mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_307_w75k_b10k
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.71641791044776
    - type: ap
      value: 33.83144952728368
    - type: f1
      value: 65.42257056593405
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.614075
    - type: ap
      value: 59.729707124101274
    - type: f1
      value: 64.38848477168871
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.842
    - type: f1
      value: 33.39663457981403
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.986
    - type: map_at_10
      value: 34.064
    - type: map_at_100
      value: 35.275
    - type: map_at_1000
      value: 35.303000000000004
    - type: map_at_3
      value: 29.610999999999997
    - type: map_at_5
      value: 32.104
    - type: mrr_at_1
      value: 20.413
    - type: mrr_at_10
      value: 34.205000000000005
    - type: mrr_at_100
      value: 35.429
    - type: mrr_at_1000
      value: 35.457
    - type: mrr_at_3
      value: 29.813000000000002
    - type: mrr_at_5
      value: 32.245000000000005
    - type: ndcg_at_1
      value: 19.986
    - type: ndcg_at_10
      value: 42.03
    - type: ndcg_at_100
      value: 47.709
    - type: ndcg_at_1000
      value: 48.372
    - type: ndcg_at_3
      value: 32.815
    - type: ndcg_at_5
      value: 37.287
    - type: precision_at_1
      value: 19.986
    - type: precision_at_10
      value: 6.757000000000001
    - type: precision_at_100
      value: 0.936
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.035
    - type: precision_at_5
      value: 10.583
    - type: recall_at_1
      value: 19.986
    - type: recall_at_10
      value: 67.568
    - type: recall_at_100
      value: 93.599
    - type: recall_at_1000
      value: 98.649
    - type: recall_at_3
      value: 42.105
    - type: recall_at_5
      value: 52.916
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 32.3683689352825
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 22.612199003814784
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.783575323019186
    - type: mrr
      value: 66.44813788858109
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.91542000311537
    - type: cos_sim_spearman
      value: 76.96982609885886
    - type: euclidean_pearson
      value: 78.2167413496553
    - type: euclidean_spearman
      value: 76.96982609885886
    - type: manhattan_pearson
      value: 78.37464609362752
    - type: manhattan_spearman
      value: 77.44875267417638
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.1948051948052
    - type: f1
      value: 71.36111601799189
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.50999941209323
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 21.012511459928128
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.223
    - type: map_at_10
      value: 28.166000000000004
    - type: map_at_100
      value: 29.25
    - type: map_at_1000
      value: 29.408
    - type: map_at_3
      value: 26.027
    - type: map_at_5
      value: 27.211999999999996
    - type: mrr_at_1
      value: 26.753
    - type: mrr_at_10
      value: 33.852
    - type: mrr_at_100
      value: 34.726
    - type: mrr_at_1000
      value: 34.806
    - type: mrr_at_3
      value: 32.046
    - type: mrr_at_5
      value: 33.112
    - type: ndcg_at_1
      value: 26.753
    - type: ndcg_at_10
      value: 32.75
    - type: ndcg_at_100
      value: 37.772
    - type: ndcg_at_1000
      value: 41.116
    - type: ndcg_at_3
      value: 29.865000000000002
    - type: ndcg_at_5
      value: 31.023
    - type: precision_at_1
      value: 26.753
    - type: precision_at_10
      value: 6.194999999999999
    - type: precision_at_100
      value: 1.089
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_3
      value: 14.449000000000002
    - type: precision_at_5
      value: 10.272
    - type: recall_at_1
      value: 21.223
    - type: recall_at_10
      value: 40.269
    - type: recall_at_100
      value: 62.9
    - type: recall_at_1000
      value: 85.92699999999999
    - type: recall_at_3
      value: 30.89
    - type: recall_at_5
      value: 34.756
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.796
    - type: map_at_10
      value: 21.91
    - type: map_at_100
      value: 22.802
    - type: map_at_1000
      value: 22.925
    - type: map_at_3
      value: 20.143
    - type: map_at_5
      value: 21.066
    - type: mrr_at_1
      value: 21.274
    - type: mrr_at_10
      value: 26.076
    - type: mrr_at_100
      value: 26.857999999999997
    - type: mrr_at_1000
      value: 26.932000000000002
    - type: mrr_at_3
      value: 24.257
    - type: mrr_at_5
      value: 25.145
    - type: ndcg_at_1
      value: 21.274
    - type: ndcg_at_10
      value: 25.428
    - type: ndcg_at_100
      value: 29.804000000000002
    - type: ndcg_at_1000
      value: 32.766
    - type: ndcg_at_3
      value: 22.434
    - type: ndcg_at_5
      value: 23.639
    - type: precision_at_1
      value: 21.274
    - type: precision_at_10
      value: 4.662
    - type: precision_at_100
      value: 0.859
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 10.552
    - type: precision_at_5
      value: 7.465
    - type: recall_at_1
      value: 16.796
    - type: recall_at_10
      value: 31.897
    - type: recall_at_100
      value: 51.413
    - type: recall_at_1000
      value: 71.885
    - type: recall_at_3
      value: 23.318
    - type: recall_at_5
      value: 26.636
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.834999999999997
    - type: map_at_10
      value: 32.919
    - type: map_at_100
      value: 34.035
    - type: map_at_1000
      value: 34.132
    - type: map_at_3
      value: 30.495
    - type: map_at_5
      value: 31.805
    - type: mrr_at_1
      value: 28.715000000000003
    - type: mrr_at_10
      value: 36.014
    - type: mrr_at_100
      value: 36.902
    - type: mrr_at_1000
      value: 36.964999999999996
    - type: mrr_at_3
      value: 33.71
    - type: mrr_at_5
      value: 34.935
    - type: ndcg_at_1
