mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mpnet_main_noPCA
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 66.17910447761194
    - type: ap
      value: 29.915098065356872
    - type: f1
      value: 60.631543297362825
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.90149999999998
    - type: ap
      value: 61.09187168996711
    - type: f1
      value: 65.41989774086741
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.592
    - type: f1
      value: 32.88401104237512
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.061
    - type: map_at_10
      value: 31.788
    - type: map_at_100
      value: 32.976
    - type: map_at_1000
      value: 33.023
    - type: map_at_3
      value: 28.438000000000002
    - type: map_at_5
      value: 30.215999999999998
    - type: mrr_at_1
      value: 19.559
    - type: mrr_at_10
      value: 31.954
    - type: mrr_at_100
      value: 33.155
    - type: mrr_at_1000
      value: 33.202999999999996
    - type: mrr_at_3
      value: 28.639
    - type: mrr_at_5
      value: 30.396
    - type: ndcg_at_1
      value: 19.061
    - type: ndcg_at_10
      value: 38.637
    - type: ndcg_at_100
      value: 44.346999999999994
    - type: ndcg_at_1000
      value: 45.655
    - type: ndcg_at_3
      value: 31.61
    - type: ndcg_at_5
      value: 34.824
    - type: precision_at_1
      value: 19.061
    - type: precision_at_10
      value: 6.046
    - type: precision_at_100
      value: 0.8699999999999999
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 13.608
    - type: precision_at_5
      value: 9.73
    - type: recall_at_1
      value: 19.061
    - type: recall_at_10
      value: 60.455000000000005
    - type: recall_at_100
      value: 86.984
    - type: recall_at_1000
      value: 97.368
    - type: recall_at_3
      value: 40.825
    - type: recall_at_5
      value: 48.649
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 34.68623909661341
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 25.576794784072156
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.4773915587609
    - type: mrr
      value: 67.98179659675505
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 63.4043881224996
    - type: cos_sim_spearman
      value: 65.99608207875342
    - type: euclidean_pearson
      value: 63.973218436948045
    - type: euclidean_spearman
      value: 65.99608207875342
    - type: manhattan_pearson
      value: 64.3531518081004
    - type: manhattan_spearman
      value: 66.24849746876352
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.89935064935065
    - type: f1
      value: 66.47055453363906
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.5700118497176
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 24.14362840535985
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.654
    - type: map_at_10
      value: 25.569999999999997
    - type: map_at_100
      value: 26.667999999999996
    - type: map_at_1000
      value: 26.83
    - type: map_at_3
      value: 23.125
    - type: map_at_5
      value: 24.506
    - type: mrr_at_1
      value: 23.748
    - type: mrr_at_10
      value: 30.552
    - type: mrr_at_100
      value: 31.409
    - type: mrr_at_1000
      value: 31.489
    - type: mrr_at_3
      value: 28.517
    - type: mrr_at_5
      value: 29.626
    - type: ndcg_at_1
      value: 23.748
    - type: ndcg_at_10
      value: 30.436000000000003
    - type: ndcg_at_100
      value: 35.355
    - type: ndcg_at_1000
      value: 38.635999999999996
    - type: ndcg_at_3
      value: 26.689
    - type: ndcg_at_5
      value: 28.377999999999997
    - type: precision_at_1
      value: 23.748
    - type: precision_at_10
      value: 6.066
    - type: precision_at_100
      value: 1.083
    - type: precision_at_1000
      value: 0.174
    - type: precision_at_3
      value: 13.065999999999999
    - type: precision_at_5
      value: 9.642000000000001
    - type: recall_at_1
      value: 18.654
    - type: recall_at_10
      value: 39.518
    - type: recall_at_100
      value: 61.329
    - type: recall_at_1000
      value: 83.851
    - type: recall_at_3
      value: 28.134999999999998
    - type: recall_at_5
      value: 32.933
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 14.155000000000001
    - type: map_at_10
      value: 19.7
    - type: map_at_100
      value: 20.568
    - type: map_at_1000
      value: 20.689
    - type: map_at_3
      value: 17.926000000000002
    - type: map_at_5
      value: 18.861
    - type: mrr_at_1
      value: 18.089
    - type: mrr_at_10
      value: 23.564
    - type: mrr_at_100
      value: 24.366
    - type: mrr_at_1000
      value: 24.442
    - type: mrr_at_3
      value: 21.847
    - type: mrr_at_5
      value: 22.783
    - type: ndcg_at_1
      value: 18.089
    - type: ndcg_at_10
      value: 23.399
    - type: ndcg_at_100
      value: 27.516000000000002
    - type: ndcg_at_1000
      value: 30.371
    - type: ndcg_at_3
      value: 20.416
    - type: ndcg_at_5
      value: 21.667
    - type: precision_at_1
      value: 18.089
    - type: precision_at_10
      value: 4.497
    - type: precision_at_100
      value: 0.8250000000000001
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 10.064
    - type: precision_at_5
      value: 7.236
    - type: recall_at_1
      value: 14.155000000000001
    - type: recall_at_10
      value: 30.598
    - type: recall_at_100
      value: 48.846000000000004
    - type: recall_at_1000
      value: 68.664
    - type: recall_at_3
      value: 21.488
    - type: recall_at_5
      value: 25.105
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 22.637999999999998
    - type: map_at_10
      value: 30.701
    - type: map_at_100
      value: 31.822
    - type: map_at_1000
      value: 31.918000000000003
    - type: map_at_3
      value: 28.050000000000004
    - type: map_at_5
      value: 29.470000000000002
    - type: mrr_at_1
      value: 26.395000000000003
    - type: mrr_at_10
      value: 33.799
    - type: mrr_at_100
      value: 34.759
    - type: mrr_at_1000
      value: 34.819
    - type: mrr_at_3
