mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mpnet_main
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 68.11940298507461
    - type: ap
      value: 30.542146596139048
    - type: f1
      value: 61.92465989589396
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 62.503875
    - type: ap
      value: 58.0577571607728
    - type: f1
      value: 62.34928241469865
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.66999999999999
    - type: f1
      value: 31.2458385101798
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 23.329
    - type: map_at_10
      value: 37.384
    - type: map_at_100
      value: 38.57
    - type: map_at_1000
      value: 38.586999999999996
    - type: map_at_3
      value: 32.492
    - type: map_at_5
      value: 35.376000000000005
    - type: mrr_at_1
      value: 23.755000000000003
    - type: mrr_at_10
      value: 37.547000000000004
    - type: mrr_at_100
      value: 38.733000000000004
    - type: mrr_at_1000
      value: 38.749
    - type: mrr_at_3
      value: 32.658
    - type: mrr_at_5
      value: 35.567
    - type: ndcg_at_1
      value: 23.329
    - type: ndcg_at_10
      value: 45.574999999999996
    - type: ndcg_at_100
      value: 50.953
    - type: ndcg_at_1000
      value: 51.354
    - type: ndcg_at_3
      value: 35.608000000000004
    - type: ndcg_at_5
      value: 40.784
    - type: precision_at_1
      value: 23.329
    - type: precision_at_10
      value: 7.183000000000001
    - type: precision_at_100
      value: 0.962
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.889
    - type: precision_at_5
      value: 11.437
    - type: recall_at_1
      value: 23.329
    - type: recall_at_10
      value: 71.83500000000001
    - type: recall_at_100
      value: 96.15899999999999
    - type: recall_at_1000
      value: 99.21799999999999
    - type: recall_at_3
      value: 44.666
    - type: recall_at_5
      value: 57.18299999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 37.14558539727219
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 27.2291028039137
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.286820678107716
    - type: mrr
      value: 69.43762916062084
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.32170750010246
    - type: cos_sim_spearman
      value: 78.48130632209363
    - type: euclidean_pearson
      value: 80.42696573048755
    - type: euclidean_spearman
      value: 78.48130632209363
    - type: manhattan_pearson
      value: 80.68662655318546
    - type: manhattan_spearman
      value: 78.4475706136436
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.05194805194805
    - type: f1
      value: 72.31114319146532
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.842006272885655
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.238443830234058
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.647000000000002
    - type: map_at_10
      value: 29.842999999999996
    - type: map_at_100
      value: 31.131999999999998
    - type: map_at_1000
      value: 31.289
    - type: map_at_3
      value: 27.534999999999997
    - type: map_at_5
      value: 28.782999999999998
    - type: mrr_at_1
      value: 28.183000000000003
    - type: mrr_at_10
      value: 35.225
    - type: mrr_at_100
      value: 36.128
    - type: mrr_at_1000
      value: 36.198
    - type: mrr_at_3
      value: 33.19
    - type: mrr_at_5
      value: 34.363
    - type: ndcg_at_1
      value: 28.183000000000003
    - type: ndcg_at_10
      value: 34.644000000000005
    - type: ndcg_at_100
      value: 40.194
    - type: ndcg_at_1000
      value: 43.289
    - type: ndcg_at_3
      value: 31.259999999999998
    - type: ndcg_at_5
      value: 32.707
    - type: precision_at_1
      value: 28.183000000000003
    - type: precision_at_10
      value: 6.666999999999999
    - type: precision_at_100
      value: 1.187
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 14.974000000000002
    - type: precision_at_5
      value: 10.844
    - type: recall_at_1
      value: 22.647000000000002
    - type: recall_at_10
      value: 42.792
    - type: recall_at_100
      value: 67.399
    - type: recall_at_1000
      value: 88.646
    - type: recall_at_3
      value: 32.535
    - type: recall_at_5
      value: 36.748999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.895000000000001
    - type: map_at_10
      value: 21.631
    - type: map_at_100
      value: 22.56
    - type: map_at_1000
      value: 22.689
    - type: map_at_3
      value: 19.799
    - type: map_at_5
      value: 20.824
    - type: mrr_at_1
      value: 20.191
    - type: mrr_at_10
      value: 25.674999999999997
    - type: mrr_at_100
      value: 26.482
    - type: mrr_at_1000
      value: 26.558
    - type: mrr_at_3
      value: 23.854
    - type: mrr_at_5
      value: 24.85
    - type: ndcg_at_1
      value: 20.191
    - type: ndcg_at_10
      value: 25.428
    - type: ndcg_at_100
      value: 29.799999999999997
    - type: ndcg_at_1000
      value: 32.927
    - type: ndcg_at_3
      value: 22.284000000000002
    - type: ndcg_at_5
      value: 23.699
    - type: precision_at_1
      value: 20.191
    - type: precision_at_10
      value: 4.7829999999999995
    - type: precision_at_100
      value: 0.876
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 10.743
    - type: precision_at_5
      value: 7.720000000000001
    - type: recall_at_1
      value: 15.895000000000001
    - type: recall_at_10
      value: 32.789
    - type: recall_at_100
      value: 52.156000000000006
    - type: recall_at_1000
      value: 73.804
    - type: recall_at_3
      value: 23.589
    - type: recall_at_5
      value: 27.486
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.465
    - type: map_at_10
      value: 33.93
    - type: map_at_100
      value: 35.07
    - type: map_at_1000
      value: 35.165
    - type: map_at_3
      value: 31.091
    - type: map_at_5
      value: 32.722
    - type: mrr_at_1
      value: 29.654999999999998
    - type: mrr_at_10
      value: 37.156
    - type: mrr_at_100