      value: 28.715000000000003
    - type: ndcg_at_10
      value: 37.524
    - type: ndcg_at_100
      value: 42.74
    - type: ndcg_at_1000
      value: 45.011
    - type: ndcg_at_3
      value: 32.927
    - type: ndcg_at_5
      value: 35.010000000000005
    - type: precision_at_1
      value: 28.715000000000003
    - type: precision_at_10
      value: 6.132
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 14.587
    - type: precision_at_5
      value: 10.169
    - type: recall_at_1
      value: 24.834999999999997
    - type: recall_at_10
      value: 48.5
    - type: recall_at_100
      value: 71.89
    - type: recall_at_1000
      value: 88.402
    - type: recall_at_3
      value: 36.052
    - type: recall_at_5
      value: 41.22
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.527000000000001
    - type: map_at_10
      value: 14.774000000000001
    - type: map_at_100
      value: 15.579
    - type: map_at_1000
      value: 15.689
    - type: map_at_3
      value: 13.481000000000002
    - type: map_at_5
      value: 14.212
    - type: mrr_at_1
      value: 11.638
    - type: mrr_at_10
      value: 15.895999999999999
    - type: mrr_at_100
      value: 16.717000000000002
    - type: mrr_at_1000
      value: 16.819
    - type: mrr_at_3
      value: 14.576
    - type: mrr_at_5
      value: 15.305
    - type: ndcg_at_1
      value: 11.638
    - type: ndcg_at_10
      value: 17.331
    - type: ndcg_at_100
      value: 21.675
    - type: ndcg_at_1000
      value: 25.127
    - type: ndcg_at_3
      value: 14.688
    - type: ndcg_at_5
      value: 15.963
    - type: precision_at_1
      value: 11.638
    - type: precision_at_10
      value: 2.7119999999999997
    - type: precision_at_100
      value: 0.52
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.29
    - type: precision_at_5
      value: 4.452
    - type: recall_at_1
      value: 10.527000000000001
    - type: recall_at_10
      value: 24.269
    - type: recall_at_100
      value: 44.942
    - type: recall_at_1000
      value: 72.14
    - type: recall_at_3
      value: 17.043
    - type: recall_at_5
      value: 20.113
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.859
    - type: map_at_10
      value: 9.765
    - type: map_at_100
      value: 10.458
    - type: map_at_1000
      value: 10.58
    - type: map_at_3
      value: 8.417
    - type: map_at_5
      value: 9.248000000000001
    - type: mrr_at_1
      value: 8.831
    - type: mrr_at_10
      value: 11.966000000000001
    - type: mrr_at_100
      value: 12.681999999999999
    - type: mrr_at_1000
      value: 12.783
    - type: mrr_at_3
      value: 10.406
    - type: mrr_at_5
      value: 11.302
    - type: ndcg_at_1
      value: 8.831
    - type: ndcg_at_10
      value: 12.094000000000001
    - type: ndcg_at_100
      value: 15.875
    - type: ndcg_at_1000
      value: 19.563
    - type: ndcg_at_3
      value: 9.442
    - type: ndcg_at_5
      value: 10.8
    - type: precision_at_1
      value: 8.831
    - type: precision_at_10
      value: 2.313
    - type: precision_at_100
      value: 0.49
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 4.353
    - type: precision_at_5
      value: 3.483
    - type: recall_at_1
      value: 6.859
    - type: recall_at_10
      value: 17.201
    - type: recall_at_100
      value: 34.441
    - type: recall_at_1000
      value: 62.007
    - type: recall_at_3
      value: 10.012
    - type: recall_at_5
      value: 13.370000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.488
    - type: map_at_10
      value: 23.080000000000002
    - type: map_at_100
      value: 24.230999999999998
    - type: map_at_1000
      value: 24.371000000000002
    - type: map_at_3
      value: 21.288
    - type: map_at_5
      value: 22.192999999999998
    - type: mrr_at_1
      value: 21.848
    - type: mrr_at_10
      value: 27.642
    - type: mrr_at_100
      value: 28.609
    - type: mrr_at_1000
      value: 28.692
    - type: mrr_at_3
      value: 25.746000000000002
    - type: mrr_at_5
      value: 26.848
    - type: ndcg_at_1
      value: 21.848
    - type: ndcg_at_10
      value: 27.032
    - type: ndcg_at_100
      value: 32.489000000000004
    - type: ndcg_at_1000
      value: 35.692
    - type: ndcg_at_3
      value: 23.874000000000002
    - type: ndcg_at_5
      value: 25.192999999999998
    - type: precision_at_1
      value: 21.848
    - type: precision_at_10
      value: 4.936999999999999
    - type: precision_at_100
      value: 0.915
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.1
    - type: precision_at_5
      value: 7.854
    - type: recall_at_1
      value: 17.488
    - type: recall_at_10
      value: 34.572
    - type: recall_at_100
      value: 58.347
    - type: recall_at_1000
      value: 80.541
    - type: recall_at_3
      value: 25.417
    - type: recall_at_5
      value: 28.998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.131
    - type: map_at_10
      value: 16.721
    - type: map_at_100
      value: 17.743000000000002
    - type: map_at_1000
      value: 17.878
    - type: map_at_3
      value: 14.92
    - type: map_at_5
      value: 15.963
    - type: mrr_at_1
      value: 14.155000000000001
    - type: mrr_at_10
      value: 19.974
    - type: mrr_at_100
      value: 20.905
    - type: mrr_at_1000
      value: 20.988
    - type: mrr_at_3
      value: 18.132
    - type: mrr_at_5
      value: 19.176000000000002
    - type: ndcg_at_1
      value: 14.155000000000001
    - type: ndcg_at_10
      value: 20.302999999999997
    - type: ndcg_at_100
      value: 25.421
    - type: ndcg_at_1000
      value: 28.832
    - type: ndcg_at_3
      value: 16.973
    - type: ndcg_at_5
      value: 18.590999999999998
    - type: precision_at_1
      value: 14.155000000000001
    - type: precision_at_10
      value: 3.904
    - type: precision_at_100
      value: 0.768
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 8.219
    - type: precision_at_5
      value: 6.187
    - type: recall_at_1
      value: 11.131
    - type: recall_at_10