      value: 31.432
    - type: mrr_at_5
      value: 32.689
    - type: ndcg_at_1
      value: 26.395000000000003
    - type: ndcg_at_10
      value: 35.547000000000004
    - type: ndcg_at_100
      value: 40.833999999999996
    - type: ndcg_at_1000
      value: 43.053000000000004
    - type: ndcg_at_3
      value: 30.570999999999998
    - type: ndcg_at_5
      value: 32.809
    - type: precision_at_1
      value: 26.395000000000003
    - type: precision_at_10
      value: 5.969
    - type: precision_at_100
      value: 0.942
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 13.793
    - type: precision_at_5
      value: 9.780999999999999
    - type: recall_at_1
      value: 22.637999999999998
    - type: recall_at_10
      value: 47.433
    - type: recall_at_100
      value: 71.063
    - type: recall_at_1000
      value: 87.107
    - type: recall_at_3
      value: 33.891
    - type: recall_at_5
      value: 39.324
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.038
    - type: map_at_10
      value: 14.238999999999999
    - type: map_at_100
      value: 15.094
    - type: map_at_1000
      value: 15.207999999999998
    - type: map_at_3
      value: 12.713
    - type: map_at_5
      value: 13.467
    - type: mrr_at_1
      value: 10.96
    - type: mrr_at_10
      value: 15.21
    - type: mrr_at_100
      value: 16.075999999999997
    - type: mrr_at_1000
      value: 16.176
    - type: mrr_at_3
      value: 13.672
    - type: mrr_at_5
      value: 14.429
    - type: ndcg_at_1
      value: 10.96
    - type: ndcg_at_10
      value: 17.014000000000003
    - type: ndcg_at_100
      value: 21.624
    - type: ndcg_at_1000
      value: 24.913
    - type: ndcg_at_3
      value: 13.825999999999999
    - type: ndcg_at_5
      value: 15.145
    - type: precision_at_1
      value: 10.96
    - type: precision_at_10
      value: 2.825
    - type: precision_at_100
      value: 0.547
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 5.951
    - type: precision_at_5
      value: 4.316
    - type: recall_at_1
      value: 10.038
    - type: recall_at_10
      value: 24.832
    - type: recall_at_100
      value: 46.743
    - type: recall_at_1000
      value: 72.21300000000001
    - type: recall_at_3
      value: 15.959999999999999
    - type: recall_at_5
      value: 19.171
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.667
    - type: map_at_10
      value: 8.973
    - type: map_at_100
      value: 9.798
    - type: map_at_1000
      value: 9.911
    - type: map_at_3
      value: 7.704
    - type: map_at_5
      value: 8.421
    - type: mrr_at_1
      value: 7.587000000000001
    - type: mrr_at_10
      value: 11.571
    - type: mrr_at_100
      value: 12.396
    - type: mrr_at_1000
      value: 12.485
    - type: mrr_at_3
      value: 9.991999999999999
    - type: mrr_at_5
      value: 10.85
    - type: ndcg_at_1
      value: 7.587000000000001
    - type: ndcg_at_10
      value: 11.613
    - type: ndcg_at_100
      value: 16.055
    - type: ndcg_at_1000
      value: 19.215
    - type: ndcg_at_3
      value: 9.014999999999999
    - type: ndcg_at_5
      value: 10.238999999999999
    - type: precision_at_1
      value: 7.587000000000001
    - type: precision_at_10
      value: 2.338
    - type: precision_at_100
      value: 0.532
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.436
    - type: precision_at_5
      value: 3.5319999999999996
    - type: recall_at_1
      value: 5.667
    - type: recall_at_10
      value: 17.343
    - type: recall_at_100
      value: 37.655
    - type: recall_at_1000
      value: 60.79
    - type: recall_at_3
      value: 10.202
    - type: recall_at_5
      value: 13.286999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 14.737
    - type: map_at_10
      value: 20.063
    - type: map_at_100
      value: 21.207
    - type: map_at_1000
      value: 21.353
    - type: map_at_3
      value: 17.809
    - type: map_at_5
      value: 19.056
    - type: mrr_at_1
      value: 18.479
    - type: mrr_at_10
      value: 24.338
    - type: mrr_at_100
      value: 25.3
    - type: mrr_at_1000
      value: 25.389
    - type: mrr_at_3
      value: 21.976000000000003
    - type: mrr_at_5
      value: 23.362
    - type: ndcg_at_1
      value: 18.479
    - type: ndcg_at_10
      value: 24.232
    - type: ndcg_at_100
      value: 29.977999999999998
    - type: ndcg_at_1000
      value: 33.384
    - type: ndcg_at_3
      value: 20.145
    - type: ndcg_at_5
      value: 22.085
    - type: precision_at_1
      value: 18.479
    - type: precision_at_10
      value: 4.649
    - type: precision_at_100
      value: 0.9209999999999999
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 9.464
    - type: precision_at_5
      value: 7.276000000000001
    - type: recall_at_1
      value: 14.737
    - type: recall_at_10
      value: 32.812000000000005
    - type: recall_at_100
      value: 58.523
    - type: recall_at_1000
      value: 82.364
    - type: recall_at_3
      value: 21.349
    - type: recall_at_5
      value: 26.16
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.33
    - type: map_at_10
      value: 14.835999999999999
    - type: map_at_100
      value: 15.865000000000002
    - type: map_at_1000
      value: 16.017
    - type: map_at_3
      value: 12.781
    - type: map_at_5
      value: 13.876
    - type: mrr_at_1
      value: 12.784999999999998
    - type: mrr_at_10
      value: 17.812
    - type: mrr_at_100
      value: 18.744
    - type: mrr_at_1000
      value: 18.845
    - type: mrr_at_3
      value: 15.753
    - type: mrr_at_5
      value: 16.866
    - type: ndcg_at_1
      value: 12.784999999999998
    - type: ndcg_at_10
      value: 18.424
    - type: ndcg_at_100
      value: 23.777
    - type: ndcg_at_1000
      value: 27.478
    - type: ndcg_at_3
      value: 14.560999999999998
    - type: ndcg_at_5
      value: 16.317999999999998
    - type: precision_at_1
      value: 12.784999999999998
    - type: precision_at_10
      value: 3.687
    - type: precision_at_100
      value: 0.767
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 7.002
