mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_nignore15
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.01492537313432
    - type: ap
      value: 35.50250124630455
    - type: f1
      value: 66.89959317702703
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.84830000000001
    - type: ap
      value: 59.73270245283254
    - type: f1
      value: 64.76353235413379
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.105999999999995
    - type: f1
      value: 33.54422658625557
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.622
    - type: map_at_10
      value: 35.826
    - type: map_at_100
      value: 37.053000000000004
    - type: map_at_1000
      value: 37.074
    - type: map_at_3
      value: 31.211
    - type: map_at_5
      value: 33.921
    - type: mrr_at_1
      value: 22.262
    - type: mrr_at_10
      value: 36.036
    - type: mrr_at_100
      value: 37.263000000000005
    - type: mrr_at_1000
      value: 37.284
    - type: mrr_at_3
      value: 31.484
    - type: mrr_at_5
      value: 34.144000000000005
    - type: ndcg_at_1
      value: 21.622
    - type: ndcg_at_10
      value: 43.922
    - type: ndcg_at_100
      value: 49.506
    - type: ndcg_at_1000
      value: 50.009
    - type: ndcg_at_3
      value: 34.372
    - type: ndcg_at_5
      value: 39.275
    - type: precision_at_1
      value: 21.622
    - type: precision_at_10
      value: 6.991
    - type: precision_at_100
      value: 0.9520000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.509
    - type: precision_at_5
      value: 11.094999999999999
    - type: recall_at_1
      value: 21.622
    - type: recall_at_10
      value: 69.915
    - type: recall_at_100
      value: 95.235
    - type: recall_at_1000
      value: 99.075
    - type: recall_at_3
      value: 43.528
    - type: recall_at_5
      value: 55.477
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 34.911008985215766
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.405265668502622
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.19334227044753
    - type: mrr
      value: 69.16600712307083
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.93657061818256
    - type: cos_sim_spearman
      value: 80.1584529707527
    - type: euclidean_pearson
      value: 81.85076602737361
    - type: euclidean_spearman
      value: 80.1584529707527
    - type: manhattan_pearson
      value: 81.32446368945303
    - type: manhattan_spearman
      value: 80.35183087097523
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.75974025974025
    - type: f1
      value: 72.01384314530861
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.205913552227386
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.518894282858902
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 23.200000000000003
    - type: map_at_10
      value: 30.767
    - type: map_at_100
      value: 31.909
    - type: map_at_1000
      value: 32.054
    - type: map_at_3
      value: 28.048000000000002
    - type: map_at_5
      value: 29.668
    - type: mrr_at_1
      value: 29.185
    - type: mrr_at_10
      value: 36.361
    - type: mrr_at_100
      value: 37.212
    - type: mrr_at_1000
      value: 37.275999999999996
    - type: mrr_at_3
      value: 34.168
    - type: mrr_at_5
      value: 35.463
    - type: ndcg_at_1
      value: 29.185
    - type: ndcg_at_10
      value: 35.735
    - type: ndcg_at_100
      value: 40.884
    - type: ndcg_at_1000
      value: 43.887
    - type: ndcg_at_3
      value: 31.839000000000002
    - type: ndcg_at_5
      value: 33.759
    - type: precision_at_1
      value: 29.185
    - type: precision_at_10
      value: 6.723999999999999
    - type: precision_at_100
      value: 1.163
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 15.165000000000001
    - type: precision_at_5
      value: 11.101999999999999
    - type: recall_at_1
      value: 23.200000000000003
    - type: recall_at_10
      value: 44.68
    - type: recall_at_100
      value: 67.47999999999999
    - type: recall_at_1000
      value: 88.152
    - type: recall_at_3
      value: 33.055
    - type: recall_at_5
      value: 38.481
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.410999999999998
    - type: map_at_10
      value: 23.605999999999998
    - type: map_at_100
      value: 24.532
    - type: map_at_1000
      value: 24.645
    - type: map_at_3
      value: 21.628
    - type: map_at_5
      value: 22.849
    - type: mrr_at_1
      value: 22.038
    - type: mrr_at_10
      value: 27.947
    - type: mrr_at_100
      value: 28.701
    - type: mrr_at_1000
      value: 28.772
    - type: mrr_at_3
      value: 26.008
    - type: mrr_at_5
      value: 27.187
    - type: ndcg_at_1
      value: 22.038
    - type: ndcg_at_10
      value: 27.632
    - type: ndcg_at_100
      value: 31.852000000000004
    - type: ndcg_at_1000
      value: 34.587
    - type: ndcg_at_3
      value: 24.274
    - type: ndcg_at_5
      value: 26.005
    - type: precision_at_1
      value: 22.038
    - type: precision_at_10
      value: 5.108
    - type: precision_at_100
      value: 0.911
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.591999999999999
    - type: precision_at_5
      value: 8.42
    - type: recall_at_1
      value: 17.410999999999998
    - type: recall_at_10
      value: 35.346
    - type: recall_at_100
      value: 53.849000000000004
    - type: recall_at_1000
      value: 72.56700000000001
    - type: recall_at_3
      value: 25.647
    - type: recall_at_5
      value: 30.288999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.1
    - type: map_at_10
      value: 35.973
    - type: map_at_100
      value: 37.1
    - type: map_at_1000
      value: 37.191
    - type: map_at_3
      value: 33.409
    - type: map_at_5
      value: 34.867
    - type: mrr_at_1
      value: 31.473000000000003
    - type: mrr_at_10
      value: 39.35
    - type: mrr_at_100
      value: 40.258
    - type: mrr_at_1000
      value: 40.314
    - type: mrr_at_3
      value: 37.106
    - type: mrr_at_5
      value: 38.316
