mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_307_w50k_b10k
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.70149253731343
    - type: ap
      value: 33.79646861902238
    - type: f1
      value: 65.39377031734182
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.577125
    - type: ap
      value: 59.69737246109206
    - type: f1
      value: 64.3577747072318
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.748
    - type: f1
      value: 33.3254582178127
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.199
    - type: map_at_10
      value: 34.28
    - type: map_at_100
      value: 35.480000000000004
    - type: map_at_1000
      value: 35.504999999999995
    - type: map_at_3
      value: 29.682
    - type: map_at_5
      value: 32.385000000000005
    - type: mrr_at_1
      value: 20.91
    - type: mrr_at_10
      value: 34.536
    - type: mrr_at_100
      value: 35.743
    - type: mrr_at_1000
      value: 35.768
    - type: mrr_at_3
      value: 29.931
    - type: mrr_at_5
      value: 32.623000000000005
    - type: ndcg_at_1
      value: 20.199
    - type: ndcg_at_10
      value: 42.278
    - type: ndcg_at_100
      value: 47.924
    - type: ndcg_at_1000
      value: 48.537
    - type: ndcg_at_3
      value: 32.815
    - type: ndcg_at_5
      value: 37.681
    - type: precision_at_1
      value: 20.199
    - type: precision_at_10
      value: 6.792
    - type: precision_at_100
      value: 0.9390000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.963999999999999
    - type: precision_at_5
      value: 10.74
    - type: recall_at_1
      value: 20.199
    - type: recall_at_10
      value: 67.923
    - type: recall_at_100
      value: 93.88300000000001
    - type: recall_at_1000
      value: 98.578
    - type: recall_at_3
      value: 41.892
    - type: recall_at_5
      value: 53.698
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 31.715994496712955
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 22.014928355542406
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.73401198259723
    - type: mrr
      value: 66.18574946137272
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.32819163750328
    - type: cos_sim_spearman
      value: 76.32884763830812
    - type: euclidean_pearson
      value: 77.6247892757331
    - type: euclidean_spearman
      value: 76.32884763830812
    - type: manhattan_pearson
      value: 77.4560490620549
    - type: manhattan_spearman
      value: 76.11679461376502
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.16883116883118
    - type: f1
      value: 71.34298475263475
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 29.528784676707033
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 19.565519101446977
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.581
    - type: map_at_10
      value: 28.322999999999997
    - type: map_at_100
      value: 29.392000000000003
    - type: map_at_1000
      value: 29.547
    - type: map_at_3
      value: 26.214
    - type: map_at_5
      value: 27.339000000000002
    - type: mrr_at_1
      value: 27.182000000000002
    - type: mrr_at_10
      value: 34.075
    - type: mrr_at_100
      value: 34.92
    - type: mrr_at_1000
      value: 34.997
    - type: mrr_at_3
      value: 32.26
    - type: mrr_at_5
      value: 33.283
    - type: ndcg_at_1
      value: 27.182000000000002
    - type: ndcg_at_10
      value: 32.903999999999996
    - type: ndcg_at_100
      value: 37.852999999999994
    - type: ndcg_at_1000
      value: 41.177
    - type: ndcg_at_3
      value: 29.976999999999997
    - type: ndcg_at_5
      value: 31.039
    - type: precision_at_1
      value: 27.182000000000002
    - type: precision_at_10
      value: 6.194999999999999
    - type: precision_at_100
      value: 1.09
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_3
      value: 14.354
    - type: precision_at_5
      value: 10.157
    - type: recall_at_1
      value: 21.581
    - type: recall_at_10
      value: 40.487
    - type: recall_at_100
      value: 62.832
    - type: recall_at_1000
      value: 85.768
    - type: recall_at_3
      value: 30.842000000000002
    - type: recall_at_5
      value: 34.497
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.495
    - type: map_at_10
      value: 21.625
    - type: map_at_100
      value: 22.506
    - type: map_at_1000
      value: 22.633
    - type: map_at_3
      value: 19.819
    - type: map_at_5
      value: 20.817
    - type: mrr_at_1
      value: 20.892
    - type: mrr_at_10
      value: 25.768
    - type: mrr_at_100
      value: 26.533
    - type: mrr_at_1000
      value: 26.61
    - type: mrr_at_3
      value: 23.96
    - type: mrr_at_5
      value: 24.893
    - type: ndcg_at_1
      value: 20.892
    - type: ndcg_at_10
      value: 25.144