    - type: precision_at_5
      value: 5.548
    - type: recall_at_1
      value: 10.33
    - type: recall_at_10
      value: 26.449
    - type: recall_at_100
      value: 50.695
    - type: recall_at_1000
      value: 76.665
    - type: recall_at_3
      value: 15.789
    - type: recall_at_5
      value: 20.233999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 11.840416666666668
    - type: map_at_10
      value: 16.582916666666666
    - type: map_at_100
      value: 17.531916666666667
    - type: map_at_1000
      value: 17.660666666666668
    - type: map_at_3
      value: 14.832333333333333
    - type: map_at_5
      value: 15.772083333333336
    - type: mrr_at_1
      value: 14.546999999999999
    - type: mrr_at_10
      value: 19.4685
    - type: mrr_at_100
      value: 20.341916666666666
    - type: mrr_at_1000
      value: 20.431083333333337
    - type: mrr_at_3
      value: 17.71991666666667
    - type: mrr_at_5
      value: 18.668333333333333
    - type: ndcg_at_1
      value: 14.546999999999999
    - type: ndcg_at_10
      value: 19.966
    - type: ndcg_at_100
      value: 24.727666666666664
    - type: ndcg_at_1000
      value: 27.955666666666666
    - type: ndcg_at_3
      value: 16.735000000000003
    - type: ndcg_at_5
      value: 18.183083333333332
    - type: precision_at_1
      value: 14.546999999999999
    - type: precision_at_10
      value: 3.711833333333334
    - type: precision_at_100
      value: 0.7289166666666667
    - type: precision_at_1000
      value: 0.1190833333333333
    - type: precision_at_3
      value: 7.868166666666668
    - type: precision_at_5
      value: 5.833083333333333
    - type: recall_at_1
      value: 11.840416666666668
    - type: recall_at_10
      value: 27.398583333333338
    - type: recall_at_100
      value: 49.24408333333333
    - type: recall_at_1000
      value: 72.64841666666666
    - type: recall_at_3
      value: 18.2145
    - type: recall_at_5
      value: 21.962500000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.075
    - type: map_at_10
      value: 12.838
    - type: map_at_100
      value: 13.655999999999999
    - type: map_at_1000
      value: 13.741
    - type: map_at_3
      value: 11.088000000000001
    - type: map_at_5
      value: 12.063
    - type: mrr_at_1
      value: 11.043
    - type: mrr_at_10
      value: 14.936
    - type: mrr_at_100
      value: 15.781999999999998
    - type: mrr_at_1000
      value: 15.859000000000002
    - type: mrr_at_3
      value: 13.241
    - type: mrr_at_5
      value: 14.261
    - type: ndcg_at_1
      value: 11.043
    - type: ndcg_at_10
      value: 15.726999999999999
    - type: ndcg_at_100
      value: 19.872999999999998
    - type: ndcg_at_1000
      value: 22.484
    - type: ndcg_at_3
      value: 12.401
    - type: ndcg_at_5
      value: 14.007
    - type: precision_at_1
      value: 11.043
    - type: precision_at_10
      value: 2.8529999999999998
    - type: precision_at_100
      value: 0.5349999999999999
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 5.675
    - type: precision_at_5
      value: 4.387
    - type: recall_at_1
      value: 9.075
    - type: recall_at_10
      value: 22.91
    - type: recall_at_100
      value: 41.839999999999996
    - type: recall_at_1000
      value: 61.913
    - type: recall_at_3
      value: 13.618
    - type: recall_at_5
      value: 17.681
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.831
    - type: map_at_10
      value: 8.876000000000001
    - type: map_at_100
      value: 9.508999999999999
    - type: map_at_1000
      value: 9.631
    - type: map_at_3
      value: 7.7829999999999995
    - type: map_at_5
      value: 8.322000000000001
    - type: mrr_at_1
      value: 7.674
    - type: mrr_at_10
      value: 11.017000000000001
    - type: mrr_at_100
      value: 11.672
    - type: mrr_at_1000
      value: 11.774
    - type: mrr_at_3
      value: 9.825000000000001
    - type: mrr_at_5
      value: 10.404
    - type: ndcg_at_1
      value: 7.674
    - type: ndcg_at_10
      value: 11.169
    - type: ndcg_at_100
      value: 14.768
    - type: ndcg_at_1000
      value: 18.358
    - type: ndcg_at_3
      value: 9.039
    - type: ndcg_at_5
      value: 9.879
    - type: precision_at_1
      value: 7.674
    - type: precision_at_10
      value: 2.175
    - type: precision_at_100
      value: 0.488
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 4.4159999999999995
    - type: precision_at_5
      value: 3.29
    - type: recall_at_1
      value: 5.831
    - type: recall_at_10
      value: 16.205
    - type: recall_at_100
      value: 33.265
    - type: recall_at_1000
      value: 60.112
    - type: recall_at_3
      value: 10.104000000000001
    - type: recall_at_5
      value: 12.26
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.262
    - type: map_at_10
      value: 14.985000000000001
    - type: map_at_100
      value: 15.933
    - type: map_at_1000
      value: 16.047
    - type: map_at_3
      value: 13.735
    - type: map_at_5
      value: 14.379
    - type: mrr_at_1
      value: 13.899000000000001
    - type: mrr_at_10
      value: 18.099999999999998
    - type: mrr_at_100
      value: 19.027
    - type: mrr_at_1000
      value: 19.117
    - type: mrr_at_3
      value: 16.76
    - type: mrr_at_5
      value: 17.477999999999998
    - type: ndcg_at_1
      value: 13.899000000000001
    - type: ndcg_at_10
      value: 17.811
    - type: ndcg_at_100
      value: 22.898
    - type: ndcg_at_1000
      value: 25.999
    - type: ndcg_at_3
      value: 15.418000000000001
    - type: ndcg_at_5
      value: 16.394000000000002
    - type: precision_at_1
      value: 13.899000000000001
    - type: precision_at_10
      value: 3.0220000000000002
    - type: precision_at_100
      value: 0.626
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 7.058000000000001
    - type: precision_at_5
      value: 4.944
    - type: recall_at_1
      value: 11.262
    - type: recall_at_10
      value: 23.663999999999998
    - type: recall_at_100
      value: 47.293
    - type: recall_at_1000
