---
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
---