mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_100
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.35820895522387
    - type: ap
      value: 32.749463629599404
    - type: f1
      value: 64.24277142151362
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.705075
    - type: ap
      value: 59.80751870729784
    - type: f1
      value: 64.44356439771583
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.642
    - type: f1
      value: 33.115627459191316
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 17.852
    - type: map_at_10
      value: 29.279
    - type: map_at_100
      value: 30.55
    - type: map_at_1000
      value: 30.605
    - type: map_at_3
      value: 25.296000000000003
    - type: map_at_5
      value: 27.498
    - type: mrr_at_1
      value: 18.137
    - type: mrr_at_10
      value: 29.398999999999997
    - type: mrr_at_100
      value: 30.677
    - type: mrr_at_1000
      value: 30.731
    - type: mrr_at_3
      value: 25.427
    - type: mrr_at_5
      value: 27.614
    - type: ndcg_at_1
      value: 17.852
    - type: ndcg_at_10
      value: 36.071999999999996
    - type: ndcg_at_100
      value: 42.403
    - type: ndcg_at_1000
      value: 43.733
    - type: ndcg_at_3
      value: 27.799000000000003
    - type: ndcg_at_5
      value: 31.805
    - type: precision_at_1
      value: 17.852
    - type: precision_at_10
      value: 5.797
    - type: precision_at_100
      value: 0.878
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 11.688
    - type: precision_at_5
      value: 8.976
    - type: recall_at_1
      value: 17.852
    - type: recall_at_10
      value: 57.965999999999994
    - type: recall_at_100
      value: 87.83800000000001
    - type: recall_at_1000
      value: 98.08
    - type: recall_at_3
      value: 35.064
    - type: recall_at_5
      value: 44.879000000000005
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 29.25407935159316
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 19.74540490543985
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 50.92680362916445
    - type: mrr
      value: 63.515697137580794
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 72.8794628935656
    - type: cos_sim_spearman
      value: 72.28899655141599
    - type: euclidean_pearson
      value: 72.84840274301827
    - type: euclidean_spearman
      value: 72.28899655141599
    - type: manhattan_pearson
      value: 72.27814398382203
    - type: manhattan_spearman
      value: 71.66970533201172
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 66.20129870129871
    - type: f1
      value: 65.02435616242589
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 28.56746746078776
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 19.212994376812908
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 17.7
    - type: map_at_10
      value: 23.182
    - type: map_at_100
      value: 24.2
    - type: map_at_1000
      value: 24.354
    - type: map_at_3
      value: 21.448
    - type: map_at_5
      value: 22.394
    - type: mrr_at_1
      value: 21.459
    - type: mrr_at_10
      value: 27.538
    - type: mrr_at_100
      value: 28.399
    - type: mrr_at_1000
      value: 28.479
    - type: mrr_at_3
      value: 25.775
    - type: mrr_at_5
      value: 26.705000000000002
    - type: ndcg_at_1
      value: 21.459
    - type: ndcg_at_10
      value: 26.987
    - type: ndcg_at_100
      value: 31.935999999999996
    - type: ndcg_at_1000
      value: 35.335
    - type: ndcg_at_3
      value: 24.214
    - type: ndcg_at_5
      value: 25.344
    - type: precision_at_1
      value: 21.459
    - type: precision_at_10
      value: 5.007000000000001
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 11.445
    - type: precision_at_5
      value: 8.155
    - type: recall_at_1
      value: 17.7
    - type: recall_at_10
      value: 33.698
    - type: recall_at_100
      value: 55.933
    - type: recall_at_1000
      value: 79.567
    - type: recall_at_3
      value: 25.331
    - type: recall_at_5
      value: 28.681
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 13.008000000000001
    - type: map_at_10
      value: 17.331
    - type: map_at_100
      value: 18.128
    - type: map_at_1000
      value: 18.253
    - type: map_at_3
      value: 15.708
    - type: map_at_5
      value: 16.601
    - type: mrr_at_1
      value: 16.624
    - type: mrr_at_10
      value: 21.038999999999998
    - type: mrr_at_100
      value: 21.782
    - type: mrr_at_1000
      value: 21.869
    - type: mrr_at_3
      value: 19.320999999999998
    - type: mrr_at_5
      value: 20.266000000000002
    - type: ndcg_at_1
      value: 16.624
    - type: ndcg_at_10
      value: 20.584
    - type: ndcg_at_100
      value: 24.43
    - type: ndcg_at_1000
      value: 27.486
    - type: ndcg_at_3
      value: 17.724999999999998
    - type: ndcg_at_5
      value: 18.990000000000002
    - type: precision_at_1
      value: 16.624
    - type: precision_at_10
      value: 3.8850000000000002
    - type: precision_at_100
      value: 0.7250000000000001
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 8.514
    - type: precision_at_5
      value: 6.204
    - type: recall_at_1
      value: 13.008000000000001
    - type: recall_at_10
      value: 26.799
    - type: recall_at_100
      value: 43.802
    - type: recall_at_1000
      value: 65.035
    - type: recall_at_3
      value: 18.411
    - type: recall_at_5
      value: 21.887999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 18.459
    - type: map_at_10
      value: 24.775
    - type: map_at_100
      value: 25.691999999999997
    - type: map_at_1000
      value: 25.802999999999997
    - type: map_at_3
      value: 22.784
    - type: map_at_5
      value: 23.764
    - type: mrr_at_1
      value: 21.379
    - type: mrr_at_10
      value: 27.555000000000003
    - type: mrr_at_100
      value: 28.355000000000004
    - type: mrr_at_1000
      value: 28.438999999999997
    - type: mrr_at_3
      value: 25.663999999999998
    - type: mrr_at_5
      value: 26.598
    - type: ndcg_at_1