    - type: ndcg_at_1
      value: 31.473000000000003
    - type: ndcg_at_10
      value: 40.831
    - type: ndcg_at_100
      value: 46.094
    - type: ndcg_at_1000
      value: 48.147
    - type: ndcg_at_3
      value: 36.187000000000005
    - type: ndcg_at_5
      value: 38.389
    - type: precision_at_1
      value: 31.473000000000003
    - type: precision_at_10
      value: 6.627
    - type: precision_at_100
      value: 1.013
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 16.092000000000002
    - type: precision_at_5
      value: 11.197
    - type: recall_at_1
      value: 27.1
    - type: recall_at_10
      value: 52.208
    - type: recall_at_100
      value: 75.913
    - type: recall_at_1000
      value: 90.623
    - type: recall_at_3
      value: 39.696999999999996
    - type: recall_at_5
      value: 45.068999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.164000000000001
    - type: map_at_10
      value: 17.209
    - type: map_at_100
      value: 18.078
    - type: map_at_1000
      value: 18.196
    - type: map_at_3
      value: 15.723999999999998
    - type: map_at_5
      value: 16.53
    - type: mrr_at_1
      value: 14.35
    - type: mrr_at_10
      value: 18.549
    - type: mrr_at_100
      value: 19.378999999999998
    - type: mrr_at_1000
      value: 19.485
    - type: mrr_at_3
      value: 17.024
    - type: mrr_at_5
      value: 17.832
    - type: ndcg_at_1
      value: 14.35
    - type: ndcg_at_10
      value: 19.949
    - type: ndcg_at_100
      value: 24.59
    - type: ndcg_at_1000
      value: 28.102
    - type: ndcg_at_3
      value: 16.894000000000002
    - type: ndcg_at_5
      value: 18.322
    - type: precision_at_1
      value: 14.35
    - type: precision_at_10
      value: 3.0620000000000003
    - type: precision_at_100
      value: 0.573
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 7.005999999999999
    - type: precision_at_5
      value: 5.017
    - type: recall_at_1
      value: 13.164000000000001
    - type: recall_at_10
      value: 27.282
    - type: recall_at_100
      value: 49.352000000000004
    - type: recall_at_1000
      value: 76.7
    - type: recall_at_3
      value: 18.93
    - type: recall_at_5
      value: 22.395
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.343
    - type: map_at_10
      value: 10.732999999999999
    - type: map_at_100
      value: 11.524
    - type: map_at_1000
      value: 11.658
    - type: map_at_3
      value: 9.501999999999999
    - type: map_at_5
      value: 10.118
    - type: mrr_at_1
      value: 9.577
    - type: mrr_at_10
      value: 13.293
    - type: mrr_at_100
      value: 14.126
    - type: mrr_at_1000
      value: 14.234
    - type: mrr_at_3
      value: 11.816
    - type: mrr_at_5
      value: 12.519
    - type: ndcg_at_1
      value: 9.577
    - type: ndcg_at_10
      value: 13.303999999999998
    - type: ndcg_at_100
      value: 17.596999999999998
    - type: ndcg_at_1000
      value: 21.406
    - type: ndcg_at_3
      value: 10.788
    - type: ndcg_at_5
      value: 11.815000000000001
    - type: precision_at_1
      value: 9.577
    - type: precision_at_10
      value: 2.512
    - type: precision_at_100
      value: 0.545
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 5.1
    - type: precision_at_5
      value: 3.781
    - type: recall_at_1
      value: 7.343
    - type: recall_at_10
      value: 18.912000000000003
    - type: recall_at_100
      value: 38.389
    - type: recall_at_1000
      value: 66.424
    - type: recall_at_3
      value: 11.851
    - type: recall_at_5
      value: 14.424000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.055
    - type: map_at_10
      value: 24.271
    - type: map_at_100
      value: 25.418000000000003
    - type: map_at_1000
      value: 25.554
    - type: map_at_3
      value: 22.067
    - type: map_at_5
      value: 23.274
    - type: mrr_at_1
      value: 22.137
    - type: mrr_at_10
      value: 28.671000000000003
    - type: mrr_at_100
      value: 29.604000000000003
    - type: mrr_at_1000
      value: 29.68
    - type: mrr_at_3
      value: 26.372
    - type: mrr_at_5
      value: 27.766999999999996
    - type: ndcg_at_1
      value: 22.137
    - type: ndcg_at_10
      value: 28.687
    - type: ndcg_at_100
      value: 34.309
    - type: ndcg_at_1000
      value: 37.316
    - type: ndcg_at_3
      value: 24.761
    - type: ndcg_at_5
      value: 26.598
    - type: precision_at_1
      value: 22.137
    - type: precision_at_10
      value: 5.3420000000000005
    - type: precision_at_100
      value: 0.9740000000000001
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.677999999999999
    - type: precision_at_5
      value: 8.527
    - type: recall_at_1
      value: 18.055
    - type: recall_at_10
      value: 37.701
    - type: recall_at_100
      value: 62.661
    - type: recall_at_1000
      value: 83.37299999999999
    - type: recall_at_3
      value: 26.491999999999997
    - type: recall_at_5
      value: 31.366
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.889999999999999
    - type: map_at_10
      value: 19.337
    - type: map_at_100
      value: 20.389
    - type: map_at_1000
      value: 20.53
    - type: map_at_3
      value: 17.404
    - type: map_at_5
      value: 18.356
    - type: mrr_at_1
      value: 17.122999999999998
    - type: mrr_at_10
      value: 22.951
    - type: mrr_at_100
      value: 23.919999999999998
    - type: mrr_at_1000
      value: 24.01
    - type: mrr_at_3
      value: 21.081
    - type: mrr_at_5
      value: 22.102
    - type: ndcg_at_1
      value: 17.122999999999998
    - type: ndcg_at_10
      value: 23.16
    - type: ndcg_at_100
      value: 28.337
    - type: ndcg_at_1000
      value: 31.808999999999997
    - type: ndcg_at_3
      value: 19.649
    - type: ndcg_at_5
      value: 21.047
    - type: precision_at_1
      value: 17.122999999999998
    - type: precision_at_10
      value: 4.406000000000001
    - type: precision_at_100
      value: 0.831
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 9.361