      value: 27.894000000000002
    - type: recall_at_100
      value: 50.52799999999999
    - type: recall_at_1000
      value: 74.969
    - type: recall_at_3
      value: 19.043
    - type: recall_at_5
      value: 22.994
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.556083333333332
    - type: map_at_10
      value: 18.54741666666667
    - type: map_at_100
      value: 19.411
    - type: map_at_1000
      value: 19.53608333333333
    - type: map_at_3
      value: 16.97208333333333
    - type: map_at_5
      value: 17.831583333333327
    - type: mrr_at_1
      value: 16.519666666666666
    - type: mrr_at_10
      value: 21.57283333333333
    - type: mrr_at_100
      value: 22.353166666666667
    - type: mrr_at_1000
      value: 22.441999999999997
    - type: mrr_at_3
      value: 19.954500000000003
    - type: mrr_at_5
      value: 20.84958333333333
    - type: ndcg_at_1
      value: 16.519666666666666
    - type: ndcg_at_10
      value: 21.846416666666666
    - type: ndcg_at_100
      value: 26.199750000000005
    - type: ndcg_at_1000
      value: 29.44333333333333
    - type: ndcg_at_3
      value: 18.98058333333334
    - type: ndcg_at_5
      value: 20.266666666666666
    - type: precision_at_1
      value: 16.519666666666666
    - type: precision_at_10
      value: 3.907999999999999
    - type: precision_at_100
      value: 0.7232500000000001
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 8.805166666666668
    - type: precision_at_5
      value: 6.317166666666665
    - type: recall_at_1
      value: 13.556083333333332
    - type: recall_at_10
      value: 28.798916666666663
    - type: recall_at_100
      value: 48.75083333333334
    - type: recall_at_1000
      value: 72.47908333333334
    - type: recall_at_3
      value: 20.702583333333333
    - type: recall_at_5
      value: 24.039250000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.536
    - type: map_at_10
      value: 14.155000000000001
    - type: map_at_100
      value: 14.77
    - type: map_at_1000
      value: 14.860999999999999
    - type: map_at_3
      value: 13.055
    - type: map_at_5
      value: 13.608999999999998
    - type: mrr_at_1
      value: 12.577
    - type: mrr_at_10
      value: 16.247
    - type: mrr_at_100
      value: 16.857
    - type: mrr_at_1000
      value: 16.942
    - type: mrr_at_3
      value: 15.056
    - type: mrr_at_5
      value: 15.647
    - type: ndcg_at_1
      value: 12.577
    - type: ndcg_at_10
      value: 16.636
    - type: ndcg_at_100
      value: 19.947
    - type: ndcg_at_1000
      value: 22.643
    - type: ndcg_at_3
      value: 14.472
    - type: ndcg_at_5
      value: 15.339
    - type: precision_at_1
      value: 12.577
    - type: precision_at_10
      value: 2.807
    - type: precision_at_100
      value: 0.48900000000000005
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 6.544
    - type: precision_at_5
      value: 4.601
    - type: recall_at_1
      value: 10.536
    - type: recall_at_10
      value: 22.345000000000002
    - type: recall_at_100
      value: 37.877
    - type: recall_at_1000
      value: 58.648
    - type: recall_at_3
      value: 16.048000000000002
    - type: recall_at_5
      value: 18.267
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.292
    - type: map_at_10
      value: 10.58
    - type: map_at_100
      value: 11.173
    - type: map_at_1000
      value: 11.29
    - type: map_at_3
      value: 9.633
    - type: map_at_5
      value: 10.163
    - type: mrr_at_1
      value: 9.016
    - type: mrr_at_10
      value: 12.757
    - type: mrr_at_100
      value: 13.370000000000001
    - type: mrr_at_1000
      value: 13.472000000000001
    - type: mrr_at_3
      value: 11.688
    - type: mrr_at_5
      value: 12.328999999999999
    - type: ndcg_at_1
      value: 9.016
    - type: ndcg_at_10
      value: 12.806000000000001
    - type: ndcg_at_100
      value: 16.174
    - type: ndcg_at_1000
      value: 19.644000000000002
    - type: ndcg_at_3
      value: 11.021
    - type: ndcg_at_5
      value: 11.871
    - type: precision_at_1
      value: 9.016
    - type: precision_at_10
      value: 2.385
    - type: precision_at_100
      value: 0.49100000000000005
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 5.322
    - type: precision_at_5
      value: 3.8890000000000002
    - type: recall_at_1
      value: 7.292
    - type: recall_at_10
      value: 17.39
    - type: recall_at_100
      value: 33.239999999999995
    - type: recall_at_1000
      value: 59.223000000000006
    - type: recall_at_3
      value: 12.44
    - type: recall_at_5
      value: 14.544
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.661000000000001
    - type: map_at_10
      value: 15.949
    - type: map_at_100
      value: 16.689999999999998
    - type: map_at_1000
      value: 16.805999999999997
    - type: map_at_3
      value: 14.398
    - type: map_at_5
      value: 15.204
    - type: mrr_at_1
      value: 14.272000000000002
    - type: mrr_at_10
      value: 18.85
    - type: mrr_at_100
      value: 19.603
    - type: mrr_at_1000
      value: 19.698999999999998
    - type: mrr_at_3
      value: 17.18
    - type: mrr_at_5
      value: 18.005
    - type: ndcg_at_1
      value: 14.272000000000002
    - type: ndcg_at_10
      value: 19.082
    - type: ndcg_at_100
      value: 23.078000000000003
    - type: ndcg_at_1000
      value: 26.444000000000003
    - type: ndcg_at_3
      value: 16.006
    - type: ndcg_at_5
      value: 17.281
    - type: precision_at_1
      value: 14.272000000000002
    - type: precision_at_10
      value: 3.321
    - type: precision_at_100
      value: 0.585
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 7.3069999999999995
    - type: precision_at_5
      value: 5.187
    - type: recall_at_1
      value: 11.661000000000001
    - type: recall_at_10
      value: 26.07
    - type: recall_at_100
      value: 44.537
    - type: recall_at_1000
      value: 69.446
    - type: recall_at_3
      value: 17.471999999999998
    - type: recall_at_5
      value: 20.744