      value: 21.379
    - type: ndcg_at_10
      value: 28.691
    - type: ndcg_at_100
      value: 33.387
    - type: ndcg_at_1000
      value: 36.299
    - type: ndcg_at_3
      value: 24.883
    - type: ndcg_at_5
      value: 26.438
    - type: precision_at_1
      value: 21.379
    - type: precision_at_10
      value: 4.777
    - type: precision_at_100
      value: 0.7799999999999999
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 11.16
    - type: precision_at_5
      value: 7.7490000000000006
    - type: recall_at_1
      value: 18.459
    - type: recall_at_10
      value: 37.964999999999996
    - type: recall_at_100
      value: 59.728
    - type: recall_at_1000
      value: 81.351
    - type: recall_at_3
      value: 27.538
    - type: recall_at_5
      value: 31.464
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 8.324
    - type: map_at_10
      value: 10.779
    - type: map_at_100
      value: 11.371
    - type: map_at_1000
      value: 11.466999999999999
    - type: map_at_3
      value: 9.922
    - type: map_at_5
      value: 10.319
    - type: mrr_at_1
      value: 9.153
    - type: mrr_at_10
      value: 11.700000000000001
    - type: mrr_at_100
      value: 12.314
    - type: mrr_at_1000
      value: 12.406
    - type: mrr_at_3
      value: 10.81
    - type: mrr_at_5
      value: 11.234
    - type: ndcg_at_1
      value: 9.153
    - type: ndcg_at_10
      value: 12.472
    - type: ndcg_at_100
      value: 15.942
    - type: ndcg_at_1000
      value: 19.118
    - type: ndcg_at_3
      value: 10.644
    - type: ndcg_at_5
      value: 11.355
    - type: precision_at_1
      value: 9.153
    - type: precision_at_10
      value: 1.921
    - type: precision_at_100
      value: 0.391
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 4.444
    - type: precision_at_5
      value: 3.073
    - type: recall_at_1
      value: 8.324
    - type: recall_at_10
      value: 16.971
    - type: recall_at_100
      value: 34.041
    - type: recall_at_1000
      value: 59.45399999999999
    - type: recall_at_3
      value: 11.77
    - type: recall_at_5
      value: 13.522
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 3.998
    - type: map_at_10
      value: 6.22
    - type: map_at_100
      value: 6.687
    - type: map_at_1000
      value: 6.796
    - type: map_at_3
      value: 5.124
    - type: map_at_5
      value: 5.705
    - type: mrr_at_1
      value: 5.224
    - type: mrr_at_10
      value: 7.915
    - type: mrr_at_100
      value: 8.433
    - type: mrr_at_1000
      value: 8.530999999999999
    - type: mrr_at_3
      value: 6.654
    - type: mrr_at_5
      value: 7.276000000000001
    - type: ndcg_at_1
      value: 5.224
    - type: ndcg_at_10
      value: 8.238
    - type: ndcg_at_100
      value: 11.126999999999999
    - type: ndcg_at_1000
      value: 14.552999999999999
    - type: ndcg_at_3
      value: 6.0249999999999995
    - type: ndcg_at_5
      value: 6.981999999999999
    - type: precision_at_1
      value: 5.224
    - type: precision_at_10
      value: 1.7160000000000002
    - type: precision_at_100
      value: 0.371
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 2.9850000000000003
    - type: precision_at_5
      value: 2.413
    - type: recall_at_1
      value: 3.998
    - type: recall_at_10
      value: 12.995999999999999
    - type: recall_at_100
      value: 26.819
    - type: recall_at_1000
      value: 52.608
    - type: recall_at_3
      value: 6.721000000000001
    - type: recall_at_5
      value: 9.198
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 12.331
    - type: map_at_10
      value: 16.913
    - type: map_at_100
      value: 17.841
    - type: map_at_1000
      value: 17.977
    - type: map_at_3
      value: 15.633
    - type: map_at_5
      value: 16.256
    - type: mrr_at_1
      value: 15.110999999999999
    - type: mrr_at_10
      value: 20.419999999999998
    - type: mrr_at_100
      value: 21.294
    - type: mrr_at_1000
      value: 21.386
    - type: mrr_at_3
      value: 18.961
    - type: mrr_at_5
      value: 19.682
    - type: ndcg_at_1
      value: 15.110999999999999
    - type: ndcg_at_10
      value: 20.115
    - type: ndcg_at_100
      value: 24.914
    - type: ndcg_at_1000
      value: 28.375
    - type: ndcg_at_3
      value: 17.732
    - type: ndcg_at_5
      value: 18.658
    - type: precision_at_1
      value: 15.110999999999999
    - type: precision_at_10
      value: 3.696
    - type: precision_at_100
      value: 0.762
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 8.566
    - type: precision_at_5
      value: 5.9670000000000005
    - type: recall_at_1
      value: 12.331
    - type: recall_at_10
      value: 26.429000000000002
    - type: recall_at_100
      value: 47.341
    - type: recall_at_1000
      value: 72.149
    - type: recall_at_3
      value: 19.467000000000002
    - type: recall_at_5
      value: 21.981
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 8.262
    - type: map_at_10
      value: 11.962
    - type: map_at_100
      value: 12.729
    - type: map_at_1000
      value: 12.86
    - type: map_at_3
      value: 10.65
    - type: map_at_5
      value: 11.388
    - type: mrr_at_1
      value: 10.502
    - type: mrr_at_10
      value: 14.715
    - type: mrr_at_100
      value: 15.484
    - type: mrr_at_1000
      value: 15.581999999999999
    - type: mrr_at_3
      value: 13.299
    - type: mrr_at_5
      value: 14.097999999999999
    - type: ndcg_at_1
      value: 10.502
    - type: ndcg_at_10
      value: 14.649000000000001
    - type: ndcg_at_100
      value: 18.738
    - type: ndcg_at_1000
      value: 22.456
    - type: ndcg_at_3
      value: 12.222
    - type: ndcg_at_5
      value: 13.314
    - type: precision_at_1
      value: 10.502
    - type: precision_at_10
      value: 2.82
    - type: precision_at_100
      value: 0.588
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 5.936
    - type: precision_at_5
      value: 4.452
    - type: recall_at_1
      value: 8.262
    - type: recall_at_10
      value: 20.168
    - type: recall_at_100