      value: 38.074000000000005
    - type: mrr_at_1000
      value: 38.132
    - type: mrr_at_3
      value: 34.608
    - type: mrr_at_5
      value: 36.077999999999996
    - type: ndcg_at_1
      value: 29.654999999999998
    - type: ndcg_at_10
      value: 38.872
    - type: ndcg_at_100
      value: 44.293
    - type: ndcg_at_1000
      value: 46.455999999999996
    - type: ndcg_at_3
      value: 33.661
    - type: ndcg_at_5
      value: 36.237
    - type: precision_at_1
      value: 29.654999999999998
    - type: precision_at_10
      value: 6.464
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 14.943000000000001
    - type: precision_at_5
      value: 10.696
    - type: recall_at_1
      value: 25.465
    - type: recall_at_10
      value: 50.8
    - type: recall_at_100
      value: 75.373
    - type: recall_at_1000
      value: 91.053
    - type: recall_at_3
      value: 36.808
    - type: recall_at_5
      value: 43.069
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.853
    - type: map_at_10
      value: 18.047
    - type: map_at_100
      value: 18.9
    - type: map_at_1000
      value: 19.017999999999997
    - type: map_at_3
      value: 16.325
    - type: map_at_5
      value: 17.281
    - type: mrr_at_1
      value: 14.124
    - type: mrr_at_10
      value: 19.344
    - type: mrr_at_100
      value: 20.194000000000003
    - type: mrr_at_1000
      value: 20.298
    - type: mrr_at_3
      value: 17.589
    - type: mrr_at_5
      value: 18.601
    - type: ndcg_at_1
      value: 14.124
    - type: ndcg_at_10
      value: 21.188000000000002
    - type: ndcg_at_100
      value: 25.856
    - type: ndcg_at_1000
      value: 29.275000000000002
    - type: ndcg_at_3
      value: 17.726
    - type: ndcg_at_5
      value: 19.397000000000002
    - type: precision_at_1
      value: 14.124
    - type: precision_at_10
      value: 3.379
    - type: precision_at_100
      value: 0.61
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.608
    - type: precision_at_5
      value: 5.537
    - type: recall_at_1
      value: 12.853
    - type: recall_at_10
      value: 29.731999999999996
    - type: recall_at_100
      value: 51.99399999999999
    - type: recall_at_1000
      value: 78.581
    - type: recall_at_3
      value: 20.339
    - type: recall_at_5
      value: 24.304000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.736000000000001
    - type: map_at_10
      value: 10.587
    - type: map_at_100
      value: 11.515
    - type: map_at_1000
      value: 11.633000000000001
    - type: map_at_3
      value: 9.24
    - type: map_at_5
      value: 9.856
    - type: mrr_at_1
      value: 8.955
    - type: mrr_at_10
      value: 13.383999999999999
    - type: mrr_at_100
      value: 14.297
    - type: mrr_at_1000
      value: 14.391000000000002
    - type: mrr_at_3
      value: 11.92
    - type: mrr_at_5
      value: 12.584999999999999
    - type: ndcg_at_1
      value: 8.955
    - type: ndcg_at_10
      value: 13.498
    - type: ndcg_at_100
      value: 18.684
    - type: ndcg_at_1000
      value: 22.105
    - type: ndcg_at_3
      value: 10.881
    - type: ndcg_at_5
      value: 11.824
    - type: precision_at_1
      value: 8.955
    - type: precision_at_10
      value: 2.662
    - type: precision_at_100
      value: 0.633
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 5.473
    - type: precision_at_5
      value: 3.9800000000000004
    - type: recall_at_1
      value: 6.736000000000001
    - type: recall_at_10
      value: 19.945
    - type: recall_at_100
      value: 43.807
    - type: recall_at_1000
      value: 69.215
    - type: recall_at_3
      value: 12.458
    - type: recall_at_5
      value: 14.878
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 19.169
    - type: map_at_10
      value: 25.34
    - type: map_at_100
      value: 26.509
    - type: map_at_1000
      value: 26.663999999999998
    - type: map_at_3
      value: 22.964000000000002
    - type: map_at_5
      value: 24.229
    - type: mrr_at_1
      value: 23.483999999999998
    - type: mrr_at_10
      value: 29.872
    - type: mrr_at_100
      value: 30.775999999999996
    - type: mrr_at_1000
      value: 30.858
    - type: mrr_at_3
      value: 27.43
    - type: mrr_at_5
      value: 28.782000000000004
    - type: ndcg_at_1
      value: 23.483999999999998
    - type: ndcg_at_10
      value: 29.859
    - type: ndcg_at_100
      value: 35.498000000000005
    - type: ndcg_at_1000
      value: 38.875
    - type: ndcg_at_3
      value: 25.635
    - type: ndcg_at_5
      value: 27.522000000000002
    - type: precision_at_1
      value: 23.483999999999998
    - type: precision_at_10
      value: 5.573
    - type: precision_at_100
      value: 1.002
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 11.902
    - type: precision_at_5
      value: 8.72
    - type: recall_at_1
      value: 19.169
    - type: recall_at_10
      value: 38.991
    - type: recall_at_100
      value: 64.13600000000001
    - type: recall_at_1000
      value: 87.45
    - type: recall_at_3
      value: 27.053
    - type: recall_at_5
      value: 31.996999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.791999999999998
    - type: map_at_10
      value: 19.362
    - type: map_at_100
      value: 20.51
    - type: map_at_1000
      value: 20.663999999999998
    - type: map_at_3
      value: 17.408
    - type: map_at_5
      value: 18.373
    - type: mrr_at_1
      value: 17.122999999999998
    - type: mrr_at_10
      value: 22.939
    - type: mrr_at_100
      value: 23.913999999999998
    - type: mrr_at_1000
      value: 24.016000000000002
    - type: mrr_at_3
      value: 20.871000000000002
    - type: mrr_at_5
      value: 22.019
    - type: ndcg_at_1
      value: 17.122999999999998
    - type: ndcg_at_10
      value: 23.219
    - type: ndcg_at_100
      value: 28.610999999999997
    - type: ndcg_at_1000
      value: 32.361000000000004
    - type: ndcg_at_3
      value: 19.657
    - type: ndcg_at_5
      value: 21.153
    - type: precision_at_1
      value: 17.122999999999998
    - type: precision_at_10
