mteb model-index region:us
---
tags:
- mteb
model-index:
- name: unsup-simcse
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.8358208955224
    - type: ap
      value: 37.70683035233076
    - type: f1
      value: 68.78678023266646
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 63.304125
    - type: ap
      value: 58.4635579061818
    - type: f1
      value: 63.21775726536531
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.21
    - type: f1
      value: 31.70875045143009
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 18.137
    - type: map_at_10
      value: 30.755
    - type: map_at_100
      value: 32.064
    - type: map_at_1000
      value: 32.1
    - type: map_at_3
      value: 26.529000000000003
    - type: map_at_5
      value: 28.993999999999996
    - type: mrr_at_1
      value: 18.563
    - type: mrr_at_10
      value: 30.915
    - type: mrr_at_100
      value: 32.225
    - type: mrr_at_1000
      value: 32.26
    - type: mrr_at_3
      value: 26.730999999999998
    - type: mrr_at_5
      value: 29.17
    - type: ndcg_at_1
      value: 18.137
    - type: ndcg_at_10
      value: 38.043
    - type: ndcg_at_100
      value: 44.436
    - type: ndcg_at_1000
      value: 45.349000000000004
    - type: ndcg_at_3
      value: 29.404000000000003
    - type: ndcg_at_5
      value: 33.851
    - type: precision_at_1
      value: 18.137
    - type: precision_at_10
      value: 6.138
    - type: precision_at_100
      value: 0.9129999999999999
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 12.589
    - type: precision_at_5
      value: 9.716
    - type: recall_at_1
      value: 18.137
    - type: recall_at_10
      value: 61.38
    - type: recall_at_100
      value: 91.252
    - type: recall_at_1000
      value: 98.36399999999999
    - type: recall_at_3
      value: 37.767
    - type: recall_at_5
      value: 48.577999999999996
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 32.293280401731245
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.868651645200988
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 51.507998420651354
    - type: mrr
      value: 64.7392604317812
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 75.4902994498795
    - type: cos_sim_spearman
      value: 75.32641515864982
    - type: euclidean_pearson
      value: 74.58993168066989
    - type: euclidean_spearman
      value: 75.32641515864982
    - type: manhattan_pearson
      value: 75.11085698985096
    - type: manhattan_spearman
      value: 75.85413802654686
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.07467532467533
    - type: f1
      value: 65.89351970361722
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.325700297722353
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 21.618349077104433
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.523
    - type: map_at_10
      value: 25.218
    - type: map_at_100
      value: 26.090999999999998
    - type: map_at_1000
      value: 26.228
    - type: map_at_3
      value: 23.147000000000002
    - type: map_at_5
      value: 24.333
    - type: mrr_at_1
      value: 23.462
    - type: mrr_at_10
      value: 29.907
    - type: mrr_at_100
      value: 30.684
    - type: mrr_at_1000
      value: 30.757
    - type: mrr_at_3
      value: 28.112
    - type: mrr_at_5
      value: 29.092000000000002
    - type: ndcg_at_1
      value: 23.462
    - type: ndcg_at_10
      value: 29.53
    - type: ndcg_at_100
      value: 33.812
    - type: ndcg_at_1000
      value: 36.941
    - type: ndcg_at_3
      value: 26.531
    - type: ndcg_at_5
      value: 27.904
    - type: precision_at_1
      value: 23.462
    - type: precision_at_10
      value: 5.608
    - type: precision_at_100
      value: 0.946
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 13.019
    - type: precision_at_5
      value: 9.27
    - type: recall_at_1
      value: 18.523
    - type: recall_at_10
      value: 37.364999999999995
    - type: recall_at_100
      value: 57.033
    - type: recall_at_1000
      value: 78.625
    - type: recall_at_3
      value: 27.863
    - type: recall_at_5
      value: 32.196000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.101
    - type: map_at_10
      value: 21.261
    - type: map_at_100
      value: 22.205
    - type: map_at_1000
      value: 22.319
    - type: map_at_3
      value: 19.509
    - type: map_at_5
      value: 20.471
    - type: mrr_at_1
      value: 20.318
    - type: mrr_at_10
      value: 25.574
    - type: mrr_at_100
      value: 26.36
    - type: mrr_at_1000
      value: 26.436
    - type: mrr_at_3
      value: 23.822
    - type: mrr_at_5
      value: 24.79
    - type: ndcg_at_1
      value: 20.318
    - type: ndcg_at_10
      value: 24.859
    - type: ndcg_at_100
      value: 29.217
    - type: ndcg_at_1000
      value: 31.979000000000003
    - type: ndcg_at_3
      value: 21.906
    - type: ndcg_at_5
      value: 23.188
    - type: precision_at_1
      value: 20.318
    - type: precision_at_10
      value: 4.682
    - type: precision_at_100
      value: 0.8670000000000001
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 10.552
    - type: precision_at_5
      value: 7.452
    - type: recall_at_1
      value: 16.101
    - type: recall_at_10
      value: 31.256
    - type: recall_at_100
      value: 50.562
    - type: recall_at_1000
      value: 69.704
    - type: recall_at_3
      value: 22.657
    - type: recall_at_5
      value: 26.301000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 21.956
    - type: map_at_10
      value: 29.03
    - type: map_at_100
      value: 29.964000000000002
    - type: map_at_1000
      value: 30.059
    - type: map_at_3
      value: 26.793
    - type: map_at_5
      value: 28.136
    - type: mrr_at_1
      value: 25.517
    - type: mrr_at_10
      value: 32.213
    - type: mrr_at_100
      value: 33.019999999999996
    - type: mrr_at_1000
      value: 33.094
    - type: mrr_at_3
      value: 30.166999999999998
    - type: mrr_at_5
      value: 31.427
    - type: ndcg_at_1
