mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mpnet_main_nobivec
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 68.14925373134328
    - type: ap
      value: 30.344492603232688
    - type: f1
      value: 61.86365588668259
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 62.152125000000005
    - type: ap
      value: 57.843425428341554
    - type: f1
      value: 62.00827686700807
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.278
    - type: f1
      value: 30.933717306850117
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 23.186
    - type: map_at_10
      value: 37.467
    - type: map_at_100
      value: 38.544
    - type: map_at_1000
      value: 38.566
    - type: map_at_3
      value: 32.717
    - type: map_at_5
      value: 35.242000000000004
    - type: mrr_at_1
      value: 23.684
    - type: mrr_at_10
      value: 37.658
    - type: mrr_at_100
      value: 38.735
    - type: mrr_at_1000
      value: 38.756
    - type: mrr_at_3
      value: 32.93
    - type: mrr_at_5
      value: 35.445
    - type: ndcg_at_1
      value: 23.186
    - type: ndcg_at_10
      value: 45.857
    - type: ndcg_at_100
      value: 50.845
    - type: ndcg_at_1000
      value: 51.334999999999994
    - type: ndcg_at_3
      value: 35.992000000000004
    - type: ndcg_at_5
      value: 40.537
    - type: precision_at_1
      value: 23.186
    - type: precision_at_10
      value: 7.283
    - type: precision_at_100
      value: 0.9560000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 15.173
    - type: precision_at_5
      value: 11.309
    - type: recall_at_1
      value: 23.186
    - type: recall_at_10
      value: 72.831
    - type: recall_at_100
      value: 95.59
    - type: recall_at_1000
      value: 99.289
    - type: recall_at_3
      value: 45.519
    - type: recall_at_5
      value: 56.543
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 36.49112092394214
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 26.956300550326922
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.21453957338802
    - type: mrr
      value: 69.1818361693708
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.00547088743242
    - type: cos_sim_spearman
      value: 79.13493567331314
    - type: euclidean_pearson
      value: 79.63047595528823
    - type: euclidean_spearman
      value: 79.13493567331314
    - type: manhattan_pearson
      value: 79.46578839548812
    - type: manhattan_spearman
      value: 78.86926696926908
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.79220779220779
    - type: f1
      value: 72.00183161777994
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.91469425290078
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.33265342571266
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.383000000000003
    - type: map_at_10
      value: 26.997
    - type: map_at_100
      value: 28.29
    - type: map_at_1000
      value: 28.444000000000003
    - type: map_at_3
      value: 24.765
    - type: map_at_5
      value: 26.072
    - type: mrr_at_1
      value: 25.894000000000002
    - type: mrr_at_10
      value: 32.336
    - type: mrr_at_100
      value: 33.291
    - type: mrr_at_1000
      value: 33.36
    - type: mrr_at_3
      value: 30.353
    - type: mrr_at_5
      value: 31.526
    - type: ndcg_at_1
      value: 25.894000000000002
    - type: ndcg_at_10
      value: 31.497999999999998
    - type: ndcg_at_100
      value: 37.271
    - type: ndcg_at_1000
      value: 40.433
    - type: ndcg_at_3
      value: 28.21
    - type: ndcg_at_5
      value: 29.754
    - type: precision_at_1
      value: 25.894000000000002
    - type: precision_at_10
      value: 6.18
    - type: precision_at_100
      value: 1.139
    - type: precision_at_1000
      value: 0.17600000000000002
    - type: precision_at_3
      value: 13.447999999999999
    - type: precision_at_5
      value: 9.871
    - type: recall_at_1
      value: 20.383000000000003
    - type: recall_at_10
      value: 38.888
    - type: recall_at_100
      value: 64.85300000000001
    - type: recall_at_1000
      value: 86.81400000000001
    - type: recall_at_3
      value: 29.254
    - type: recall_at_5
      value: 33.742
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.414
    - type: map_at_10
      value: 21.178
    - type: map_at_100
      value: 22.112000000000002
    - type: map_at_1000
      value: 22.245
    - type: map_at_3
      value: 19.313
    - type: map_at_5
      value: 20.252
    - type: mrr_at_1
      value: 19.49
    - type: mrr_at_10
      value: 25.066
    - type: mrr_at_100
      value: 25.885
    - type: mrr_at_1000
      value: 25.96
    - type: mrr_at_3
      value: 23.132
    - type: mrr_at_5
      value: 24.09
    - type: ndcg_at_1
      value: 19.49
    - type: ndcg_at_10
      value: 25.009999999999998
    - type: ndcg_at_100
      value: 29.376
    - type: ndcg_at_1000
      value: 32.53
    - type: ndcg_at_3
      value: 21.707
    - type: ndcg_at_5
      value: 22.98
    - type: precision_at_1
      value: 19.49
    - type: precision_at_10
      value: 4.777
    - type: precision_at_100
      value: 0.8659999999999999
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 10.446
    - type: precision_at_5
      value: 7.452
    - type: recall_at_1
      value: 15.414
    - type: recall_at_10
      value: 32.584
    - type: recall_at_100
      value: 51.912000000000006
    - type: recall_at_1000
      value: 73.636
    - type: recall_at_3
      value: 22.966
    - type: recall_at_5
      value: 26.484
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.104
    - type: map_at_10
      value: 33.625
    - type: map_at_100
      value: 34.815000000000005
    - type: map_at_1000
      value: 34.910999999999994
    - type: map_at_3
      value: 30.894
    - type: map_at_5
      value: 32.507000000000005
    - type: mrr_at_1
      value: 29.279
    - type: mrr_at_10
      value: 36.942
    - type: mrr_at_100
      value: 37.88
    - type: mrr_at_1000
      value: 37.941