      value: 4.3950000000000005
    - type: precision_at_100
      value: 0.852
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 9.399000000000001
    - type: precision_at_5
      value: 6.963
    - type: recall_at_1
      value: 13.791999999999998
    - type: recall_at_10
      value: 31.407
    - type: recall_at_100
      value: 54.69199999999999
    - type: recall_at_1000
      value: 81.281
    - type: recall_at_3
      value: 21.253
    - type: recall_at_5
      value: 25.22
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.433916666666665
    - type: map_at_10
      value: 19.892166666666668
    - type: map_at_100
      value: 20.87308333333333
    - type: map_at_1000
      value: 21.008416666666665
    - type: map_at_3
      value: 18.058666666666667
    - type: map_at_5
      value: 19.015583333333336
    - type: mrr_at_1
      value: 17.51
    - type: mrr_at_10
      value: 23.03275
    - type: mrr_at_100
      value: 23.89025
    - type: mrr_at_1000
      value: 23.980333333333334
    - type: mrr_at_3
      value: 21.20616666666667
    - type: mrr_at_5
      value: 22.195833333333333
    - type: ndcg_at_1
      value: 17.51
    - type: ndcg_at_10
      value: 23.55825
    - type: ndcg_at_100
      value: 28.414249999999996
    - type: ndcg_at_1000
      value: 31.749083333333328
    - type: ndcg_at_3
      value: 20.22475
    - type: ndcg_at_5
      value: 21.668916666666664
    - type: precision_at_1
      value: 17.51
    - type: precision_at_10
      value: 4.271333333333334
    - type: precision_at_100
      value: 0.8016666666666666
    - type: precision_at_1000
      value: 0.12825
    - type: precision_at_3
      value: 9.423833333333336
    - type: precision_at_5
      value: 6.818833333333334
    - type: recall_at_1
      value: 14.433916666666665
    - type: recall_at_10
      value: 31.521166666666662
    - type: recall_at_100
      value: 53.71125
    - type: recall_at_1000
      value: 77.92325000000001
    - type: recall_at_3
      value: 22.02575
    - type: recall_at_5
      value: 25.789916666666663
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.074
    - type: map_at_10
      value: 15.728
    - type: map_at_100
      value: 16.442999999999998
    - type: map_at_1000
      value: 16.536
    - type: map_at_3
      value: 14.082
    - type: map_at_5
      value: 14.808
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.687
    - type: mrr_at_100
      value: 18.436
    - type: mrr_at_1000
      value: 18.515
    - type: mrr_at_3
      value: 16.181
    - type: mrr_at_5
      value: 16.84
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.778
    - type: ndcg_at_100
      value: 22.817999999999998
    - type: ndcg_at_1000
      value: 25.657999999999998
    - type: ndcg_at_3
      value: 15.606
    - type: ndcg_at_5
      value: 16.727
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.2520000000000002
    - type: precision_at_100
      value: 0.5780000000000001
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 7.156999999999999
    - type: precision_at_5
      value: 5.061
    - type: recall_at_1
      value: 11.074
    - type: recall_at_10
      value: 26.479999999999997
    - type: recall_at_100
      value: 45.61
    - type: recall_at_1000
      value: 67.586
    - type: recall_at_3
      value: 17.377000000000002
    - type: recall_at_5
      value: 20.238
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.303999999999999
    - type: map_at_10
      value: 10.779
    - type: map_at_100
      value: 11.484
    - type: map_at_1000
      value: 11.616
    - type: map_at_3
      value: 9.62
    - type: map_at_5
      value: 10.263
    - type: mrr_at_1
      value: 9.394
    - type: mrr_at_10
      value: 13.22
    - type: mrr_at_100
      value: 13.924
    - type: mrr_at_1000
      value: 14.032
    - type: mrr_at_3
      value: 11.912
    - type: mrr_at_5
      value: 12.671
    - type: ndcg_at_1
      value: 9.394
    - type: ndcg_at_10
      value: 13.276
    - type: ndcg_at_100
      value: 17.118
    - type: ndcg_at_1000
      value: 20.878
    - type: ndcg_at_3
      value: 11.084
    - type: ndcg_at_5
      value: 12.113999999999999
    - type: precision_at_1
      value: 9.394
    - type: precision_at_10
      value: 2.533
    - type: precision_at_100
      value: 0.538
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 5.391
    - type: precision_at_5
      value: 4.0329999999999995
    - type: recall_at_1
      value: 7.303999999999999
    - type: recall_at_10
      value: 18.523999999999997
    - type: recall_at_100
      value: 36.452
    - type: recall_at_1000
      value: 64.38199999999999
    - type: recall_at_3
      value: 12.366000000000001
    - type: recall_at_5
      value: 14.994
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.963
    - type: map_at_10
      value: 17.46
    - type: map_at_100
      value: 18.297
    - type: map_at_1000
      value: 18.428
    - type: map_at_3
      value: 15.709999999999999
    - type: map_at_5
      value: 16.551
    - type: mrr_at_1
      value: 15.485
    - type: mrr_at_10
      value: 20.501
    - type: mrr_at_100
      value: 21.278
    - type: mrr_at_1000
      value: 21.379
    - type: mrr_at_3
      value: 18.548000000000002
    - type: mrr_at_5
      value: 19.537
    - type: ndcg_at_1
      value: 15.485
    - type: ndcg_at_10
      value: 20.994
    - type: ndcg_at_100
      value: 25.506
    - type: ndcg_at_1000
      value: 29.022
    - type: ndcg_at_3
      value: 17.410999999999998
    - type: ndcg_at_5
      value: 18.808
    - type: precision_at_1
      value: 15.485
    - type: precision_at_10
      value: 3.666
    - type: precision_at_100
      value: 0.662
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 7.898
    - type: precision_at_5
      value: 5.672
    - type: recall_at_1
      value: 12.963
    - type: recall_at_10
      value: 29.201
    - type: recall_at_100
      value: 50.109
    - type: recall_at_1000
      value: 75.797
    - type: recall_at_3
      value: 18.989
    - type: recall_at_5
