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---
tags:
- mteb
model-index:
- name: outputs
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 74.77611940298507
- type: ap
value: 38.659370276865076
- type: f1
value: 69.18624151883213
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 71.88822499999999
- type: ap
value: 65.7475853706323
- type: f1
value: 71.64345959951606
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 36.702
- type: f1
value: 36.486058675686145
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 59.82383145710488
- type: mrr
value: 73.21857274765863
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.37337662337663
- type: f1
value: 81.289348604581
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 42.6
- type: f1
value: 38.82966298132199
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 63.95960000000001
- type: ap
value: 59.154441687893424
- type: f1
value: 63.51742877753398
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 90.19151846785226
- type: f1
value: 89.77813606418552
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 69.49612403100775
- type: f1
value: 51.78231643994976
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 68.56422326832549
- type: f1
value: 66.26365253593288
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 74.1492938802959
- type: f1
value: 73.70903086994016
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 31.3771165511325
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 30.27581967398213
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 50.511386972203965
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_spearman
value: 79.98414510640178
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_spearman
value: 77.64204203564495
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_spearman
value: 81.22687311442783
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_spearman
value: 77.93754398407367
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_spearman
value: 86.87196133587727
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_spearman
value: 83.30965159294298
- 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_spearman
value: 87.35073354189797
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_spearman
value: 60.99179493644602
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.74257425742574
- type: cos_sim_ap
value: 92.97872460676444
- type: cos_sim_f1
value: 86.72114402451481
- type: cos_sim_precision
value: 88.62212943632568
- type: cos_sim_recall
value: 84.89999999999999
- type: dot_accuracy
value: 99.390099009901
- type: dot_ap
value: 72.39239550100473
- type: dot_f1
value: 68.02325581395348
- type: dot_precision
value: 65.97744360902256
- type: dot_recall
value: 70.19999999999999
- type: euclidean_accuracy
value: 99.73762376237623
- type: euclidean_ap
value: 92.24916685896034
- type: euclidean_f1
value: 86.27654065251166
- type: euclidean_precision
value: 89.47368421052632
- type: euclidean_recall
value: 83.3
- type: manhattan_accuracy
value: 99.72277227722772
- type: manhattan_ap
value: 91.62644605063902
- type: manhattan_f1
value: 85.31395952257395
- type: manhattan_precision
value: 88.67313915857605
- type: manhattan_recall
value: 82.19999999999999
- type: max_accuracy
value: 99.74257425742574
- type: max_ap
value: 92.97872460676444
- type: max_f1
value: 86.72114402451481
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 51.78651344887864
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 30.15363599595173
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.52696387178271
- type: cos_sim_spearman
value: 32.47398402334527
- type: dot_pearson
value: 26.0757353734924
- type: dot_spearman
value: 26.575602924656312
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.85140000000001
- type: ap
value: 14.001243881017503
- type: f1
value: 53.912015688441606
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 41.37699125904245
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 82.57733802229242
- type: cos_sim_ap
value: 62.440909740391874
- type: cos_sim_f1
value: 57.90203327171904
- type: cos_sim_precision
value: 51.50020550760378
- type: cos_sim_recall
value: 66.12137203166228
- type: dot_accuracy
value: 78.49436728854981
- type: dot_ap
value: 42.7253590301706
- type: dot_f1
value: 44.52768134478349
- type: dot_precision
value: 34.05533817775294
- type: dot_recall
value: 64.30079155672823
- type: euclidean_accuracy
value: 82.58925910472671
- type: euclidean_ap
value: 61.9842141906814
- type: euclidean_f1
value: 57.77560259390677
- type: euclidean_precision
value: 53.86721423682409
- type: euclidean_recall
value: 62.29551451187335
- type: manhattan_accuracy
value: 82.684627764201
- type: manhattan_ap
value: 62.47855660560243
- type: manhattan_f1
value: 58.2642070075523
- type: manhattan_precision
value: 54.88686727315139
- type: manhattan_recall
value: 62.0844327176781
- type: max_accuracy
value: 82.684627764201
- type: max_ap
value: 62.47855660560243
- type: max_f1
value: 58.2642070075523
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.09911902821437
- type: cos_sim_ap
value: 84.09731023646366
- type: cos_sim_f1
value: 76.33028879931959
- type: cos_sim_precision
value: 73.43294201351831
- type: cos_sim_recall
value: 79.46566060979366
- type: dot_accuracy
value: 80.50801412659604
- type: dot_ap
value: 63.063159135876546
- type: dot_f1
value: 60.9384164222874
- type: dot_precision
value: 52.82453960004519
- type: dot_recall
value: 71.99722821065599
- type: euclidean_accuracy
value: 87.96522684053247
- type: euclidean_ap
value: 83.71026431772258
- type: euclidean_f1
value: 75.9441737792593
- type: euclidean_precision
value: 72.43379218782755
- type: euclidean_recall
value: 79.81213427779488
- type: manhattan_accuracy
value: 87.96716730702062
- type: manhattan_ap
value: 83.71499169638365
- type: manhattan_f1
value: 75.90983888867629
- type: manhattan_precision
value: 75.46222323670395
- type: manhattan_recall
value: 76.36279642747151
- type: max_accuracy
value: 88.09911902821437
- type: max_ap
value: 84.09731023646366
- type: max_f1
value: 76.33028879931959
--- |