      value: 69.907
    - type: recall_at_3
      value: 16.713
    - type: recall_at_5
      value: 19.366
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 11.904
    - type: map_at_10
      value: 16.628999999999998
    - type: map_at_100
      value: 17.779
    - type: map_at_1000
      value: 17.985
    - type: map_at_3
      value: 15.107999999999999
    - type: map_at_5
      value: 15.673
    - type: mrr_at_1
      value: 15.217
    - type: mrr_at_10
      value: 19.952
    - type: mrr_at_100
      value: 20.921
    - type: mrr_at_1000
      value: 21.029
    - type: mrr_at_3
      value: 18.379
    - type: mrr_at_5
      value: 18.992
    - type: ndcg_at_1
      value: 15.217
    - type: ndcg_at_10
      value: 20.173
    - type: ndcg_at_100
      value: 25.15
    - type: ndcg_at_1000
      value: 29.402
    - type: ndcg_at_3
      value: 17.513
    - type: ndcg_at_5
      value: 18.246000000000002
    - type: precision_at_1
      value: 15.217
    - type: precision_at_10
      value: 4.15
    - type: precision_at_100
      value: 0.962
    - type: precision_at_1000
      value: 0.187
    - type: precision_at_3
      value: 8.564
    - type: precision_at_5
      value: 6.126
    - type: recall_at_1
      value: 11.904
    - type: recall_at_10
      value: 26.458
    - type: recall_at_100
      value: 49.964999999999996
    - type: recall_at_1000
      value: 79.372
    - type: recall_at_3
      value: 18.127
    - type: recall_at_5
      value: 20.426
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 7.794
    - type: map_at_10
      value: 11.584999999999999
    - type: map_at_100
      value: 12.484
    - type: map_at_1000
      value: 12.598
    - type: map_at_3
      value: 10.166
    - type: map_at_5
      value: 11.171000000000001
    - type: mrr_at_1
      value: 8.688
    - type: mrr_at_10
      value: 12.770999999999999
    - type: mrr_at_100
      value: 13.651
    - type: mrr_at_1000
      value: 13.749
    - type: mrr_at_3
      value: 11.245
    - type: mrr_at_5
      value: 12.280000000000001
    - type: ndcg_at_1
      value: 8.688
    - type: ndcg_at_10
      value: 14.047
    - type: ndcg_at_100
      value: 18.904
    - type: ndcg_at_1000
      value: 22.175
    - type: ndcg_at_3
      value: 11.225999999999999
    - type: ndcg_at_5
      value: 13.03
    - type: precision_at_1
      value: 8.688
    - type: precision_at_10
      value: 2.311
    - type: precision_at_100
      value: 0.519
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 4.929
    - type: precision_at_5
      value: 3.9190000000000005
    - type: recall_at_1
      value: 7.794
    - type: recall_at_10
      value: 20.561
    - type: recall_at_100
      value: 43.712
    - type: recall_at_1000
      value: 68.82300000000001
    - type: recall_at_3
      value: 13.197999999999999
    - type: recall_at_5
      value: 17.602999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.777
    - type: map_at_10
      value: 10.610999999999999
    - type: map_at_100
      value: 11.914
    - type: map_at_1000
      value: 12.120000000000001
    - type: map_at_3
      value: 8.485
    - type: map_at_5
      value: 9.532
    - type: mrr_at_1
      value: 12.964
    - type: mrr_at_10
      value: 21.23
    - type: mrr_at_100
      value: 22.387999999999998
    - type: mrr_at_1000
      value: 22.459
    - type: mrr_at_3
      value: 17.849999999999998
    - type: mrr_at_5
      value: 19.785
    - type: ndcg_at_1
      value: 12.964
    - type: ndcg_at_10
      value: 16.059
    - type: ndcg_at_100
      value: 22.384
    - type: ndcg_at_1000
      value: 26.373
    - type: ndcg_at_3
      value: 11.855
    - type: ndcg_at_5
      value: 13.437
    - type: precision_at_1
      value: 12.964
    - type: precision_at_10
      value: 5.388
    - type: precision_at_100
      value: 1.221
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 8.86
    - type: precision_at_5
      value: 7.492
    - type: recall_at_1
      value: 5.777
    - type: recall_at_10
      value: 21.085
    - type: recall_at_100
      value: 43.699
    - type: recall_at_1000
      value: 66.295
    - type: recall_at_3
      value: 11.202
    - type: recall_at_5
      value: 15.029
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.8080000000000003
    - type: map_at_10
      value: 6.64
    - type: map_at_100
      value: 9.282
    - type: map_at_1000
      value: 10.083
    - type: map_at_3
      value: 4.709
    - type: map_at_5
      value: 5.5169999999999995
    - type: mrr_at_1
      value: 32.0
    - type: mrr_at_10
      value: 41.715
    - type: mrr_at_100
      value: 42.617
    - type: mrr_at_1000
      value: 42.649
    - type: mrr_at_3
      value: 38.417
    - type: mrr_at_5
      value: 40.454
    - type: ndcg_at_1
      value: 23.0
    - type: ndcg_at_10
      value: 17.944
    - type: ndcg_at_100
      value: 20.96
    - type: ndcg_at_1000
      value: 27.433000000000003
    - type: ndcg_at_3
      value: 19.371
    - type: ndcg_at_5
      value: 18.555
    - type: precision_at_1
      value: 32.0
    - type: precision_at_10
      value: 16.225
    - type: precision_at_100
      value: 5.455
    - type: precision_at_1000
      value: 1.25
    - type: precision_at_3
      value: 23.333000000000002
    - type: precision_at_5
      value: 20.4
    - type: recall_at_1
      value: 2.8080000000000003
    - type: recall_at_10
      value: 10.945
    - type: recall_at_100
      value: 27.131
    - type: recall_at_1000
      value: 49.501
    - type: recall_at_3
      value: 5.773
    - type: recall_at_5
      value: 7.649
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.46
    - type: f1
      value: 39.33621025032797
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 11.975
    - type: map_at_10
      value: 17.531
    - type: map_at_100
      value: 18.384
    - type: map_at_1000
      value: 18.464
    - type: map_at_3
      value: 15.634
    - type: map_at_5
      value: 16.649
    - type: mrr_at_1
      value: 12.616
    - type: mrr_at_10
      value: 18.508
    - type: mrr_at_100