      value: 38.405
    - type: recall_at_1000
      value: 65.694
    - type: recall_at_3
      value: 13.428999999999998
    - type: recall_at_5
      value: 16.229
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 10.117416666666665
    - type: map_at_10
      value: 13.858333333333334
    - type: map_at_100
      value: 14.565166666666668
    - type: map_at_1000
      value: 14.68266666666667
    - type: map_at_3
      value: 12.60983333333333
    - type: map_at_5
      value: 13.277416666666667
    - type: mrr_at_1
      value: 12.332833333333335
    - type: mrr_at_10
      value: 16.376333333333335
    - type: mrr_at_100
      value: 17.063333333333333
    - type: mrr_at_1000
      value: 17.1535
    - type: mrr_at_3
      value: 15.040666666666667
    - type: mrr_at_5
      value: 15.764833333333334
    - type: ndcg_at_1
      value: 12.332833333333335
    - type: ndcg_at_10
      value: 16.51366666666667
    - type: ndcg_at_100
      value: 20.2845
    - type: ndcg_at_1000
      value: 23.54025
    - type: ndcg_at_3
      value: 14.171250000000002
    - type: ndcg_at_5
      value: 15.193583333333333
    - type: precision_at_1
      value: 12.332833333333335
    - type: precision_at_10
      value: 2.983083333333333
    - type: precision_at_100
      value: 0.58325
    - type: precision_at_1000
      value: 0.10250000000000001
    - type: precision_at_3
      value: 6.626083333333334
    - type: precision_at_5
      value: 4.774916666666665
    - type: recall_at_1
      value: 10.117416666666665
    - type: recall_at_10
      value: 22.14666666666667
    - type: recall_at_100
      value: 39.5745
    - type: recall_at_1000
      value: 63.73550000000001
    - type: recall_at_3
      value: 15.431666666666665
    - type: recall_at_5
      value: 18.1215
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 7.431
    - type: map_at_10
      value: 10.172
    - type: map_at_100
      value: 10.639999999999999
    - type: map_at_1000
      value: 10.716000000000001
    - type: map_at_3
      value: 9.242
    - type: map_at_5
      value: 9.614
    - type: mrr_at_1
      value: 9.202
    - type: mrr_at_10
      value: 12.08
    - type: mrr_at_100
      value: 12.58
    - type: mrr_at_1000
      value: 12.649
    - type: mrr_at_3
      value: 11.145
    - type: mrr_at_5
      value: 11.59
    - type: ndcg_at_1
      value: 9.202
    - type: ndcg_at_10
      value: 12.291
    - type: ndcg_at_100
      value: 14.940999999999999
    - type: ndcg_at_1000
      value: 17.325
    - type: ndcg_at_3
      value: 10.446
    - type: ndcg_at_5
      value: 11.027000000000001
    - type: precision_at_1
      value: 9.202
    - type: precision_at_10
      value: 2.193
    - type: precision_at_100
      value: 0.388
    - type: precision_at_1000
      value: 0.065
    - type: precision_at_3
      value: 4.806
    - type: precision_at_5
      value: 3.374
    - type: recall_at_1
      value: 7.431
    - type: recall_at_10
      value: 17.197000000000003
    - type: recall_at_100
      value: 29.704000000000004
    - type: recall_at_1000
      value: 48.278999999999996
    - type: recall_at_3
      value: 11.616999999999999
    - type: recall_at_5
      value: 13.181000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.348
    - type: map_at_10
      value: 7.591
    - type: map_at_100
      value: 8.109
    - type: map_at_1000
      value: 8.206
    - type: map_at_3
      value: 6.782000000000001
    - type: map_at_5
      value: 7.244000000000001
    - type: mrr_at_1
      value: 6.641
    - type: mrr_at_10
      value: 9.281
    - type: mrr_at_100
      value: 9.838
    - type: mrr_at_1000
      value: 9.922
    - type: mrr_at_3
      value: 8.286999999999999
    - type: mrr_at_5
      value: 8.866999999999999
    - type: ndcg_at_1
      value: 6.641
    - type: ndcg_at_10
      value: 9.302000000000001
    - type: ndcg_at_100
      value: 12.200999999999999
    - type: ndcg_at_1000
      value: 15.223999999999998
    - type: ndcg_at_3
      value: 7.692
    - type: ndcg_at_5
      value: 8.474
    - type: precision_at_1
      value: 6.641
    - type: precision_at_10
      value: 1.755
    - type: precision_at_100
      value: 0.388
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 3.6249999999999996
    - type: precision_at_5
      value: 2.753
    - type: recall_at_1
      value: 5.348
    - type: recall_at_10
      value: 12.887
    - type: recall_at_100
      value: 26.391
    - type: recall_at_1000
      value: 49.156
    - type: recall_at_3
      value: 8.519
    - type: recall_at_5
      value: 10.431
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 7.9750000000000005
    - type: map_at_10
      value: 11.28
    - type: map_at_100
      value: 11.953
    - type: map_at_1000
      value: 12.051
    - type: map_at_3
      value: 10.022
    - type: map_at_5
      value: 10.807
    - type: mrr_at_1
      value: 9.795
    - type: mrr_at_10
      value: 13.544999999999998
    - type: mrr_at_100
      value: 14.249999999999998
    - type: mrr_at_1000
      value: 14.341000000000001
    - type: mrr_at_3
      value: 12.174
    - type: mrr_at_5
      value: 13.041
    - type: ndcg_at_1
      value: 9.795
    - type: ndcg_at_10
      value: 13.697000000000001
    - type: ndcg_at_100
      value: 17.389
    - type: ndcg_at_1000
      value: 20.46
    - type: ndcg_at_3
      value: 11.277
    - type: ndcg_at_5
      value: 12.579
    - type: precision_at_1
      value: 9.795
    - type: precision_at_10
      value: 2.435
    - type: precision_at_100
      value: 0.481
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 5.255
    - type: precision_at_5
      value: 3.955
    - type: recall_at_1
      value: 7.9750000000000005
    - type: recall_at_10
      value: 18.981
    - type: recall_at_100
      value: 36.178
    - type: recall_at_1000
      value: 59.46900000000001
    - type: recall_at_3
      value: 12.371
    - type: recall_at_5
      value: 15.613
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 10.742
    - type: map_at_10
      value: 15.346000000000002