    - type: mrr_at_3
      value: 34.556
    - type: mrr_at_5
      value: 35.916
    - type: ndcg_at_1
      value: 29.279
    - type: ndcg_at_10
      value: 38.485
    - type: ndcg_at_100
      value: 43.974999999999994
    - type: ndcg_at_1000
      value: 46.165
    - type: ndcg_at_3
      value: 33.537
    - type: ndcg_at_5
      value: 36.025
    - type: precision_at_1
      value: 29.279
    - type: precision_at_10
      value: 6.351
    - type: precision_at_100
      value: 1.001
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 14.963000000000001
    - type: precision_at_5
      value: 10.646
    - type: recall_at_1
      value: 25.104
    - type: recall_at_10
      value: 50.047
    - type: recall_at_100
      value: 74.678
    - type: recall_at_1000
      value: 90.471
    - type: recall_at_3
      value: 36.671
    - type: recall_at_5
      value: 42.797000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.626999999999999
    - type: map_at_10
      value: 17.686
    - type: map_at_100
      value: 18.568
    - type: map_at_1000
      value: 18.68
    - type: map_at_3
      value: 16.051000000000002
    - type: map_at_5
      value: 16.969
    - type: mrr_at_1
      value: 13.898
    - type: mrr_at_10
      value: 18.987000000000002
    - type: mrr_at_100
      value: 19.853
    - type: mrr_at_1000
      value: 19.955000000000002
    - type: mrr_at_3
      value: 17.307
    - type: mrr_at_5
      value: 18.262
    - type: ndcg_at_1
      value: 13.898
    - type: ndcg_at_10
      value: 20.799
    - type: ndcg_at_100
      value: 25.598
    - type: ndcg_at_1000
      value: 28.945
    - type: ndcg_at_3
      value: 17.482
    - type: ndcg_at_5
      value: 19.073
    - type: precision_at_1
      value: 13.898
    - type: precision_at_10
      value: 3.3329999999999997
    - type: precision_at_100
      value: 0.61
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.571
    - type: precision_at_5
      value: 5.492
    - type: recall_at_1
      value: 12.626999999999999
    - type: recall_at_10
      value: 29.261
    - type: recall_at_100
      value: 52.297000000000004
    - type: recall_at_1000
      value: 78.34
    - type: recall_at_3
      value: 20.188
    - type: recall_at_5
      value: 23.971999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.918
    - type: map_at_10
      value: 10.688
    - type: map_at_100
      value: 11.62
    - type: map_at_1000
      value: 11.733
    - type: map_at_3
      value: 9.203
    - type: map_at_5
      value: 10.084999999999999
    - type: mrr_at_1
      value: 9.08
    - type: mrr_at_10
      value: 13.447000000000001
    - type: mrr_at_100
      value: 14.377999999999998
    - type: mrr_at_1000
      value: 14.468
    - type: mrr_at_3
      value: 11.899
    - type: mrr_at_5
      value: 12.788
    - type: ndcg_at_1
      value: 9.08
    - type: ndcg_at_10
      value: 13.608999999999998
    - type: ndcg_at_100
      value: 18.845
    - type: ndcg_at_1000
      value: 22.252
    - type: ndcg_at_3
      value: 10.771
    - type: ndcg_at_5
      value: 12.225
    - type: precision_at_1
      value: 9.08
    - type: precision_at_10
      value: 2.6870000000000003
    - type: precision_at_100
      value: 0.641
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 5.390000000000001
    - type: precision_at_5
      value: 4.204
    - type: recall_at_1
      value: 6.918
    - type: recall_at_10
      value: 20.076
    - type: recall_at_100
      value: 44.185
    - type: recall_at_1000
      value: 69.705
    - type: recall_at_3
      value: 12.147
    - type: recall_at_5
      value: 15.903
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.603
    - type: map_at_10
      value: 24.552
    - type: map_at_100
      value: 25.771
    - type: map_at_1000
      value: 25.917
    - type: map_at_3
      value: 22.286
    - type: map_at_5
      value: 23.398
    - type: mrr_at_1
      value: 22.522000000000002
    - type: mrr_at_10
      value: 28.986
    - type: mrr_at_100
      value: 29.94
    - type: mrr_at_1000
      value: 30.016
    - type: mrr_at_3
      value: 26.612000000000002
    - type: mrr_at_5
      value: 27.907
    - type: ndcg_at_1
      value: 22.522000000000002
    - type: ndcg_at_10
      value: 28.937
    - type: ndcg_at_100
      value: 34.821000000000005
    - type: ndcg_at_1000
      value: 38.086
    - type: ndcg_at_3
      value: 24.879
    - type: ndcg_at_5
      value: 26.576
    - type: precision_at_1
      value: 22.522000000000002
    - type: precision_at_10
      value: 5.371
    - type: precision_at_100
      value: 0.9979999999999999
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 11.517
    - type: precision_at_5
      value: 8.277
    - type: recall_at_1
      value: 18.603
    - type: recall_at_10
      value: 37.669999999999995
    - type: recall_at_100
      value: 63.918
    - type: recall_at_1000
      value: 86.482
    - type: recall_at_3
      value: 26.308
    - type: recall_at_5
      value: 30.830000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.38
    - type: map_at_10
      value: 18.875
    - type: map_at_100
      value: 20.008
    - type: map_at_1000
      value: 20.158
    - type: map_at_3
      value: 16.959
    - type: map_at_5
      value: 17.858999999999998
    - type: mrr_at_1
      value: 16.667
    - type: mrr_at_10
      value: 22.409000000000002
    - type: mrr_at_100
      value: 23.391000000000002
    - type: mrr_at_1000
      value: 23.488
    - type: mrr_at_3
      value: 20.491
    - type: mrr_at_5
      value: 21.478
    - type: ndcg_at_1
      value: 16.667
    - type: ndcg_at_10
      value: 22.721
    - type: ndcg_at_100
      value: 28.17
    - type: ndcg_at_1000
      value: 31.886
    - type: ndcg_at_3
      value: 19.261
    - type: ndcg_at_5
      value: 20.575
    - type: precision_at_1
      value: 16.667
    - type: precision_at_10
      value: 4.349
    - type: precision_at_100
      value: 0.839
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 9.399000000000001