      value: 19.375999999999998
    - type: mrr_at_1000
      value: 19.451
    - type: mrr_at_3
      value: 16.542
    - type: mrr_at_5
      value: 17.596
    - type: ndcg_at_1
      value: 12.616
    - type: ndcg_at_10
      value: 21.026
    - type: ndcg_at_100
      value: 25.588
    - type: ndcg_at_1000
      value: 27.945999999999998
    - type: ndcg_at_3
      value: 17.069000000000003
    - type: ndcg_at_5
      value: 18.903
    - type: precision_at_1
      value: 12.616
    - type: precision_at_10
      value: 3.351
    - type: precision_at_100
      value: 0.583
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 7.251
    - type: precision_at_5
      value: 5.299
    - type: recall_at_1
      value: 11.975
    - type: recall_at_10
      value: 31.141999999999996
    - type: recall_at_100
      value: 52.893
    - type: recall_at_1000
      value: 71.345
    - type: recall_at_3
      value: 20.288999999999998
    - type: recall_at_5
      value: 24.731
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.273
    - type: map_at_10
      value: 8.871
    - type: map_at_100
      value: 9.959999999999999
    - type: map_at_1000
      value: 10.158000000000001
    - type: map_at_3
      value: 7.566000000000001
    - type: map_at_5
      value: 8.27
    - type: mrr_at_1
      value: 10.34
    - type: mrr_at_10
      value: 15.906999999999998
    - type: mrr_at_100
      value: 16.964000000000002
    - type: mrr_at_1000
      value: 17.063
    - type: mrr_at_3
      value: 14.222999999999999
    - type: mrr_at_5
      value: 15.110999999999999
    - type: ndcg_at_1
      value: 10.34
    - type: ndcg_at_10
      value: 12.492
    - type: ndcg_at_100
      value: 18.321
    - type: ndcg_at_1000
      value: 23.01
    - type: ndcg_at_3
      value: 10.497
    - type: ndcg_at_5
      value: 11.263
    - type: precision_at_1
      value: 10.34
    - type: precision_at_10
      value: 3.611
    - type: precision_at_100
      value: 0.9440000000000001
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 7.202
    - type: precision_at_5
      value: 5.525
    - type: recall_at_1
      value: 5.273
    - type: recall_at_10
      value: 16.216
    - type: recall_at_100
      value: 39.699
    - type: recall_at_1000
      value: 68.939
    - type: recall_at_3
      value: 10.099
    - type: recall_at_5
      value: 12.565000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 12.849
    - type: map_at_10
      value: 18.05
    - type: map_at_100
      value: 18.75
    - type: map_at_1000
      value: 18.848000000000003
    - type: map_at_3
      value: 16.567
    - type: map_at_5
      value: 17.366999999999997
    - type: mrr_at_1
      value: 25.698999999999998
    - type: mrr_at_10
      value: 31.706
    - type: mrr_at_100
      value: 32.389
    - type: mrr_at_1000
      value: 32.455
    - type: mrr_at_3
      value: 29.982
    - type: mrr_at_5
      value: 30.918
    - type: ndcg_at_1
      value: 25.698999999999998
    - type: ndcg_at_10
      value: 23.515
    - type: ndcg_at_100
      value: 27.023999999999997
    - type: ndcg_at_1000
      value: 29.568
    - type: ndcg_at_3
      value: 20.516000000000002
    - type: ndcg_at_5
      value: 21.92
    - type: precision_at_1
      value: 25.698999999999998
    - type: precision_at_10
      value: 5.256
    - type: precision_at_100
      value: 0.8089999999999999
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 12.987000000000002
    - type: precision_at_5
      value: 8.907
    - type: recall_at_1
      value: 12.849
    - type: recall_at_10
      value: 26.279999999999998
    - type: recall_at_100
      value: 40.425
    - type: recall_at_1000
      value: 57.475
    - type: recall_at_3
      value: 19.48
    - type: recall_at_5
      value: 22.269
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.348
    - type: ap
      value: 59.61111885993664
    - type: f1
      value: 63.961804601173654
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.439
    - type: map_at_10
      value: 9.328
    - type: map_at_100
      value: 10.15
    - type: map_at_1000
      value: 10.253
    - type: map_at_3
      value: 7.815999999999999
    - type: map_at_5
      value: 8.603
    - type: mrr_at_1
      value: 5.63
    - type: mrr_at_10
      value: 9.602
    - type: mrr_at_100
      value: 10.431
    - type: mrr_at_1000
      value: 10.532
    - type: mrr_at_3
      value: 8.075000000000001
    - type: mrr_at_5
      value: 8.868
    - type: ndcg_at_1
      value: 5.6160000000000005
    - type: ndcg_at_10
      value: 11.882
    - type: ndcg_at_100
      value: 16.470000000000002
    - type: ndcg_at_1000
      value: 19.608999999999998
    - type: ndcg_at_3
      value: 8.698
    - type: ndcg_at_5
      value: 10.127
    - type: precision_at_1
      value: 5.6160000000000005
    - type: precision_at_10
      value: 2.0660000000000003
    - type: precision_at_100
      value: 0.445
    - type: precision_at_1000
      value: 0.07200000000000001
    - type: precision_at_3
      value: 3.811
    - type: precision_at_5
      value: 3.006
    - type: recall_at_1
      value: 5.439
    - type: recall_at_10
      value: 19.85
    - type: recall_at_100
      value: 42.443999999999996
    - type: recall_at_1000
      value: 67.71000000000001
    - type: recall_at_3
      value: 11.01
    - type: recall_at_5
      value: 14.482000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.34610123119015
    - type: f1
      value: 86.87824748448996
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 55.30551755585955
    - type: f1
      value: 37.30830810806748
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.56489576328177
    - type: f1
      value: 58.53640872383665
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.9731002017485
    - type: f1
      value: 68.70974796245125
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.278314945309308
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.548588443187253
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.152886820612594
    - type: mrr
      value: 29.929031477073426
