sentence-transformers feature-extraction sentence-similarity mteb text-classification arxiv:1910.09700 model-index region:us
---
pipeline_tag: text-classification
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: KE Sieve_model
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 79.05970149253731
    - type: ap
      value: 42.7075359884682
    - type: f1
      value: 72.99649470402085
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 70.193
    - type: ap
      value: 64.37171698026376
    - type: f1
      value: 69.99260638185035
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.288000000000004
    - type: f1
      value: 34.00390576721439
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 70.37283775714532
    - type: cos_sim_spearman
      value: 65.28702977793742
    - type: euclidean_pearson
      value: 68.81678452970543
    - type: euclidean_spearman
      value: 66.10212250382912
    - type: manhattan_pearson
      value: 70.06439132928513
    - type: manhattan_spearman
      value: 66.10212250382912
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.88961038961038
    - type: f1
      value: 75.71295362599926
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 40.26
    - type: f1
      value: 35.91571484611428
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 61.1396
    - type: ap
      value: 57.0336104684589
    - type: f1
      value: 60.711055351249385
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.21842225262198
    - type: f1
      value: 86.60570158294514
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 69.44824441404468
    - type: f1
      value: 51.1702284173121
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.60188298587761
    - type: f1
      value: 64.57658770410065
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.36987222595829
    - type: f1
      value: 70.34853403058946
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 78.1402991982508
    - type: cos_sim_spearman
      value: 76.01438891892613
    - type: euclidean_pearson
      value: 76.07791972310307
    - type: euclidean_spearman
      value: 76.4750927224088
    - type: manhattan_pearson
      value: 78.7022742184064
    - type: manhattan_spearman
      value: 76.4750927224088
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.41946856528065
    - type: cos_sim_spearman
      value: 71.2452368975646
    - type: euclidean_pearson
      value: 68.76119955717198
    - type: euclidean_spearman
      value: 70.40762520824568
    - type: manhattan_pearson
      value: 76.1638570991111
    - type: manhattan_spearman
      value: 70.40762520824568
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.86983630535461
    - type: cos_sim_spearman
      value: 78.39885607110992
    - type: euclidean_pearson
      value: 75.81565277674996
    - type: euclidean_spearman
      value: 78.70053430302474
    - type: manhattan_pearson
      value: 78.14484348028292
    - type: manhattan_spearman
      value: 78.70053430302474
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.52542250553228
    - type: cos_sim_spearman
      value: 74.23425444398934
    - type: euclidean_pearson
      value: 73.63790688920109
    - type: euclidean_spearman
      value: 74.14127580980806
    - type: manhattan_pearson
      value: 76.76724842158396
    - type: manhattan_spearman
      value: 74.14127580980806
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.9319282262523
    - type: cos_sim_spearman
      value: 81.40861373830771
    - type: euclidean_pearson
      value: 79.61339072348075
    - type: euclidean_spearman
      value: 82.1601716091385
    - type: manhattan_pearson
      value: 81.76770515821788
    - type: manhattan_spearman
      value: 82.1601716091385
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 78.83953330477087
    - type: cos_sim_spearman
      value: 79.1312883671738
    - type: euclidean_pearson
      value: 77.02068269010785
    - type: euclidean_spearman
      value: 78.85332564873545
    - type: manhattan_pearson
      value: 78.66151014252961
    - type: manhattan_spearman
      value: 78.85332564873545
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 77.06164373590121
    - type: cos_sim_spearman
      value: 76.99890844656588
    - type: euclidean_pearson
      value: 73.39118839457844
    - type: euclidean_spearman
      value: 77.11144988540109
    - type: manhattan_pearson
      value: 77.20681515013695
    - type: manhattan_spearman
      value: 77.11144988540109
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 77.60555084043324
    - type: cos_sim_spearman
      value: 76.04445852887906
    - type: euclidean_pearson
      value: 72.71133101639413
    - type: euclidean_spearman
      value: 75.91338695530828
    - type: manhattan_pearson
      value: 77.35612564470868
    - type: manhattan_spearman
      value: 75.91338695530828
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.41618617815928
    - type: cos_sim_spearman
      value: 77.60195378076503
    - type: euclidean_pearson