    - type: precision_at_5
      value: 6.781
    - type: recall_at_1
      value: 13.38
    - type: recall_at_10
      value: 30.903999999999996
    - type: recall_at_100
      value: 54.75299999999999
    - type: recall_at_1000
      value: 81.188
    - type: recall_at_3
      value: 21.007
    - type: recall_at_5
      value: 24.568
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.091916666666668
    - type: map_at_10
      value: 19.413999999999998
    - type: map_at_100
      value: 20.39841666666667
    - type: map_at_1000
      value: 20.53091666666667
    - type: map_at_3
      value: 17.59308333333333
    - type: map_at_5
      value: 18.568
    - type: mrr_at_1
      value: 17.024666666666665
    - type: mrr_at_10
      value: 22.45566666666667
    - type: mrr_at_100
      value: 23.328166666666668
    - type: mrr_at_1000
      value: 23.417166666666667
    - type: mrr_at_3
      value: 20.65191666666667
    - type: mrr_at_5
      value: 21.653499999999998
    - type: ndcg_at_1
      value: 17.024666666666665
    - type: ndcg_at_10
      value: 23.004916666666666
    - type: ndcg_at_100
      value: 27.916083333333336
    - type: ndcg_at_1000
      value: 31.23883333333334
    - type: ndcg_at_3
      value: 19.685750000000002
    - type: ndcg_at_5
      value: 21.177416666666666
    - type: precision_at_1
      value: 17.024666666666665
    - type: precision_at_10
      value: 4.170999999999999
    - type: precision_at_100
      value: 0.7939999999999999
    - type: precision_at_1000
      value: 0.12708333333333333
    - type: precision_at_3
      value: 9.142083333333332
    - type: precision_at_5
      value: 6.64275
    - type: recall_at_1
      value: 14.091916666666668
    - type: recall_at_10
      value: 30.80275
    - type: recall_at_100
      value: 53.32091666666666
    - type: recall_at_1000
      value: 77.51058333333333
    - type: recall_at_3
      value: 21.45283333333333
    - type: recall_at_5
      value: 25.315333333333335
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.844
    - type: map_at_10
      value: 15.121
    - type: map_at_100
      value: 15.837000000000002
    - type: map_at_1000
      value: 15.928
    - type: map_at_3
      value: 13.629
    - type: map_at_5
      value: 14.462
    - type: mrr_at_1
      value: 12.577
    - type: mrr_at_10
      value: 16.93
    - type: mrr_at_100
      value: 17.701
    - type: mrr_at_1000
      value: 17.782999999999998
    - type: mrr_at_3
      value: 15.440000000000001
    - type: mrr_at_5
      value: 16.314
    - type: ndcg_at_1
      value: 12.577
    - type: ndcg_at_10
      value: 17.947
    - type: ndcg_at_100
      value: 22.055
    - type: ndcg_at_1000
      value: 24.854000000000003
    - type: ndcg_at_3
      value: 15.003
    - type: ndcg_at_5
      value: 16.433
    - type: precision_at_1
      value: 12.577
    - type: precision_at_10
      value: 3.0669999999999997
    - type: precision_at_100
      value: 0.557
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.748
    - type: precision_at_5
      value: 4.968999999999999
    - type: recall_at_1
      value: 10.844
    - type: recall_at_10
      value: 25.014999999999997
    - type: recall_at_100
      value: 44.542
    - type: recall_at_1000
      value: 65.969
    - type: recall_at_3
      value: 16.766000000000002
    - type: recall_at_5
      value: 20.348
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.180000000000001
    - type: map_at_10
      value: 10.648
    - type: map_at_100
      value: 11.34
    - type: map_at_1000
      value: 11.472
    - type: map_at_3
      value: 9.506
    - type: map_at_5
      value: 10.064
    - type: mrr_at_1
      value: 9.222
    - type: mrr_at_10
      value: 13.023000000000001
    - type: mrr_at_100
      value: 13.733
    - type: mrr_at_1000
      value: 13.841999999999999
    - type: mrr_at_3
      value: 11.774
    - type: mrr_at_5
      value: 12.404
    - type: ndcg_at_1
      value: 9.222
    - type: ndcg_at_10
      value: 13.111999999999998
    - type: ndcg_at_100
      value: 16.936999999999998
    - type: ndcg_at_1000
      value: 20.712
    - type: ndcg_at_3
      value: 10.953
    - type: ndcg_at_5
      value: 11.809
    - type: precision_at_1
      value: 9.222
    - type: precision_at_10
      value: 2.5090000000000003
    - type: precision_at_100
      value: 0.536
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 5.357
    - type: precision_at_5
      value: 3.909
    - type: recall_at_1
      value: 7.180000000000001
    - type: recall_at_10
      value: 18.318
    - type: recall_at_100
      value: 36.187000000000005
    - type: recall_at_1000
      value: 64.29
    - type: recall_at_3
      value: 12.191
    - type: recall_at_5
      value: 14.421999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.847
    - type: map_at_10
      value: 17.381
    - type: map_at_100
      value: 18.246000000000002
    - type: map_at_1000
      value: 18.372
    - type: map_at_3
      value: 15.934000000000001
    - type: map_at_5
      value: 16.525000000000002
    - type: mrr_at_1
      value: 15.299
    - type: mrr_at_10
      value: 20.291999999999998
    - type: mrr_at_100
      value: 21.14
    - type: mrr_at_1000
      value: 21.238
    - type: mrr_at_3
      value: 18.688
    - type: mrr_at_5
      value: 19.369
    - type: ndcg_at_1
      value: 15.299
    - type: ndcg_at_10
      value: 20.684
    - type: ndcg_at_100
      value: 25.362000000000002
    - type: ndcg_at_1000
      value: 28.897000000000002
    - type: ndcg_at_3
      value: 17.708
    - type: ndcg_at_5
      value: 18.654
    - type: precision_at_1
      value: 15.299
    - type: precision_at_10
      value: 3.535
    - type: precision_at_100
      value: 0.66
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 8.053
    - type: precision_at_5
      value: 5.485
    - type: recall_at_1
      value: 12.847
    - type: recall_at_10
      value: 28.218
    - type: recall_at_100