    - type: map_at_100
      value: 16.153000000000002
    - type: map_at_1000
      value: 16.311999999999998
    - type: map_at_3
      value: 14.222999999999999
    - type: map_at_5
      value: 14.777000000000001
    - type: mrr_at_1
      value: 14.032
    - type: mrr_at_10
      value: 18.83
    - type: mrr_at_100
      value: 19.564999999999998
    - type: mrr_at_1000
      value: 19.655
    - type: mrr_at_3
      value: 17.523
    - type: mrr_at_5
      value: 18.244
    - type: ndcg_at_1
      value: 14.032
    - type: ndcg_at_10
      value: 18.496000000000002
    - type: ndcg_at_100
      value: 22.377
    - type: ndcg_at_1000
      value: 26.284000000000002
    - type: ndcg_at_3
      value: 16.520000000000003
    - type: ndcg_at_5
      value: 17.276
    - type: precision_at_1
      value: 14.032
    - type: precision_at_10
      value: 3.5770000000000004
    - type: precision_at_100
      value: 0.783
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_3
      value: 7.971
    - type: precision_at_5
      value: 5.692
    - type: recall_at_1
      value: 10.742
    - type: recall_at_10
      value: 24.157999999999998
    - type: recall_at_100
      value: 42.091
    - type: recall_at_1000
      value: 70.054
    - type: recall_at_3
      value: 17.916999999999998
    - type: recall_at_5
      value: 20.131
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 7.831
    - type: map_at_10
      value: 10.749
    - type: map_at_100
      value: 11.279
    - type: map_at_1000
      value: 11.397
    - type: map_at_3
      value: 9.78
    - type: map_at_5
      value: 10.459999999999999
    - type: mrr_at_1
      value: 8.872
    - type: mrr_at_10
      value: 11.898
    - type: mrr_at_100
      value: 12.466000000000001
    - type: mrr_at_1000
      value: 12.583
    - type: mrr_at_3
      value: 10.875
    - type: mrr_at_5
      value: 11.577
    - type: ndcg_at_1
      value: 8.872
    - type: ndcg_at_10
      value: 12.642000000000001
    - type: ndcg_at_100
      value: 16.032
    - type: ndcg_at_1000
      value: 19.567999999999998
    - type: ndcg_at_3
      value: 10.674999999999999
    - type: ndcg_at_5
      value: 11.886
    - type: precision_at_1
      value: 8.872
    - type: precision_at_10
      value: 2.015
    - type: precision_at_100
      value: 0.41200000000000003
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.806
    - type: precision_at_5
      value: 3.512
    - type: recall_at_1
      value: 7.831
    - type: recall_at_10
      value: 17.511
    - type: recall_at_100
      value: 34.461000000000006
    - type: recall_at_1000
      value: 62.01
    - type: recall_at_3
      value: 12.089
    - type: recall_at_5
      value: 15.139
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 3.3300000000000005
    - type: map_at_10
      value: 5.8709999999999996
    - type: map_at_100
      value: 6.7860000000000005
    - type: map_at_1000
      value: 6.955
    - type: map_at_3
      value: 4.714
    - type: map_at_5
      value: 5.26
    - type: mrr_at_1
      value: 7.101
    - type: mrr_at_10
      value: 12.125
    - type: mrr_at_100
      value: 13.200000000000001
    - type: mrr_at_1000
      value: 13.295000000000002
    - type: mrr_at_3
      value: 10.119
    - type: mrr_at_5
      value: 11.038
    - type: ndcg_at_1
      value: 7.101
    - type: ndcg_at_10
      value: 9.159
    - type: ndcg_at_100
      value: 14.030000000000001
    - type: ndcg_at_1000
      value: 18.013
    - type: ndcg_at_3
      value: 6.6739999999999995
    - type: ndcg_at_5
      value: 7.4719999999999995
    - type: precision_at_1
      value: 7.101
    - type: precision_at_10
      value: 3.16
    - type: precision_at_100
      value: 0.84
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 5.081
    - type: precision_at_5
      value: 4.143
    - type: recall_at_1
      value: 3.3300000000000005
    - type: recall_at_10
      value: 12.215
    - type: recall_at_100
      value: 29.683999999999997
    - type: recall_at_1000
      value: 52.951
    - type: recall_at_3
      value: 6.356000000000001
    - type: recall_at_5
      value: 8.315
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 1.718
    - type: map_at_10
      value: 3.639
    - type: map_at_100
      value: 4.853
    - type: map_at_1000
      value: 5.219
    - type: map_at_3
      value: 2.6149999999999998
    - type: map_at_5
      value: 3.073
    - type: mrr_at_1
      value: 20.0
    - type: mrr_at_10
      value: 26.88
    - type: mrr_at_100
      value: 27.753
    - type: mrr_at_1000
      value: 27.822000000000003
    - type: mrr_at_3
      value: 24.667
    - type: mrr_at_5
      value: 25.654
    - type: ndcg_at_1
      value: 15.0
    - type: ndcg_at_10
      value: 10.878
    - type: ndcg_at_100
      value: 12.011
    - type: ndcg_at_1000
      value: 16.492
    - type: ndcg_at_3
      value: 12.818999999999999
    - type: ndcg_at_5
      value: 11.554
    - type: precision_at_1
      value: 20.0
    - type: precision_at_10
      value: 9.625
    - type: precision_at_100
      value: 3.037
    - type: precision_at_1000
      value: 0.7080000000000001
    - type: precision_at_3
      value: 15.082999999999998
    - type: precision_at_5
      value: 12.1
    - type: recall_at_1
      value: 1.718
    - type: recall_at_10
      value: 5.716
    - type: recall_at_100
      value: 14.266000000000002
    - type: recall_at_1000
      value: 30.012
    - type: recall_at_3
      value: 3.108
    - type: recall_at_5
      value: 4.181
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 41.114999999999995
    - type: f1
      value: 37.00141090816854
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 5.523
    - type: map_at_10
      value: 8.036
    - type: map_at_100
      value: 8.581999999999999
    - type: map_at_1000
      value: 8.657
    - type: map_at_3
      value: 7.13
    - type: map_at_5
      value: 7.536
    - type: mrr_at_1
      value: 5.836
    - type: mrr_at_10
      value: 8.547
    - type: mrr_at_100
      value: 9.123000000000001
