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metadata
tags:
  - mteb
model-index:
  - name: all-mpnet-base-v2-negation
    results:
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_counterfactual
          name: MTEB AmazonCounterfactualClassification (en)
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 72.6268656716418
          - type: ap
            value: 36.40585820220466
          - type: f1
            value: 67.06383995428979
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_polarity
          name: MTEB AmazonPolarityClassification
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 85.11834999999999
          - type: ap
            value: 79.72843246428603
          - type: f1
            value: 85.08938287851875
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_reviews_multi
          name: MTEB AmazonReviewsClassification (en)
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 37.788000000000004
          - type: f1
            value: 37.40475118737949
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-p2p
          name: MTEB ArxivClusteringP2P
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 45.73138953773995
      - task:
          type: Clustering
        dataset:
          type: mteb/arxiv-clustering-s2s
          name: MTEB ArxivClusteringS2S
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 39.13609863309245
      - task:
          type: Reranking
        dataset:
          type: mteb/askubuntudupquestions-reranking
          name: MTEB AskUbuntuDupQuestions
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 65.56639026991134
          - type: mrr
            value: 77.8122938926263
      - task:
          type: STS
        dataset:
          type: mteb/biosses-sts
          name: MTEB BIOSSES
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 72.27098152643569
          - type: cos_sim_spearman
            value: 71.13475338373253
          - type: euclidean_pearson
            value: 70.48545151074218
          - type: euclidean_spearman
            value: 69.49917394727082
          - type: manhattan_pearson
            value: 69.2653740752147
          - type: manhattan_spearman
            value: 68.59192435931085
      - task:
          type: Classification
        dataset:
          type: mteb/banking77
          name: MTEB Banking77Classification
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 84.7012987012987
          - type: f1
            value: 84.61766470772943
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-p2p
          name: MTEB BiorxivClusteringP2P
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 37.61314886948818
      - task:
          type: Clustering
        dataset:
          type: mteb/biorxiv-clustering-s2s
          name: MTEB BiorxivClusteringS2S
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 34.496442588205205
      - task:
          type: Classification
        dataset:
          type: mteb/emotion
          name: MTEB EmotionClassification
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 45.63
          - type: f1
            value: 40.24119129248194
      - task:
          type: Classification
        dataset:
          type: mteb/imdb
          name: MTEB ImdbClassification
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 74.73479999999999
          - type: ap
            value: 68.80435332319863
          - type: f1
            value: 74.66014345440416
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_domain
          name: MTEB MTOPDomainClassification (en)
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 93.06429548563612
          - type: f1
            value: 92.91686969560733
      - task:
          type: Classification
        dataset:
          type: mteb/mtop_intent
          name: MTEB MTOPIntentClassification (en)
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 78.19197446420428
          - type: f1
            value: 61.50020940946492
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_intent
          name: MTEB MassiveIntentClassification (en)
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 73.86684599865502
          - type: f1
            value: 72.11245795864379
      - task:
          type: Classification
        dataset:
          type: mteb/amazon_massive_scenario
          name: MTEB MassiveScenarioClassification (en)
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 77.53866845998655
          - type: f1
            value: 77.51746806908895
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-p2p
          name: MTEB MedrxivClusteringP2P
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 33.66744884855605
      - task:
          type: Clustering
        dataset:
          type: mteb/medrxiv-clustering-s2s
          name: MTEB MedrxivClusteringS2S
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 31.951900966550262
      - task:
          type: Reranking
        dataset:
          type: mteb/mind_small
          name: MTEB MindSmallReranking
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 29.34485636178124
          - type: mrr
            value: 30.118035109577022
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering
          name: MTEB RedditClustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 47.14306531904168
      - task:
          type: Clustering
        dataset:
          type: mteb/reddit-clustering-p2p
          name: MTEB RedditClusteringP2P
          config: default
          split: test
          revision: 282350215ef01743dc01b456c7f5241fa8937f16
        metrics:
          - type: v_measure
            value: 51.59878183893005
      - task:
          type: STS
        dataset:
          type: mteb/sickr-sts
          name: MTEB SICK-R
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 78.5530506834234
          - type: cos_sim_spearman
            value: 77.45787185404667
          - type: euclidean_pearson