      value: 49.816
    - type: recall_at_1000
      value: 75.868
    - type: recall_at_3
      value: 19.636
    - type: recall_at_5
      value: 22.224
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.645
    - type: map_at_10
      value: 20.493
    - type: map_at_100
      value: 21.743000000000002
    - type: map_at_1000
      value: 21.951
    - type: map_at_3
      value: 18.584
    - type: map_at_5
      value: 19.628
    - type: mrr_at_1
      value: 17.984
    - type: mrr_at_10
      value: 23.879
    - type: mrr_at_100
      value: 24.87
    - type: mrr_at_1000
      value: 24.965
    - type: mrr_at_3
      value: 22.167
    - type: mrr_at_5
      value: 23.294
    - type: ndcg_at_1
      value: 17.984
    - type: ndcg_at_10
      value: 24.567
    - type: ndcg_at_100
      value: 29.818
    - type: ndcg_at_1000
      value: 33.667
    - type: ndcg_at_3
      value: 21.453
    - type: ndcg_at_5
      value: 23.018
    - type: precision_at_1
      value: 17.984
    - type: precision_at_10
      value: 4.862
    - type: precision_at_100
      value: 1.1280000000000001
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 10.343
    - type: precision_at_5
      value: 7.747
    - type: recall_at_1
      value: 14.645
    - type: recall_at_10
      value: 32.102000000000004
    - type: recall_at_100
      value: 56.472
    - type: recall_at_1000
      value: 82.901
    - type: recall_at_3
      value: 22.814
    - type: recall_at_5
      value: 26.904
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.158
    - type: map_at_10
      value: 15.723999999999998
    - type: map_at_100
      value: 16.431
    - type: map_at_1000
      value: 16.56
    - type: map_at_3
      value: 13.993
    - type: map_at_5
      value: 14.995
    - type: mrr_at_1
      value: 12.384
    - type: mrr_at_10
      value: 17.171
    - type: mrr_at_100
      value: 17.876
    - type: mrr_at_1000
      value: 17.990000000000002
    - type: mrr_at_3
      value: 15.404000000000002
    - type: mrr_at_5
      value: 16.494
    - type: ndcg_at_1
      value: 12.384
    - type: ndcg_at_10
      value: 18.69
    - type: ndcg_at_100
      value: 22.765
    - type: ndcg_at_1000
      value: 26.439
    - type: ndcg_at_3
      value: 15.265
    - type: ndcg_at_5
      value: 17.007
    - type: precision_at_1
      value: 12.384
    - type: precision_at_10
      value: 3.031
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.47
    - type: precision_at_5
      value: 4.88
    - type: recall_at_1
      value: 11.158
    - type: recall_at_10
      value: 26.55
    - type: recall_at_100
      value: 46.238
    - type: recall_at_1000
      value: 74.46300000000001
    - type: recall_at_3
      value: 17.485999999999997
    - type: recall_at_5
      value: 21.59
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.375
    - type: map_at_10
      value: 11.718
    - type: map_at_100
      value: 13.245999999999999
    - type: map_at_1000
      value: 13.459
    - type: map_at_3
      value: 9.607000000000001
    - type: map_at_5
      value: 10.639999999999999
    - type: mrr_at_1
      value: 14.788
    - type: mrr_at_10
      value: 24.168
    - type: mrr_at_100
      value: 25.419999999999998
    - type: mrr_at_1000
      value: 25.480999999999998
    - type: mrr_at_3
      value: 20.955
    - type: mrr_at_5
      value: 22.802
    - type: ndcg_at_1
      value: 14.788
    - type: ndcg_at_10
      value: 17.721
    - type: ndcg_at_100
      value: 24.833
    - type: ndcg_at_1000
      value: 29.01
    - type: ndcg_at_3
      value: 13.714
    - type: ndcg_at_5
      value: 15.160000000000002
    - type: precision_at_1
      value: 14.788
    - type: precision_at_10
      value: 5.876
    - type: precision_at_100
      value: 1.341
    - type: precision_at_1000
      value: 0.211
    - type: precision_at_3
      value: 10.467
    - type: precision_at_5
      value: 8.391
    - type: recall_at_1
      value: 6.375
    - type: recall_at_10
      value: 22.598
    - type: recall_at_100
      value: 47.835
    - type: recall_at_1000
      value: 71.758
    - type: recall_at_3
      value: 13.033
    - type: recall_at_5
      value: 16.858
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.1579999999999995
    - type: map_at_10
      value: 9.283
    - type: map_at_100
      value: 13.092
    - type: map_at_1000
      value: 14.033999999999999
    - type: map_at_3
      value: 6.463000000000001
    - type: map_at_5
      value: 7.701
    - type: mrr_at_1
      value: 41.25
    - type: mrr_at_10
      value: 50.105999999999995
    - type: mrr_at_100
      value: 50.879
    - type: mrr_at_1000
      value: 50.912
    - type: mrr_at_3
      value: 47.292
    - type: mrr_at_5
      value: 48.766999999999996
    - type: ndcg_at_1
      value: 29.625
    - type: ndcg_at_10
      value: 23.26
    - type: ndcg_at_100
      value: 26.556
    - type: ndcg_at_1000
      value: 33.271
    - type: ndcg_at_3
      value: 25.665
    - type: ndcg_at_5
      value: 24.404
    - type: precision_at_1
      value: 41.25
    - type: precision_at_10
      value: 21.075
    - type: precision_at_100
      value: 6.748
    - type: precision_at_1000
      value: 1.444
    - type: precision_at_3
      value: 30.75
    - type: precision_at_5
      value: 26.700000000000003
    - type: recall_at_1
      value: 4.1579999999999995
    - type: recall_at_10
      value: 13.834
    - type: recall_at_100
      value: 33.318999999999996
    - type: recall_at_1000
      value: 56.806999999999995
    - type: recall_at_3
      value: 7.417999999999999
    - type: recall_at_5
      value: 9.872
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.825
    - type: f1
      value: 43.13728772840347
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.036000000000001
    - type: map_at_10
      value: 21.296
    - type: map_at_100
      value: 22.165000000000003
    - type: map_at_1000
      value: 22.24
    - type: map_at_3
      value: 19.186
    - type: map_at_5