      value: 22.601
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.260000000000002
    - type: map_at_10
      value: 21.165
    - type: map_at_100
      value: 22.400000000000002
    - type: map_at_1000
      value: 22.612
    - type: map_at_3
      value: 19.427
    - type: map_at_5
      value: 20.312
    - type: mrr_at_1
      value: 19.368
    - type: mrr_at_10
      value: 25.148
    - type: mrr_at_100
      value: 26.143
    - type: mrr_at_1000
      value: 26.235000000000003
    - type: mrr_at_3
      value: 23.584
    - type: mrr_at_5
      value: 24.433
    - type: ndcg_at_1
      value: 19.368
    - type: ndcg_at_10
      value: 25.239
    - type: ndcg_at_100
      value: 30.509999999999998
    - type: ndcg_at_1000
      value: 34.326
    - type: ndcg_at_3
      value: 22.57
    - type: ndcg_at_5
      value: 23.668
    - type: precision_at_1
      value: 19.368
    - type: precision_at_10
      value: 4.9799999999999995
    - type: precision_at_100
      value: 1.117
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 11.067
    - type: precision_at_5
      value: 7.904999999999999
    - type: recall_at_1
      value: 15.260000000000002
    - type: recall_at_10
      value: 32.368
    - type: recall_at_100
      value: 56.908
    - type: recall_at_1000
      value: 82.708
    - type: recall_at_3
      value: 23.816000000000003
    - type: recall_at_5
      value: 27.191
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.049
    - type: map_at_10
      value: 14.834
    - type: map_at_100
      value: 15.656999999999998
    - type: map_at_1000
      value: 15.787
    - type: map_at_3
      value: 13.503000000000002
    - type: map_at_5
      value: 14.185
    - type: mrr_at_1
      value: 11.275
    - type: mrr_at_10
      value: 16.242
    - type: mrr_at_100
      value: 17.037
    - type: mrr_at_1000
      value: 17.152
    - type: mrr_at_3
      value: 14.787
    - type: mrr_at_5
      value: 15.591
    - type: ndcg_at_1
      value: 11.275
    - type: ndcg_at_10
      value: 17.704
    - type: ndcg_at_100
      value: 22.083
    - type: ndcg_at_1000
      value: 25.817
    - type: ndcg_at_3
      value: 14.921999999999999
    - type: ndcg_at_5
      value: 16.171
    - type: precision_at_1
      value: 11.275
    - type: precision_at_10
      value: 2.902
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 6.531000000000001
    - type: precision_at_5
      value: 4.695
    - type: recall_at_1
      value: 10.049
    - type: recall_at_10
      value: 25.224999999999998
    - type: recall_at_100
      value: 45.899
    - type: recall_at_1000
      value: 74.576
    - type: recall_at_3
      value: 17.726
    - type: recall_at_5
      value: 20.752000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.762
    - type: map_at_10
      value: 12.867
    - type: map_at_100
      value: 14.478
    - type: map_at_1000
      value: 14.696000000000002
    - type: map_at_3
      value: 10.437000000000001
    - type: map_at_5
      value: 11.689
    - type: mrr_at_1
      value: 15.309000000000001
    - type: mrr_at_10
      value: 25.839000000000002
    - type: mrr_at_100
      value: 26.994
    - type: mrr_at_1000
      value: 27.056
    - type: mrr_at_3
      value: 22.400000000000002
    - type: mrr_at_5
      value: 24.451999999999998
    - type: ndcg_at_1
      value: 15.309000000000001
    - type: ndcg_at_10
      value: 19.384999999999998
    - type: ndcg_at_100
      value: 26.517000000000003
    - type: ndcg_at_1000
      value: 30.676
    - type: ndcg_at_3
      value: 14.876000000000001
    - type: ndcg_at_5
      value: 16.611
    - type: precision_at_1
      value: 15.309000000000001
    - type: precision_at_10
      value: 6.489000000000001
    - type: precision_at_100
      value: 1.409
    - type: precision_at_1000
      value: 0.217
    - type: precision_at_3
      value: 11.530999999999999
    - type: precision_at_5
      value: 9.381
    - type: recall_at_1
      value: 6.762
    - type: recall_at_10
      value: 24.996
    - type: recall_at_100
      value: 50.202999999999996
    - type: recall_at_1000
      value: 73.87899999999999
    - type: recall_at_3
      value: 14.149000000000001
    - type: recall_at_5
      value: 18.648
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.846
    - type: map_at_10
      value: 9.048
    - type: map_at_100
      value: 12.656
    - type: map_at_1000
      value: 13.605999999999998
    - type: map_at_3
      value: 6.293
    - type: map_at_5
      value: 7.5920000000000005
    - type: mrr_at_1
      value: 41.5
    - type: mrr_at_10
      value: 51.08200000000001
    - type: mrr_at_100
      value: 51.82299999999999
    - type: mrr_at_1000
      value: 51.856
    - type: mrr_at_3
      value: 48.5
    - type: mrr_at_5
      value: 49.836999999999996
    - type: ndcg_at_1
      value: 30.375000000000004
    - type: ndcg_at_10
      value: 23.343
    - type: ndcg_at_100
      value: 26.261000000000003
    - type: ndcg_at_1000
      value: 33.053
    - type: ndcg_at_3
      value: 25.814999999999998
    - type: ndcg_at_5
      value: 24.583
    - type: precision_at_1
      value: 41.5
    - type: precision_at_10
      value: 20.849999999999998
    - type: precision_at_100
      value: 6.635000000000001
    - type: precision_at_1000
      value: 1.438
    - type: precision_at_3
      value: 30.833
    - type: precision_at_5
      value: 26.85
    - type: recall_at_1
      value: 3.846
    - type: recall_at_10
      value: 13.83
    - type: recall_at_100
      value: 32.757999999999996
    - type: recall_at_1000
      value: 56.25
    - type: recall_at_3
      value: 7.574
    - type: recall_at_5
      value: 10.071
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.62
    - type: f1
      value: 42.79767018915584
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 15.677
    - type: map_at_10
      value: 23.551
    - type: map_at_100
      value: 24.442
    - type: map_at_1000
      value: 24.514
    - type: map_at_3
      value: 21.192
    - type: map_at_5