    - type: mrr_at_1000
      value: 9.197
    - type: mrr_at_3
      value: 7.563000000000001
    - type: mrr_at_5
      value: 8.006
    - type: ndcg_at_1
      value: 5.836
    - type: ndcg_at_10
      value: 9.764000000000001
    - type: ndcg_at_100
      value: 12.866
    - type: ndcg_at_1000
      value: 15.243
    - type: ndcg_at_3
      value: 7.7700000000000005
    - type: ndcg_at_5
      value: 8.518
    - type: precision_at_1
      value: 5.836
    - type: precision_at_10
      value: 1.6070000000000002
    - type: precision_at_100
      value: 0.331
    - type: precision_at_1000
      value: 0.055
    - type: precision_at_3
      value: 3.2849999999999997
    - type: precision_at_5
      value: 2.37
    - type: recall_at_1
      value: 5.523
    - type: recall_at_10
      value: 14.795
    - type: recall_at_100
      value: 29.932
    - type: recall_at_1000
      value: 48.946
    - type: recall_at_3
      value: 9.208
    - type: recall_at_5
      value: 10.984
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.135
    - type: map_at_10
      value: 6.433999999999999
    - type: map_at_100
      value: 7.196
    - type: map_at_1000
      value: 7.356999999999999
    - type: map_at_3
      value: 5.339
    - type: map_at_5
      value: 5.878
    - type: mrr_at_1
      value: 8.796
    - type: mrr_at_10
      value: 12.357999999999999
    - type: mrr_at_100
      value: 13.208
    - type: mrr_at_1000
      value: 13.318
    - type: mrr_at_3
      value: 10.777000000000001
    - type: mrr_at_5
      value: 11.525
    - type: ndcg_at_1
      value: 8.796
    - type: ndcg_at_10
      value: 9.332
    - type: ndcg_at_100
      value: 13.517999999999999
    - type: ndcg_at_1000
      value: 17.907999999999998
    - type: ndcg_at_3
      value: 7.481999999999999
    - type: ndcg_at_5
      value: 8.065
    - type: precision_at_1
      value: 8.796
    - type: precision_at_10
      value: 2.8240000000000003
    - type: precision_at_100
      value: 0.705
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_3
      value: 4.887
    - type: precision_at_5
      value: 3.8580000000000005
    - type: recall_at_1
      value: 4.135
    - type: recall_at_10
      value: 12.292
    - type: recall_at_100
      value: 28.915999999999997
    - type: recall_at_1000
      value: 57.477999999999994
    - type: recall_at_3
      value: 6.747
    - type: recall_at_5
      value: 8.667
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 5.928
    - type: map_at_10
      value: 8.469
    - type: map_at_100
      value: 8.936
    - type: map_at_1000
      value: 9.02
    - type: map_at_3
      value: 7.582
    - type: map_at_5
      value: 8.021
    - type: mrr_at_1
      value: 11.857
    - type: mrr_at_10
      value: 15.675
    - type: mrr_at_100
      value: 16.273
    - type: mrr_at_1000
      value: 16.356
    - type: mrr_at_3
      value: 14.347999999999999
    - type: mrr_at_5
      value: 14.995
    - type: ndcg_at_1
      value: 11.857
    - type: ndcg_at_10
      value: 11.651
    - type: ndcg_at_100
      value: 14.374999999999998
    - type: ndcg_at_1000
      value: 16.912
    - type: ndcg_at_3
      value: 9.625
    - type: ndcg_at_5
      value: 10.474
    - type: precision_at_1
      value: 11.857
    - type: precision_at_10
      value: 2.777
    - type: precision_at_100
      value: 0.503
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.140000000000001
    - type: precision_at_5
      value: 4.362
    - type: recall_at_1
      value: 5.928
    - type: recall_at_10
      value: 13.883000000000001
    - type: recall_at_100
      value: 25.137999999999998
    - type: recall_at_1000
      value: 42.315999999999995
    - type: recall_at_3
      value: 9.21
    - type: recall_at_5
      value: 10.905
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 65.4388
    - type: ap
      value: 60.440774024423426
    - type: f1
      value: 65.31315753102281
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 3.4479999999999995
    - type: map_at_10
      value: 5.74
    - type: map_at_100
      value: 6.2780000000000005
    - type: map_at_1000
      value: 6.358999999999999
    - type: map_at_3
      value: 4.82
    - type: map_at_5
      value: 5.3
    - type: mrr_at_1
      value: 3.5389999999999997
    - type: mrr_at_10
      value: 5.906000000000001
    - type: mrr_at_100
      value: 6.455
    - type: mrr_at_1000
      value: 6.5360000000000005
    - type: mrr_at_3
      value: 4.9639999999999995
    - type: mrr_at_5
      value: 5.453
    - type: ndcg_at_1
      value: 3.5389999999999997
    - type: ndcg_at_10
      value: 7.255000000000001
    - type: ndcg_at_100
      value: 10.308
    - type: ndcg_at_1000
      value: 12.93
    - type: ndcg_at_3
      value: 5.314
    - type: ndcg_at_5
      value: 6.184
    - type: precision_at_1
      value: 3.5389999999999997
    - type: precision_at_10
      value: 1.246
    - type: precision_at_100
      value: 0.28500000000000003
    - type: precision_at_1000
      value: 0.051000000000000004
    - type: precision_at_3
      value: 2.297
    - type: precision_at_5
      value: 1.814
    - type: recall_at_1
      value: 3.4479999999999995
    - type: recall_at_10
      value: 11.982
    - type: recall_at_100
      value: 27.123
    - type: recall_at_1000
      value: 48.489
    - type: recall_at_3
      value: 6.607
    - type: recall_at_5
      value: 8.706
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.9484724122207
    - type: f1
      value: 85.39768490584245
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 58.48837209302326
    - type: f1
      value: 39.10849416181491
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.632145258910555
    - type: f1
      value: 58.09773014884143
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.68325487558843
    - type: f1
      value: 65.91204845805859
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.41069242141184
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.307848920918044
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.270878365120332