      value: 20.366999999999997
    - type: mrr_at_1
      value: 14.865999999999998
    - type: mrr_at_10
      value: 22.503
    - type: mrr_at_100
      value: 23.376
    - type: mrr_at_1000
      value: 23.444000000000003
    - type: mrr_at_3
      value: 20.262
    - type: mrr_at_5
      value: 21.525
    - type: ndcg_at_1
      value: 14.865999999999998
    - type: ndcg_at_10
      value: 25.568
    - type: ndcg_at_100
      value: 30.131999999999998
    - type: ndcg_at_1000
      value: 32.242
    - type: ndcg_at_3
      value: 21.178
    - type: ndcg_at_5
      value: 23.317
    - type: precision_at_1
      value: 14.865999999999998
    - type: precision_at_10
      value: 4.098
    - type: precision_at_100
      value: 0.661
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 9.211
    - type: precision_at_5
      value: 6.666999999999999
    - type: recall_at_1
      value: 14.036000000000001
    - type: recall_at_10
      value: 37.775999999999996
    - type: recall_at_100
      value: 59.243
    - type: recall_at_1000
      value: 75.583
    - type: recall_at_3
      value: 25.857000000000003
    - type: recall_at_5
      value: 30.982
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.859999999999999
    - type: map_at_10
      value: 11.631
    - type: map_at_100
      value: 12.795000000000002
    - type: map_at_1000
      value: 12.992999999999999
    - type: map_at_3
      value: 10.08
    - type: map_at_5
      value: 10.772
    - type: mrr_at_1
      value: 13.58
    - type: mrr_at_10
      value: 19.564999999999998
    - type: mrr_at_100
      value: 20.669999999999998
    - type: mrr_at_1000
      value: 20.761
    - type: mrr_at_3
      value: 17.824
    - type: mrr_at_5
      value: 18.619
    - type: ndcg_at_1
      value: 13.58
    - type: ndcg_at_10
      value: 15.78
    - type: ndcg_at_100
      value: 21.707
    - type: ndcg_at_1000
      value: 26.226
    - type: ndcg_at_3
      value: 13.719000000000001
    - type: ndcg_at_5
      value: 14.183000000000002
    - type: precision_at_1
      value: 13.58
    - type: precision_at_10
      value: 4.552
    - type: precision_at_100
      value: 1.028
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 9.311
    - type: precision_at_5
      value: 6.79
    - type: recall_at_1
      value: 6.859999999999999
    - type: recall_at_10
      value: 20.054
    - type: recall_at_100
      value: 43.822
    - type: recall_at_1000
      value: 71.665
    - type: recall_at_3
      value: 13.008000000000001
    - type: recall_at_5
      value: 15.381
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 14.045
    - type: map_at_10
      value: 20.054
    - type: map_at_100
      value: 20.89
    - type: map_at_1000
      value: 20.999000000000002
    - type: map_at_3
      value: 18.297
    - type: map_at_5
      value: 19.231
    - type: mrr_at_1
      value: 28.089
    - type: mrr_at_10
      value: 34.583999999999996
    - type: mrr_at_100
      value: 35.337
    - type: mrr_at_1000
      value: 35.400999999999996
    - type: mrr_at_3
      value: 32.66
    - type: mrr_at_5
      value: 33.743
    - type: ndcg_at_1
      value: 28.089
    - type: ndcg_at_10
      value: 25.999
    - type: ndcg_at_100
      value: 30.023
    - type: ndcg_at_1000
      value: 32.742
    - type: ndcg_at_3
      value: 22.519
    - type: ndcg_at_5
      value: 24.15
    - type: precision_at_1
      value: 28.089
    - type: precision_at_10
      value: 5.858
    - type: precision_at_100
      value: 0.909
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 14.265
    - type: precision_at_5
      value: 9.85
    - type: recall_at_1
      value: 14.045
    - type: recall_at_10
      value: 29.291
    - type: recall_at_100
      value: 45.436
    - type: recall_at_1000
      value: 63.666
    - type: recall_at_3
      value: 21.398
    - type: recall_at_5
      value: 24.625
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 61.8104
    - type: ap
      value: 57.38352158221927
    - type: f1
      value: 61.535478192568135
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.821
    - type: map_at_10
      value: 10.403
    - type: map_at_100
      value: 11.271
    - type: map_at_1000
      value: 11.375
    - type: map_at_3
      value: 8.764
    - type: map_at_5
      value: 9.588000000000001
    - type: mrr_at_1
      value: 6.0600000000000005
    - type: mrr_at_10
      value: 10.709
    - type: mrr_at_100
      value: 11.583
    - type: mrr_at_1000
      value: 11.684
    - type: mrr_at_3
      value: 9.046999999999999
    - type: mrr_at_5
      value: 9.894
    - type: ndcg_at_1
      value: 6.032
    - type: ndcg_at_10
      value: 13.264999999999999
    - type: ndcg_at_100
      value: 18.016
    - type: ndcg_at_1000
      value: 21.226
    - type: ndcg_at_3
      value: 9.82
    - type: ndcg_at_5
      value: 11.309
    - type: precision_at_1
      value: 6.032
    - type: precision_at_10
      value: 2.305
    - type: precision_at_100
      value: 0.477
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.365
    - type: precision_at_5
      value: 3.367
    - type: recall_at_1
      value: 5.821
    - type: recall_at_10
      value: 22.165000000000003
    - type: recall_at_100
      value: 45.357
    - type: recall_at_1000
      value: 71.28
    - type: recall_at_3
      value: 12.631
    - type: recall_at_5
      value: 16.211000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.38349293205654
    - type: f1
      value: 87.54736120600828
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 55.23483812129503
    - type: f1
      value: 37.290140441414046
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.139878950907864
    - type: f1
      value: 59.50881927994892
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.01008742434432
    - type: f1
      value: 68.42281820836324
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.15718904178607
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.70725540281151