    - type: precision_at_5
      value: 6.804
    - type: recall_at_1
      value: 13.889999999999999
    - type: recall_at_10
      value: 31.162
    - type: recall_at_100
      value: 53.862
    - type: recall_at_1000
      value: 78.668
    - type: recall_at_3
      value: 21.276999999999997
    - type: recall_at_5
      value: 24.945999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.876916666666668
    - type: map_at_10
      value: 20.335916666666666
    - type: map_at_100
      value: 21.264833333333335
    - type: map_at_1000
      value: 21.392083333333332
    - type: map_at_3
      value: 18.571416666666668
    - type: map_at_5
      value: 19.552416666666666
    - type: mrr_at_1
      value: 17.9935
    - type: mrr_at_10
      value: 23.497000000000003
    - type: mrr_at_100
      value: 24.318666666666665
    - type: mrr_at_1000
      value: 24.404583333333328
    - type: mrr_at_3
      value: 21.74641666666667
    - type: mrr_at_5
      value: 22.727416666666667
    - type: ndcg_at_1
      value: 17.9935
    - type: ndcg_at_10
      value: 23.92941666666667
    - type: ndcg_at_100
      value: 28.531999999999996
    - type: ndcg_at_1000
      value: 31.72616666666667
    - type: ndcg_at_3
      value: 20.738083333333332
    - type: ndcg_at_5
      value: 22.215416666666666
    - type: precision_at_1
      value: 17.9935
    - type: precision_at_10
      value: 4.256916666666667
    - type: precision_at_100
      value: 0.7820833333333335
    - type: precision_at_1000
      value: 0.12375000000000003
    - type: precision_at_3
      value: 9.594916666666666
    - type: precision_at_5
      value: 6.911333333333333
    - type: recall_at_1
      value: 14.876916666666668
    - type: recall_at_10
      value: 31.664250000000006
    - type: recall_at_100
      value: 52.60891666666667
    - type: recall_at_1000
      value: 75.82383333333334
    - type: recall_at_3
      value: 22.649833333333333
    - type: recall_at_5
      value: 26.4515
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.74
    - type: map_at_10
      value: 15.364
    - type: map_at_100
      value: 16.066
    - type: map_at_1000
      value: 16.147
    - type: map_at_3
      value: 13.871
    - type: map_at_5
      value: 14.724
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.657
    - type: mrr_at_100
      value: 18.299000000000003
    - type: mrr_at_1000
      value: 18.369
    - type: mrr_at_3
      value: 16.104
    - type: mrr_at_5
      value: 16.986
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.429000000000002
    - type: ndcg_at_100
      value: 22.144
    - type: ndcg_at_1000
      value: 24.647
    - type: ndcg_at_3
      value: 15.542
    - type: ndcg_at_5
      value: 16.929
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.19
    - type: precision_at_100
      value: 0.5579999999999999
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 7.156999999999999
    - type: precision_at_5
      value: 5.215
    - type: recall_at_1
      value: 10.74
    - type: recall_at_10
      value: 25.762
    - type: recall_at_100
      value: 43.132999999999996
    - type: recall_at_1000
      value: 62.26199999999999
    - type: recall_at_3
      value: 17.629
    - type: recall_at_5
      value: 21.125
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.707
    - type: map_at_10
      value: 11.26
    - type: map_at_100
      value: 11.918
    - type: map_at_1000
      value: 12.043
    - type: map_at_3
      value: 10.169
    - type: map_at_5
      value: 10.817
    - type: mrr_at_1
      value: 9.429
    - type: mrr_at_10
      value: 13.5
    - type: mrr_at_100
      value: 14.177999999999999
    - type: mrr_at_1000
      value: 14.280000000000001
    - type: mrr_at_3
      value: 12.273
    - type: mrr_at_5
      value: 13.048000000000002
    - type: ndcg_at_1
      value: 9.429
    - type: ndcg_at_10
      value: 13.697999999999999
    - type: ndcg_at_100
      value: 17.427
    - type: ndcg_at_1000
      value: 21.013
    - type: ndcg_at_3
      value: 11.639
    - type: ndcg_at_5
      value: 12.705
    - type: precision_at_1
      value: 9.429
    - type: precision_at_10
      value: 2.546
    - type: precision_at_100
      value: 0.534
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 5.666
    - type: precision_at_5
      value: 4.212
    - type: recall_at_1
      value: 7.707
    - type: recall_at_10
      value: 18.901
    - type: recall_at_100
      value: 36.38
    - type: recall_at_1000
      value: 63.017999999999994
    - type: recall_at_3
      value: 13.123999999999999
    - type: recall_at_5
      value: 15.834000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.034
    - type: map_at_10
      value: 17.943
    - type: map_at_100
      value: 18.787000000000003
    - type: map_at_1000
      value: 18.907
    - type: map_at_3
      value: 16.508
    - type: map_at_5
      value: 17.267
    - type: mrr_at_1
      value: 15.485
    - type: mrr_at_10
      value: 20.801
    - type: mrr_at_100
      value: 21.632
    - type: mrr_at_1000
      value: 21.731
    - type: mrr_at_3
      value: 19.279
    - type: mrr_at_5
      value: 20.09
    - type: ndcg_at_1
      value: 15.485
    - type: ndcg_at_10
      value: 21.301000000000002
    - type: ndcg_at_100
      value: 25.606
    - type: ndcg_at_1000
      value: 29.109
    - type: ndcg_at_3
      value: 18.451999999999998
    - type: ndcg_at_5
      value: 19.685
    - type: precision_at_1
      value: 15.485
    - type: precision_at_10
      value: 3.6470000000000002
    - type: precision_at_100
      value: 0.639
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 8.551
    - type: precision_at_5
      value: 5.989
    - type: recall_at_1
      value: 13.034
    - type: recall_at_10
      value: 28.909000000000002
    - type: recall_at_100
      value: 48.28
    - type: recall_at_1000
      value: 74.375
    - type: recall_at_3
      value: 20.871000000000002
    - type: recall_at_5
      value: 24.066000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.667