      value: 25.517
    - type: ndcg_at_10
      value: 33.165
    - type: ndcg_at_100
      value: 37.781
    - type: ndcg_at_1000
      value: 40.303
    - type: ndcg_at_3
      value: 29.095
    - type: ndcg_at_5
      value: 31.223
    - type: precision_at_1
      value: 25.517
    - type: precision_at_10
      value: 5.361
    - type: precision_at_100
      value: 0.8330000000000001
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 12.831999999999999
    - type: precision_at_5
      value: 9.103
    - type: recall_at_1
      value: 21.956
    - type: recall_at_10
      value: 42.634
    - type: recall_at_100
      value: 63.774
    - type: recall_at_1000
      value: 82.548
    - type: recall_at_3
      value: 31.813000000000002
    - type: recall_at_5
      value: 36.992000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 8.831999999999999
    - type: map_at_10
      value: 12.455
    - type: map_at_100
      value: 13.142000000000001
    - type: map_at_1000
      value: 13.238
    - type: map_at_3
      value: 10.995000000000001
    - type: map_at_5
      value: 11.837
    - type: mrr_at_1
      value: 9.605
    - type: mrr_at_10
      value: 13.444999999999999
    - type: mrr_at_100
      value: 14.119000000000002
    - type: mrr_at_1000
      value: 14.21
    - type: mrr_at_3
      value: 11.902
    - type: mrr_at_5
      value: 12.817
    - type: ndcg_at_1
      value: 9.605
    - type: ndcg_at_10
      value: 14.899000000000001
    - type: ndcg_at_100
      value: 18.788
    - type: ndcg_at_1000
      value: 21.861
    - type: ndcg_at_3
      value: 11.923
    - type: ndcg_at_5
      value: 13.420000000000002
    - type: precision_at_1
      value: 9.605
    - type: precision_at_10
      value: 2.4410000000000003
    - type: precision_at_100
      value: 0.46299999999999997
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 5.009
    - type: precision_at_5
      value: 3.7969999999999997
    - type: recall_at_1
      value: 8.831999999999999
    - type: recall_at_10
      value: 21.626
    - type: recall_at_100
      value: 40.585
    - type: recall_at_1000
      value: 64.842
    - type: recall_at_3
      value: 13.719000000000001
    - type: recall_at_5
      value: 17.222
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.013999999999999
    - type: map_at_10
      value: 7.323
    - type: map_at_100
      value: 7.921
    - type: map_at_1000
      value: 8.044
    - type: map_at_3
      value: 6.389
    - type: map_at_5
      value: 6.958
    - type: mrr_at_1
      value: 6.715999999999999
    - type: mrr_at_10
      value: 9.33
    - type: mrr_at_100
      value: 10.03
    - type: mrr_at_1000
      value: 10.133000000000001
    - type: mrr_at_3
      value: 8.354000000000001
    - type: mrr_at_5
      value: 8.895
    - type: ndcg_at_1
      value: 6.715999999999999
    - type: ndcg_at_10
      value: 9.146
    - type: ndcg_at_100
      value: 12.703000000000001
    - type: ndcg_at_1000
      value: 16.246
    - type: ndcg_at_3
      value: 7.376
    - type: ndcg_at_5
      value: 8.27
    - type: precision_at_1
      value: 6.715999999999999
    - type: precision_at_10
      value: 1.729
    - type: precision_at_100
      value: 0.422
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 3.6479999999999997
    - type: precision_at_5
      value: 2.7359999999999998
    - type: recall_at_1
      value: 5.013999999999999
    - type: recall_at_10
      value: 12.928
    - type: recall_at_100
      value: 29.298000000000002
    - type: recall_at_1000
      value: 55.632000000000005
    - type: recall_at_3
      value: 8.011
    - type: recall_at_5
      value: 10.333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.629999999999999
    - type: map_at_10
      value: 20.529
    - type: map_at_100
      value: 21.555
    - type: map_at_1000
      value: 21.688
    - type: map_at_3
      value: 18.733
    - type: map_at_5
      value: 19.761
    - type: mrr_at_1
      value: 19.057
    - type: mrr_at_10
      value: 24.482
    - type: mrr_at_100
      value: 25.348
    - type: mrr_at_1000
      value: 25.436999999999998
    - type: mrr_at_3
      value: 22.698
    - type: mrr_at_5
      value: 23.766000000000002
    - type: ndcg_at_1
      value: 19.057
    - type: ndcg_at_10
      value: 24.121000000000002
    - type: ndcg_at_100
      value: 29.215000000000003
    - type: ndcg_at_1000
      value: 32.506
    - type: ndcg_at_3
      value: 21.096999999999998
    - type: ndcg_at_5
      value: 22.546
    - type: precision_at_1
      value: 19.057
    - type: precision_at_10
      value: 4.389
    - type: precision_at_100
      value: 0.83
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 9.881
    - type: precision_at_5
      value: 7.161
    - type: recall_at_1
      value: 15.629999999999999
    - type: recall_at_10
      value: 31.217
    - type: recall_at_100
      value: 53.800000000000004
    - type: recall_at_1000
      value: 77.012
    - type: recall_at_3
      value: 22.416
    - type: recall_at_5
      value: 26.368000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.217
    - type: map_at_10
      value: 15.401000000000002
    - type: map_at_100
      value: 16.187
    - type: map_at_1000
      value: 16.314999999999998
    - type: map_at_3
      value: 14.030000000000001
    - type: map_at_5
      value: 14.784
    - type: mrr_at_1
      value: 14.041
    - type: mrr_at_10
      value: 18.81
    - type: mrr_at_100
      value: 19.534000000000002
    - type: mrr_at_1000
      value: 19.628
    - type: mrr_at_3
      value: 17.314
    - type: mrr_at_5
      value: 18.232
    - type: ndcg_at_1
      value: 14.041
    - type: ndcg_at_10
      value: 18.457
    - type: ndcg_at_100
      value: 22.616
    - type: ndcg_at_1000
      value: 25.991999999999997
    - type: ndcg_at_3
      value: 15.943999999999999
    - type: ndcg_at_5
      value: 17.096
    - type: precision_at_1
      value: 14.041
    - type: precision_at_10
      value: 3.39
    - type: precision_at_100
      value: 0.651