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.927012755857614
    - type: mrr
      value: 31.985831468302077
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.168
    - type: map_at_10
      value: 8.12
    - type: map_at_100
      value: 10.453999999999999
    - type: map_at_1000
      value: 11.937000000000001
    - type: map_at_3
      value: 6.069
    - type: map_at_5
      value: 7.138999999999999
    - type: mrr_at_1
      value: 34.056
    - type: mrr_at_10
      value: 43.980000000000004
    - type: mrr_at_100
      value: 44.638
    - type: mrr_at_1000
      value: 44.699
    - type: mrr_at_3
      value: 41.538000000000004
    - type: mrr_at_5
      value: 43.208999999999996
    - type: ndcg_at_1
      value: 32.507999999999996
    - type: ndcg_at_10
      value: 25.377
    - type: ndcg_at_100
      value: 24.298000000000002
    - type: ndcg_at_1000
      value: 34.327000000000005
    - type: ndcg_at_3
      value: 28.883
    - type: ndcg_at_5
      value: 27.49
    - type: precision_at_1
      value: 34.056
    - type: precision_at_10
      value: 18.978
    - type: precision_at_100
      value: 6.842
    - type: precision_at_1000
      value: 2.073
    - type: precision_at_3
      value: 27.348
    - type: precision_at_5
      value: 23.839
    - type: recall_at_1
      value: 4.168
    - type: recall_at_10
      value: 12.405
    - type: recall_at_100
      value: 26.067
    - type: recall_at_1000
      value: 62.019000000000005
    - type: recall_at_3
      value: 7.381
    - type: recall_at_5
      value: 9.678
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.621
    - type: map_at_10
      value: 13.205
    - type: map_at_100
      value: 14.377999999999998
    - type: map_at_1000
      value: 14.488000000000001
    - type: map_at_3
      value: 10.835
    - type: map_at_5
      value: 12.056000000000001
    - type: mrr_at_1
      value: 8.72
    - type: mrr_at_10
      value: 14.746
    - type: mrr_at_100
      value: 15.814
    - type: mrr_at_1000
      value: 15.903
    - type: mrr_at_3
      value: 12.205
    - type: mrr_at_5
      value: 13.526
    - type: ndcg_at_1
      value: 8.72
    - type: ndcg_at_10
      value: 17.230999999999998
    - type: ndcg_at_100
      value: 23.157
    - type: ndcg_at_1000
      value: 26.11
    - type: ndcg_at_3
      value: 12.215
    - type: ndcg_at_5
      value: 14.448
    - type: precision_at_1
      value: 8.72
    - type: precision_at_10
      value: 3.3489999999999998
    - type: precision_at_100
      value: 0.6689999999999999
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 5.765
    - type: precision_at_5
      value: 4.71
    - type: recall_at_1
      value: 7.621
    - type: recall_at_10
      value: 28.346
    - type: recall_at_100
      value: 55.905
    - type: recall_at_1000
      value: 78.568
    - type: recall_at_3
      value: 14.888000000000002
    - type: recall_at_5
      value: 20.119
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 64.12400000000001
    - type: map_at_10
      value: 77.009
    - type: map_at_100
      value: 77.77
    - type: map_at_1000
      value: 77.803
    - type: map_at_3
      value: 74.05000000000001
    - type: map_at_5
      value: 75.846
    - type: mrr_at_1
      value: 73.78
    - type: mrr_at_10
      value: 80.87100000000001
    - type: mrr_at_100
      value: 81.109
    - type: mrr_at_1000
      value: 81.114
    - type: mrr_at_3
      value: 79.415
    - type: mrr_at_5
      value: 80.345
    - type: ndcg_at_1
      value: 73.81
    - type: ndcg_at_10
      value: 81.50699999999999
    - type: ndcg_at_100
      value: 83.518
    - type: ndcg_at_1000
      value: 83.868
    - type: ndcg_at_3
      value: 77.96600000000001
    - type: ndcg_at_5
      value: 79.794
    - type: precision_at_1
      value: 73.81
    - type: precision_at_10
      value: 12.367
    - type: precision_at_100
      value: 1.469
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.94
    - type: precision_at_5
      value: 22.438
    - type: recall_at_1
      value: 64.12400000000001
    - type: recall_at_10
      value: 90.283
    - type: recall_at_100
      value: 97.76
    - type: recall_at_1000
      value: 99.714
    - type: recall_at_3
      value: 80.15299999999999
    - type: recall_at_5
      value: 85.208
    - type: map_at_1
      value: 3.2030000000000003
    - type: map_at_10
      value: 7.474
    - type: map_at_100
      value: 8.898
    - type: map_at_1000
      value: 9.168
    - type: map_at_3
      value: 5.45
    - type: map_at_5
      value: 6.363
    - type: mrr_at_1
      value: 15.7
    - type: mrr_at_10
      value: 23.682
    - type: mrr_at_100
      value: 24.855
    - type: mrr_at_1000
      value: 24.939
    - type: mrr_at_3
      value: 20.782999999999998
    - type: mrr_at_5
      value: 22.208
    - type: ndcg_at_1
      value: 15.7
    - type: ndcg_at_10
      value: 13.235
    - type: ndcg_at_100
      value: 19.679
    - type: ndcg_at_1000
      value: 25.088
    - type: ndcg_at_3
      value: 12.394
    - type: ndcg_at_5
      value: 10.717
    - type: precision_at_1
      value: 15.7
    - type: precision_at_10
      value: 6.909999999999999
    - type: precision_at_100
      value: 1.633
    - type: precision_at_1000
      value: 0.294
    - type: precision_at_3
      value: 11.466999999999999
    - type: precision_at_5
      value: 9.28
    - type: recall_at_1
      value: 3.2030000000000003
    - type: recall_at_10
      value: 14.002999999999998
    - type: recall_at_100
      value: 33.12
    - type: recall_at_1000
      value: 59.675
    - type: recall_at_3
      value: 6.978
    - type: recall_at_5
      value: 9.388
    - type: map_at_1
      value: 0.109
    - type: map_at_10
      value: 0.893
    - type: map_at_100
      value: 5.261
    - type: map_at_1000
      value: 13.122
    - type: map_at_3
      value: 0.317
    - type: map_at_5
      value: 0.488
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 62.352
    - type: mrr_at_100