      value: 22.499
    - type: mrr_at_1
      value: 16.742
    - type: mrr_at_10
      value: 25.019000000000002
    - type: mrr_at_100
      value: 25.894000000000002
    - type: mrr_at_1000
      value: 25.958
    - type: mrr_at_3
      value: 22.555
    - type: mrr_at_5
      value: 23.909
    - type: ndcg_at_1
      value: 16.742
    - type: ndcg_at_10
      value: 28.247
    - type: ndcg_at_100
      value: 32.797
    - type: ndcg_at_1000
      value: 34.809
    - type: ndcg_at_3
      value: 23.358999999999998
    - type: ndcg_at_5
      value: 25.705
    - type: precision_at_1
      value: 16.742
    - type: precision_at_10
      value: 4.532
    - type: precision_at_100
      value: 0.701
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 10.145999999999999
    - type: precision_at_5
      value: 7.342
    - type: recall_at_1
      value: 15.677
    - type: recall_at_10
      value: 41.571000000000005
    - type: recall_at_100
      value: 62.834999999999994
    - type: recall_at_1000
      value: 78.387
    - type: recall_at_3
      value: 28.214
    - type: recall_at_5
      value: 33.891
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.5520000000000005
    - type: map_at_10
      value: 12.378
    - type: map_at_100
      value: 13.572999999999999
    - type: map_at_1000
      value: 13.79
    - type: map_at_3
      value: 10.737
    - type: map_at_5
      value: 11.629000000000001
    - type: mrr_at_1
      value: 15.123000000000001
    - type: mrr_at_10
      value: 21.001
    - type: mrr_at_100
      value: 22.112000000000002
    - type: mrr_at_1000
      value: 22.21
    - type: mrr_at_3
      value: 19.264
    - type: mrr_at_5
      value: 20.166999999999998
    - type: ndcg_at_1
      value: 15.123000000000001
    - type: ndcg_at_10
      value: 16.699
    - type: ndcg_at_100
      value: 22.688
    - type: ndcg_at_1000
      value: 27.394000000000002
    - type: ndcg_at_3
      value: 14.516000000000002
    - type: ndcg_at_5
      value: 15.336
    - type: precision_at_1
      value: 15.123000000000001
    - type: precision_at_10
      value: 4.7219999999999995
    - type: precision_at_100
      value: 1.065
    - type: precision_at_1000
      value: 0.188
    - type: precision_at_3
      value: 9.825000000000001
    - type: precision_at_5
      value: 7.284
    - type: recall_at_1
      value: 7.5520000000000005
    - type: recall_at_10
      value: 20.887
    - type: recall_at_100
      value: 44.613
    - type: recall_at_1000
      value: 73.55699999999999
    - type: recall_at_3
      value: 13.715
    - type: recall_at_5
      value: 16.75
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 15.314
    - type: map_at_10
      value: 21.73
    - type: map_at_100
      value: 22.595000000000002
    - type: map_at_1000
      value: 22.7
    - type: map_at_3
      value: 19.914
    - type: map_at_5
      value: 20.891000000000002
    - type: mrr_at_1
      value: 30.628
    - type: mrr_at_10
      value: 37.302
    - type: mrr_at_100
      value: 38.04
    - type: mrr_at_1000
      value: 38.102999999999994
    - type: mrr_at_3
      value: 35.445
    - type: mrr_at_5
      value: 36.464999999999996
    - type: ndcg_at_1
      value: 30.628
    - type: ndcg_at_10
      value: 27.986
    - type: ndcg_at_100
      value: 32.103
    - type: ndcg_at_1000
      value: 34.739
    - type: ndcg_at_3
      value: 24.48
    - type: ndcg_at_5
      value: 26.125
    - type: precision_at_1
      value: 30.628
    - type: precision_at_10
      value: 6.243
    - type: precision_at_100
      value: 0.955
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 15.517
    - type: precision_at_5
      value: 10.613999999999999
    - type: recall_at_1
      value: 15.314
    - type: recall_at_10
      value: 31.215
    - type: recall_at_100
      value: 47.752
    - type: recall_at_1000
      value: 65.422
    - type: recall_at_3
      value: 23.275000000000002
    - type: recall_at_5
      value: 26.535999999999998
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 61.661200000000015
    - type: ap
      value: 57.26137842361126
    - type: f1
      value: 61.44069729315865
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.308999999999999
    - type: map_at_10
      value: 11.003
    - type: map_at_100
      value: 11.865
    - type: map_at_1000
      value: 11.974
    - type: map_at_3
      value: 9.309000000000001
    - type: map_at_5
      value: 10.145999999999999
    - type: mrr_at_1
      value: 6.5329999999999995
    - type: mrr_at_10
      value: 11.296000000000001
    - type: mrr_at_100
      value: 12.168
    - type: mrr_at_1000
      value: 12.273
    - type: mrr_at_3
      value: 9.582
    - type: mrr_at_5
      value: 10.42
    - type: ndcg_at_1
      value: 6.519
    - type: ndcg_at_10
      value: 13.998
    - type: ndcg_at_100
      value: 18.701
    - type: ndcg_at_1000
      value: 21.944
    - type: ndcg_at_3
      value: 10.383000000000001
    - type: ndcg_at_5
      value: 11.898
    - type: precision_at_1
      value: 6.519
    - type: precision_at_10
      value: 2.4330000000000003
    - type: precision_at_100
      value: 0.486
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.585
    - type: precision_at_5
      value: 3.5130000000000003
    - type: recall_at_1
      value: 6.308999999999999
    - type: recall_at_10
      value: 23.381
    - type: recall_at_100
      value: 46.25
    - type: recall_at_1000
      value: 72.261
    - type: recall_at_3
      value: 13.239
    - type: recall_at_5
      value: 16.902
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.84313725490198
    - type: f1
      value: 87.24204022782286
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.409028727770185
    - type: f1
      value: 38.57449573016968
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.010759919300604
    - type: f1
      value: 60.290520300650584
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.65232010759918
    - type: f1
      value: 69.36104886302014
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.364401278066065