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 7.534000000000001
    - type: precision_at_5
      value: 5.525
    - type: recall_at_1
      value: 11.217
    - type: recall_at_10
      value: 24.568
    - type: recall_at_100
      value: 43.454
    - type: recall_at_1000
      value: 67.69
    - type: recall_at_3
      value: 17.413
    - type: recall_at_5
      value: 20.383000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.025
    - type: map_at_10
      value: 16.28216666666667
    - type: map_at_100
      value: 17.044916666666666
    - type: map_at_1000
      value: 17.159416666666665
    - type: map_at_3
      value: 14.794166666666667
    - type: map_at_5
      value: 15.65475
    - type: mrr_at_1
      value: 14.642249999999999
    - type: mrr_at_10
      value: 19.092833333333335
    - type: mrr_at_100
      value: 19.81375
    - type: mrr_at_1000
      value: 19.901249999999997
    - type: mrr_at_3
      value: 17.602999999999998
    - type: mrr_at_5
      value: 18.462083333333336
    - type: ndcg_at_1
      value: 14.642249999999999
    - type: ndcg_at_10
      value: 19.229916666666664
    - type: ndcg_at_100
      value: 23.18841666666667
    - type: ndcg_at_1000
      value: 26.286000000000005
    - type: ndcg_at_3
      value: 16.579916666666666
    - type: ndcg_at_5
      value: 17.851583333333334
    - type: precision_at_1
      value: 14.642249999999999
    - type: precision_at_10
      value: 3.4223333333333334
    - type: precision_at_100
      value: 0.6358333333333333
    - type: precision_at_1000
      value: 0.10575000000000001
    - type: precision_at_3
      value: 7.6842500000000005
    - type: precision_at_5
      value: 5.5715
    - type: recall_at_1
      value: 12.025
    - type: recall_at_10
      value: 25.470750000000002
    - type: recall_at_100
      value: 43.7285
    - type: recall_at_1000
      value: 66.525
    - type: recall_at_3
      value: 17.878083333333336
    - type: recall_at_5
      value: 21.252750000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 8.567
    - type: map_at_10
      value: 11.591
    - type: map_at_100
      value: 12.248000000000001
    - type: map_at_1000
      value: 12.318999999999999
    - type: map_at_3
      value: 10.456999999999999
    - type: map_at_5
      value: 11.020000000000001
    - type: mrr_at_1
      value: 10.428999999999998
    - type: mrr_at_10
      value: 13.758000000000001
    - type: mrr_at_100
      value: 14.363000000000001
    - type: mrr_at_1000
      value: 14.427000000000001
    - type: mrr_at_3
      value: 12.577
    - type: mrr_at_5
      value: 13.167000000000002
    - type: ndcg_at_1
      value: 10.428999999999998
    - type: ndcg_at_10
      value: 13.911999999999999
    - type: ndcg_at_100
      value: 17.307
    - type: ndcg_at_1000
      value: 19.478
    - type: ndcg_at_3
      value: 11.659
    - type: ndcg_at_5
      value: 12.555
    - type: precision_at_1
      value: 10.428999999999998
    - type: precision_at_10
      value: 2.423
    - type: precision_at_100
      value: 0.449
    - type: precision_at_1000
      value: 0.06899999999999999
    - type: precision_at_3
      value: 5.317
    - type: precision_at_5
      value: 3.804
    - type: recall_at_1
      value: 8.567
    - type: recall_at_10
      value: 19.122
    - type: recall_at_100
      value: 35.021
    - type: recall_at_1000
      value: 51.857
    - type: recall_at_3
      value: 12.696
    - type: recall_at_5
      value: 15.015
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.414000000000001
    - type: map_at_10
      value: 9.049999999999999
    - type: map_at_100
      value: 9.587
    - type: map_at_1000
      value: 9.689
    - type: map_at_3
      value: 8.113
    - type: map_at_5
      value: 8.591
    - type: mrr_at_1
      value: 8.19
    - type: mrr_at_10
      value: 11.232000000000001
    - type: mrr_at_100
      value: 11.799
    - type: mrr_at_1000
      value: 11.888
    - type: mrr_at_3
      value: 10.145999999999999
    - type: mrr_at_5
      value: 10.691
    - type: ndcg_at_1
      value: 8.19
    - type: ndcg_at_10
      value: 11.1
    - type: ndcg_at_100
      value: 14.074
    - type: ndcg_at_1000
      value: 17.169
    - type: ndcg_at_3
      value: 9.302000000000001
    - type: ndcg_at_5
      value: 10.034
    - type: precision_at_1
      value: 8.19
    - type: precision_at_10
      value: 2.072
    - type: precision_at_100
      value: 0.42900000000000005
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 4.393
    - type: precision_at_5
      value: 3.2140000000000004
    - type: recall_at_1
      value: 6.414000000000001
    - type: recall_at_10
      value: 15.354999999999999
    - type: recall_at_100
      value: 29.186
    - type: recall_at_1000
      value: 52.445
    - type: recall_at_3
      value: 10.197000000000001
    - type: recall_at_5
      value: 12.136
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 10.596
    - type: map_at_10
      value: 13.754
    - type: map_at_100
      value: 14.362
    - type: map_at_1000
      value: 14.472
    - type: map_at_3
      value: 12.450999999999999
    - type: map_at_5
      value: 13.156
    - type: mrr_at_1
      value: 12.592999999999998
    - type: mrr_at_10
      value: 15.906
    - type: mrr_at_100
      value: 16.564
    - type: mrr_at_1000
      value: 16.669
    - type: mrr_at_3
      value: 14.459
    - type: mrr_at_5
      value: 15.261
    - type: ndcg_at_1
      value: 12.592999999999998
    - type: ndcg_at_10
      value: 16.166
    - type: ndcg_at_100
      value: 19.496
    - type: ndcg_at_1000
      value: 22.825
    - type: ndcg_at_3
      value: 13.591000000000001
    - type: ndcg_at_5
      value: 14.727
    - type: precision_at_1
      value: 12.592999999999998
    - type: precision_at_10
      value: 2.733
    - type: precision_at_100
      value: 0.485
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 5.908
    - type: precision_at_5
      value: 4.328
    - type: recall_at_1
      value: 10.596