    - type: ndcg_at_100
      value: 29.425
    - type: ndcg_at_1000
      value: 32.436
    - type: ndcg_at_3
      value: 22.105
    - type: ndcg_at_5
      value: 23.416
    - type: precision_at_1
      value: 20.892
    - type: precision_at_10
      value: 4.6240000000000006
    - type: precision_at_100
      value: 0.8500000000000001
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.403
    - type: precision_at_5
      value: 7.4270000000000005
    - type: recall_at_1
      value: 16.495
    - type: recall_at_10
      value: 31.627
    - type: recall_at_100
      value: 50.653999999999996
    - type: recall_at_1000
      value: 71.38
    - type: recall_at_3
      value: 22.987
    - type: recall_at_5
      value: 26.518000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.19
    - type: map_at_10
      value: 33.159
    - type: map_at_100
      value: 34.223
    - type: map_at_1000
      value: 34.322
    - type: map_at_3
      value: 30.866
    - type: map_at_5
      value: 32.016
    - type: mrr_at_1
      value: 29.091
    - type: mrr_at_10
      value: 36.208
    - type: mrr_at_100
      value: 37.059999999999995
    - type: mrr_at_1000
      value: 37.124
    - type: mrr_at_3
      value: 34.001999999999995
    - type: mrr_at_5
      value: 35.089999999999996
    - type: ndcg_at_1
      value: 29.091
    - type: ndcg_at_10
      value: 37.696000000000005
    - type: ndcg_at_100
      value: 42.774
    - type: ndcg_at_1000
      value: 45.064
    - type: ndcg_at_3
      value: 33.298
    - type: ndcg_at_5
      value: 35.089
    - type: precision_at_1
      value: 29.091
    - type: precision_at_10
      value: 6.132
    - type: precision_at_100
      value: 0.9530000000000001
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 14.754000000000001
    - type: precision_at_5
      value: 10.082
    - type: recall_at_1
      value: 25.19
    - type: recall_at_10
      value: 48.542
    - type: recall_at_100
      value: 71.475
    - type: recall_at_1000
      value: 88.157
    - type: recall_at_3
      value: 36.512
    - type: recall_at_5
      value: 40.998000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.979
    - type: map_at_10
      value: 15.160000000000002
    - type: map_at_100
      value: 15.927
    - type: map_at_1000
      value: 16.039
    - type: map_at_3
      value: 13.905000000000001
    - type: map_at_5
      value: 14.603
    - type: mrr_at_1
      value: 12.09
    - type: mrr_at_10
      value: 16.317999999999998
    - type: mrr_at_100
      value: 17.094
    - type: mrr_at_1000
      value: 17.198
    - type: mrr_at_3
      value: 15.028
    - type: mrr_at_5
      value: 15.712000000000002
    - type: ndcg_at_1
      value: 12.09
    - type: ndcg_at_10
      value: 17.71
    - type: ndcg_at_100
      value: 21.923000000000002
    - type: ndcg_at_1000
      value: 25.407999999999998
    - type: ndcg_at_3
      value: 15.139
    - type: ndcg_at_5
      value: 16.372
    - type: precision_at_1
      value: 12.09
    - type: precision_at_10
      value: 2.768
    - type: precision_at_100
      value: 0.521
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.478000000000001
    - type: precision_at_5
      value: 4.542
    - type: recall_at_1
      value: 10.979
    - type: recall_at_10
      value: 24.548000000000002
    - type: recall_at_100
      value: 44.659
    - type: recall_at_1000
      value: 72.15899999999999
    - type: recall_at_3
      value: 17.552
    - type: recall_at_5
      value: 20.584
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.703
    - type: map_at_10
      value: 9.588000000000001
    - type: map_at_100
      value: 10.312000000000001
    - type: map_at_1000
      value: 10.428999999999998
    - type: map_at_3
      value: 8.473
    - type: map_at_5
      value: 9.118
    - type: mrr_at_1
      value: 8.706
    - type: mrr_at_10
      value: 11.818
    - type: mrr_at_100
      value: 12.568999999999999
    - type: mrr_at_1000
      value: 12.664
    - type: mrr_at_3
      value: 10.551
    - type: mrr_at_5
      value: 11.235000000000001
    - type: ndcg_at_1
      value: 8.706
    - type: ndcg_at_10
      value: 11.823
    - type: ndcg_at_100
      value: 15.674
    - type: ndcg_at_1000
      value: 19.256
    - type: ndcg_at_3
      value: 9.637
    - type: ndcg_at_5
      value: 10.661
    - type: precision_at_1
      value: 8.706
    - type: precision_at_10
      value: 2.251
    - type: precision_at_100
      value: 0.484
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.601999999999999
    - type: precision_at_5
      value: 3.458
    - type: recall_at_1
      value: 6.703
    - type: recall_at_10
      value: 16.579
    - type: recall_at_100
      value: 34.054
    - type: recall_at_1000
      value: 60.769