      value: 78.16168735305624
    - type: euclidean_spearman
      value: 77.67819163961478
    - type: manhattan_pearson
      value: 78.40140865643386
    - type: manhattan_spearman
      value: 77.67819163961478
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 71.44561691901534
    - type: cos_sim_spearman
      value: 70.39834592402187
    - type: euclidean_pearson
      value: 71.5559771884868
    - type: euclidean_spearman
      value: 70.11301222833383
    - type: manhattan_pearson
      value: 71.51922693185502
    - type: manhattan_spearman
      value: 70.11301222833383
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 86.7214978664316
    - type: cos_sim_spearman
      value: 85.4010906321244
    - type: euclidean_pearson
      value: 84.6346870837772
    - type: euclidean_spearman
      value: 85.72569452807713
    - type: manhattan_pearson
      value: 86.96159961830801
    - type: manhattan_spearman
      value: 85.72569452807713
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 72.09730265741813
    - type: cos_sim_spearman
      value: 71.0352138913937
    - type: euclidean_pearson
      value: 72.55713973075069
    - type: euclidean_spearman
      value: 71.41534122613018
    - type: manhattan_pearson
      value: 72.55966082460004
    - type: manhattan_spearman
      value: 71.41534122613018
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.03153344804768
    - type: cos_sim_spearman
      value: 81.58711344537957
    - type: euclidean_pearson
      value: 81.23021018553894
    - type: euclidean_spearman
      value: 81.92757732356259
    - type: manhattan_pearson
      value: 82.15831176471193
    - type: manhattan_spearman
      value: 81.92757732356259
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 83.82880794136425
    - type: cos_sim_spearman
      value: 82.77088436337785
    - type: euclidean_pearson
      value: 81.25832734044387
    - type: euclidean_spearman
      value: 83.62944563056716
    - type: manhattan_pearson
      value: 84.53726605538859
    - type: manhattan_spearman
      value: 83.62944563056716
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.4156098242599
    - type: cos_sim_spearman
      value: 77.15842055051796
    - type: euclidean_pearson
      value: 78.9792127917851
    - type: euclidean_spearman
      value: 78.09974898801255
    - type: manhattan_pearson
      value: 79.0925556678293
    - type: manhattan_spearman
      value: 78.09974898801255
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.90712716373704
    - type: cos_sim_spearman
      value: 81.519207224176
    - type: euclidean_pearson
      value: 82.74512409664257
    - type: euclidean_spearman
      value: 81.99923052819682
    - type: manhattan_pearson
      value: 83.32430067509108
    - type: manhattan_spearman
      value: 81.99923052819682
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 81.93681389517745
    - type: cos_sim_spearman
      value: 80.70090384624984
    - type: euclidean_pearson
      value: 82.04806027549073
    - type: euclidean_spearman
      value: 81.45677948183294
    - type: manhattan_pearson
      value: 82.62825908719917
    - type: manhattan_spearman
      value: 81.45677948183294
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 57.8307489054962
    - type: cos_sim_spearman
      value: 58.62505961044144
    - type: euclidean_pearson
      value: 55.77564028818849
    - type: euclidean_spearman
      value: 58.03263946623424
    - type: manhattan_pearson
      value: 57.934500833835756
    - type: manhattan_spearman
      value: 58.03263946623424
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 34.274519281072244
    - type: cos_sim_spearman
      value: 41.84134494905925
    - type: euclidean_pearson
      value: 24.113418166636
    - type: euclidean_spearman
      value: 42.55202188864813
    - type: manhattan_pearson
      value: 34.64265468569397
    - type: manhattan_spearman
      value: 42.55202188864813
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 55.477886702880916
    - type: cos_sim_spearman
      value: 57.226736875881365
    - type: euclidean_pearson
      value: 51.58883207688278
    - type: euclidean_spearman
      value: 57.86581420207087
    - type: manhattan_pearson
      value: 55.6341174643668
    - type: manhattan_spearman
      value: 57.86581420207087
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 20.336503083893273
    - type: cos_sim_spearman
      value: 36.367365959741676
    - type: euclidean_pearson
      value: 3.9896117703332306
    - type: euclidean_spearman
      value: 35.58006670036499
    - type: manhattan_pearson
      value: 19.472741193199475
    - type: manhattan_spearman
      value: 35.58006670036499
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (tr)
      type: mteb/sts22-crosslingual-sts
      config: tr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 52.55051438010185
    - type: cos_sim_spearman
      value: 52.71302742082575
    - type: euclidean_pearson
      value: 51.51870956964007