    - type: recall_at_10
      value: 21.698999999999998
    - type: recall_at_100
      value: 37.044
    - type: recall_at_1000
      value: 62.214999999999996
    - type: recall_at_3
      value: 14.501
    - type: recall_at_5
      value: 17.319000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.658
    - type: map_at_10
      value: 17.258000000000003
    - type: map_at_100
      value: 18.08
    - type: map_at_1000
      value: 18.248
    - type: map_at_3
      value: 15.648000000000001
    - type: map_at_5
      value: 16.659
    - type: mrr_at_1
      value: 15.613
    - type: mrr_at_10
      value: 20.379
    - type: mrr_at_100
      value: 21.15
    - type: mrr_at_1000
      value: 21.247
    - type: mrr_at_3
      value: 18.808
    - type: mrr_at_5
      value: 19.707
    - type: ndcg_at_1
      value: 15.613
    - type: ndcg_at_10
      value: 20.515
    - type: ndcg_at_100
      value: 24.618000000000002
    - type: ndcg_at_1000
      value: 28.407
    - type: ndcg_at_3
      value: 18.059
    - type: ndcg_at_5
      value: 19.274
    - type: precision_at_1
      value: 15.613
    - type: precision_at_10
      value: 3.8739999999999997
    - type: precision_at_100
      value: 0.8019999999999999
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 8.696
    - type: precision_at_5
      value: 6.364
    - type: recall_at_1
      value: 12.658
    - type: recall_at_10
      value: 27.004
    - type: recall_at_100
      value: 46.245000000000005
    - type: recall_at_1000
      value: 72.696
    - type: recall_at_3
      value: 18.907
    - type: recall_at_5
      value: 22.666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.792
    - type: map_at_10
      value: 12.516
    - type: map_at_100
      value: 13.197000000000001
    - type: map_at_1000
      value: 13.294
    - type: map_at_3
      value: 11.265
    - type: map_at_5
      value: 12.151
    - type: mrr_at_1
      value: 10.166
    - type: mrr_at_10
      value: 14.078
    - type: mrr_at_100
      value: 14.793999999999999
    - type: mrr_at_1000
      value: 14.889
    - type: mrr_at_3
      value: 12.876999999999999
    - type: mrr_at_5
      value: 13.700000000000001
    - type: ndcg_at_1
      value: 10.166
    - type: ndcg_at_10
      value: 14.889
    - type: ndcg_at_100
      value: 18.634
    - type: ndcg_at_1000
      value: 21.725
    - type: ndcg_at_3
      value: 12.475999999999999
    - type: ndcg_at_5
      value: 13.982
    - type: precision_at_1
      value: 10.166
    - type: precision_at_10
      value: 2.366
    - type: precision_at_100
      value: 0.453
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 5.422
    - type: precision_at_5
      value: 4.104
    - type: recall_at_1
      value: 8.792
    - type: recall_at_10
      value: 20.875
    - type: recall_at_100
      value: 38.74
    - type: recall_at_1000
      value: 63.034
    - type: recall_at_3
      value: 14.344000000000001
    - type: recall_at_5
      value: 18.102
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.908
    - type: map_at_10
      value: 10.325
    - type: map_at_100
      value: 11.652
    - type: map_at_1000
      value: 11.847000000000001
    - type: map_at_3
      value: 8.519
    - type: map_at_5
      value: 9.407
    - type: mrr_at_1
      value: 13.16
    - type: mrr_at_10
      value: 21.617
    - type: mrr_at_100
      value: 22.712
    - type: mrr_at_1000
      value: 22.785
    - type: mrr_at_3
      value: 18.806
    - type: mrr_at_5
      value: 20.324
    - type: ndcg_at_1
      value: 13.16
    - type: ndcg_at_10
      value: 15.695999999999998
    - type: ndcg_at_100
      value: 22.006999999999998
    - type: ndcg_at_1000
      value: 26.226
    - type: ndcg_at_3
      value: 12.213000000000001
    - type: ndcg_at_5
      value: 13.403
    - type: precision_at_1
      value: 13.16
    - type: precision_at_10
      value: 5.199
    - type: precision_at_100
      value: 1.199
    - type: precision_at_1000
      value: 0.197
    - type: precision_at_3
      value: 9.468
    - type: precision_at_5
      value: 7.478999999999999
    - type: recall_at_1
      value: 5.908
    - type: recall_at_10
      value: 19.898
    - type: recall_at_100
      value: 42.46
    - type: recall_at_1000
      value: 67.06400000000001
    - type: recall_at_3
      value: 11.417
    - type: recall_at_5
      value: 14.610000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.923
    - type: map_at_10
      value: 6.648999999999999
    - type: map_at_100
      value: 9.408
    - type: map_at_1000
      value: 10.181
    - type: map_at_3
      value: 4.709
    - type: map_at_5
      value: 5.5329999999999995
    - type: mrr_at_1
      value: 33.75
    - type: mrr_at_10
      value: 42.895
    - type: mrr_at_100
      value: 43.759
    - type: mrr_at_1000
      value: 43.796
    - type: mrr_at_3
      value: 40.167
    - type: mrr_at_5
      value: 41.492000000000004
    - type: ndcg_at_1
      value: 24.375
    - type: ndcg_at_10
      value: 18.611
    - type: ndcg_at_100
      value: 21.141
    - type: ndcg_at_1000
      value: 27.177
    - type: ndcg_at_3
      value: 21.035
    - type: ndcg_at_5
      value: 19.703
    - type: precision_at_1
      value: 33.75
    - type: precision_at_10
      value: 16.8
    - type: precision_at_100
      value: 5.4399999999999995
    - type: precision_at_1000
      value: 1.208
    - type: precision_at_3
      value: 25.25
    - type: precision_at_5
      value: 21.55
    - type: recall_at_1
      value: 2.923
    - type: recall_at_10
      value: 10.530000000000001
    - type: recall_at_100
      value: 26.943
    - type: recall_at_1000
      value: 47.449999999999996
    - type: recall_at_3
      value: 5.608
    - type: recall_at_5
      value: 7.259
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 40.15
    - type: f1
      value: 36.73372782577792
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.628
    - type: map_at_10
      value: 18.238
    - type: map_at_100
      value: 19.085