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.037
    - type: map_at_10
      value: 19.348000000000003
    - type: map_at_100
      value: 20.357
    - type: map_at_1000
      value: 20.53
    - type: map_at_3
      value: 17.979
    - type: map_at_5
      value: 18.773
    - type: mrr_at_1
      value: 16.403000000000002
    - type: mrr_at_10
      value: 22.846
    - type: mrr_at_100
      value: 23.622
    - type: mrr_at_1000
      value: 23.708000000000002
    - type: mrr_at_3
      value: 21.377
    - type: mrr_at_5
      value: 22.325
    - type: ndcg_at_1
      value: 16.403000000000002
    - type: ndcg_at_10
      value: 23.275000000000002
    - type: ndcg_at_100
      value: 27.79
    - type: ndcg_at_1000
      value: 31.371
    - type: ndcg_at_3
      value: 21.035
    - type: ndcg_at_5
      value: 22.209
    - type: precision_at_1
      value: 16.403000000000002
    - type: precision_at_10
      value: 4.644
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 10.408000000000001
    - type: precision_at_5
      value: 7.5889999999999995
    - type: recall_at_1
      value: 13.037
    - type: recall_at_10
      value: 30.239
    - type: recall_at_100
      value: 51.649
    - type: recall_at_1000
      value: 76.57000000000001
    - type: recall_at_3
      value: 23.677999999999997
    - type: recall_at_5
      value: 26.755000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.288
    - type: map_at_10
      value: 15.201999999999998
    - type: map_at_100
      value: 15.844
    - type: map_at_1000
      value: 15.963
    - type: map_at_3
      value: 13.828999999999999
    - type: map_at_5
      value: 14.530999999999999
    - type: mrr_at_1
      value: 12.753999999999998
    - type: mrr_at_10
      value: 16.753999999999998
    - type: mrr_at_100
      value: 17.387
    - type: mrr_at_1000
      value: 17.498
    - type: mrr_at_3
      value: 15.28
    - type: mrr_at_5
      value: 16.066
    - type: ndcg_at_1
      value: 12.753999999999998
    - type: ndcg_at_10
      value: 17.896
    - type: ndcg_at_100
      value: 21.632
    - type: ndcg_at_1000
      value: 25.111
    - type: ndcg_at_3
      value: 15.03
    - type: ndcg_at_5
      value: 16.281000000000002
    - type: precision_at_1
      value: 12.753999999999998
    - type: precision_at_10
      value: 2.884
    - type: precision_at_100
      value: 0.516
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 6.531000000000001
    - type: precision_at_5
      value: 4.658
    - type: recall_at_1
      value: 11.288
    - type: recall_at_10
      value: 24.941
    - type: recall_at_100
      value: 43.246
    - type: recall_at_1000
      value: 69.991
    - type: recall_at_3
      value: 17.018
    - type: recall_at_5
      value: 20.074
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.522
    - type: map_at_10
      value: 9.718
    - type: map_at_100
      value: 10.987
    - type: map_at_1000
      value: 11.185
    - type: map_at_3
      value: 7.89
    - type: map_at_5
      value: 8.794
    - type: mrr_at_1
      value: 12.508
    - type: mrr_at_10
      value: 20.039
    - type: mrr_at_100
      value: 21.271
    - type: mrr_at_1000
      value: 21.353
    - type: mrr_at_3
      value: 17.394000000000002
    - type: mrr_at_5
      value: 18.889
    - type: ndcg_at_1
      value: 12.508
    - type: ndcg_at_10
      value: 14.698
    - type: ndcg_at_100
      value: 20.794
    - type: ndcg_at_1000
      value: 24.978
    - type: ndcg_at_3
      value: 11.229
    - type: ndcg_at_5
      value: 12.483
    - type: precision_at_1
      value: 12.508
    - type: precision_at_10
      value: 4.925
    - type: precision_at_100
      value: 1.1360000000000001
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 8.512
    - type: precision_at_5
      value: 6.893000000000001
    - type: recall_at_1
      value: 5.522
    - type: recall_at_10
      value: 18.645999999999997
    - type: recall_at_100
      value: 40.231
    - type: recall_at_1000
      value: 64.398
    - type: recall_at_3
      value: 10.520999999999999
    - type: recall_at_5
      value: 13.686000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.2840000000000003
    - type: map_at_10
      value: 7.598000000000001
    - type: map_at_100
      value: 10.347000000000001
    - type: map_at_1000
      value: 11.106
    - type: map_at_3
      value: 5.428999999999999
    - type: map_at_5
      value: 6.365
    - type: mrr_at_1
      value: 34.75
    - type: mrr_at_10
      value: 43.762
    - type: mrr_at_100
      value: 44.546
    - type: mrr_at_1000
      value: 44.592
    - type: mrr_at_3
      value: 41.125
    - type: mrr_at_5
      value: 42.699999999999996
    - type: ndcg_at_1
      value: 25.25
    - type: ndcg_at_10
      value: 20.081
    - type: ndcg_at_100
      value: 21.996
    - type: ndcg_at_1000
      value: 28.327999999999996
    - type: ndcg_at_3
      value: 22.421
    - type: ndcg_at_5
      value: 21.227999999999998
    - type: precision_at_1
      value: 34.75
    - type: precision_at_10
      value: 17.925
    - type: precision_at_100
      value: 5.437
    - type: precision_at_1000
      value: 1.157
    - type: precision_at_3
      value: 26.333000000000002
    - type: precision_at_5
      value: 23.0
    - type: recall_at_1
      value: 3.2840000000000003
    - type: recall_at_10
      value: 11.799999999999999
    - type: recall_at_100
      value: 27.08
    - type: recall_at_1000
      value: 48.348
    - type: recall_at_3
      value: 6.701
    - type: recall_at_5
      value: 8.515
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.57
    - type: f1
      value: 39.68887710167085
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 11.396
    - type: map_at_10
      value: 17.108999999999998
    - type: map_at_100
      value: 17.953
    - type: map_at_1000
      value: 18.035999999999998
    - type: map_at_3
      value: 15.177
    - type: map_at_5
      value: 16.232
    - type: mrr_at_1
      value: 12.166
    - type: mrr_at_10