    - type: map_at_10
      value: 21.229
    - type: map_at_100
      value: 22.303
    - type: map_at_1000
      value: 22.512
    - type: map_at_3
      value: 19.527
    - type: map_at_5
      value: 20.415
    - type: mrr_at_1
      value: 18.379
    - type: mrr_at_10
      value: 24.829
    - type: mrr_at_100
      value: 25.623
    - type: mrr_at_1000
      value: 25.712000000000003
    - type: mrr_at_3
      value: 23.09
    - type: mrr_at_5
      value: 23.979
    - type: ndcg_at_1
      value: 18.379
    - type: ndcg_at_10
      value: 25.462
    - type: ndcg_at_100
      value: 30.255
    - type: ndcg_at_1000
      value: 34.019
    - type: ndcg_at_3
      value: 22.567999999999998
    - type: ndcg_at_5
      value: 23.79
    - type: precision_at_1
      value: 18.379
    - type: precision_at_10
      value: 4.9799999999999995
    - type: precision_at_100
      value: 1.099
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 10.870000000000001
    - type: precision_at_5
      value: 7.866
    - type: recall_at_1
      value: 14.667
    - type: recall_at_10
      value: 33.550000000000004
    - type: recall_at_100
      value: 56.123999999999995
    - type: recall_at_1000
      value: 81.883
    - type: recall_at_3
      value: 24.944
    - type: recall_at_5
      value: 28.055000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.212
    - type: map_at_10
      value: 16.339000000000002
    - type: map_at_100
      value: 17.154
    - type: map_at_1000
      value: 17.268
    - type: map_at_3
      value: 15.0
    - type: map_at_5
      value: 15.744
    - type: mrr_at_1
      value: 13.863
    - type: mrr_at_10
      value: 18.055
    - type: mrr_at_100
      value: 18.892
    - type: mrr_at_1000
      value: 18.992
    - type: mrr_at_3
      value: 16.636
    - type: mrr_at_5
      value: 17.44
    - type: ndcg_at_1
      value: 13.863
    - type: ndcg_at_10
      value: 18.965
    - type: ndcg_at_100
      value: 23.289
    - type: ndcg_at_1000
      value: 26.672
    - type: ndcg_at_3
      value: 16.264
    - type: ndcg_at_5
      value: 17.541
    - type: precision_at_1
      value: 13.863
    - type: precision_at_10
      value: 2.939
    - type: precision_at_100
      value: 0.545
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.901
    - type: precision_at_5
      value: 4.806
    - type: recall_at_1
      value: 12.212
    - type: recall_at_10
      value: 25.557999999999996
    - type: recall_at_100
      value: 45.884
    - type: recall_at_1000
      value: 71.841
    - type: recall_at_3
      value: 18.281
    - type: recall_at_5
      value: 21.368000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.991
    - type: map_at_10
      value: 11.031
    - type: map_at_100
      value: 12.415
    - type: map_at_1000
      value: 12.601999999999999
    - type: map_at_3
      value: 8.752
    - type: map_at_5
      value: 9.873999999999999
    - type: mrr_at_1
      value: 13.355
    - type: mrr_at_10
      value: 22.002
    - type: mrr_at_100
      value: 23.146
    - type: mrr_at_1000
      value: 23.218
    - type: mrr_at_3
      value: 18.719
    - type: mrr_at_5
      value: 20.543
    - type: ndcg_at_1
      value: 13.355
    - type: ndcg_at_10
      value: 16.711000000000002
    - type: ndcg_at_100
      value: 23.073
    - type: ndcg_at_1000
      value: 27.108999999999998
    - type: ndcg_at_3
      value: 12.289
    - type: ndcg_at_5
      value: 13.943
    - type: precision_at_1
      value: 13.355
    - type: precision_at_10
      value: 5.648000000000001
    - type: precision_at_100
      value: 1.248
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 9.359
    - type: precision_at_5
      value: 7.739
    - type: recall_at_1
      value: 5.991
    - type: recall_at_10
      value: 21.898
    - type: recall_at_100
      value: 44.324000000000005
    - type: recall_at_1000
      value: 67.777
    - type: recall_at_3
      value: 11.527
    - type: recall_at_5
      value: 15.61
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.125
    - type: map_at_10
      value: 9.629999999999999
    - type: map_at_100
      value: 13.306000000000001
    - type: map_at_1000
      value: 14.26
    - type: map_at_3
      value: 6.894
    - type: map_at_5
      value: 8.19
    - type: mrr_at_1
      value: 39.25
    - type: mrr_at_10
      value: 49.495
    - type: mrr_at_100
      value: 50.139
    - type: mrr_at_1000
      value: 50.169
    - type: mrr_at_3
      value: 46.333
    - type: mrr_at_5
      value: 48.008
    - type: ndcg_at_1
      value: 28.499999999999996
    - type: ndcg_at_10
      value: 23.794
    - type: ndcg_at_100
      value: 26.632
    - type: ndcg_at_1000
      value: 33.382
    - type: ndcg_at_3
      value: 26.282
    - type: ndcg_at_5
      value: 25.113000000000003
    - type: precision_at_1
      value: 39.25
    - type: precision_at_10
      value: 21.075
    - type: precision_at_100
      value: 6.607
    - type: precision_at_1000
      value: 1.366
    - type: precision_at_3
      value: 31.667
    - type: precision_at_5
      value: 27.150000000000002
    - type: recall_at_1
      value: 4.125
    - type: recall_at_10
      value: 14.603
    - type: recall_at_100
      value: 32.888
    - type: recall_at_1000
      value: 55.901
    - type: recall_at_3
      value: 8.396
    - type: recall_at_5
      value: 10.902000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.39999999999999
    - type: f1
      value: 41.19798638036962
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 15.998999999999999
    - type: map_at_10
      value: 24.037
    - type: map_at_100
      value: 24.979000000000003
    - type: map_at_1000
      value: 25.052000000000003
    - type: map_at_3
      value: 21.537
    - type: map_at_5
      value: 22.926
    - type: mrr_at_1
      value: 17.072000000000003
    - type: mrr_at_10
      value: 25.526
    - type: mrr_at_100
      value: 26.464
    - type: mrr_at_1000
      value: 26.528000000000002
    - type: mrr_at_3