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.8699999999999997
    - type: map_at_10
      value: 6.952999999999999
    - type: map_at_100
      value: 9.008
    - type: map_at_1000
      value: 10.302999999999999
    - type: map_at_3
      value: 5.478000000000001
    - type: map_at_5
      value: 6.16
    - type: mrr_at_1
      value: 30.031000000000002
    - type: mrr_at_10
      value: 39.985
    - type: mrr_at_100
      value: 40.83
    - type: mrr_at_1000
      value: 40.888000000000005
    - type: mrr_at_3
      value: 37.307
    - type: mrr_at_5
      value: 39.056000000000004
    - type: ndcg_at_1
      value: 27.864
    - type: ndcg_at_10
      value: 21.708
    - type: ndcg_at_100
      value: 21.933
    - type: ndcg_at_1000
      value: 31.895
    - type: ndcg_at_3
      value: 24.476
    - type: ndcg_at_5
      value: 23.402
    - type: precision_at_1
      value: 30.031000000000002
    - type: precision_at_10
      value: 15.728
    - type: precision_at_100
      value: 6.099
    - type: precision_at_1000
      value: 1.9689999999999999
    - type: precision_at_3
      value: 22.704
    - type: precision_at_5
      value: 19.875999999999998
    - type: recall_at_1
      value: 3.8699999999999997
    - type: recall_at_10
      value: 10.691
    - type: recall_at_100
      value: 25.198999999999998
    - type: recall_at_1000
      value: 60.172000000000004
    - type: recall_at_3
      value: 6.428000000000001
    - type: recall_at_5
      value: 8.078000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.394
    - type: map_at_10
      value: 13.954
    - type: map_at_100
      value: 15.109
    - type: map_at_1000
      value: 15.209
    - type: map_at_3
      value: 11.873000000000001
    - type: map_at_5
      value: 12.883
    - type: mrr_at_1
      value: 9.589
    - type: mrr_at_10
      value: 15.543000000000001
    - type: mrr_at_100
      value: 16.63
    - type: mrr_at_1000
      value: 16.715
    - type: mrr_at_3
      value: 13.334999999999999
    - type: mrr_at_5
      value: 14.432
    - type: ndcg_at_1
      value: 9.589
    - type: ndcg_at_10
      value: 17.755000000000003
    - type: ndcg_at_100
      value: 23.519000000000002
    - type: ndcg_at_1000
      value: 26.238
    - type: ndcg_at_3
      value: 13.36
    - type: ndcg_at_5
      value: 15.183
    - type: precision_at_1
      value: 9.589
    - type: precision_at_10
      value: 3.311
    - type: precision_at_100
      value: 0.655
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.267
    - type: precision_at_5
      value: 4.786
    - type: recall_at_1
      value: 8.394
    - type: recall_at_10
      value: 28.061000000000003
    - type: recall_at_100
      value: 54.56999999999999
    - type: recall_at_1000
      value: 75.476
    - type: recall_at_3
      value: 16.259
    - type: recall_at_5
      value: 20.488
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.926
    - type: map_at_10
      value: 74.431
    - type: map_at_100
      value: 75.199
    - type: map_at_1000
      value: 75.234
    - type: map_at_3
      value: 71.533
    - type: map_at_5
      value: 73.247
    - type: mrr_at_1
      value: 71.13000000000001
    - type: mrr_at_10
      value: 78.53
    - type: mrr_at_100
      value: 78.8
    - type: mrr_at_1000
      value: 78.807
    - type: mrr_at_3
      value: 77.077
    - type: mrr_at_5
      value: 77.987
    - type: ndcg_at_1
      value: 71.17
    - type: ndcg_at_10
      value: 79.048
    - type: ndcg_at_100
      value: 81.219
    - type: ndcg_at_1000
      value: 81.652
    - type: ndcg_at_3
      value: 75.482
    - type: ndcg_at_5
      value: 77.268
    - type: precision_at_1
      value: 71.17
    - type: precision_at_10
      value: 11.962
    - type: precision_at_100
      value: 1.432
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 32.747
    - type: precision_at_5
      value: 21.63
    - type: recall_at_1
      value: 61.926
    - type: recall_at_10
      value: 88.012
    - type: recall_at_100
      value: 96.27799999999999
    - type: recall_at_1000
      value: 98.798
    - type: recall_at_3
      value: 77.802
    - type: recall_at_5
      value: 82.753
    - type: map_at_1
      value: 2.563
    - type: map_at_10
      value: 6.295000000000001
    - type: map_at_100
      value: 7.7090000000000005
    - type: map_at_1000
      value: 7.969999999999999
    - type: map_at_3
      value: 4.598
    - type: map_at_5
      value: 5.407
    - type: mrr_at_1
      value: 12.6
    - type: mrr_at_10
      value: 20.418
    - type: mrr_at_100
      value: 21.662
    - type: mrr_at_1000
      value: 21.757
    - type: mrr_at_3
      value: 17.7
    - type: mrr_at_5
      value: 19.13
    - type: ndcg_at_1
      value: 12.6
    - type: ndcg_at_10
      value: 11.451
    - type: ndcg_at_100
      value: 18.031
    - type: ndcg_at_1000
      value: 23.324
    - type: ndcg_at_3
      value: 10.620000000000001
    - type: ndcg_at_5
      value: 9.318999999999999
    - type: precision_at_1
      value: 12.6
    - type: precision_at_10
      value: 6.069999999999999
    - type: precision_at_100
      value: 1.574
    - type: precision_at_1000
      value: 0.28500000000000003
    - type: precision_at_3
      value: 10.067
    - type: precision_at_5
      value: 8.28
    - type: recall_at_1
      value: 2.563
    - type: recall_at_10
      value: 12.303
    - type: recall_at_100
      value: 31.936999999999998
    - type: recall_at_1000
      value: 57.857
    - type: recall_at_3
      value: 6.143
    - type: recall_at_5
      value: 8.402999999999999
    - type: map_at_1
      value: 0.13999999999999999
    - type: map_at_10
      value: 1.079
    - type: map_at_100
      value: 5.253
    - type: map_at_1000
      value: 11.628
    - type: map_at_3
      value: 0.381
    - type: map_at_5
      value: 0.5910000000000001
    - type: mrr_at_1
      value: 64.0
    - type: mrr_at_10
      value: 73.52199999999999
    - type: mrr_at_100
      value: 73.76599999999999
    - type: mrr_at_1000
      value: 73.76599999999999