      value: 18.236
    - type: mrr_at_100
      value: 19.1
    - type: mrr_at_1000
      value: 19.176000000000002
    - type: mrr_at_3
      value: 16.212
    - type: mrr_at_5
      value: 17.317
    - type: ndcg_at_1
      value: 12.166
    - type: ndcg_at_10
      value: 20.671999999999997
    - type: ndcg_at_100
      value: 25.227
    - type: ndcg_at_1000
      value: 27.613
    - type: ndcg_at_3
      value: 16.656000000000002
    - type: ndcg_at_5
      value: 18.549
    - type: precision_at_1
      value: 12.166
    - type: precision_at_10
      value: 3.3529999999999998
    - type: precision_at_100
      value: 0.582
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 7.141
    - type: precision_at_5
      value: 5.272
    - type: recall_at_1
      value: 11.396
    - type: recall_at_10
      value: 30.825999999999997
    - type: recall_at_100
      value: 52.641000000000005
    - type: recall_at_1000
      value: 71.34899999999999
    - type: recall_at_3
      value: 19.886
    - type: recall_at_5
      value: 24.417
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.534
    - type: map_at_10
      value: 9.422
    - type: map_at_100
      value: 10.471
    - type: map_at_1000
      value: 10.655000000000001
    - type: map_at_3
      value: 7.938000000000001
    - type: map_at_5
      value: 8.569
    - type: mrr_at_1
      value: 11.265
    - type: mrr_at_10
      value: 16.473
    - type: mrr_at_100
      value: 17.491
    - type: mrr_at_1000
      value: 17.592
    - type: mrr_at_3
      value: 14.738000000000001
    - type: mrr_at_5
      value: 15.470999999999998
    - type: ndcg_at_1
      value: 11.265
    - type: ndcg_at_10
      value: 13.194
    - type: ndcg_at_100
      value: 18.403
    - type: ndcg_at_1000
      value: 22.804
    - type: ndcg_at_3
      value: 10.92
    - type: ndcg_at_5
      value: 11.445
    - type: precision_at_1
      value: 11.265
    - type: precision_at_10
      value: 3.9510000000000005
    - type: precision_at_100
      value: 0.909
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_3
      value: 7.4590000000000005
    - type: precision_at_5
      value: 5.648000000000001
    - type: recall_at_1
      value: 5.534
    - type: recall_at_10
      value: 17.299999999999997
    - type: recall_at_100
      value: 37.901
    - type: recall_at_1000
      value: 65.745
    - type: recall_at_3
      value: 10.138
    - type: recall_at_5
      value: 12.078999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.633000000000001
    - type: map_at_10
      value: 19.076
    - type: map_at_100
      value: 19.851
    - type: map_at_1000
      value: 19.961000000000002
    - type: map_at_3
      value: 17.451
    - type: map_at_5
      value: 18.33
    - type: mrr_at_1
      value: 27.265
    - type: mrr_at_10
      value: 33.426
    - type: mrr_at_100
      value: 34.154
    - type: mrr_at_1000
      value: 34.226
    - type: mrr_at_3
      value: 31.648
    - type: mrr_at_5
      value: 32.613
    - type: ndcg_at_1
      value: 27.265
    - type: ndcg_at_10
      value: 24.81
    - type: ndcg_at_100
      value: 28.668
    - type: ndcg_at_1000
      value: 31.474000000000004
    - type: ndcg_at_3
      value: 21.586
    - type: ndcg_at_5
      value: 23.091
    - type: precision_at_1
      value: 27.265
    - type: precision_at_10
      value: 5.5440000000000005
    - type: precision_at_100
      value: 0.8659999999999999
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 13.594000000000001
    - type: precision_at_5
      value: 9.347999999999999
    - type: recall_at_1
      value: 13.633000000000001
    - type: recall_at_10
      value: 27.717999999999996
    - type: recall_at_100
      value: 43.322
    - type: recall_at_1000
      value: 62.107
    - type: recall_at_3
      value: 20.392
    - type: recall_at_5
      value: 23.369
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.9896
    - type: ap
      value: 59.21073897376523
    - type: f1
      value: 63.83200686849996
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.203
    - type: map_at_10
      value: 9.144
    - type: map_at_100
      value: 9.93
    - type: map_at_1000
      value: 10.03
    - type: map_at_3
      value: 7.703
    - type: map_at_5
      value: 8.488
    - type: mrr_at_1
      value: 5.3580000000000005
    - type: mrr_at_10
      value: 9.392
    - type: mrr_at_100
      value: 10.188
    - type: mrr_at_1000
      value: 10.286
    - type: mrr_at_3
      value: 7.927
    - type: mrr_at_5
      value: 8.725
    - type: ndcg_at_1
      value: 5.344
    - type: ndcg_at_10
      value: 11.625
    - type: ndcg_at_100
      value: 15.953999999999999
    - type: ndcg_at_1000
      value: 19.003999999999998
    - type: ndcg_at_3
      value: 8.615
    - type: ndcg_at_5
      value: 10.038
    - type: precision_at_1
      value: 5.344
    - type: precision_at_10
      value: 2.013
    - type: precision_at_100
      value: 0.426
    - type: precision_at_1000
      value: 0.06899999999999999
    - type: precision_at_3
      value: 3.816
    - type: precision_at_5
      value: 3.0140000000000002
    - type: recall_at_1
      value: 5.203
    - type: recall_at_10
      value: 19.336000000000002
    - type: recall_at_100
      value: 40.534
    - type: recall_at_1000
      value: 65.063
    - type: recall_at_3
      value: 11.06
    - type: recall_at_5
      value: 14.488999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.34336525307798
    - type: f1
      value: 88.44434240756266
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.546283629730944
    - type: f1
      value: 40.1240023106233
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.956960322797585
    - type: f1
      value: 59.679846427125426
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.69535978480161
    - type: f1
      value: 67.29552687986417
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.401510844328
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.30315769309524
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.572900233549426