      value: 22.922
    - type: mrr_at_5
      value: 24.391
    - type: ndcg_at_1
      value: 17.072000000000003
    - type: ndcg_at_10
      value: 28.933999999999997
    - type: ndcg_at_100
      value: 33.812999999999995
    - type: ndcg_at_1000
      value: 35.874
    - type: ndcg_at_3
      value: 23.746000000000002
    - type: ndcg_at_5
      value: 26.264
    - type: precision_at_1
      value: 17.072000000000003
    - type: precision_at_10
      value: 4.6739999999999995
    - type: precision_at_100
      value: 0.732
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 10.326
    - type: precision_at_5
      value: 7.531000000000001
    - type: recall_at_1
      value: 15.998999999999999
    - type: recall_at_10
      value: 42.888999999999996
    - type: recall_at_100
      value: 65.864
    - type: recall_at_1000
      value: 81.872
    - type: recall_at_3
      value: 28.735
    - type: recall_at_5
      value: 34.817
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.0889999999999995
    - type: map_at_10
      value: 11.533
    - type: map_at_100
      value: 12.626999999999999
    - type: map_at_1000
      value: 12.831000000000001
    - type: map_at_3
      value: 9.524000000000001
    - type: map_at_5
      value: 10.484
    - type: mrr_at_1
      value: 13.889000000000001
    - type: mrr_at_10
      value: 20.035
    - type: mrr_at_100
      value: 21.041999999999998
    - type: mrr_at_1000
      value: 21.142
    - type: mrr_at_3
      value: 17.695
    - type: mrr_at_5
      value: 18.83
    - type: ndcg_at_1
      value: 13.889000000000001
    - type: ndcg_at_10
      value: 16.122
    - type: ndcg_at_100
      value: 21.485000000000003
    - type: ndcg_at_1000
      value: 26.101999999999997
    - type: ndcg_at_3
      value: 12.967999999999998
    - type: ndcg_at_5
      value: 13.975000000000001
    - type: precision_at_1
      value: 13.889000000000001
    - type: precision_at_10
      value: 4.769
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 8.693
    - type: precision_at_5
      value: 6.79
    - type: recall_at_1
      value: 7.0889999999999995
    - type: recall_at_10
      value: 21.163999999999998
    - type: recall_at_100
      value: 42.247
    - type: recall_at_1000
      value: 71.395
    - type: recall_at_3
      value: 11.694
    - type: recall_at_5
      value: 15.051
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 17.752000000000002
    - type: map_at_10
      value: 25.064999999999998
    - type: map_at_100
      value: 26.003999999999998
    - type: map_at_1000
      value: 26.116
    - type: map_at_3
      value: 23.064
    - type: map_at_5
      value: 24.149
    - type: mrr_at_1
      value: 35.503
    - type: mrr_at_10
      value: 42.649
    - type: mrr_at_100
      value: 43.389
    - type: mrr_at_1000
      value: 43.445
    - type: mrr_at_3
      value: 40.699999999999996
    - type: mrr_at_5
      value: 41.817
    - type: ndcg_at_1
      value: 35.503
    - type: ndcg_at_10
      value: 31.968000000000004
    - type: ndcg_at_100
      value: 36.257
    - type: ndcg_at_1000
      value: 38.928000000000004
    - type: ndcg_at_3
      value: 28.176000000000002
    - type: ndcg_at_5
      value: 29.994
    - type: precision_at_1
      value: 35.503
    - type: precision_at_10
      value: 7.0440000000000005
    - type: precision_at_100
      value: 1.046
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_3
      value: 17.763
    - type: precision_at_5
      value: 12.1
    - type: recall_at_1
      value: 17.752000000000002
    - type: recall_at_10
      value: 35.219
    - type: recall_at_100
      value: 52.309000000000005
    - type: recall_at_1000
      value: 70.162
    - type: recall_at_3
      value: 26.644000000000002
    - type: recall_at_5
      value: 30.25
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.9016
    - type: ap
      value: 59.11956601013746
    - type: f1
      value: 63.68974251662037
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.561999999999999
    - type: map_at_10
      value: 11.378
    - type: map_at_100
      value: 12.258
    - type: map_at_1000
      value: 12.361
    - type: map_at_3
      value: 9.577
    - type: map_at_5
      value: 10.525
    - type: mrr_at_1
      value: 6.762
    - type: mrr_at_10
      value: 11.674
    - type: mrr_at_100
      value: 12.554000000000002
    - type: mrr_at_1000
      value: 12.654000000000002
    - type: mrr_at_3
      value: 9.833
    - type: mrr_at_5
      value: 10.806000000000001
    - type: ndcg_at_1
      value: 6.734
    - type: ndcg_at_10
      value: 14.459
    - type: ndcg_at_100
      value: 19.317999999999998
    - type: ndcg_at_1000
      value: 22.407
    - type: ndcg_at_3
      value: 10.666
    - type: ndcg_at_5
      value: 12.393
    - type: precision_at_1
      value: 6.734
    - type: precision_at_10
      value: 2.5069999999999997
    - type: precision_at_100
      value: 0.505
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.6850000000000005
    - type: precision_at_5
      value: 3.682
    - type: recall_at_1
      value: 6.561999999999999
    - type: recall_at_10
      value: 24.07
    - type: recall_at_100
      value: 47.856
    - type: recall_at_1000
      value: 72.654
    - type: recall_at_3
      value: 13.584
    - type: recall_at_5
      value: 17.76
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.86000911992703
    - type: f1
      value: 87.98975696911226
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 58.38349293205655
    - type: f1
      value: 40.01779036138312
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.852723604572965
    - type: f1
      value: 60.13917532573332
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.14727639542704
    - type: f1
      value: 66.7653952309667
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.504423289782554
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.331311574764182
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.79405962065405
    - type: mrr
      value: 30.80981570313803