    - type: euclidean_spearman
      value: 53.81785040820307
    - type: manhattan_pearson
      value: 52.83864930315768
    - type: manhattan_spearman
      value: 53.81785040820307
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ar)
      type: mteb/sts22-crosslingual-sts
      config: ar
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 50.058410116717056
    - type: cos_sim_spearman
      value: 52.60613795295755
    - type: euclidean_pearson
      value: 44.34171068199546
    - type: euclidean_spearman
      value: 50.972497500185995
    - type: manhattan_pearson
      value: 48.47153098268435
    - type: manhattan_spearman
      value: 50.972497500185995
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 48.18132407899186
    - type: cos_sim_spearman
      value: 53.35340508300852
    - type: euclidean_pearson
      value: 39.82149695080574
    - type: euclidean_spearman
      value: 52.682446757364744
    - type: manhattan_pearson
      value: 47.28762038747965
    - type: manhattan_spearman
      value: 52.682446757364744
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 56.658087211796015
    - type: cos_sim_spearman
      value: 60.00152778866955
    - type: euclidean_pearson
      value: 49.64087381385087
    - type: euclidean_spearman
      value: 60.15322267559951
    - type: manhattan_pearson
      value: 56.343272070378504
    - type: manhattan_spearman
      value: 60.15322267559951
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 70.45337327084312
    - type: cos_sim_spearman
      value: 72.79410290057697
    - type: euclidean_pearson
      value: 65.79888764581077
    - type: euclidean_spearman
      value: 71.95723099514818
    - type: manhattan_pearson
      value: 69.39143945386915
    - type: manhattan_spearman
      value: 71.95723099514818
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 54.250555833893486
    - type: cos_sim_spearman
      value: 49.08853609665319
    - type: euclidean_pearson
      value: 56.41903104763859
    - type: euclidean_spearman
      value: 48.5360965015595
    - type: manhattan_pearson
      value: 55.42445266426144
    - type: manhattan_spearman
      value: 48.5360965015595
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 66.77771892182398
    - type: cos_sim_spearman
      value: 67.29191603287435
    - type: euclidean_pearson
      value: 67.17511110245552
    - type: euclidean_spearman
      value: 68.48737613290533
    - type: manhattan_pearson
      value: 67.84988405103397
    - type: manhattan_spearman
      value: 68.48737613290533
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (it)
      type: mteb/sts22-crosslingual-sts
      config: it
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 62.28155325846798
    - type: cos_sim_spearman
      value: 64.16669097648895
    - type: euclidean_pearson
      value: 59.403028984978356
    - type: euclidean_spearman
      value: 64.53234398252941
    - type: manhattan_pearson
      value: 62.71911466592815
    - type: manhattan_spearman
      value: 64.53234398252941
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 66.52507293566482
    - type: cos_sim_spearman
      value: 67.7160213688307
    - type: euclidean_pearson
      value: 67.20401581128685
    - type: euclidean_spearman
      value: 73.5516139257937
    - type: manhattan_pearson
      value: 69.31380011990255
    - type: manhattan_spearman
      value: 73.5516139257937
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 66.00687646805075
    - type: cos_sim_spearman
      value: 64.45259281540577
    - type: euclidean_pearson
      value: 67.27796918266225
    - type: euclidean_spearman
      value: 63.85338920706559
    - type: manhattan_pearson
      value: 67.1156006669401
    - type: manhattan_spearman
      value: 63.85338920706559
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-it)
      type: mteb/sts22-crosslingual-sts
      config: es-it
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 58.377177955731966
    - type: cos_sim_spearman
      value: 57.93025327632129
    - type: euclidean_pearson
      value: 59.93402849184793
    - type: euclidean_spearman
      value: 60.01820523185587
    - type: manhattan_pearson
      value: 60.315338046091725
    - type: manhattan_spearman
      value: 60.01820523185587
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 53.82667440921093
    - type: cos_sim_spearman
      value: 50.5954961502418
    - type: euclidean_pearson
      value: 55.73092376619234
    - type: euclidean_spearman
      value: 55.313175399483484
    - type: manhattan_pearson
      value: 56.81790111656754
    - type: manhattan_spearman
      value: 55.313175399483484
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 37.23788982242752
    - type: cos_sim_spearman
      value: 50.44074153238998
    - type: euclidean_pearson
      value: 41.25620114235842
    - type: euclidean_spearman
      value: 50.817224893459255
    - type: manhattan_pearson
      value: 40.20839143792603
    - type: manhattan_spearman
      value: 50.817224893459255