    - type: mrr
      value: 29.057926505909254
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 1.855
    - type: map_at_10
      value: 3.582
    - type: map_at_100
      value: 4.694
    - type: map_at_1000
      value: 5.739
    - type: map_at_3
      value: 2.677
    - type: map_at_5
      value: 3.1
    - type: mrr_at_1
      value: 18.884999999999998
    - type: mrr_at_10
      value: 27.256999999999998
    - type: mrr_at_100
      value: 28.327999999999996
    - type: mrr_at_1000
      value: 28.402
    - type: mrr_at_3
      value: 24.2
    - type: mrr_at_5
      value: 26.011
    - type: ndcg_at_1
      value: 17.957
    - type: ndcg_at_10
      value: 14.051
    - type: ndcg_at_100
      value: 14.282
    - type: ndcg_at_1000
      value: 24.3
    - type: ndcg_at_3
      value: 15.478
    - type: ndcg_at_5
      value: 14.782
    - type: precision_at_1
      value: 18.884999999999998
    - type: precision_at_10
      value: 10.743
    - type: precision_at_100
      value: 4.449
    - type: precision_at_1000
      value: 1.7670000000000001
    - type: precision_at_3
      value: 14.654
    - type: precision_at_5
      value: 12.940999999999999
    - type: recall_at_1
      value: 1.855
    - type: recall_at_10
      value: 6.861000000000001
    - type: recall_at_100
      value: 18.044
    - type: recall_at_1000
      value: 52.712
    - type: recall_at_3
      value: 3.3369999999999997
    - type: recall_at_5
      value: 4.562
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 4.881
    - type: map_at_10
      value: 8.241999999999999
    - type: map_at_100
      value: 8.956999999999999
    - type: map_at_1000
      value: 9.062000000000001
    - type: map_at_3
      value: 6.981
    - type: map_at_5
      value: 7.61
    - type: mrr_at_1
      value: 5.5329999999999995
    - type: mrr_at_10
      value: 9.184000000000001
    - type: mrr_at_100
      value: 9.918000000000001
    - type: mrr_at_1000
      value: 10.018
    - type: mrr_at_3
      value: 7.836
    - type: mrr_at_5
      value: 8.518
    - type: ndcg_at_1
      value: 5.5329999999999995
    - type: ndcg_at_10
      value: 10.554
    - type: ndcg_at_100
      value: 14.341999999999999
    - type: ndcg_at_1000
      value: 17.458000000000002
    - type: ndcg_at_3
      value: 7.8759999999999994
    - type: ndcg_at_5
      value: 9.023
    - type: precision_at_1
      value: 5.5329999999999995
    - type: precision_at_10
      value: 1.944
    - type: precision_at_100
      value: 0.411
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 3.669
    - type: precision_at_5
      value: 2.8160000000000003
    - type: recall_at_1
      value: 4.881
    - type: recall_at_10
      value: 16.898
    - type: recall_at_100
      value: 34.625
    - type: recall_at_1000
      value: 58.901
    - type: recall_at_3
      value: 9.651
    - type: recall_at_5
      value: 12.35
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 53.159
    - type: map_at_10
      value: 64.053
    - type: map_at_100
      value: 64.938
    - type: map_at_1000
      value: 64.994
    - type: map_at_3
      value: 61.413
    - type: map_at_5
      value: 62.966
    - type: mrr_at_1
      value: 61.129999999999995
    - type: mrr_at_10
      value: 68.84400000000001
    - type: mrr_at_100
      value: 69.3
    - type: mrr_at_1000
      value: 69.319
    - type: mrr_at_3
      value: 67.113
    - type: mrr_at_5
      value: 68.162
    - type: ndcg_at_1
      value: 61.160000000000004
    - type: ndcg_at_10
      value: 68.944
    - type: ndcg_at_100
      value: 72.10499999999999
    - type: ndcg_at_1000
      value: 73.046
    - type: ndcg_at_3
      value: 65.223
    - type: ndcg_at_5
      value: 67.05
    - type: precision_at_1
      value: 61.160000000000004
    - type: precision_at_10
      value: 10.392999999999999
    - type: precision_at_100
      value: 1.327
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 28.13
    - type: precision_at_5
      value: 18.656
    - type: recall_at_1
      value: 53.159
    - type: recall_at_10
      value: 78.412
    - type: recall_at_100
      value: 91.399
    - type: recall_at_1000
      value: 97.52
    - type: recall_at_3
      value: 67.794
    - type: recall_at_5
      value: 72.801
    - type: map_at_1
      value: 1.8450000000000002
    - type: map_at_10
      value: 4.172
    - type: map_at_100
      value: 5.092
    - type: map_at_1000
      value: 5.3100000000000005
    - type: map_at_3
      value: 3.093
    - type: map_at_5
      value: 3.6450000000000005
    - type: mrr_at_1
      value: 9.1
    - type: mrr_at_10
      value: 15.15
    - type: mrr_at_100
      value: 16.216
    - type: mrr_at_1000
      value: 16.332
    - type: mrr_at_3
      value: 12.55
    - type: mrr_at_5
      value: 13.975000000000001
    - type: ndcg_at_1
      value: 9.1
    - type: ndcg_at_10
      value: 8.065999999999999
    - type: ndcg_at_100
      value: 12.982
    - type: ndcg_at_1000
      value: 18.046
    - type: ndcg_at_3
      value: 7.295999999999999
    - type: ndcg_at_5
      value: 6.572
    - type: precision_at_1
      value: 9.1
    - type: precision_at_10
      value: 4.29
    - type: precision_at_100
      value: 1.16
    - type: precision_at_1000
      value: 0.23900000000000002
    - type: precision_at_3
      value: 6.833
    - type: precision_at_5
      value: 5.88
    - type: recall_at_1
      value: 1.8450000000000002
    - type: recall_at_10
      value: 8.706999999999999
    - type: recall_at_100
      value: 23.645
    - type: recall_at_1000
      value: 48.597
    - type: recall_at_3
      value: 4.175
    - type: recall_at_5
      value: 5.973
    - type: map_at_1
      value: 0.058
    - type: map_at_10
      value: 0.445
    - type: map_at_100
      value: 2.489
    - type: map_at_1000
      value: 6.3100000000000005
    - type: map_at_3
      value: 0.16999999999999998
    - type: map_at_5
      value: 0.254
    - type: mrr_at_1
      value: 32.0
    - type: mrr_at_10
      value: 46.016
    - type: mrr_at_100
      value: 46.683
    - type: mrr_at_1000