    - type: mrr_at_3
      value: 70.0
    - type: mrr_at_5
      value: 73.3
    - type: ndcg_at_1
      value: 54.0
    - type: ndcg_at_10
      value: 51.539
    - type: ndcg_at_100
      value: 36.793
    - type: ndcg_at_1000
      value: 31.445
    - type: ndcg_at_3
      value: 55.358
    - type: ndcg_at_5
      value: 54.09
    - type: precision_at_1
      value: 62.0
    - type: precision_at_10
      value: 56.99999999999999
    - type: precision_at_100
      value: 38.5
    - type: precision_at_1000
      value: 14.89
    - type: precision_at_3
      value: 62.0
    - type: precision_at_5
      value: 60.4
    - type: recall_at_1
      value: 0.13999999999999999
    - type: recall_at_10
      value: 1.363
    - type: recall_at_100
      value: 8.437
    - type: recall_at_1000
      value: 30.009000000000004
    - type: recall_at_3
      value: 0.42100000000000004
    - type: recall_at_5
      value: 0.707
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 36.54351503776994
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 42.81751164015398
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.50532608207854
    - type: cos_sim_spearman
      value: 63.950267363046066
    - type: euclidean_pearson
      value: 71.48900145754592
    - type: euclidean_spearman
      value: 63.95025108189094
    - type: manhattan_pearson
      value: 71.46914891725389
    - type: manhattan_spearman
      value: 63.805631301153234
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 78.67166222228276
    - type: cos_sim_spearman
      value: 70.58796687266529
    - type: euclidean_pearson
      value: 77.16081310919238
    - type: euclidean_spearman
      value: 70.58929744987967
    - type: manhattan_pearson
      value: 76.68488607691035
    - type: manhattan_spearman
      value: 70.0327430835916
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 71.4524578899399
    - type: cos_sim_spearman
      value: 75.05284552914544
    - type: euclidean_pearson
      value: 74.26921865890489
    - type: euclidean_spearman
      value: 75.05285774089658
    - type: manhattan_pearson
      value: 74.0956567190936
    - type: manhattan_spearman
      value: 74.86222540130267
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 71.81980218034083
    - type: cos_sim_spearman
      value: 70.20861321413521
    - type: euclidean_pearson
      value: 72.00956058839543
    - type: euclidean_spearman
      value: 70.20860352828727
    - type: manhattan_pearson
      value: 71.71938025408232
    - type: manhattan_spearman
      value: 69.92067749588861
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 73.83235504179899
    - type: cos_sim_spearman
      value: 76.8445071883385
    - type: euclidean_pearson
      value: 76.65192888366596
    - type: euclidean_spearman
      value: 76.84451551851657
    - type: manhattan_pearson
      value: 76.66668017197009
    - type: manhattan_spearman
      value: 76.87341672884972
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 61.12551529075429
    - type: cos_sim_spearman
      value: 66.67758627454123
    - type: euclidean_pearson
      value: 66.59173996480177
    - type: euclidean_spearman
      value: 66.67785877747411
    - type: manhattan_pearson
      value: 66.37511769336047
    - type: manhattan_spearman
      value: 66.5054471994654
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 75.06291607690841
    - type: cos_sim_spearman
      value: 77.37108970488741
    - type: euclidean_pearson
      value: 77.70305630603308
    - type: euclidean_spearman
      value: 77.37196769029644
    - type: manhattan_pearson
      value: 77.1370834969229
    - type: manhattan_spearman
      value: 76.96954286371034
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 39.50668978875873
    - type: cos_sim_spearman
      value: 54.957434504461666
    - type: euclidean_pearson
      value: 48.82819878233644
    - type: euclidean_spearman
      value: 54.957434504461666
    - type: manhattan_pearson
      value: 49.070752263382204
    - type: manhattan_spearman
      value: 54.96085273619171
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 69.07035417658656
    - type: cos_sim_spearman
      value: 67.38139313155563
    - type: euclidean_pearson
      value: 70.40908067018542
    - type: euclidean_spearman
      value: 67.38141160926612
    - type: manhattan_pearson
      value: 70.23111585340908
    - type: manhattan_spearman
      value: 67.21952079135802
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.02197891095322
    - type: mrr
      value: 89.87414908983537
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 29.833
    - type: map_at_10
      value: 38.287
    - type: map_at_100
      value: 39.269999999999996
    - type: map_at_1000
      value: 39.359
    - type: map_at_3
      value: 35.221999999999994
    - type: map_at_5
      value: 37.364000000000004
    - type: mrr_at_1
      value: 31.333
    - type: mrr_at_10
      value: 39.601
    - type: mrr_at_100
      value: 40.465
    - type: mrr_at_1000
      value: 40.538000000000004
    - type: mrr_at_3
      value: 36.722
    - type: mrr_at_5
      value: 38.756
    - type: ndcg_at_1
      value: 31.333
    - type: ndcg_at_10
      value: 43.177
    - type: ndcg_at_100
      value: 48.275
    - type: ndcg_at_1000
      value: 50.474
    - type: ndcg_at_3
      value: 37.316
    - type: ndcg_at_5
      value: 40.977999999999994
    - type: precision_at_1
      value: 31.333
    - type: precision_at_10
      value: 6.2330000000000005
    - type: precision_at_100
      value: 0.9169999999999999
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 14.889
    - type: precision_at_5
      value: 10.867
    - type: recall_at_1
      value: 29.833
    - type: recall_at_10
      value: 57.138999999999996
    - type: recall_at_100
      value: 81.406
    - type: recall_at_1000
      value: 98.26700000000001
    - type: recall_at_3
      value: 41.75
    - type: recall_at_5
      value: 50.5
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.58316831683169
    - type: cos_sim_ap