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 28.00495863318603
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.917670435424853
    - type: mrr
      value: 31.929615376181395
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.279
    - type: map_at_10
      value: 8.491999999999999
    - type: map_at_100
      value: 10.969
    - type: map_at_1000
      value: 12.396
    - type: map_at_3
      value: 6.254999999999999
    - type: map_at_5
      value: 7.417
    - type: mrr_at_1
      value: 34.056
    - type: mrr_at_10
      value: 43.877
    - type: mrr_at_100
      value: 44.590999999999994
    - type: mrr_at_1000
      value: 44.651
    - type: mrr_at_3
      value: 41.382999999999996
    - type: mrr_at_5
      value: 42.838
    - type: ndcg_at_1
      value: 32.198
    - type: ndcg_at_10
      value: 25.971
    - type: ndcg_at_100
      value: 25.112000000000002
    - type: ndcg_at_1000
      value: 34.83
    - type: ndcg_at_3
      value: 29.018
    - type: ndcg_at_5
      value: 28.447
    - type: precision_at_1
      value: 34.056
    - type: precision_at_10
      value: 19.412
    - type: precision_at_100
      value: 7.053
    - type: precision_at_1000
      value: 2.061
    - type: precision_at_3
      value: 27.761000000000003
    - type: precision_at_5
      value: 25.076999999999998
    - type: recall_at_1
      value: 4.279
    - type: recall_at_10
      value: 12.917000000000002
    - type: recall_at_100
      value: 27.386
    - type: recall_at_1000
      value: 62.90599999999999
    - type: recall_at_3
      value: 7.234999999999999
    - type: recall_at_5
      value: 9.866
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.427
    - type: map_at_10
      value: 14.471
    - type: map_at_100
      value: 15.704
    - type: map_at_1000
      value: 15.809000000000001
    - type: map_at_3
      value: 12.059000000000001
    - type: map_at_5
      value: 13.288
    - type: mrr_at_1
      value: 9.647
    - type: mrr_at_10
      value: 16.064999999999998
    - type: mrr_at_100
      value: 17.212
    - type: mrr_at_1000
      value: 17.297
    - type: mrr_at_3
      value: 13.562
    - type: mrr_at_5
      value: 14.843
    - type: ndcg_at_1
      value: 9.647
    - type: ndcg_at_10
      value: 18.613
    - type: ndcg_at_100
      value: 24.834999999999997
    - type: ndcg_at_1000
      value: 27.716
    - type: ndcg_at_3
      value: 13.605
    - type: ndcg_at_5
      value: 15.797
    - type: precision_at_1
      value: 9.647
    - type: precision_at_10
      value: 3.531
    - type: precision_at_100
      value: 0.7060000000000001
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.431000000000001
    - type: precision_at_5
      value: 5.093
    - type: recall_at_1
      value: 8.427
    - type: recall_at_10
      value: 29.995
    - type: recall_at_100
      value: 58.760999999999996
    - type: recall_at_1000
      value: 81.033
    - type: recall_at_3
      value: 16.621
    - type: recall_at_5
      value: 21.69
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.709
    - type: map_at_10
      value: 76.66
    - type: map_at_100
      value: 77.444
    - type: map_at_1000
      value: 77.474
    - type: map_at_3
      value: 73.639
    - type: map_at_5
      value: 75.495
    - type: mrr_at_1
      value: 73.42
    - type: mrr_at_10
      value: 80.643
    - type: mrr_at_100
      value: 80.886
    - type: mrr_at_1000
      value: 80.891
    - type: mrr_at_3
      value: 79.163
    - type: mrr_at_5
      value: 80.132
    - type: ndcg_at_1
      value: 73.44000000000001
    - type: ndcg_at_10
      value: 81.26100000000001
    - type: ndcg_at_100
      value: 83.34
    - type: ndcg_at_1000
      value: 83.65599999999999
    - type: ndcg_at_3
      value: 77.593
    - type: ndcg_at_5
      value: 79.552
    - type: precision_at_1
      value: 73.44000000000001
    - type: precision_at_10
      value: 12.356
    - type: precision_at_100
      value: 1.472
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.733000000000004
    - type: precision_at_5
      value: 22.398
    - type: recall_at_1
      value: 63.709
    - type: recall_at_10
      value: 90.24
    - type: recall_at_100
      value: 97.992
    - type: recall_at_1000
      value: 99.725
    - type: recall_at_3
      value: 79.843
    - type: recall_at_5
      value: 85.199
    - type: map_at_1
      value: 3.098
    - type: map_at_10
      value: 7.359999999999999
    - type: map_at_100
      value: 8.888
    - type: map_at_1000
      value: 9.158
    - type: map_at_3
      value: 5.406
    - type: map_at_5
      value: 6.308999999999999
    - type: mrr_at_1
      value: 15.2
    - type: mrr_at_10
      value: 23.508000000000003
    - type: mrr_at_100
      value: 24.709
    - type: mrr_at_1000
      value: 24.787
    - type: mrr_at_3
      value: 20.383000000000003
    - type: mrr_at_5
      value: 22.103
    - type: ndcg_at_1
      value: 15.2
    - type: ndcg_at_10
      value: 13.174
    - type: ndcg_at_100
      value: 19.885
    - type: ndcg_at_1000
      value: 25.247999999999998
    - type: ndcg_at_3
      value: 12.242
    - type: ndcg_at_5
      value: 10.702
    - type: precision_at_1
      value: 15.2
    - type: precision_at_10
      value: 6.93
    - type: precision_at_100
      value: 1.6709999999999998
    - type: precision_at_1000
      value: 0.296
    - type: precision_at_3
      value: 11.4
    - type: precision_at_5
      value: 9.379999999999999
    - type: recall_at_1
      value: 3.098
    - type: recall_at_10
      value: 14.048
    - type: recall_at_100
      value: 33.902
    - type: recall_at_1000
      value: 60.17
    - type: recall_at_3
      value: 6.9430000000000005
    - type: recall_at_5
      value: 9.498
    - type: map_at_1
      value: 0.125
    - type: map_at_10
      value: 0.86
    - type: map_at_100
      value: 4.665
    - type: map_at_1000
      value: 11.877
    - type: map_at_3
      value: 0.299
    - type: map_at_5
      value: 0.47200000000000003
    - type: mrr_at_1
      value: 50.0