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 58.03829696246709
    - type: cos_sim_spearman
      value: 73.24670207647144
    - type: euclidean_pearson
      value: 55.854312917676864
    - type: euclidean_spearman
      value: 73.24670207647144
    - type: manhattan_pearson
      value: 58.529125221260614
    - type: manhattan_spearman
      value: 73.24670207647144
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 82.10559795910007
    - type: cos_sim_spearman
      value: 81.33502456405203
    - type: euclidean_pearson
      value: 80.71725031531976
    - type: euclidean_spearman
      value: 81.48140012027567
    - type: manhattan_pearson
      value: 82.33088191846421
    - type: manhattan_spearman
      value: 81.48140012027567
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.47227722772277
    - type: cos_sim_ap
      value: 77.36042895972905
    - type: cos_sim_f1
      value: 72.23880597014924
    - type: cos_sim_precision
      value: 71.88118811881188
    - type: cos_sim_recall
      value: 72.6
    - type: dot_accuracy
      value: 99.409900990099
    - type: dot_ap
      value: 68.42835773716114
    - type: dot_f1
      value: 65.83783783783784
    - type: dot_precision
      value: 71.6470588235294
    - type: dot_recall
      value: 60.9
    - type: euclidean_accuracy
      value: 99.48019801980197
    - type: euclidean_ap
      value: 76.69004973047716
    - type: euclidean_f1
      value: 72.51638930912759
    - type: euclidean_precision
      value: 73.14343845371313
    - type: euclidean_recall
      value: 71.89999999999999
    - type: manhattan_accuracy
      value: 99.48019801980197
    - type: manhattan_ap
      value: 76.69004973047716
    - type: manhattan_f1
      value: 72.51638930912759
    - type: manhattan_precision
      value: 73.14343845371313
    - type: manhattan_recall
      value: 71.89999999999999
    - type: max_accuracy
      value: 99.48019801980197
    - type: max_ap
      value: 77.36042895972905
    - type: max_f1
      value: 72.51638930912759
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.2614
    - type: ap
      value: 13.421228681716107
    - type: f1
      value: 53.71534671651974
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.48783248443689
    - type: f1
      value: 54.7405015752634
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.22703701496096
    - type: cos_sim_ap
      value: 63.58031791834936
    - type: cos_sim_f1
      value: 59.3132854578097
    - type: cos_sim_precision
      value: 51.60093713393206
    - type: cos_sim_recall
      value: 69.73614775725594
    - type: dot_accuracy
      value: 81.96936281814389
    - type: dot_ap
      value: 59.07547966241098
    - type: dot_f1
      value: 56.032535020334386
    - type: dot_precision
      value: 48.99249308573686
    - type: dot_recall
      value: 65.4353562005277
    - type: euclidean_accuracy
      value: 83.26280026226381
    - type: euclidean_ap
      value: 63.64817520735364
    - type: euclidean_f1
      value: 59.91221653255303
    - type: euclidean_precision
      value: 55.68902991840435
    - type: euclidean_recall
      value: 64.82849604221636
    - type: manhattan_accuracy
      value: 83.26280026226381
    - type: manhattan_ap
      value: 63.64817520735364
    - type: manhattan_f1
      value: 59.91221653255303
    - type: manhattan_precision
      value: 55.68902991840435
    - type: manhattan_recall
      value: 64.82849604221636
    - type: max_accuracy
      value: 83.26280026226381
    - type: max_ap
      value: 63.64817520735364
    - type: max_f1
      value: 59.91221653255303
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.49563395040167
    - type: cos_sim_ap
      value: 82.6398035947217
    - type: cos_sim_f1
      value: 74.74134990715125
    - type: cos_sim_precision
      value: 73.59504440629898
    - type: cos_sim_recall
      value: 75.92392978133662
    - type: dot_accuracy
      value: 85.70264291535685
    - type: dot_ap
      value: 76.35175453791561
    - type: dot_f1
      value: 70.42039872869113
    - type: dot_precision
      value: 66.31972789115646
    - type: dot_recall
      value: 75.06159531875576
    - type: euclidean_accuracy
      value: 87.51503861528312
    - type: euclidean_ap
      value: 82.74416973508781
    - type: euclidean_f1
      value: 75.0812647754137
    - type: euclidean_precision
      value: 72.15989775631922
    - type: euclidean_recall
      value: 78.2491530643671
    - type: manhattan_accuracy
      value: 87.51503861528312
    - type: manhattan_ap
      value: 82.74416973508781
    - type: manhattan_f1
      value: 75.0812647754137
    - type: manhattan_precision
      value: 72.15989775631922
    - type: manhattan_recall
      value: 78.2491530643671
    - type: max_accuracy
      value: 87.51503861528312
    - type: max_ap
      value: 82.74416973508781
    - type: max_f1
      value: 75.0812647754137
---
# paraphrase-multilingual-mpnet-base-v2-KE_Sieve

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