    - type: map_at_1000
      value: 19.17
    - type: map_at_3
      value: 16.322
    - type: map_at_5
      value: 17.357
    - type: mrr_at_1
      value: 13.441
    - type: mrr_at_10
      value: 19.373
    - type: mrr_at_100
      value: 20.232
    - type: mrr_at_1000
      value: 20.31
    - type: mrr_at_3
      value: 17.389
    - type: mrr_at_5
      value: 18.467
    - type: ndcg_at_1
      value: 13.441
    - type: ndcg_at_10
      value: 21.823
    - type: ndcg_at_100
      value: 26.216
    - type: ndcg_at_1000
      value: 28.614
    - type: ndcg_at_3
      value: 17.845
    - type: ndcg_at_5
      value: 19.705000000000002
    - type: precision_at_1
      value: 13.441
    - type: precision_at_10
      value: 3.476
    - type: precision_at_100
      value: 0.584
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 7.596
    - type: precision_at_5
      value: 5.5329999999999995
    - type: recall_at_1
      value: 12.628
    - type: recall_at_10
      value: 32.062000000000005
    - type: recall_at_100
      value: 52.661
    - type: recall_at_1000
      value: 71.38799999999999
    - type: recall_at_3
      value: 21.175
    - type: recall_at_5
      value: 25.665
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.919
    - type: map_at_10
      value: 7.489
    - type: map_at_100
      value: 8.347
    - type: map_at_1000
      value: 8.520999999999999
    - type: map_at_3
      value: 6.7299999999999995
    - type: map_at_5
      value: 7.079000000000001
    - type: mrr_at_1
      value: 9.105
    - type: mrr_at_10
      value: 13.303
    - type: mrr_at_100
      value: 14.262
    - type: mrr_at_1000
      value: 14.371999999999998
    - type: mrr_at_3
      value: 12.217
    - type: mrr_at_5
      value: 12.773000000000001
    - type: ndcg_at_1
      value: 9.105
    - type: ndcg_at_10
      value: 10.194
    - type: ndcg_at_100
      value: 14.875
    - type: ndcg_at_1000
      value: 19.111
    - type: ndcg_at_3
      value: 9.113
    - type: ndcg_at_5
      value: 9.369
    - type: precision_at_1
      value: 9.105
    - type: precision_at_10
      value: 2.762
    - type: precision_at_100
      value: 0.738
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 5.864
    - type: precision_at_5
      value: 4.259
    - type: recall_at_1
      value: 4.919
    - type: recall_at_10
      value: 12.597
    - type: recall_at_100
      value: 31.233
    - type: recall_at_1000
      value: 58.312
    - type: recall_at_3
      value: 8.892
    - type: recall_at_5
      value: 10.116999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.275
    - type: map_at_10
      value: 18.406
    - type: map_at_100
      value: 19.148
    - type: map_at_1000
      value: 19.25
    - type: map_at_3
      value: 16.855999999999998
    - type: map_at_5
      value: 17.706
    - type: mrr_at_1
      value: 26.55
    - type: mrr_at_10
      value: 32.561
    - type: mrr_at_100
      value: 33.283
    - type: mrr_at_1000
      value: 33.352
    - type: mrr_at_3
      value: 30.767
    - type: mrr_at_5
      value: 31.801000000000002
    - type: ndcg_at_1
      value: 26.55
    - type: ndcg_at_10
      value: 24.031
    - type: ndcg_at_100
      value: 27.76
    - type: ndcg_at_1000
      value: 30.426
    - type: ndcg_at_3
      value: 20.91
    - type: ndcg_at_5
      value: 22.417
    - type: precision_at_1
      value: 26.55
    - type: precision_at_10
      value: 5.3629999999999995
    - type: precision_at_100
      value: 0.8380000000000001
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 13.167000000000002
    - type: precision_at_5
      value: 9.091000000000001
    - type: recall_at_1
      value: 13.275
    - type: recall_at_10
      value: 26.813
    - type: recall_at_100
      value: 41.891
    - type: recall_at_1000
      value: 59.804
    - type: recall_at_3
      value: 19.75
    - type: recall_at_5
      value: 22.728
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 62.651999999999994
    - type: ap
      value: 58.13172545320704
    - type: f1
      value: 62.47429101001618
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 4.661
    - type: map_at_10
      value: 8.003
    - type: map_at_100
      value: 8.741
    - type: map_at_1000
      value: 8.834
    - type: map_at_3
      value: 6.765000000000001
    - type: map_at_5
      value: 7.396999999999999
    - type: mrr_at_1
      value: 4.814
    - type: mrr_at_10
      value: 8.25
    - type: mrr_at_100
      value: 8.997
    - type: mrr_at_1000
      value: 9.088000000000001
    - type: mrr_at_3
      value: 6.988999999999999
    - type: mrr_at_5
      value: 7.630000000000001
    - type: ndcg_at_1
      value: 4.771
    - type: ndcg_at_10
      value: 10.142
    - type: ndcg_at_100
      value: 14.282
    - type: ndcg_at_1000
      value: 17.169
    - type: ndcg_at_3
      value: 7.531000000000001
    - type: ndcg_at_5
      value: 8.671
    - type: precision_at_1
      value: 4.771
    - type: precision_at_10
      value: 1.7510000000000001
    - type: precision_at_100
      value: 0.38999999999999996
    - type: precision_at_1000
      value: 0.064
    - type: precision_at_3
      value: 3.314
    - type: precision_at_5
      value: 2.5669999999999997
    - type: recall_at_1
      value: 4.661
    - type: recall_at_10
      value: 16.792
    - type: recall_at_100
      value: 37.221
    - type: recall_at_1000
      value: 60.550000000000004
    - type: recall_at_3
      value: 9.549000000000001
    - type: recall_at_5
      value: 12.276
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.74555403556772
    - type: f1
      value: 85.29014785765409
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.1016871865025
    - type: f1
      value: 39.799156304661324
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.29253530598522
    - type: f1
      value: 57.58027304406067
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.4862138533961
    - type: f1
      value: 65.09934822244887
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.405192268682242