    - type: mrr_at_10
      value: 64.711
    - type: mrr_at_100
      value: 65.065
    - type: mrr_at_1000
      value: 65.065
    - type: mrr_at_3
      value: 62.0
    - type: mrr_at_5
      value: 62.9
    - type: ndcg_at_1
      value: 43.0
    - type: ndcg_at_10
      value: 43.147999999999996
    - type: ndcg_at_100
      value: 33.417
    - type: ndcg_at_1000
      value: 31.341
    - type: ndcg_at_3
      value: 43.653999999999996
    - type: ndcg_at_5
      value: 43.21
    - type: precision_at_1
      value: 50.0
    - type: precision_at_10
      value: 48.199999999999996
    - type: precision_at_100
      value: 35.46
    - type: precision_at_1000
      value: 15.342
    - type: precision_at_3
      value: 48.0
    - type: precision_at_5
      value: 47.599999999999994
    - type: recall_at_1
      value: 0.125
    - type: recall_at_10
      value: 1.145
    - type: recall_at_100
      value: 7.727
    - type: recall_at_1000
      value: 30.742000000000004
    - type: recall_at_3
      value: 0.356
    - type: recall_at_5
      value: 0.5780000000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 42.214155529412366
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 48.10171269080449
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.69196724733715
    - type: cos_sim_spearman
      value: 65.00669029968084
    - type: euclidean_pearson
      value: 71.35623218354901
    - type: euclidean_spearman
      value: 65.00662504036774
    - type: manhattan_pearson
      value: 69.46286814034032
    - type: manhattan_spearman
      value: 64.05091703970768
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 75.45675254280496
    - type: cos_sim_spearman
      value: 67.48465522195806
    - type: euclidean_pearson
      value: 71.932572180082
    - type: euclidean_spearman
      value: 67.48597260989263
    - type: manhattan_pearson
      value: 70.01381315407934
    - type: manhattan_spearman
      value: 66.83129276722313
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.56784955823615
    - type: cos_sim_spearman
      value: 77.1656947836492
    - type: euclidean_pearson
      value: 76.86159714478943
    - type: euclidean_spearman
      value: 77.16570697849755
    - type: manhattan_pearson
      value: 77.05983226779968
    - type: manhattan_spearman
      value: 77.43229771628044
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.28801641888653
    - type: cos_sim_spearman
      value: 72.72947194978411
    - type: euclidean_pearson
      value: 76.2115552769551
    - type: euclidean_spearman
      value: 72.72946226092458
    - type: manhattan_pearson
      value: 75.19019262864614
    - type: manhattan_spearman
      value: 72.18378967267259
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.73471725204746
    - type: cos_sim_spearman
      value: 80.79015625826382
    - type: euclidean_pearson
      value: 80.81110611872813
    - type: euclidean_spearman
      value: 80.79016252191039
    - type: manhattan_pearson
      value: 79.93979968573043
    - type: manhattan_spearman
      value: 80.07556394648903
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.47923638473124
    - type: cos_sim_spearman
      value: 75.71286196807024
    - type: euclidean_pearson
      value: 75.83804880943377
    - type: euclidean_spearman
      value: 75.71341236422742
    - type: manhattan_pearson
      value: 75.93646913049322
    - type: manhattan_spearman
      value: 75.85181752457555
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.62219071209913
    - type: cos_sim_spearman
      value: 83.44167690000958
    - type: euclidean_pearson
      value: 83.28214784087085
    - type: euclidean_spearman
      value: 83.44255138870209
    - type: manhattan_pearson
      value: 82.77261607066816
    - type: manhattan_spearman
      value: 83.06899474864443
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 64.70345108985259
    - type: cos_sim_spearman
      value: 62.482753044620786
    - type: euclidean_pearson
      value: 64.79437494489187
    - type: euclidean_spearman
      value: 62.482753044620786
    - type: manhattan_pearson
      value: 63.71939825347573
    - type: manhattan_spearman
      value: 61.174953862000336
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.07865440954043
    - type: cos_sim_spearman
      value: 74.54667758834077
    - type: euclidean_pearson
      value: 76.48558570428264
    - type: euclidean_spearman
      value: 74.54672598094477
    - type: manhattan_pearson
      value: 76.06256712227383
    - type: manhattan_spearman
      value: 74.42758128821515
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 75.15143418949978
    - type: mrr
      value: 91.98409705762647
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.417
    - type: map_at_10
      value: 42.594
    - type: map_at_100
      value: 43.535000000000004
    - type: map_at_1000
      value: 43.6
    - type: map_at_3
      value: 39.759
    - type: map_at_5
      value: 41.506
    - type: mrr_at_1
      value: 35.667
    - type: mrr_at_10
      value: 44.446000000000005
    - type: mrr_at_100
      value: 45.244
    - type: mrr_at_1000
      value: 45.300000000000004
    - type: mrr_at_3
      value: 42.167
    - type: mrr_at_5
      value: 43.5
    - type: ndcg_at_1
      value: 35.667
    - type: ndcg_at_10
      value: 47.591
    - type: ndcg_at_100
      value: 52.611
    - type: ndcg_at_1000
      value: 54.31
    - type: ndcg_at_3
      value: 42.356
    - type: ndcg_at_5
      value: 45.194
    - type: precision_at_1
      value: 35.667
    - type: precision_at_10
      value: 6.7669999999999995
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 16.889000000000003
    - type: precision_at_5
      value: 11.799999999999999
    - type: recall_at_1
      value: 33.417
    - type: recall_at_10
      value: 61.260999999999996
    - type: recall_at_100
      value: 85.556
    - type: recall_at_1000
      value: 98.867
    - type: recall_at_3
      value: 47.528
    - type: recall_at_5
      value: 54.388999999999996