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.8309999999999995
    - type: map_at_10
      value: 8.15
    - type: map_at_100
      value: 10.295
    - type: map_at_1000
      value: 11.649
    - type: map_at_3
      value: 6.088
    - type: map_at_5
      value: 7.138
    - type: mrr_at_1
      value: 33.745999999999995
    - type: mrr_at_10
      value: 43.422
    - type: mrr_at_100
      value: 44.193
    - type: mrr_at_1000
      value: 44.261
    - type: mrr_at_3
      value: 40.506
    - type: mrr_at_5
      value: 42.812
    - type: ndcg_at_1
      value: 31.579
    - type: ndcg_at_10
      value: 25.357000000000003
    - type: ndcg_at_100
      value: 23.597
    - type: ndcg_at_1000
      value: 33.143
    - type: ndcg_at_3
      value: 28.778
    - type: ndcg_at_5
      value: 27.92
    - type: precision_at_1
      value: 33.745999999999995
    - type: precision_at_10
      value: 18.854000000000003
    - type: precision_at_100
      value: 6.464
    - type: precision_at_1000
      value: 1.9900000000000002
    - type: precision_at_3
      value: 27.450999999999997
    - type: precision_at_5
      value: 24.52
    - type: recall_at_1
      value: 3.8309999999999995
    - type: recall_at_10
      value: 12.18
    - type: recall_at_100
      value: 25.258999999999997
    - type: recall_at_1000
      value: 59.059
    - type: recall_at_3
      value: 7.353
    - type: recall_at_5
      value: 9.777
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.132
    - type: map_at_10
      value: 15.934999999999999
    - type: map_at_100
      value: 17.168
    - type: map_at_1000
      value: 17.266000000000002
    - type: map_at_3
      value: 13.296
    - type: map_at_5
      value: 14.713000000000001
    - type: mrr_at_1
      value: 10.342
    - type: mrr_at_10
      value: 17.535
    - type: mrr_at_100
      value: 18.689
    - type: mrr_at_1000
      value: 18.77
    - type: mrr_at_3
      value: 14.846
    - type: mrr_at_5
      value: 16.337
    - type: ndcg_at_1
      value: 10.342
    - type: ndcg_at_10
      value: 20.409
    - type: ndcg_at_100
      value: 26.672
    - type: ndcg_at_1000
      value: 29.321
    - type: ndcg_at_3
      value: 14.982000000000001
    - type: ndcg_at_5
      value: 17.522
    - type: precision_at_1
      value: 10.342
    - type: precision_at_10
      value: 3.8440000000000003
    - type: precision_at_100
      value: 0.741
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 7.0489999999999995
    - type: precision_at_5
      value: 5.632000000000001
    - type: recall_at_1
      value: 9.132
    - type: recall_at_10
      value: 32.800000000000004
    - type: recall_at_100
      value: 61.895999999999994
    - type: recall_at_1000
      value: 82.146
    - type: recall_at_3
      value: 18.342
    - type: recall_at_5
      value: 24.242
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 64.005
    - type: map_at_10
      value: 76.709
    - type: map_at_100
      value: 77.464
    - type: map_at_1000
      value: 77.498
    - type: map_at_3
      value: 73.75699999999999
    - type: map_at_5
      value: 75.553
    - type: mrr_at_1
      value: 73.81
    - type: mrr_at_10
      value: 81.006
    - type: mrr_at_100
      value: 81.23599999999999
    - type: mrr_at_1000
      value: 81.241
    - type: mrr_at_3
      value: 79.56800000000001
    - type: mrr_at_5
      value: 80.50399999999999
    - type: ndcg_at_1
      value: 73.85000000000001
    - type: ndcg_at_10
      value: 81.33399999999999
    - type: ndcg_at_100
      value: 83.378
    - type: ndcg_at_1000
      value: 83.726
    - type: ndcg_at_3
      value: 77.791
    - type: ndcg_at_5
      value: 79.636
    - type: precision_at_1
      value: 73.85000000000001
    - type: precision_at_10
      value: 12.262
    - type: precision_at_100
      value: 1.461
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.672999999999995
    - type: precision_at_5
      value: 22.253999999999998
    - type: recall_at_1
      value: 64.005
    - type: recall_at_10
      value: 90.137
    - type: recall_at_100
      value: 97.77799999999999
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_3
      value: 79.972
    - type: recall_at_5
      value: 85.10799999999999
    - type: map_at_1
      value: 3.008
    - type: map_at_10
      value: 7.086
    - type: map_at_100
      value: 8.498
    - type: map_at_1000
      value: 8.744
    - type: map_at_3
      value: 5.2330000000000005
    - type: map_at_5
      value: 6.188
    - type: mrr_at_1
      value: 14.799999999999999
    - type: mrr_at_10
      value: 22.731
    - type: mrr_at_100
      value: 23.963
    - type: mrr_at_1000
      value: 24.046
    - type: mrr_at_3
      value: 19.950000000000003
    - type: mrr_at_5
      value: 21.38
    - type: ndcg_at_1
      value: 14.799999999999999
    - type: ndcg_at_10
      value: 12.581999999999999
    - type: ndcg_at_100
      value: 19.024
    - type: ndcg_at_1000
      value: 24.075
    - type: ndcg_at_3
      value: 11.937000000000001
    - type: ndcg_at_5
      value: 10.427
    - type: precision_at_1
      value: 14.799999999999999
    - type: precision_at_10
      value: 6.5
    - type: precision_at_100
      value: 1.591
    - type: precision_at_1000
      value: 0.281
    - type: precision_at_3
      value: 11.1
    - type: precision_at_5
      value: 9.120000000000001
    - type: recall_at_1
      value: 3.008
    - type: recall_at_10
      value: 13.197000000000001
    - type: recall_at_100
      value: 32.323
    - type: recall_at_1000
      value: 57.172999999999995
    - type: recall_at_3
      value: 6.753000000000001
    - type: recall_at_5
      value: 9.248000000000001
    - type: map_at_1
      value: 0.129
    - type: map_at_10
      value: 0.717
    - type: map_at_100
      value: 3.6580000000000004
    - type: map_at_1000
      value: 9.374
    - type: map_at_3
      value: 0.302
    - type: map_at_5
      value: 0.422
    - type: mrr_at_1
      value: 56.00000000000001
    - type: mrr_at_10
      value: 67.475