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.459696217158037
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.380882515419433
    - type: mrr
      value: 30.311119546825378
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.06
    - type: map_at_10
      value: 5.1659999999999995
    - type: map_at_100
      value: 6.596
    - type: map_at_1000
      value: 7.661
    - type: map_at_3
      value: 4.208
    - type: map_at_5
      value: 4.662
    - type: mrr_at_1
      value: 26.935
    - type: mrr_at_10
      value: 35.577
    - type: mrr_at_100
      value: 36.548
    - type: mrr_at_1000
      value: 36.616
    - type: mrr_at_3
      value: 33.024
    - type: mrr_at_5
      value: 34.587
    - type: ndcg_at_1
      value: 25.232
    - type: ndcg_at_10
      value: 17.793999999999997
    - type: ndcg_at_100
      value: 17.47
    - type: ndcg_at_1000
      value: 26.964
    - type: ndcg_at_3
      value: 21.428
    - type: ndcg_at_5
      value: 19.868
    - type: precision_at_1
      value: 26.935
    - type: precision_at_10
      value: 13.034
    - type: precision_at_100
      value: 5.006
    - type: precision_at_1000
      value: 1.7870000000000001
    - type: precision_at_3
      value: 20.124
    - type: precision_at_5
      value: 16.966
    - type: recall_at_1
      value: 3.06
    - type: recall_at_10
      value: 7.896
    - type: recall_at_100
      value: 20.28
    - type: recall_at_1000
      value: 53.613
    - type: recall_at_3
      value: 4.8309999999999995
    - type: recall_at_5
      value: 5.994
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.4959999999999996
    - type: map_at_10
      value: 12.836
    - type: map_at_100
      value: 13.835
    - type: map_at_1000
      value: 13.94
    - type: map_at_3
      value: 10.896
    - type: map_at_5
      value: 11.956
    - type: mrr_at_1
      value: 8.575000000000001
    - type: mrr_at_10
      value: 14.292
    - type: mrr_at_100
      value: 15.24
    - type: mrr_at_1000
      value: 15.332
    - type: mrr_at_3
      value: 12.22
    - type: mrr_at_5
      value: 13.379
    - type: ndcg_at_1
      value: 8.575000000000001
    - type: ndcg_at_10
      value: 16.36
    - type: ndcg_at_100
      value: 21.598
    - type: ndcg_at_1000
      value: 24.547
    - type: ndcg_at_3
      value: 12.305000000000001
    - type: ndcg_at_5
      value: 14.249
    - type: precision_at_1
      value: 8.575000000000001
    - type: precision_at_10
      value: 3.024
    - type: precision_at_100
      value: 0.602
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 5.726
    - type: precision_at_5
      value: 4.537
    - type: recall_at_1
      value: 7.4959999999999996
    - type: recall_at_10
      value: 25.898
    - type: recall_at_100
      value: 50.495000000000005
    - type: recall_at_1000
      value: 73.206
    - type: recall_at_3
      value: 15.124
    - type: recall_at_5
      value: 19.667
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.19499999999999
    - type: map_at_10
      value: 70.086
    - type: map_at_100
      value: 70.922
    - type: map_at_1000
      value: 70.967
    - type: map_at_3
      value: 67.274
    - type: map_at_5
      value: 68.948
    - type: mrr_at_1
      value: 66.85
    - type: mrr_at_10
      value: 74.74499999999999
    - type: mrr_at_100
      value: 75.09
    - type: mrr_at_1000
      value: 75.102
    - type: mrr_at_3
      value: 73.15
    - type: mrr_at_5
      value: 74.153
    - type: ndcg_at_1
      value: 66.92
    - type: ndcg_at_10
      value: 74.998
    - type: ndcg_at_100
      value: 77.66499999999999
    - type: ndcg_at_1000
      value: 78.309
    - type: ndcg_at_3
      value: 71.287
    - type: ndcg_at_5
      value: 73.154
    - type: precision_at_1
      value: 66.92
    - type: precision_at_10
      value: 11.347999999999999
    - type: precision_at_100
      value: 1.394
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 30.857
    - type: precision_at_5
      value: 20.419999999999998
    - type: recall_at_1
      value: 58.19499999999999
    - type: recall_at_10
      value: 84.407
    - type: recall_at_100
      value: 95.089
    - type: recall_at_1000
      value: 99.032
    - type: recall_at_3
      value: 73.847
    - type: recall_at_5
      value: 78.994
    - type: map_at_1
      value: 2.273
    - type: map_at_10
      value: 5.082
    - type: map_at_100
      value: 6.081
    - type: map_at_1000
      value: 6.3
    - type: map_at_3
      value: 3.887
    - type: map_at_5
      value: 4.455
    - type: mrr_at_1
      value: 11.1
    - type: mrr_at_10
      value: 17.724
    - type: mrr_at_100
      value: 18.815
    - type: mrr_at_1000
      value: 18.927
    - type: mrr_at_3
      value: 15.45
    - type: mrr_at_5
      value: 16.665
    - type: ndcg_at_1
      value: 11.1
    - type: ndcg_at_10
      value: 9.337
    - type: ndcg_at_100
      value: 14.328
    - type: ndcg_at_1000
      value: 19.358
    - type: ndcg_at_3
      value: 9.055
    - type: ndcg_at_5
      value: 7.782
    - type: precision_at_1
      value: 11.1
    - type: precision_at_10
      value: 4.760000000000001
    - type: precision_at_100
      value: 1.208
    - type: precision_at_1000
      value: 0.243
    - type: precision_at_3
      value: 8.5
    - type: precision_at_5
      value: 6.72
    - type: recall_at_1
      value: 2.273
    - type: recall_at_10
      value: 9.708
    - type: recall_at_100
      value: 24.490000000000002
    - type: recall_at_1000
      value: 49.378
    - type: recall_at_3
      value: 5.207
    - type: recall_at_5
      value: 6.855
    - type: map_at_1
      value: 0.086
    - type: map_at_10
      value: 0.471
    - type: map_at_100
      value: 2.222
    - type: map_at_1000
      value: 5.461
    - type: map_at_3
      value: 0.182
    - type: map_at_5
      value: 0.28200000000000003
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 52.78
    - type: mrr_at_100
      value: 53.761
    - type: mrr_at_1000
      value: 53.761