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.73267326732673
    - type: cos_sim_ap
      value: 92.36951341438333
    - type: cos_sim_f1
      value: 86.04073522106309
    - type: cos_sim_precision
      value: 85.48864758144127
    - type: cos_sim_recall
      value: 86.6
    - type: dot_accuracy
      value: 99.73267326732673
    - type: dot_ap
      value: 92.36951341438333
    - type: dot_f1
      value: 86.04073522106309
    - type: dot_precision
      value: 85.48864758144127
    - type: dot_recall
      value: 86.6
    - type: euclidean_accuracy
      value: 99.73267326732673
    - type: euclidean_ap
      value: 92.36951341438333
    - type: euclidean_f1
      value: 86.04073522106309
    - type: euclidean_precision
      value: 85.48864758144127
    - type: euclidean_recall
      value: 86.6
    - type: manhattan_accuracy
      value: 99.74455445544554
    - type: manhattan_ap
      value: 92.96894184904977
    - type: manhattan_f1
      value: 86.8917576961271
    - type: manhattan_precision
      value: 86.29191321499013
    - type: manhattan_recall
      value: 87.5
    - type: max_accuracy
      value: 99.74455445544554
    - type: max_ap
      value: 92.96894184904977
    - type: max_f1
      value: 86.8917576961271
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 45.349940718460374
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 31.266631844140036
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.02550203348626
    - type: mrr
      value: 42.442651302945414
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.22842420698354
    - type: cos_sim_spearman
      value: 30.568909812744543
    - type: dot_pearson
      value: 30.228424144316747
    - type: dot_spearman
      value: 30.619692862283827
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.585
    - type: map_at_10
      value: 7.398000000000001
    - type: map_at_100
      value: 13.603000000000002
    - type: map_at_1000
      value: 15.267
    - type: map_at_3
      value: 3.857
    - type: map_at_5
      value: 5.509
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 39.883
    - type: mrr_at_100
      value: 41.082
    - type: mrr_at_1000
      value: 41.082
    - type: mrr_at_3
      value: 35.034
    - type: mrr_at_5
      value: 37.483
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 21.221999999999998
    - type: ndcg_at_100
      value: 34.851
    - type: ndcg_at_1000
      value: 46.26
    - type: ndcg_at_3
      value: 21.906
    - type: ndcg_at_5
      value: 21.229
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 19.796
    - type: precision_at_100
      value: 8.122
    - type: precision_at_1000
      value: 1.541
    - type: precision_at_3
      value: 23.810000000000002
    - type: precision_at_5
      value: 22.041
    - type: recall_at_1
      value: 1.585
    - type: recall_at_10
      value: 13.664000000000001
    - type: recall_at_100
      value: 49.559
    - type: recall_at_1000
      value: 83.978
    - type: recall_at_3
      value: 5.088
    - type: recall_at_5
      value: 8.203000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.68520000000001
    - type: ap
      value: 14.622321024533974
    - type: f1
      value: 55.1924859473184
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.34748160724392
    - type: f1
      value: 53.518629300332755
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 40.22582442073446
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.46408773916671
    - type: cos_sim_ap
      value: 60.57612839124909
    - type: cos_sim_f1
      value: 58.366606170598914
    - type: cos_sim_precision
      value: 53.899441340782126
    - type: cos_sim_recall
      value: 63.641160949868066
    - type: dot_accuracy
      value: 82.46408773916671
    - type: dot_ap
      value: 60.57612839124909
    - type: dot_f1
      value: 58.366606170598914
    - type: dot_precision
      value: 53.899441340782126
    - type: dot_recall
      value: 63.641160949868066
    - type: euclidean_accuracy
      value: 82.46408773916671
    - type: euclidean_ap
      value: 60.57612839124909
    - type: euclidean_f1
      value: 58.366606170598914
    - type: euclidean_precision
      value: 53.899441340782126
    - type: euclidean_recall
      value: 63.641160949868066
    - type: manhattan_accuracy
      value: 81.68921738093819
    - type: manhattan_ap
      value: 58.62502289564927
    - type: manhattan_f1
      value: 57.40318906605921
    - type: manhattan_precision
      value: 50.50100200400801
    - type: manhattan_recall
      value: 66.49076517150397
    - type: max_accuracy
      value: 82.46408773916671
    - type: max_ap
      value: 60.57612839124909
    - type: max_f1
      value: 58.366606170598914
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.89602980556526
    - type: cos_sim_ap
      value: 81.92992391915341
    - type: cos_sim_f1
      value: 74.31139877741819
    - type: cos_sim_precision
      value: 69.71393873971124
    - type: cos_sim_recall
      value: 79.55805358792732
    - type: dot_accuracy
      value: 86.89602980556526
    - type: dot_ap
      value: 81.92992407440505
    - type: dot_f1
      value: 74.31139877741819
    - type: dot_precision
      value: 69.71393873971124
    - type: dot_recall
      value: 79.55805358792732
    - type: euclidean_accuracy
      value: 86.89602980556526
    - type: euclidean_ap
      value: 81.92992329073074
    - type: euclidean_f1
      value: 74.31139877741819
    - type: euclidean_precision
      value: 69.71393873971124
    - type: euclidean_recall
      value: 79.55805358792732
    - type: manhattan_accuracy
      value: 86.94454146776886
    - type: manhattan_ap
      value: 81.96535237136042
    - type: manhattan_f1
      value: 74.41181834761991
    - type: manhattan_precision
      value: 70.70076939072572
    - type: manhattan_recall
      value: 78.53403141361257
    - type: max_accuracy
      value: 86.94454146776886
    - type: max_ap
      value: 81.96535237136042
    - type: max_f1
      value: 74.41181834761991
---