    - type: mrr_at_100
      value: 68.018
    - type: mrr_at_1000
      value: 68.035
    - type: mrr_at_3
      value: 65.667
    - type: mrr_at_5
      value: 66.567
    - type: ndcg_at_1
      value: 50.0
    - type: ndcg_at_10
      value: 40.910999999999994
    - type: ndcg_at_100
      value: 30.386999999999997
    - type: ndcg_at_1000
      value: 27.009
    - type: ndcg_at_3
      value: 46.776
    - type: ndcg_at_5
      value: 42.504
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 43.6
    - type: precision_at_100
      value: 31.64
    - type: precision_at_1000
      value: 13.214
    - type: precision_at_3
      value: 50.0
    - type: precision_at_5
      value: 44.800000000000004
    - type: recall_at_1
      value: 0.129
    - type: recall_at_10
      value: 0.95
    - type: recall_at_100
      value: 6.526999999999999
    - type: recall_at_1000
      value: 25.894000000000002
    - type: recall_at_3
      value: 0.34299999999999997
    - type: recall_at_5
      value: 0.49899999999999994
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.423003368001304
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 47.05364643191673
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.82474380833001
    - type: cos_sim_spearman
      value: 66.06084939474535
    - type: euclidean_pearson
      value: 71.1524270169037
    - type: euclidean_spearman
      value: 66.06095698159474
    - type: manhattan_pearson
      value: 68.79401530108056
    - type: manhattan_spearman
      value: 64.55149376982865
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.40557358335994
    - type: cos_sim_spearman
      value: 67.61862451971042
    - type: euclidean_pearson
      value: 70.41404072782692
    - type: euclidean_spearman
      value: 67.6198686410611
    - type: manhattan_pearson
      value: 68.97879579551457
    - type: manhattan_spearman
      value: 67.2295683767691
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.0503994579303
    - type: cos_sim_spearman
      value: 79.15391592614903
    - type: euclidean_pearson
      value: 78.84085468610613
    - type: euclidean_spearman
      value: 79.15395372943995
    - type: manhattan_pearson
      value: 78.64185478146945
    - type: manhattan_spearman
      value: 79.14714263528944
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.3615928485999
    - type: cos_sim_spearman
      value: 74.97382110132605
    - type: euclidean_pearson
      value: 77.23854527060215
    - type: euclidean_spearman
      value: 74.97381140978526
    - type: manhattan_pearson
      value: 76.07931709400336
    - type: manhattan_spearman
      value: 74.24120638811475
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.20257664300357
    - type: cos_sim_spearman
      value: 82.00047913551732
    - type: euclidean_pearson
      value: 81.9647778954467
    - type: euclidean_spearman
      value: 82.0004776230638
    - type: manhattan_pearson
      value: 81.71577106207948
    - type: manhattan_spearman
      value: 81.99682550355493
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.25724348036597
    - type: cos_sim_spearman
      value: 77.44730180182509
    - type: euclidean_pearson
      value: 77.07257885830403
    - type: euclidean_spearman
      value: 77.44757329765216
    - type: manhattan_pearson
      value: 77.56516524638705
    - type: manhattan_spearman
      value: 77.96306993156203
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.12218819562516
    - type: cos_sim_spearman
      value: 85.1670421446071
    - type: euclidean_pearson
      value: 84.780712654921
    - type: euclidean_spearman
      value: 85.16791563947264
    - type: manhattan_pearson
      value: 84.55044493571614
    - type: manhattan_spearman
      value: 85.27489322017652
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.36228072576271
    - type: cos_sim_spearman
      value: 60.8804162279283
    - type: euclidean_pearson
      value: 63.45076147869696
    - type: euclidean_spearman
      value: 60.8804162279283
    - type: manhattan_pearson
      value: 62.75925080903245
    - type: manhattan_spearman
      value: 60.42286149492114
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.42867098481462
    - type: cos_sim_spearman
      value: 77.27498110374914
    - type: euclidean_pearson
      value: 78.31189930366395
    - type: euclidean_spearman
      value: 77.27499957014132
    - type: manhattan_pearson
      value: 77.5492342797482
    - type: manhattan_spearman
      value: 76.70759132287284
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.88088283802969
    - type: mrr
      value: 91.2407327603406
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 34.75
    - type: map_at_10
      value: 43.795
    - type: map_at_100
      value: 44.897999999999996
    - type: map_at_1000
      value: 44.964999999999996
    - type: map_at_3
      value: 41.235
    - type: map_at_5
      value: 42.785000000000004
    - type: mrr_at_1
      value: 37.0
    - type: mrr_at_10
      value: 45.608
    - type: mrr_at_100
      value: 46.556999999999995
    - type: mrr_at_1000
      value: 46.62
    - type: mrr_at_3
      value: 43.333
    - type: mrr_at_5
      value: 44.733000000000004
    - type: ndcg_at_1
      value: 37.0
    - type: ndcg_at_10
      value: 48.620000000000005
    - type: ndcg_at_100
      value: 53.772
    - type: ndcg_at_1000
      value: 55.403999999999996
    - type: ndcg_at_3
      value: 43.741
    - type: ndcg_at_5
      value: 46.358
    - type: precision_at_1
      value: 37.0
    - type: precision_at_10
      value: 6.800000000000001
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 17.666999999999998
    - type: precision_at_5
      value: 12.0
    - type: recall_at_1
      value: 34.75
    - type: recall_at_10
      value: 61.87200000000001
    - type: recall_at_100
      value: 85.317
    - type: recall_at_1000
      value: 97.8
    - type: recall_at_3
      value: 48.567
    - type: recall_at_5
      value: 55.233
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.71485148514851