    - type: mrr
      value: 29.419117722742016
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.627
    - type: map_at_10
      value: 6.662
    - type: map_at_100
      value: 8.429
    - type: map_at_1000
      value: 9.669
    - type: map_at_3
      value: 5.106
    - type: map_at_5
      value: 5.7410000000000005
    - type: mrr_at_1
      value: 31.889
    - type: mrr_at_10
      value: 40.531
    - type: mrr_at_100
      value: 41.237
    - type: mrr_at_1000
      value: 41.304
    - type: mrr_at_3
      value: 37.926
    - type: mrr_at_5
      value: 39.474
    - type: ndcg_at_1
      value: 29.256999999999998
    - type: ndcg_at_10
      value: 21.928
    - type: ndcg_at_100
      value: 20.74
    - type: ndcg_at_1000
      value: 30.375000000000004
    - type: ndcg_at_3
      value: 25.296000000000003
    - type: ndcg_at_5
      value: 23.602999999999998
    - type: precision_at_1
      value: 31.579
    - type: precision_at_10
      value: 16.067999999999998
    - type: precision_at_100
      value: 5.972
    - type: precision_at_1000
      value: 1.918
    - type: precision_at_3
      value: 23.735999999999997
    - type: precision_at_5
      value: 20.124
    - type: recall_at_1
      value: 3.627
    - type: recall_at_10
      value: 10.487
    - type: recall_at_100
      value: 22.634
    - type: recall_at_1000
      value: 57.052
    - type: recall_at_3
      value: 5.975
    - type: recall_at_5
      value: 7.495
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.954
    - type: map_at_10
      value: 13.513
    - type: map_at_100
      value: 14.582
    - type: map_at_1000
      value: 14.687
    - type: map_at_3
      value: 11.437999999999999
    - type: map_at_5
      value: 12.531999999999998
    - type: mrr_at_1
      value: 9.038
    - type: mrr_at_10
      value: 14.932
    - type: mrr_at_100
      value: 15.978
    - type: mrr_at_1000
      value: 16.066
    - type: mrr_at_3
      value: 12.775
    - type: mrr_at_5
      value: 13.937
    - type: ndcg_at_1
      value: 9.038
    - type: ndcg_at_10
      value: 17.224
    - type: ndcg_at_100
      value: 22.869
    - type: ndcg_at_1000
      value: 25.816
    - type: ndcg_at_3
      value: 12.878
    - type: ndcg_at_5
      value: 14.874
    - type: precision_at_1
      value: 9.038
    - type: precision_at_10
      value: 3.2009999999999996
    - type: precision_at_100
      value: 0.643
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 6.053999999999999
    - type: precision_at_5
      value: 4.728000000000001
    - type: recall_at_1
      value: 7.954
    - type: recall_at_10
      value: 27.448
    - type: recall_at_100
      value: 53.966
    - type: recall_at_1000
      value: 76.69
    - type: recall_at_3
      value: 15.740000000000002
    - type: recall_at_5
      value: 20.466
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.474
    - type: map_at_10
      value: 74.008
    - type: map_at_100
      value: 74.79599999999999
    - type: map_at_1000
      value: 74.833
    - type: map_at_3
      value: 71.127
    - type: map_at_5
      value: 72.858
    - type: mrr_at_1
      value: 70.86
    - type: mrr_at_10
      value: 78.428
    - type: mrr_at_100
      value: 78.693
    - type: mrr_at_1000
      value: 78.7
    - type: mrr_at_3
      value: 76.942
    - type: mrr_at_5
      value: 77.88199999999999
    - type: ndcg_at_1
      value: 70.89
    - type: ndcg_at_10
      value: 78.804
    - type: ndcg_at_100
      value: 81.082
    - type: ndcg_at_1000
      value: 81.527
    - type: ndcg_at_3
      value: 75.202
    - type: ndcg_at_5
      value: 77.031
    - type: precision_at_1
      value: 70.89
    - type: precision_at_10
      value: 11.923
    - type: precision_at_100
      value: 1.4409999999999998
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 32.65
    - type: precision_at_5
      value: 21.58
    - type: recall_at_1
      value: 61.474
    - type: recall_at_10
      value: 88.056
    - type: recall_at_100
      value: 96.814
    - type: recall_at_1000
      value: 99.395
    - type: recall_at_3
      value: 77.656
    - type: recall_at_5
      value: 82.796
    - type: map_at_1
      value: 2.675
    - type: map_at_10
      value: 6.066
    - type: map_at_100
      value: 7.263999999999999
    - type: map_at_1000
      value: 7.51
    - type: map_at_3
      value: 4.404
    - type: map_at_5
      value: 5.181
    - type: mrr_at_1
      value: 13.200000000000001
    - type: mrr_at_10
      value: 20.189
    - type: mrr_at_100
      value: 21.445
    - type: mrr_at_1000
      value: 21.536
    - type: mrr_at_3
      value: 17.666999999999998
    - type: mrr_at_5
      value: 19.002
    - type: ndcg_at_1
      value: 13.200000000000001
    - type: ndcg_at_10
      value: 11.025
    - type: ndcg_at_100
      value: 16.828000000000003
    - type: ndcg_at_1000
      value: 21.982
    - type: ndcg_at_3
      value: 10.231
    - type: ndcg_at_5
      value: 8.963000000000001
    - type: precision_at_1
      value: 13.200000000000001
    - type: precision_at_10
      value: 5.76
    - type: precision_at_100
      value: 1.422
    - type: precision_at_1000
      value: 0.267
    - type: precision_at_3
      value: 9.367
    - type: precision_at_5
      value: 7.76
    - type: recall_at_1
      value: 2.675
    - type: recall_at_10
      value: 11.675
    - type: recall_at_100
      value: 28.875
    - type: recall_at_1000
      value: 54.173
    - type: recall_at_3
      value: 5.708
    - type: recall_at_5
      value: 7.863
    - type: map_at_1
      value: 0.11100000000000002
    - type: map_at_10
      value: 0.679
    - type: map_at_100
      value: 3.8249999999999997
    - type: map_at_1000
      value: 9.285
    - type: map_at_3
      value: 0.27299999999999996
    - type: map_at_5
      value: 0.396
    - type: mrr_at_1
      value: 48.0
    - type: mrr_at_10
      value: 58.839
    - type: mrr_at_100
      value: 59.419999999999995
    - type: mrr_at_1000
      value: 59.419999999999995