      value: 46.719
    - type: mrr_at_3
      value: 41.667
    - type: mrr_at_5
      value: 42.967
    - type: ndcg_at_1
      value: 26.0
    - type: ndcg_at_10
      value: 29.885
    - type: ndcg_at_100
      value: 22.958000000000002
    - type: ndcg_at_1000
      value: 22.244
    - type: ndcg_at_3
      value: 29.787999999999997
    - type: ndcg_at_5
      value: 29.494999999999997
    - type: precision_at_1
      value: 32.0
    - type: precision_at_10
      value: 33.800000000000004
    - type: precision_at_100
      value: 24.52
    - type: precision_at_1000
      value: 11.196
    - type: precision_at_3
      value: 35.333
    - type: precision_at_5
      value: 34.0
    - type: recall_at_1
      value: 0.058
    - type: recall_at_10
      value: 0.657
    - type: recall_at_100
      value: 5.069
    - type: recall_at_1000
      value: 22.447
    - type: recall_at_3
      value: 0.2
    - type: recall_at_5
      value: 0.32299999999999995
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 30.140589231842256
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 39.92770613505385
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.59024815989618
    - type: cos_sim_spearman
      value: 68.11624653233133
    - type: euclidean_pearson
      value: 73.27920094980502
    - type: euclidean_spearman
      value: 68.11632959681863
    - type: manhattan_pearson
      value: 72.54935141266294
    - type: manhattan_spearman
      value: 67.12457070604133
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 69.40126270570799
    - type: cos_sim_spearman
      value: 62.14207404840335
    - type: euclidean_pearson
      value: 66.27602017682412
    - type: euclidean_spearman
      value: 62.143384728461314
    - type: manhattan_pearson
      value: 67.07706053549664
    - type: manhattan_spearman
      value: 63.06497657163255
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.5989515866992
    - type: cos_sim_spearman
      value: 77.15211512453997
    - type: euclidean_pearson
      value: 76.70296919445704
    - type: euclidean_spearman
      value: 77.15215294384531
    - type: manhattan_pearson
      value: 77.00183340244841
    - type: manhattan_spearman
      value: 77.54347126493187
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 73.76592708615566
    - type: cos_sim_spearman
      value: 70.57102535486983
    - type: euclidean_pearson
      value: 73.16493844323281
    - type: euclidean_spearman
      value: 70.57101566858893
    - type: manhattan_pearson
      value: 73.3644832097739
    - type: manhattan_spearman
      value: 70.93527541966915
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 75.95076880553377
    - type: cos_sim_spearman
      value: 77.68458699868269
    - type: euclidean_pearson
      value: 77.7470713475935
    - type: euclidean_spearman
      value: 77.6845933113232
    - type: manhattan_pearson
      value: 78.19369618957612
    - type: manhattan_spearman
      value: 78.11088657087784
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 71.9715763028299
    - type: cos_sim_spearman
      value: 73.53220647955904
    - type: euclidean_pearson
      value: 73.57406594330985
    - type: euclidean_spearman
      value: 73.53303581777323
    - type: manhattan_pearson
      value: 74.03967460920595
    - type: manhattan_spearman
      value: 74.05778553630698
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.73667148725723
    - type: cos_sim_spearman
      value: 80.81028828869353
    - type: euclidean_pearson
      value: 81.15810431179573
    - type: euclidean_spearman
      value: 80.81116429309112
    - type: manhattan_pearson
      value: 81.55719120035107
    - type: manhattan_spearman
      value: 81.20882260152872
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.43534524580482
    - type: cos_sim_spearman
      value: 59.839157733781434
    - type: euclidean_pearson
      value: 61.83093863698779
    - type: euclidean_spearman
      value: 59.839157733781434
    - type: manhattan_pearson
      value: 62.55988010471628
    - type: manhattan_spearman
      value: 60.30306061143011
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 72.25188934839379
    - type: cos_sim_spearman
      value: 70.9113050369473
    - type: euclidean_pearson
      value: 72.68710352046212
    - type: euclidean_spearman
      value: 70.9113534378691
    - type: manhattan_pearson
      value: 73.09745859415004
    - type: manhattan_spearman
      value: 71.26505067192102
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 67.5036392977626
    - type: mrr
      value: 87.43891003694925
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 20.889
    - type: map_at_10
      value: 27.165
    - type: map_at_100
      value: 28.368
    - type: map_at_1000
      value: 28.483999999999998
    - type: map_at_3
      value: 25.180999999999997
    - type: map_at_5
      value: 26.269
    - type: mrr_at_1
      value: 22.0
    - type: mrr_at_10
      value: 28.512999999999998
    - type: mrr_at_100
      value: 29.531000000000002
    - type: mrr_at_1000
      value: 29.635
    - type: mrr_at_3
      value: 26.611
    - type: mrr_at_5
      value: 27.594
    - type: ndcg_at_1
      value: 22.0
    - type: ndcg_at_10
      value: 30.814000000000004
    - type: ndcg_at_100
      value: 36.647999999999996
    - type: ndcg_at_1000
      value: 39.81
    - type: ndcg_at_3
      value: 26.845999999999997
    - type: ndcg_at_5
      value: 28.677999999999997
    - type: precision_at_1
      value: 22.0
    - type: precision_at_10
      value: 4.5
    - type: precision_at_100
      value: 0.773
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 10.778
    - type: precision_at_5
      value: 7.5329999999999995
    - type: recall_at_1
      value: 20.889
    - type: recall_at_10
      value: 40.861
    - type: recall_at_100
      value: 68.089
    - type: recall_at_1000
      value: 93.05
    - type: recall_at_3
      value: 30.083
    - type: recall_at_5
      value: 34.556
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.47524752475248