    - type: cos_sim_ap
      value: 91.89197853928673
    - type: cos_sim_f1
      value: 85.48387096774194
    - type: cos_sim_precision
      value: 86.1788617886179
    - type: cos_sim_recall
      value: 84.8
    - type: dot_accuracy
      value: 99.71485148514851
    - type: dot_ap
      value: 91.89197853928673
    - type: dot_f1
      value: 85.48387096774194
    - type: dot_precision
      value: 86.1788617886179
    - type: dot_recall
      value: 84.8
    - type: euclidean_accuracy
      value: 99.71485148514851
    - type: euclidean_ap
      value: 91.89197853928673
    - type: euclidean_f1
      value: 85.48387096774194
    - type: euclidean_precision
      value: 86.1788617886179
    - type: euclidean_recall
      value: 84.8
    - type: manhattan_accuracy
      value: 99.76633663366337
    - type: manhattan_ap
      value: 93.70793412033116
    - type: manhattan_f1
      value: 87.77050830397583
    - type: manhattan_precision
      value: 88.34853090172238
    - type: manhattan_recall
      value: 87.2
    - type: max_accuracy
      value: 99.76633663366337
    - type: max_ap
      value: 93.70793412033116
    - type: max_f1
      value: 87.77050830397583
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 42.040101504017464
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.736735784987
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.30708664346592
    - type: mrr
      value: 43.91143578643579
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.57246866942087
    - type: cos_sim_spearman
      value: 30.69719029010722
    - type: dot_pearson
      value: 30.572468627823802
    - type: dot_spearman
      value: 30.675070232612644
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.8429999999999997
    - type: map_at_10
      value: 8.476
    - type: map_at_100
      value: 14.779
    - type: map_at_1000
      value: 16.381
    - type: map_at_3
      value: 4.361000000000001
    - type: map_at_5
      value: 6.064
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 44.039
    - type: mrr_at_100
      value: 45.024
    - type: mrr_at_1000
      value: 45.024
    - type: mrr_at_3
      value: 41.156
    - type: mrr_at_5
      value: 42.075
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 22.672
    - type: ndcg_at_100
      value: 35.961999999999996
    - type: ndcg_at_1000
      value: 47.365
    - type: ndcg_at_3
      value: 26.016000000000002
    - type: ndcg_at_5
      value: 23.794999999999998
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 20.816000000000003
    - type: precision_at_100
      value: 8.245
    - type: precision_at_1000
      value: 1.555
    - type: precision_at_3
      value: 27.891
    - type: precision_at_5
      value: 24.082
    - type: recall_at_1
      value: 1.8429999999999997
    - type: recall_at_10
      value: 14.37
    - type: recall_at_100
      value: 49.120999999999995
    - type: recall_at_1000
      value: 83.98400000000001
    - type: recall_at_3
      value: 5.641
    - type: recall_at_5
      value: 8.321000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.1968
    - type: ap
      value: 14.44161573930493
    - type: f1
      value: 54.83573235336061
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 50.94510469722694
    - type: f1
      value: 51.12605321866063
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 37.53693681679847
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.60851165285807
    - type: cos_sim_ap
      value: 65.18156857786212
    - type: cos_sim_f1
      value: 62.61223512510475
    - type: cos_sim_precision
      value: 57.30878807801885
    - type: cos_sim_recall
      value: 68.99736147757255
    - type: dot_accuracy
      value: 83.60851165285807
    - type: dot_ap
      value: 65.18156857786212
    - type: dot_f1
      value: 62.61223512510475
    - type: dot_precision
      value: 57.30878807801885
    - type: dot_recall
      value: 68.99736147757255
    - type: euclidean_accuracy
      value: 83.60851165285807
    - type: euclidean_ap
      value: 65.18156857786212
    - type: euclidean_f1
      value: 62.61223512510475
    - type: euclidean_precision
      value: 57.30878807801885
    - type: euclidean_recall
      value: 68.99736147757255
    - type: manhattan_accuracy
      value: 82.49389044525243
    - type: manhattan_ap
      value: 62.03288965473206
    - type: manhattan_f1
      value: 59.25074695472304
    - type: manhattan_precision
      value: 52.483713355048856
    - type: manhattan_recall
      value: 68.02110817941951
    - type: max_accuracy
      value: 83.60851165285807
    - type: max_ap
      value: 65.18156857786212
    - type: max_f1
      value: 62.61223512510475
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.60235960724958
    - type: cos_sim_ap
      value: 83.31122009321201
    - type: cos_sim_f1
      value: 75.5953714072415
    - type: cos_sim_precision
      value: 73.36617881466454
    - type: cos_sim_recall
      value: 77.96427471512165
    - type: dot_accuracy
      value: 87.60235960724958
    - type: dot_ap
      value: 83.31122039383348
    - type: dot_f1
      value: 75.5953714072415
    - type: dot_precision
      value: 73.36617881466454
    - type: dot_recall
      value: 77.96427471512165
    - type: euclidean_accuracy
      value: 87.60235960724958
    - type: euclidean_ap
      value: 83.31123735759617
    - type: euclidean_f1
      value: 75.5953714072415
    - type: euclidean_precision
      value: 73.36617881466454
    - type: euclidean_recall
      value: 77.96427471512165
    - type: manhattan_accuracy
      value: 87.58295494236815
    - type: manhattan_ap
      value: 83.15022211312501
    - type: manhattan_f1
      value: 75.28497215681878
    - type: manhattan_precision
      value: 73.14982932674849
    - type: manhattan_recall
      value: 77.54850631352016
    - type: max_accuracy
      value: 87.60235960724958
    - type: max_ap
      value: 83.31123735759617
    - type: max_f1
      value: 75.5953714072415
---