      value: 62.941
    - type: mrr_at_1000
      value: 62.941
    - type: mrr_at_3
      value: 60.0
    - type: mrr_at_5
      value: 61.4
    - type: ndcg_at_1
      value: 38.0
    - type: ndcg_at_10
      value: 42.480000000000004
    - type: ndcg_at_100
      value: 34.835
    - type: ndcg_at_1000
      value: 32.592
    - type: ndcg_at_3
      value: 44.665
    - type: ndcg_at_5
      value: 43.911
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 46.800000000000004
    - type: precision_at_100
      value: 37.4
    - type: precision_at_1000
      value: 15.918
    - type: precision_at_3
      value: 51.333
    - type: precision_at_5
      value: 49.2
    - type: recall_at_1
      value: 0.109
    - type: recall_at_10
      value: 1.154
    - type: recall_at_100
      value: 8.389000000000001
    - type: recall_at_1000
      value: 32.096000000000004
    - type: recall_at_3
      value: 0.387
    - type: recall_at_5
      value: 0.612
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 44.162118605127525
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 46.70881745207942
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.64379518764505
    - type: cos_sim_spearman
      value: 65.03593875325868
    - type: euclidean_pearson
      value: 71.30716734159877
    - type: euclidean_spearman
      value: 65.0358725107667
    - type: manhattan_pearson
      value: 69.64008883410301
    - type: manhattan_spearman
      value: 64.1709357952613
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 76.10760678507381
    - type: cos_sim_spearman
      value: 68.35350054782432
    - type: euclidean_pearson
      value: 72.65776988973283
    - type: euclidean_spearman
      value: 68.35478315887251
    - type: manhattan_pearson
      value: 70.5706666450866
    - type: manhattan_spearman
      value: 67.13814826706063
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.32161265212544
    - type: cos_sim_spearman
      value: 76.93198204035276
    - type: euclidean_pearson
      value: 76.60126151642021
    - type: euclidean_spearman
      value: 76.93199423707081
    - type: manhattan_pearson
      value: 76.5056121876099
    - type: manhattan_spearman
      value: 76.86184669371214
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.10524062982039
    - type: cos_sim_spearman
      value: 72.59969217378233
    - type: euclidean_pearson
      value: 76.10064294747684
    - type: euclidean_spearman
      value: 72.59968248507782
    - type: manhattan_pearson
      value: 75.2538128834374
    - type: manhattan_spearman
      value: 72.14612849441266
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.92563014030377
    - type: cos_sim_spearman
      value: 80.98166673776733
    - type: euclidean_pearson
      value: 80.9596078291122
    - type: euclidean_spearman
      value: 80.9816574633563
    - type: manhattan_pearson
      value: 79.89230536933664
    - type: manhattan_spearman
      value: 80.00574493608646
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.19795257280954
    - type: cos_sim_spearman
      value: 75.43790136296928
    - type: euclidean_pearson
      value: 75.57117891505544
    - type: euclidean_spearman
      value: 75.43845178483879
    - type: manhattan_pearson
      value: 75.41513445680592
    - type: manhattan_spearman
      value: 75.38085076755232
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.61027585526848
    - type: cos_sim_spearman
      value: 83.72082588978941
    - type: euclidean_pearson
      value: 83.72701589311066
    - type: euclidean_spearman
      value: 83.7217002176894
    - type: manhattan_pearson
      value: 83.24293225606534
    - type: manhattan_spearman
      value: 83.4135678831862
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 64.42651773313223
    - type: cos_sim_spearman
      value: 61.7038845289896
    - type: euclidean_pearson
      value: 64.54756406367291
    - type: euclidean_spearman
      value: 61.7038845289896
    - type: manhattan_pearson
      value: 63.51018692682091
    - type: manhattan_spearman
      value: 60.45964817925399
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 75.55989105968095
    - type: cos_sim_spearman
      value: 73.7042941496097
    - type: euclidean_pearson
      value: 75.91151565422992
    - type: euclidean_spearman
      value: 73.70428269603238
    - type: manhattan_pearson
      value: 75.4126729336794
    - type: manhattan_spearman
      value: 73.5240782951808
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.49865014688187
    - type: mrr
      value: 91.71895823856607
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.306000000000004
    - type: map_at_10
      value: 41.848
    - type: map_at_100
      value: 42.909000000000006
    - type: map_at_1000
      value: 42.981
    - type: map_at_3
      value: 39.389
    - type: map_at_5
      value: 41.031
    - type: mrr_at_1
      value: 35.333
    - type: mrr_at_10
      value: 43.641000000000005
    - type: mrr_at_100
      value: 44.539
    - type: mrr_at_1000
      value: 44.603
    - type: mrr_at_3
      value: 41.611
    - type: mrr_at_5
      value: 42.943999999999996
    - type: ndcg_at_1
      value: 35.333
    - type: ndcg_at_10
      value: 46.452
    - type: ndcg_at_100
      value: 51.7
    - type: ndcg_at_1000
      value: 53.622
    - type: ndcg_at_3
      value: 41.833
    - type: ndcg_at_5
      value: 44.553
    - type: precision_at_1
      value: 35.333
    - type: precision_at_10
      value: 6.4670000000000005
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 16.667
    - type: precision_at_5
      value: 11.533
    - type: recall_at_1
      value: 33.306000000000004
    - type: recall_at_10
      value: 59.0
    - type: recall_at_100
      value: 83.556
    - type: recall_at_1000
      value: 98.6
    - type: recall_at_3
      value: 46.639
    - type: recall_at_5
      value: 53.306
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.69108910891089
    - type: cos_sim_ap
