metadata
pipeline_tag: text-classification
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: KE Sieve_model
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
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:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
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:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 34.288000000000004
- type: f1
value: 34.00390576721439
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
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:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 75.88961038961038
- type: f1
value: 75.71295362599926
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 40.26
- type: f1
value: 35.91571484611428
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
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:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 87.21842225262198
- type: f1
value: 86.60570158294514
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 69.44824441404468
- type: f1
value: 51.1702284173121
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 65.60188298587761
- type: f1
value: 64.57658770410065
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 70.36987222595829
- type: f1
value: 70.34853403058946
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
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:
type: mteb/sts12-sts
name: MTEB STS12
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:
type: mteb/sts13-sts
name: MTEB STS13
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:
type: mteb/sts14-sts
name: MTEB STS14
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:
type: mteb/sts15-sts
name: MTEB STS15
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:
type: mteb/sts16-sts
name: MTEB STS16
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ko-ko)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (ar-ar)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-ar)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-de)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-tr)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-en)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (es-es)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (fr-en)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (it-en)
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:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (nl-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (tr)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ar)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (ru)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (it)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (pl-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (zh-en)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (es-it)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-fr)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (de-pl)
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:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (fr-pl)
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:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
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:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
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:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
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:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 54.48783248443689
- type: f1
value: 54.7405015752634
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
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:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
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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