            value: 76.37727601604011
          - type: euclidean_spearman
            value: 77.14250754925013
          - type: manhattan_pearson
            value: 75.85855462882735
          - type: manhattan_spearman
            value: 76.6223895689777
      - task:
          type: STS
        dataset:
          type: mteb/sts12-sts
          name: MTEB STS12
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 83.1019526956277
          - type: cos_sim_spearman
            value: 72.98362332123834
          - type: euclidean_pearson
            value: 78.42992808997602
          - type: euclidean_spearman
            value: 70.79569301491145
          - type: manhattan_pearson
            value: 77.96413528436207
          - type: manhattan_spearman
            value: 70.34707852104586
      - task:
          type: STS
        dataset:
          type: mteb/sts13-sts
          name: MTEB STS13
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 85.09200805966644
          - type: cos_sim_spearman
            value: 85.52497834636847
          - type: euclidean_pearson
            value: 84.20407512505086
          - type: euclidean_spearman
            value: 85.35640946044332
          - type: manhattan_pearson
            value: 83.79425758102826
          - type: manhattan_spearman
            value: 84.9531731481683
      - task:
          type: STS
        dataset:
          type: mteb/sts14-sts
          name: MTEB STS14
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 82.43419245577238
          - type: cos_sim_spearman
            value: 79.87215923164575
          - type: euclidean_pearson
            value: 80.99628882719712
          - type: euclidean_spearman
            value: 79.2671186335978
          - type: manhattan_pearson
            value: 80.47076166661054
          - type: manhattan_spearman
            value: 78.82329686631051
      - task:
          type: STS
        dataset:
          type: mteb/sts15-sts
          name: MTEB STS15
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 84.67294508915346
          - type: cos_sim_spearman
            value: 85.34528695616378
          - type: euclidean_pearson
            value: 83.65270617275111
          - type: euclidean_spearman
            value: 84.64456096952591
          - type: manhattan_pearson
            value: 83.26416114783083
          - type: manhattan_spearman
            value: 84.26944094512996
      - task:
          type: STS
        dataset:
          type: mteb/sts16-sts
          name: MTEB STS16
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 80.70172607906416
          - type: cos_sim_spearman
            value: 81.96031310316046
          - type: euclidean_pearson
            value: 82.34820192315314
          - type: euclidean_spearman
            value: 82.72576940549405
          - type: manhattan_pearson
            value: 81.93093910116202
          - type: manhattan_spearman
            value: 82.25431799152639
      - 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: 90.43640731744911
          - type: cos_sim_spearman
            value: 90.16343998541602
          - type: euclidean_pearson
            value: 89.49834342254633
          - type: euclidean_spearman
            value: 90.17304989919288
          - type: manhattan_pearson
            value: 89.32424382015218
          - type: manhattan_spearman
            value: 89.91884845996768
      - 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: 62.06205206393254
          - type: cos_sim_spearman
            value: 60.920792876665885
          - type: euclidean_pearson
            value: 60.49188637403393
          - type: euclidean_spearman
            value: 60.73500415357452
          - type: manhattan_pearson
            value: 59.94692152491976
          - type: manhattan_spearman
            value: 60.215426858338994
      - task:
          type: STS
        dataset:
          type: mteb/stsbenchmark-sts
          name: MTEB STSBenchmark
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 84.78948820087687
          - type: cos_sim_spearman
            value: 84.64531509697663
          - type: euclidean_pearson
            value: 84.77264321816324
          - type: euclidean_spearman
            value: 84.67485410196043
          - type: manhattan_pearson
            value: 84.43100272264775
          - type: manhattan_spearman
            value: 84.29254033404217
      - task:
          type: Reranking
        dataset:
          type: mteb/scidocs-reranking
          name: MTEB SciDocsRR
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 88.39411601972704
          - type: mrr
            value: 96.49192583016112
      - task:
          type: PairClassification
        dataset:
          type: mteb/sprintduplicatequestions-pairclassification
          name: MTEB SprintDuplicateQuestions
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.55445544554455
          - type: cos_sim_ap
            value: 84.82462858434408
          - type: cos_sim_f1
            value: 76.11464968152866
          - type: cos_sim_precision
            value: 81.10859728506787
          - type: cos_sim_recall
            value: 71.7
          - type: dot_accuracy
            value: 99.48613861386139
          - type: dot_ap
            value: 80.97278220281665
          - type: dot_f1
            value: 72.2914669223394
          - type: dot_precision
            value: 69.42909760589319
          - type: dot_recall
            value: 75.4
          - type: euclidean_accuracy
            value: 99.56138613861386
          - type: euclidean_ap
            value: 85.21566333946467
          - type: euclidean_f1
            value: 76.60239708181345
          - type: euclidean_precision
            value: 79.97823721436343
          - type: euclidean_recall
            value: 73.5
          - type: manhattan_accuracy
