
      value: 78.15913085997471
    - type: euclidean_pearson
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    - type: euclidean_spearman
      value: 77.9122894221527
    - type: main_score
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    - type: manhattan_pearson
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    - type: manhattan_spearman
      value: 77.95971728547582
    - type: pearson
      value: 79.68602301743276
    - type: spearman
      value: 78.15913085997471
    task:
      type: STS
  - dataset:
      config: pl
      name: MTEB STS22 (pl)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
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      value: 42.01062393061261
    - type: cosine_spearman
      value: 42.79076406559122
    - type: euclidean_pearson
      value: 28.57786522106708
    - type: euclidean_spearman
      value: 42.51040813516686
    - type: main_score
      value: 42.79076406559122
    - type: manhattan_pearson
      value: 28.855884350706653
    - type: manhattan_spearman
      value: 42.77481125184737
    - type: pearson
      value: 42.01062393061261
    - type: spearman
      value: 42.79076406559122
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciFact-PL
      revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e
      split: test
      type: clarin-knext/scifact-pl
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      value: 59.494
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      value: 69.893
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      value: 70.45
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      value: 67.037
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      value: 68.777
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      value: 62.66666666666667
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    - type: ndcg_at_1
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    - type: ndcg_at_10
      value: 74.434
    - type: ndcg_at_100
      value: 76.655
    - type: ndcg_at_1000
      value: 77.08
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      value: 75.588
    - type: ndcg_at_3
      value: 69.75099999999999
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      value: 72.09100000000001
    - type: precision_at_1
      value: 62.666999999999994
    - type: precision_at_10
      value: 9.9
    - type: precision_at_100
      value: 1.097
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_20
      value: 5.2
    - type: precision_at_3
      value: 27.0
    - type: precision_at_5
      value: 17.933
    - type: recall_at_1
      value: 59.494
    - type: recall_at_10
      value: 87.13300000000001
    - type: recall_at_100
      value: 96.667
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 91.43299999999999
    - type: recall_at_3
      value: 74.461
    - type: recall_at_5
      value: 80.34400000000001
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB TRECCOVID-PL
      revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
      split: test
      type: clarin-knext/trec-covid-pl
    metrics:
    - type: main_score
      value: 82.749
    - type: map_at_1
      value: 0.20400000000000001
    - type: map_at_10
      value: 2.099
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    task:
      type: Retrieval