      value: 90.4977489865437
    - type: cos_sim_f1
      value: 83.7493632195619
    - type: cos_sim_precision
      value: 85.35825545171339
    - type: cos_sim_recall
      value: 82.19999999999999
    - type: dot_accuracy
      value: 99.69108910891089
    - type: dot_ap
      value: 90.4977489865437
    - type: dot_f1
      value: 83.7493632195619
    - type: dot_precision
      value: 85.35825545171339
    - type: dot_recall
      value: 82.19999999999999
    - type: euclidean_accuracy
      value: 99.69108910891089
    - type: euclidean_ap
      value: 90.4977489865437
    - type: euclidean_f1
      value: 83.7493632195619
    - type: euclidean_precision
      value: 85.35825545171339
    - type: euclidean_recall
      value: 82.19999999999999
    - type: manhattan_accuracy
      value: 99.70792079207921
    - type: manhattan_ap
      value: 91.16860160199867
    - type: manhattan_f1
      value: 84.73874806001035
    - type: manhattan_precision
      value: 87.78135048231512
    - type: manhattan_recall
      value: 81.89999999999999
    - type: max_accuracy
      value: 99.70792079207921
    - type: max_ap
      value: 91.16860160199867
    - type: max_f1
      value: 84.73874806001035
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 43.35434708006249
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 31.335469165398756
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.97374025833599
    - type: mrr
      value: 42.262077179356595
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.976845934718288
    - type: cos_sim_spearman
      value: 31.683535959644406
    - type: dot_pearson
      value: 30.97684544705739
    - type: dot_spearman
      value: 31.732556691703294
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.7489999999999999
    - type: map_at_10
      value: 7.498
    - type: map_at_100
      value: 13.675
    - type: map_at_1000
      value: 15.379999999999999
    - type: map_at_3
      value: 4.073
    - type: map_at_5
      value: 5.575
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 39.521
    - type: mrr_at_100
      value: 40.63
    - type: mrr_at_1000
      value: 40.63
    - type: mrr_at_3
      value: 35.034
    - type: mrr_at_5
      value: 36.870999999999995
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 20.269000000000002
    - type: ndcg_at_100
      value: 34.174
    - type: ndcg_at_1000
      value: 46.137
    - type: ndcg_at_3
      value: 22.977
    - type: ndcg_at_5
      value: 21.604
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 18.776
    - type: precision_at_100
      value: 7.939
    - type: precision_at_1000
      value: 1.555
    - type: precision_at_3
      value: 25.169999999999998
    - type: precision_at_5
      value: 22.857
    - type: recall_at_1
      value: 1.7489999999999999
    - type: recall_at_10
      value: 13.354
    - type: recall_at_100
      value: 48.303000000000004
    - type: recall_at_1000
      value: 84.65
    - type: recall_at_3
      value: 5.293
    - type: recall_at_5
      value: 7.994
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.8018
    - type: ap
      value: 14.536819438052662
    - type: f1
      value: 55.19152517845791
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.52574985851726
    - type: f1
      value: 53.69703116168891
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 38.1774041110333
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.9991655242296
    - type: cos_sim_ap
      value: 58.53652893055794
    - type: cos_sim_f1
      value: 56.55495317890586
    - type: cos_sim_precision
      value: 53.051317614424406
    - type: cos_sim_recall
      value: 60.554089709762536
    - type: dot_accuracy
      value: 81.9991655242296
    - type: dot_ap
      value: 58.53652893055794
    - type: dot_f1
      value: 56.55495317890586
    - type: dot_precision
      value: 53.051317614424406
    - type: dot_recall
      value: 60.554089709762536
    - type: euclidean_accuracy
      value: 81.9991655242296
    - type: euclidean_ap
      value: 58.53652809144572
    - type: euclidean_f1
      value: 56.55495317890586
    - type: euclidean_precision
      value: 53.051317614424406
    - type: euclidean_recall
      value: 60.554089709762536
    - type: manhattan_accuracy
      value: 81.55808547416106
    - type: manhattan_ap
      value: 56.9619587668482
    - type: manhattan_f1
      value: 55.47429078014184
    - type: manhattan_precision
      value: 47.82193351165457
    - type: manhattan_recall
      value: 66.04221635883904
    - type: max_accuracy
      value: 81.9991655242296
    - type: max_ap
      value: 58.53652893055794
    - type: max_f1
      value: 56.55495317890586
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.946481934257
    - type: cos_sim_ap
      value: 81.66664549248112
    - type: cos_sim_f1
      value: 74.09368335907051
    - type: cos_sim_precision
      value: 70.90781140042223
    - type: cos_sim_recall
      value: 77.57930397289806
    - type: dot_accuracy
      value: 86.946481934257
    - type: dot_ap
      value: 81.66664549326697
    - type: dot_f1
      value: 74.09368335907051
    - type: dot_precision
      value: 70.90781140042223
    - type: dot_recall
      value: 77.57930397289806
    - type: euclidean_accuracy
      value: 86.946481934257
    - type: euclidean_ap
      value: 81.66664561833119
    - type: euclidean_f1
      value: 74.09368335907051
    - type: euclidean_precision
      value: 70.90781140042223
    - type: euclidean_recall
      value: 77.57930397289806
    - type: manhattan_accuracy
      value: 86.89602980556526
    - type: manhattan_ap
      value: 81.68402162687751
    - type: manhattan_f1
      value: 73.93715341959334
    - type: manhattan_precision
      value: 71.11363959607453
    - type: manhattan_recall
      value: 76.9941484447182
    - type: max_accuracy
      value: 86.946481934257
    - type: max_ap
      value: 81.68402162687751
    - type: max_f1
      value: 74.09368335907051
---