      value: 82.6462064416366
    - type: cos_sim_f1
      value: 77.26315789473685
    - type: cos_sim_precision
      value: 81.55555555555556
    - type: cos_sim_recall
      value: 73.4
    - type: dot_accuracy
      value: 99.58316831683169
    - type: dot_ap
      value: 82.6462064416366
    - type: dot_f1
      value: 77.26315789473685
    - type: dot_precision
      value: 81.55555555555556
    - type: dot_recall
      value: 73.4
    - type: euclidean_accuracy
      value: 99.58316831683169
    - type: euclidean_ap
      value: 82.6462064416366
    - type: euclidean_f1
      value: 77.26315789473685
    - type: euclidean_precision
      value: 81.55555555555556
    - type: euclidean_recall
      value: 73.4
    - type: manhattan_accuracy
      value: 99.57821782178218
    - type: manhattan_ap
      value: 82.3670006669661
    - type: manhattan_f1
      value: 77.11999999999999
    - type: manhattan_precision
      value: 82.62857142857143
    - type: manhattan_recall
      value: 72.3
    - type: max_accuracy
      value: 99.58316831683169
    - type: max_ap
      value: 82.6462064416366
    - type: max_f1
      value: 77.26315789473685
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 42.59790960171173
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.956333203561826
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.9812498422993
    - type: mrr
      value: 42.344545772854595
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.695847196650142
    - type: cos_sim_spearman
      value: 30.534902785383718
    - type: dot_pearson
      value: 29.695847286724714
    - type: dot_spearman
      value: 30.592233541319345
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.058
    - type: map_at_10
      value: 3.489
    - type: map_at_100
      value: 6.140000000000001
    - type: map_at_1000
      value: 7.64
    - type: map_at_3
      value: 1.9869999999999999
    - type: map_at_5
      value: 2.7560000000000002
    - type: mrr_at_1
      value: 16.326999999999998
    - type: mrr_at_10
      value: 28.401
    - type: mrr_at_100
      value: 30.148000000000003
    - type: mrr_at_1000
      value: 30.176
    - type: mrr_at_3
      value: 24.83
    - type: mrr_at_5
      value: 27.177
    - type: ndcg_at_1
      value: 16.326999999999998
    - type: ndcg_at_10
      value: 11.527999999999999
    - type: ndcg_at_100
      value: 20.453
    - type: ndcg_at_1000
      value: 34.776
    - type: ndcg_at_3
      value: 12.548
    - type: ndcg_at_5
      value: 12.884
    - type: precision_at_1
      value: 16.326999999999998
    - type: precision_at_10
      value: 10.204
    - type: precision_at_100
      value: 4.939
    - type: precision_at_1000
      value: 1.384
    - type: precision_at_3
      value: 12.925
    - type: precision_at_5
      value: 13.469000000000001
    - type: recall_at_1
      value: 1.058
    - type: recall_at_10
      value: 7.285
    - type: recall_at_100
      value: 31.226
    - type: recall_at_1000
      value: 76.411
    - type: recall_at_3
      value: 2.8850000000000002
    - type: recall_at_5
      value: 5.012
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 72.5196
    - type: ap
      value: 14.311411048632412
    - type: f1
      value: 55.34603523807063
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.571590265987545
    - type: f1
      value: 55.663207973491524
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 34.94801375931444
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.99320498301246
    - type: cos_sim_ap
      value: 60.23275872716229
    - type: cos_sim_f1
      value: 57.59280089988752
    - type: cos_sim_precision
      value: 54.7138446924721
    - type: cos_sim_recall
      value: 60.79155672823219
    - type: dot_accuracy
      value: 81.99320498301246
    - type: dot_ap
      value: 60.23275872716229
    - type: dot_f1
      value: 57.59280089988752
    - type: dot_precision
      value: 54.7138446924721
    - type: dot_recall
      value: 60.79155672823219
    - type: euclidean_accuracy
      value: 81.99320498301246
    - type: euclidean_ap
      value: 60.23275872716229
    - type: euclidean_f1
      value: 57.59280089988752
    - type: euclidean_precision
      value: 54.7138446924721
    - type: euclidean_recall
      value: 60.79155672823219
    - type: manhattan_accuracy
      value: 82.16010013709246
    - type: manhattan_ap
      value: 60.48952698123763
    - type: manhattan_f1
      value: 57.775614504745676
    - type: manhattan_precision
      value: 53.61336946702801
    - type: manhattan_recall
      value: 62.638522427440634
    - type: max_accuracy
      value: 82.16010013709246
    - type: max_ap
      value: 60.48952698123763
    - type: max_f1
      value: 57.775614504745676
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 85.33007334963325
    - type: cos_sim_ap
      value: 77.62492992192084
    - type: cos_sim_f1
      value: 69.31098696461825
    - type: cos_sim_precision
      value: 67.12595585052662
    - type: cos_sim_recall
      value: 71.64305512781029
    - type: dot_accuracy
      value: 85.33007334963325
    - type: dot_ap
      value: 77.62492984681593
    - type: dot_f1
      value: 69.31098696461825
    - type: dot_precision
      value: 67.12595585052662
    - type: dot_recall
      value: 71.64305512781029
    - type: euclidean_accuracy
      value: 85.33007334963325
    - type: euclidean_ap
      value: 77.6249299283142
    - type: euclidean_f1
      value: 69.31098696461825
    - type: euclidean_precision
      value: 67.12595585052662
    - type: euclidean_recall
      value: 71.64305512781029
    - type: manhattan_accuracy
      value: 85.32037101719253
    - type: manhattan_ap
      value: 77.58409435269972
    - type: manhattan_f1
      value: 69.31577184953677
    - type: manhattan_precision
      value: 67.06746346029232
    - type: manhattan_recall
      value: 71.72004927625501
    - type: max_accuracy
      value: 85.33007334963325
    - type: max_ap
      value: 77.6249299283142
    - type: max_f1
      value: 69.31577184953677
---