    - type: mrr_at_3
      value: 49.333
    - type: mrr_at_5
      value: 50.632999999999996
    - type: ndcg_at_1
      value: 37.0
    - type: ndcg_at_10
      value: 31.411
    - type: ndcg_at_100
      value: 22.314999999999998
    - type: ndcg_at_1000
      value: 20.274
    - type: ndcg_at_3
      value: 32.089
    - type: ndcg_at_5
      value: 32.08
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 34.4
    - type: precision_at_100
      value: 23.28
    - type: precision_at_1000
      value: 10.162
    - type: precision_at_3
      value: 35.333
    - type: precision_at_5
      value: 35.199999999999996
    - type: recall_at_1
      value: 0.086
    - type: recall_at_10
      value: 0.696
    - type: recall_at_100
      value: 4.758
    - type: recall_at_1000
      value: 20.024
    - type: recall_at_3
      value: 0.22100000000000003
    - type: recall_at_5
      value: 0.366
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 33.78467254732863
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 40.672180041658585
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.31271548030631
    - type: cos_sim_spearman
      value: 66.39869412209516
    - type: euclidean_pearson
      value: 71.7717241609781
    - type: euclidean_spearman
      value: 66.3987881681945
    - type: manhattan_pearson
      value: 69.11732057374952
    - type: manhattan_spearman
      value: 64.37112055858346
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 67.60073903347859
    - type: cos_sim_spearman
      value: 60.19179782879366
    - type: euclidean_pearson
      value: 64.11314220006894
    - type: euclidean_spearman
      value: 60.19314941038865
    - type: manhattan_pearson
      value: 61.97187813126979
    - type: manhattan_spearman
      value: 59.52596441655491
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 72.51824007418035
    - type: cos_sim_spearman
      value: 74.95359317393202
    - type: euclidean_pearson
      value: 74.49726165629166
    - type: euclidean_spearman
      value: 74.95363101082553
    - type: manhattan_pearson
      value: 74.5505822303686
    - type: manhattan_spearman
      value: 74.83106654959558
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 73.94027055461791
    - type: cos_sim_spearman
      value: 71.75613187630412
    - type: euclidean_pearson
      value: 73.52053251964922
    - type: euclidean_spearman
      value: 71.7561221886074
    - type: manhattan_pearson
      value: 72.95807486480041
    - type: manhattan_spearman
      value: 71.44311778711412
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 76.99843680559651
    - type: cos_sim_spearman
      value: 78.23842744383246
    - type: euclidean_pearson
      value: 78.32126716441479
    - type: euclidean_spearman
      value: 78.23842600076793
    - type: manhattan_pearson
      value: 78.70809726482216
    - type: manhattan_spearman
      value: 78.76466032861859
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 73.14424089430341
    - type: cos_sim_spearman
      value: 74.3751435229468
    - type: euclidean_pearson
      value: 73.9331135556646
    - type: euclidean_spearman
      value: 74.37541530605985
    - type: manhattan_pearson
      value: 74.39888961544435
    - type: manhattan_spearman
      value: 74.94721230089296
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 80.75441723905766
    - type: cos_sim_spearman
      value: 82.73557833304935
    - type: euclidean_pearson
      value: 82.69115254893079
    - type: euclidean_spearman
      value: 82.73645322846139
    - type: manhattan_pearson
      value: 82.51722585478409
    - type: manhattan_spearman
      value: 82.86707120159535
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.07059194085915
    - type: cos_sim_spearman
      value: 59.76151504162761
    - type: euclidean_pearson
      value: 62.11407131924416
    - type: euclidean_spearman
      value: 59.76151504162761
    - type: manhattan_pearson
      value: 61.32842825569698
    - type: manhattan_spearman
      value: 59.571314861791656
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 74.0915974515931
    - type: cos_sim_spearman
      value: 72.55883845653092
    - type: euclidean_pearson
      value: 74.18910803867354
    - type: euclidean_spearman
      value: 72.55885692831839
    - type: manhattan_pearson
      value: 74.2142152931368
    - type: manhattan_spearman
      value: 72.99331929242176
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 68.94137239589007
    - type: mrr
      value: 88.63889287908896
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 24.389
    - type: map_at_10
      value: 32.143
    - type: map_at_100
      value: 32.873000000000005
    - type: map_at_1000
      value: 32.972
    - type: map_at_3
      value: 29.583
    - type: map_at_5
      value: 31.008000000000003
    - type: mrr_at_1
      value: 25.667
    - type: mrr_at_10
      value: 33.274
    - type: mrr_at_100
      value: 33.913
    - type: mrr_at_1000
      value: 33.997
    - type: mrr_at_3
      value: 30.833
    - type: mrr_at_5
      value: 32.167
    - type: ndcg_at_1
      value: 25.667
    - type: ndcg_at_10
      value: 36.897999999999996
    - type: ndcg_at_100
      value: 41.038999999999994
    - type: ndcg_at_1000
      value: 43.896
    - type: ndcg_at_3
      value: 31.682
    - type: ndcg_at_5
      value: 34.178
    - type: precision_at_1
      value: 25.667
    - type: precision_at_10
      value: 5.567
    - type: precision_at_100
      value: 0.8
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 13.222000000000001
    - type: precision_at_5
      value: 9.333
    - type: recall_at_1
      value: 24.389
    - type: recall_at_10
      value: 50.833
    - type: recall_at_100
      value: 71.311
    - type: recall_at_1000
      value: 94.11699999999999
    - type: recall_at_3
      value: 36.361
    - type: recall_at_5
      value: 42.528
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.55841584158416
    - type: cos_sim_ap
      value: 82.22304986475189