    - type: mrr_at_3
      value: 55.00000000000001
    - type: mrr_at_5
      value: 56.89999999999999
    - type: ndcg_at_1
      value: 41.0
    - type: ndcg_at_10
      value: 35.836
    - type: ndcg_at_100
      value: 28.149
    - type: ndcg_at_1000
      value: 25.856
    - type: ndcg_at_3
      value: 39.184000000000005
    - type: ndcg_at_5
      value: 37.309
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 39.0
    - type: precision_at_100
      value: 29.7
    - type: precision_at_1000
      value: 12.864
    - type: precision_at_3
      value: 43.333
    - type: precision_at_5
      value: 40.400000000000006
    - type: recall_at_1
      value: 0.11100000000000002
    - type: recall_at_10
      value: 0.894
    - type: recall_at_100
      value: 6.444
    - type: recall_at_1000
      value: 25.243
    - type: recall_at_3
      value: 0.311
    - type: recall_at_5
      value: 0.471
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 34.90409674230351
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 43.15515899635581
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.73075802333739
    - type: cos_sim_spearman
      value: 67.84289404493155
    - type: euclidean_pearson
      value: 72.99765907409036
    - type: euclidean_spearman
      value: 67.84297651880989
    - type: manhattan_pearson
      value: 71.56824568898308
    - type: manhattan_spearman
      value: 66.49154112140326
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.15762265059362
    - type: cos_sim_spearman
      value: 67.06089989163219
    - type: euclidean_pearson
      value: 70.47335445930443
    - type: euclidean_spearman
      value: 67.06203229762373
    - type: manhattan_pearson
      value: 71.4377325677922
    - type: manhattan_spearman
      value: 68.40504987244773
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.36180280086563
    - type: cos_sim_spearman
      value: 78.77519784149617
    - type: euclidean_pearson
      value: 78.35593578221615
    - type: euclidean_spearman
      value: 78.77523564781683
    - type: manhattan_pearson
      value: 78.86787717837672
    - type: manhattan_spearman
      value: 79.39186388148488
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.58231513495421
    - type: cos_sim_spearman
      value: 74.49349421503516
    - type: euclidean_pearson
      value: 76.83261970721901
    - type: euclidean_spearman
      value: 74.4934845240682
    - type: manhattan_pearson
      value: 76.93964525607548
    - type: manhattan_spearman
      value: 74.92015195647967
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.1326777711964
    - type: cos_sim_spearman
      value: 81.22730751796163
    - type: euclidean_pearson
      value: 81.25069343254962
    - type: euclidean_spearman
      value: 81.22730800357442
    - type: manhattan_pearson
      value: 81.89815505669003
    - type: manhattan_spearman
      value: 82.02113941562317
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.45738534759084
    - type: cos_sim_spearman
      value: 76.91650991022456
    - type: euclidean_pearson
      value: 76.63155234592621
    - type: euclidean_spearman
      value: 76.9170601938253
    - type: manhattan_pearson
      value: 77.33411034896274
    - type: manhattan_spearman
      value: 77.75936963273696
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.88607666461446
    - type: cos_sim_spearman
      value: 84.10579933135438
    - type: euclidean_pearson
      value: 84.22914136437043
    - type: euclidean_spearman
      value: 84.10667343750598
    - type: manhattan_pearson
      value: 84.54468730779816
    - type: manhattan_spearman
      value: 84.61630648277088
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.229353870984085
    - type: cos_sim_spearman
      value: 60.68370513051131
    - type: euclidean_pearson
      value: 63.22117293489078
    - type: euclidean_spearman
      value: 60.68370513051131
    - type: manhattan_pearson
      value: 63.49146703165777
    - type: manhattan_spearman
      value: 61.32348416931768
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.1763291511081
    - type: cos_sim_spearman
      value: 75.83877626537955
    - type: euclidean_pearson
      value: 77.36233283234974
    - type: euclidean_spearman
      value: 75.83879473341474
    - type: manhattan_pearson
      value: 77.45006581598014
    - type: manhattan_spearman
      value: 75.95747982186211
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.10229760427933
    - type: mrr
      value: 90.24918799428605
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 32.639
    - type: map_at_10
      value: 39.007999999999996
    - type: map_at_100
      value: 40.101
    - type: map_at_1000
      value: 40.177
    - type: map_at_3
      value: 36.889
    - type: map_at_5
      value: 38.013999999999996
    - type: mrr_at_1
      value: 35.0
    - type: mrr_at_10
      value: 40.883
    - type: mrr_at_100
      value: 41.818
    - type: mrr_at_1000
      value: 41.88
    - type: mrr_at_3
      value: 39.056000000000004
    - type: mrr_at_5
      value: 40.022000000000006
    - type: ndcg_at_1
      value: 35.0
    - type: ndcg_at_10
      value: 42.94
    - type: ndcg_at_100
      value: 48.592999999999996
    - type: ndcg_at_1000
      value: 50.588
    - type: ndcg_at_3
      value: 38.799
    - type: ndcg_at_5
      value: 40.644999999999996
    - type: precision_at_1
      value: 35.0
    - type: precision_at_10
      value: 5.933
    - type: precision_at_100
      value: 0.91
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 15.333
    - type: precision_at_5
      value: 10.267
    - type: recall_at_1
      value: 32.639
    - type: recall_at_10
      value: 53.556000000000004
    - type: recall_at_100
      value: 80.51700000000001
    - type: recall_at_1000
      value: 96.133
    - type: recall_at_3
      value: 42.0
    - type: recall_at_5
      value: 46.583000000000006
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.63465346534653
    - type: cos_sim_ap