            value: 99.55148514851486
          - type: manhattan_ap
            value: 84.49960192851891
          - type: manhattan_f1
            value: 75.9681697612732
          - type: manhattan_precision
            value: 80.90395480225989
          - type: manhattan_recall
            value: 71.6
          - type: max_accuracy
            value: 99.56138613861386
          - type: max_ap
            value: 85.21566333946467
          - type: max_f1
            value: 76.60239708181345
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering
          name: MTEB StackExchangeClustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 49.33929838947165
      - task:
          type: Clustering
        dataset:
          type: mteb/stackexchange-clustering-p2p
          name: MTEB StackExchangeClusteringP2P
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 31.523973661953686
      - task:
          type: Reranking
        dataset:
          type: mteb/stackoverflowdupquestions-reranking
          name: MTEB StackOverflowDupQuestions
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 52.22408767861519
          - type: mrr
            value: 53.16279921059333
      - task:
          type: Summarization
        dataset:
          type: mteb/summeval
          name: MTEB SummEval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 28.128173244098726
          - type: cos_sim_spearman
            value: 30.149225143523662
          - type: dot_pearson
            value: 24.322914168643386
          - type: dot_spearman
            value: 26.38194545372431
      - task:
          type: Classification
        dataset:
          type: mteb/toxic_conversations_50k
          name: MTEB ToxicConversationsClassification
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 67.6684
          - type: ap
            value: 12.681984793717413
          - type: f1
            value: 51.97637585601529
      - task:
          type: Classification
        dataset:
          type: mteb/tweet_sentiment_extraction
          name: MTEB TweetSentimentExtractionClassification
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 58.44086021505377
          - type: f1
            value: 58.68058329615692
      - task:
          type: Clustering
        dataset:
          type: mteb/twentynewsgroups-clustering
          name: MTEB TwentyNewsgroupsClustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 44.226944341054015
      - task:
          type: PairClassification
        dataset:
          type: mteb/twittersemeval2015-pairclassification
          name: MTEB TwitterSemEval2015
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 86.87488823985218
          - type: cos_sim_ap
            value: 76.85283892335002
          - type: cos_sim_f1
            value: 70.42042042042041
          - type: cos_sim_precision
            value: 66.96811042360781
          - type: cos_sim_recall
            value: 74.24802110817942
          - type: dot_accuracy
            value: 84.85426476724086
          - type: dot_ap
            value: 70.77036812650887
          - type: dot_f1
            value: 66.4901577069184
          - type: dot_precision
            value: 58.97488258117215
          - type: dot_recall
            value: 76.2005277044855
          - type: euclidean_accuracy
            value: 86.95833581689217
          - type: euclidean_ap
            value: 77.05903224969623
          - type: euclidean_f1
            value: 70.75323419175432
          - type: euclidean_precision
            value: 65.2979245704084
          - type: euclidean_recall
            value: 77.20316622691293
          - type: manhattan_accuracy
            value: 86.88084878106932
          - type: manhattan_ap
            value: 76.95056209047733
          - type: manhattan_f1
            value: 70.61542203843348
          - type: manhattan_precision
            value: 65.50090252707581
          - type: manhattan_recall
            value: 76.59630606860158
          - type: max_accuracy
            value: 86.95833581689217
          - type: max_ap
            value: 77.05903224969623
          - type: max_f1
            value: 70.75323419175432
      - task:
          type: PairClassification
        dataset:
          type: mteb/twitterurlcorpus-pairclassification
          name: MTEB TwitterURLCorpus
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 88.43870066363954
          - type: cos_sim_ap
            value: 84.77197321507954
          - type: cos_sim_f1
            value: 76.91440595175472
          - type: cos_sim_precision
            value: 75.11375311903713
          - type: cos_sim_recall
            value: 78.80351093316908
          - type: dot_accuracy
            value: 87.60624054022587
          - type: dot_ap
            value: 83.16574114504616
          - type: dot_f1
            value: 75.5050226294293
          - type: dot_precision
            value: 72.30953555571217
          - type: dot_recall
            value: 78.99599630428088
          - type: euclidean_accuracy
            value: 88.2951061435169
          - type: euclidean_ap
            value: 84.28559058741602
          - type: euclidean_f1
            value: 76.7921146953405
          - type: euclidean_precision
            value: 74.54334589736156
          - type: euclidean_recall
            value: 79.1807822605482
          - type: manhattan_accuracy
            value: 88.23883261536074
          - type: manhattan_ap
            value: 84.20593815258039
          - type: manhattan_f1
            value: 76.74366281685916
          - type: manhattan_precision
            value: 74.80263157894737
          - type: manhattan_recall
            value: 78.78811210348013
          - type: max_accuracy
            value: 88.43870066363954
          - type: max_ap
            value: 84.77197321507954
          - type: max_f1
            value: 76.91440595175472