    - type: cos_sim_ap
      value: 75.756486791625
    - type: cos_sim_f1
      value: 70.0162074554295
    - type: cos_sim_precision
      value: 76.14571092831962
    - type: cos_sim_recall
      value: 64.8
    - type: dot_accuracy
      value: 99.47524752475248
    - type: dot_ap
      value: 75.756486791625
    - type: dot_f1
      value: 70.0162074554295
    - type: dot_precision
      value: 76.14571092831962
    - type: dot_recall
      value: 64.8
    - type: euclidean_accuracy
      value: 99.47524752475248
    - type: euclidean_ap
      value: 75.756486791625
    - type: euclidean_f1
      value: 70.0162074554295
    - type: euclidean_precision
      value: 76.14571092831962
    - type: euclidean_recall
      value: 64.8
    - type: manhattan_accuracy
      value: 99.53069306930693
    - type: manhattan_ap
      value: 78.93311079752957
    - type: manhattan_f1
      value: 72.61292166952545
    - type: manhattan_precision
      value: 84.77970627503338
    - type: manhattan_recall
      value: 63.5
    - type: max_accuracy
      value: 99.53069306930693
    - type: max_ap
      value: 78.93311079752957
    - type: max_f1
      value: 72.61292166952545
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 38.956591584917824
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.829387041051085
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.618168302388256
    - type: mrr
      value: 42.031210211357276
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.716182681356333
    - type: cos_sim_spearman
      value: 28.852160879670087
    - type: dot_pearson
      value: 29.716182648715844
    - type: dot_spearman
      value: 28.951026187665967
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.157
    - type: map_at_10
      value: 6.787999999999999
    - type: map_at_100
      value: 9.948
    - type: map_at_1000
      value: 11.331
    - type: map_at_3
      value: 4.642
    - type: map_at_5
      value: 5.718999999999999
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 39.195
    - type: mrr_at_100
      value: 40.778999999999996
    - type: mrr_at_1000
      value: 40.797
    - type: mrr_at_3
      value: 36.394999999999996
    - type: mrr_at_5
      value: 38.129000000000005
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 17.936
    - type: ndcg_at_100
      value: 26.552999999999997
    - type: ndcg_at_1000
      value: 38.318000000000005
    - type: ndcg_at_3
      value: 24.192
    - type: ndcg_at_5
      value: 21.732000000000003
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 14.285999999999998
    - type: precision_at_100
      value: 5.489999999999999
    - type: precision_at_1000
      value: 1.2710000000000001
    - type: precision_at_3
      value: 24.490000000000002
    - type: precision_at_5
      value: 20.816000000000003
    - type: recall_at_1
      value: 2.157
    - type: recall_at_10
      value: 9.729000000000001
    - type: recall_at_100
      value: 32.688
    - type: recall_at_1000
      value: 69.123
    - type: recall_at_3
      value: 5.26
    - type: recall_at_5
      value: 7.109
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 67.9134
    - type: ap
      value: 12.774220384041032
    - type: f1
      value: 52.153059662642434
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.613469156762875
    - type: f1
      value: 53.786522868566145
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 30.747359446594245
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.97806520832091
    - type: cos_sim_ap
      value: 66.35427447671117
    - type: cos_sim_f1
      value: 63.0426851514046
    - type: cos_sim_precision
      value: 58.47056169636815
    - type: cos_sim_recall
      value: 68.3905013192612
    - type: dot_accuracy
      value: 83.97806520832091
    - type: dot_ap
      value: 66.35427447671117
    - type: dot_f1
      value: 63.0426851514046
    - type: dot_precision
      value: 58.47056169636815
    - type: dot_recall
      value: 68.3905013192612
    - type: euclidean_accuracy
      value: 83.97806520832091
    - type: euclidean_ap
      value: 66.35427447671117
    - type: euclidean_f1
      value: 63.0426851514046
    - type: euclidean_precision
      value: 58.47056169636815
    - type: euclidean_recall
      value: 68.3905013192612
    - type: manhattan_accuracy
      value: 83.97210466710378
    - type: manhattan_ap
      value: 65.97618382203181
    - type: manhattan_f1
      value: 62.53991648243675
    - type: manhattan_precision
      value: 58.501838235294116
    - type: manhattan_recall
      value: 67.17678100263852
    - type: max_accuracy
      value: 83.97806520832091
    - type: max_ap
      value: 66.35427447671117
    - type: max_f1
      value: 63.0426851514046
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.71362595567975
    - type: cos_sim_ap
      value: 80.86796720185393
    - type: cos_sim_f1
      value: 73.24097703244622
    - type: cos_sim_precision
      value: 69.5540783824955
    - type: cos_sim_recall
      value: 77.34062211271944
    - type: dot_accuracy
      value: 86.71362595567975
    - type: dot_ap
      value: 80.86797238493406
    - type: dot_f1
      value: 73.24097703244622
    - type: dot_precision
      value: 69.5540783824955
    - type: dot_recall
      value: 77.34062211271944
    - type: euclidean_accuracy
      value: 86.71362595567975
    - type: euclidean_ap
      value: 80.86796690301992
    - type: euclidean_f1
      value: 73.24097703244622
    - type: euclidean_precision
      value: 69.5540783824955
    - type: euclidean_recall
      value: 77.34062211271944
    - type: manhattan_accuracy
      value: 86.64376916210657
    - type: manhattan_ap
      value: 80.8520473693602
    - type: manhattan_f1
      value: 73.15887850467291
    - type: manhattan_precision
      value: 71.10158407208255
    - type: manhattan_recall
      value: 75.33877425315676
    - type: max_accuracy
      value: 86.71362595567975
    - type: max_ap
      value: 80.86797238493406
    - type: max_f1
      value: 73.24097703244622
---