      value: 87.35445585086691
    - type: cos_sim_f1
      value: 80.60956384655807
    - type: cos_sim_precision
      value: 84.9390919158361
    - type: cos_sim_recall
      value: 76.7
    - type: dot_accuracy
      value: 99.63465346534653
    - type: dot_ap
      value: 87.35445585086691
    - type: dot_f1
      value: 80.60956384655807
    - type: dot_precision
      value: 84.9390919158361
    - type: dot_recall
      value: 76.7
    - type: euclidean_accuracy
      value: 99.63465346534653
    - type: euclidean_ap
      value: 87.35445585086691
    - type: euclidean_f1
      value: 80.60956384655807
    - type: euclidean_precision
      value: 84.9390919158361
    - type: euclidean_recall
      value: 76.7
    - type: manhattan_accuracy
      value: 99.6970297029703
    - type: manhattan_ap
      value: 90.68997415814273
    - type: manhattan_f1
      value: 84.33981576253838
    - type: manhattan_precision
      value: 86.37316561844864
    - type: manhattan_recall
      value: 82.39999999999999
    - type: max_accuracy
      value: 99.6970297029703
    - type: max_ap
      value: 90.68997415814273
    - type: max_f1
      value: 84.33981576253838
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 37.79012296970403
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.17355447643775
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.12070306689919
    - type: mrr
      value: 43.573166008827776
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.133865143991105
    - type: cos_sim_spearman
      value: 29.440326561177667
    - type: dot_pearson
      value: 30.133865125920966
    - type: dot_spearman
      value: 29.435121388222697
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.664
    - type: map_at_10
      value: 8.955
    - type: map_at_100
      value: 14.658
    - type: map_at_1000
      value: 16.243
    - type: map_at_3
      value: 5.002
    - type: map_at_5
      value: 6.609
    - type: mrr_at_1
      value: 36.735
    - type: mrr_at_10
      value: 47.676
    - type: mrr_at_100
      value: 48.504999999999995
    - type: mrr_at_1000
      value: 48.504999999999995
    - type: mrr_at_3
      value: 43.197
    - type: mrr_at_5
      value: 46.054
    - type: ndcg_at_1
      value: 33.672999999999995
    - type: ndcg_at_10
      value: 21.986
    - type: ndcg_at_100
      value: 35.127
    - type: ndcg_at_1000
      value: 46.345
    - type: ndcg_at_3
      value: 27.017999999999997
    - type: ndcg_at_5
      value: 24.57
    - type: precision_at_1
      value: 36.735
    - type: precision_at_10
      value: 19.184
    - type: precision_at_100
      value: 7.714
    - type: precision_at_1000
      value: 1.484
    - type: precision_at_3
      value: 27.211000000000002
    - type: precision_at_5
      value: 24.490000000000002
    - type: recall_at_1
      value: 2.664
    - type: recall_at_10
      value: 13.305
    - type: recall_at_100
      value: 46.623
    - type: recall_at_1000
      value: 81.056
    - type: recall_at_3
      value: 5.844
    - type: recall_at_5
      value: 8.605
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.0554
    - type: ap
      value: 13.578604741323947
    - type: f1
      value: 53.720604206564516
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.5851726089417
    - type: f1
      value: 53.78179835467554
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.95662139054496
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.62043273529235
    - type: cos_sim_ap
      value: 65.34515253479756
    - type: cos_sim_f1
      value: 62.530532486565704
    - type: cos_sim_precision
      value: 58.20827648931333
    - type: cos_sim_recall
      value: 67.54617414248021
    - type: dot_accuracy
      value: 83.62043273529235
    - type: dot_ap
      value: 65.34515253479756
    - type: dot_f1
      value: 62.530532486565704
    - type: dot_precision
      value: 58.20827648931333
    - type: dot_recall
      value: 67.54617414248021
    - type: euclidean_accuracy
      value: 83.62043273529235
    - type: euclidean_ap
      value: 65.34515253479756
    - type: euclidean_f1
      value: 62.530532486565704
    - type: euclidean_precision
      value: 58.20827648931333
    - type: euclidean_recall
      value: 67.54617414248021
    - type: manhattan_accuracy
      value: 83.40585325147524
    - type: manhattan_ap
      value: 64.01718862141554
    - type: manhattan_f1
      value: 61.092923696801805
    - type: manhattan_precision
      value: 58.429672447013495
    - type: manhattan_recall
      value: 64.01055408970976
    - type: max_accuracy
      value: 83.62043273529235
    - type: max_ap
      value: 65.34515253479756
    - type: max_f1
      value: 62.530532486565704
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.48981255093724
    - type: cos_sim_ap
      value: 82.67603725088865
    - type: cos_sim_f1
      value: 74.82442124038498
    - type: cos_sim_precision
      value: 72.31200172376643
    - type: cos_sim_recall
      value: 77.51770865414228
    - type: dot_accuracy
      value: 87.48981255093724
    - type: dot_ap
      value: 82.6760377923082
    - type: dot_f1
      value: 74.82442124038498
    - type: dot_precision
      value: 72.31200172376643
    - type: dot_recall
      value: 77.51770865414228
    - type: euclidean_accuracy
      value: 87.48981255093724
    - type: euclidean_ap
      value: 82.6760372072607
    - type: euclidean_f1
      value: 74.82442124038498
    - type: euclidean_precision
      value: 72.31200172376643
    - type: euclidean_recall
      value: 77.51770865414228
    - type: manhattan_accuracy
      value: 87.40055109248263
    - type: manhattan_ap
      value: 82.74988489269892
    - type: manhattan_f1
      value: 75.01184359170584
    - type: manhattan_precision
      value: 71.21012938490279
    - type: manhattan_recall
      value: 79.24237757930396
    - type: max_accuracy
      value: 87.48981255093724
    - type: max_ap
      value: 82.74988489269892
    - type: max_f1
      value: 75.01184359170584
---