    - type: cos_sim_f1
      value: 75.87939698492463
    - type: cos_sim_precision
      value: 76.26262626262627
    - type: cos_sim_recall
      value: 75.5
    - type: dot_accuracy
      value: 99.55841584158416
    - type: dot_ap
      value: 82.22304986475189
    - type: dot_f1
      value: 75.87939698492463
    - type: dot_precision
      value: 76.26262626262627
    - type: dot_recall
      value: 75.5
    - type: euclidean_accuracy
      value: 99.55841584158416
    - type: euclidean_ap
      value: 82.22304986475189
    - type: euclidean_f1
      value: 75.87939698492463
    - type: euclidean_precision
      value: 76.26262626262627
    - type: euclidean_recall
      value: 75.5
    - type: manhattan_accuracy
      value: 99.65643564356435
    - type: manhattan_ap
      value: 88.59947381749205
    - type: manhattan_f1
      value: 81.93515182707155
    - type: manhattan_precision
      value: 84.41145281018028
    - type: manhattan_recall
      value: 79.60000000000001
    - type: max_accuracy
      value: 99.65643564356435
    - type: max_ap
      value: 88.59947381749205
    - type: max_f1
      value: 81.93515182707155
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 40.15487119938627
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.454412099949135
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.30437085806053
    - type: mrr
      value: 41.771443425855196
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.730978898878607
    - type: cos_sim_spearman
      value: 30.39763492615794
    - type: dot_pearson
      value: 29.730978853483407
    - type: dot_spearman
      value: 30.39986658115624
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.881
    - type: map_at_10
      value: 6.317
    - type: map_at_100
      value: 10.148
    - type: map_at_1000
      value: 11.607000000000001
    - type: map_at_3
      value: 3.7859999999999996
    - type: map_at_5
      value: 4.93
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 39.155
    - type: mrr_at_100
      value: 40.329
    - type: mrr_at_1000
      value: 40.349000000000004
    - type: mrr_at_3
      value: 34.694
    - type: mrr_at_5
      value: 37.041000000000004
    - type: ndcg_at_1
      value: 24.490000000000002
    - type: ndcg_at_10
      value: 18.057000000000002
    - type: ndcg_at_100
      value: 27.607
    - type: ndcg_at_1000
      value: 39.967000000000006
    - type: ndcg_at_3
      value: 21.055
    - type: ndcg_at_5
      value: 19.653000000000002
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 16.122
    - type: precision_at_100
      value: 6.162999999999999
    - type: precision_at_1000
      value: 1.392
    - type: precision_at_3
      value: 21.769
    - type: precision_at_5
      value: 19.592000000000002
    - type: recall_at_1
      value: 1.881
    - type: recall_at_10
      value: 10.749
    - type: recall_at_100
      value: 37.302
    - type: recall_at_1000
      value: 75.095
    - type: recall_at_3
      value: 4.716
    - type: recall_at_5
      value: 6.851
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.23680000000002
    - type: ap
      value: 13.734287974781228
    - type: f1
      value: 53.447029519181534
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.062818336162984
    - type: f1
      value: 52.230909643972744
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.52730094235677
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.66078559933241
    - type: cos_sim_ap
      value: 62.37683883217069
    - type: cos_sim_f1
      value: 59.312101910828034
    - type: cos_sim_precision
      value: 57.33990147783251
    - type: cos_sim_recall
      value: 61.42480211081794
    - type: dot_accuracy
      value: 82.66078559933241
    - type: dot_ap
      value: 62.37683883217069
    - type: dot_f1
      value: 59.312101910828034
    - type: dot_precision
      value: 57.33990147783251
    - type: dot_recall
      value: 61.42480211081794
    - type: euclidean_accuracy
      value: 82.66078559933241
    - type: euclidean_ap
      value: 62.37683883217069
    - type: euclidean_f1
      value: 59.312101910828034
    - type: euclidean_precision
      value: 57.33990147783251
    - type: euclidean_recall
      value: 61.42480211081794
    - type: manhattan_accuracy
      value: 82.05281039518388
    - type: manhattan_ap
      value: 60.00452983178683
    - type: manhattan_f1
      value: 57.13604387742935
    - type: manhattan_precision
      value: 52.120948444637804
    - type: manhattan_recall
      value: 63.21899736147757
    - type: max_accuracy
      value: 82.66078559933241
    - type: max_ap
      value: 62.37683883217069
    - type: max_f1
      value: 59.312101910828034
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.01245779485389
    - type: cos_sim_ap
      value: 82.11640979696757
    - type: cos_sim_f1
      value: 74.081541218638
    - type: cos_sim_precision
      value: 71.91214844882575
    - type: cos_sim_recall
      value: 76.38589467200492
    - type: dot_accuracy
      value: 87.01245779485389
    - type: dot_ap
      value: 82.11640812292269
    - type: dot_f1
      value: 74.081541218638
    - type: dot_precision
      value: 71.91214844882575
    - type: dot_recall
      value: 76.38589467200492
    - type: euclidean_accuracy
      value: 87.01245779485389
    - type: euclidean_ap
      value: 82.11641535703677
    - type: euclidean_f1
      value: 74.081541218638
    - type: euclidean_precision
      value: 71.91214844882575
    - type: euclidean_recall
      value: 76.38589467200492
    - type: manhattan_accuracy
      value: 87.16963558039352
    - type: manhattan_ap
      value: 82.32473549889242
    - type: manhattan_f1
      value: 74.42121825129242
    - type: manhattan_precision
      value: 72.47191011235955
    - type: manhattan_recall
      value: 76.47828765013858
    - type: max_accuracy
      value: 87.16963558039352
    - type: max_ap
      value: 82.32473549889242
    - type: max_f1
      value: 74.42121825129242
---