    - type: recall_at_3
      value: 10.530000000000001
    - type: recall_at_5
      value: 13.126
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.688000000000002
    - type: map_at_10
      value: 23.169
    - type: map_at_100
      value: 24.275
    - type: map_at_1000
      value: 24.409
    - type: map_at_3
      value: 21.284
    - type: map_at_5
      value: 22.171
    - type: mrr_at_1
      value: 22.233
    - type: mrr_at_10
      value: 27.857
    - type: mrr_at_100
      value: 28.76
    - type: mrr_at_1000
      value: 28.841
    - type: mrr_at_3
      value: 25.857999999999997
    - type: mrr_at_5
      value: 26.922
    - type: ndcg_at_1
      value: 22.233
    - type: ndcg_at_10
      value: 27.203
    - type: ndcg_at_100
      value: 32.543
    - type: ndcg_at_1000
      value: 35.654
    - type: ndcg_at_3
      value: 23.863
    - type: ndcg_at_5
      value: 25.117
    - type: precision_at_1
      value: 22.233
    - type: precision_at_10
      value: 4.957000000000001
    - type: precision_at_100
      value: 0.919
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.036
    - type: precision_at_5
      value: 7.8149999999999995
    - type: recall_at_1
      value: 17.688000000000002
    - type: recall_at_10
      value: 34.969
    - type: recall_at_100
      value: 58.370999999999995
    - type: recall_at_1000
      value: 80.02
    - type: recall_at_3
      value: 25.332
    - type: recall_at_5
      value: 28.703
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.15
    - type: map_at_10
      value: 16.797
    - type: map_at_100
      value: 17.822
    - type: map_at_1000
      value: 17.956
    - type: map_at_3
      value: 14.985999999999999
    - type: map_at_5
      value: 16.044
    - type: mrr_at_1
      value: 14.155000000000001
    - type: mrr_at_10
      value: 20.01
    - type: mrr_at_100
      value: 20.966
    - type: mrr_at_1000
      value: 21.049
    - type: mrr_at_3
      value: 18.227
    - type: mrr_at_5
      value: 19.231
    - type: ndcg_at_1
      value: 14.155000000000001
    - type: ndcg_at_10
      value: 20.327
    - type: ndcg_at_100
      value: 25.490000000000002
    - type: ndcg_at_1000
      value: 28.854000000000003
    - type: ndcg_at_3
      value: 17.046
    - type: ndcg_at_5
      value: 18.647
    - type: precision_at_1
      value: 14.155000000000001
    - type: precision_at_10
      value: 3.893
    - type: precision_at_100
      value: 0.771
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 8.219
    - type: precision_at_5
      value: 6.164
    - type: recall_at_1
      value: 11.15
    - type: recall_at_10
      value: 27.750999999999998
    - type: recall_at_100
      value: 50.612
    - type: recall_at_1000
      value: 74.617
    - type: recall_at_3
      value: 19.101000000000003
    - type: recall_at_5
      value: 22.999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.562333333333335
    - type: map_at_10
      value: 18.514583333333334
    - type: map_at_100
      value: 19.362916666666667
    - type: map_at_1000
      value: 19.48625
    - type: map_at_3
      value: 16.955583333333337
    - type: map_at_5
      value: 17.788
    - type: mrr_at_1
      value: 16.54575
    - type: mrr_at_10
      value: 21.549249999999997
    - type: mrr_at_100
      value: 22.318500000000004
    - type: mrr_at_1000
      value: 22.405583333333333
    - type: mrr_at_3
      value: 19.9585
    - type: mrr_at_5
      value: 20.82183333333333
    - type: ndcg_at_1
      value: 16.54575
    - type: ndcg_at_10
      value: 21.80341666666667
    - type: ndcg_at_100
      value: 26.133833333333328
    - type: ndcg_at_1000
      value: 29.348666666666666
    - type: ndcg_at_3
      value: 18.973499999999998
    - type: ndcg_at_5
      value: 20.200833333333332
    - type: precision_at_1
      value: 16.54575
    - type: precision_at_10
      value: 3.895333333333334
    - type: precision_at_100
      value: 0.7226666666666668
    - type: precision_at_1000
      value: 0.11775
    - type: precision_at_3
      value: 8.796666666666667
    - type: precision_at_5
      value: 6.278083333333333
    - type: recall_at_1
      value: 13.562333333333335
    - type: recall_at_10
      value: 28.738833333333336
    - type: recall_at_100
      value: 48.66516666666668
    - type: recall_at_1000
      value: 72.21291666666666
    - type: recall_at_3
      value: 20.722166666666663
    - type: recall_at_5
      value: 23.920416666666668
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.612
    - type: map_at_10
      value: 14.233
    - type: map_at_100
      value: 14.804999999999998
    - type: map_at_1000
      value: 14.887
    - type: map_at_3
      value: 13.050999999999998
    - type: map_at_5
      value: 13.642999999999999
    - type: mrr_at_1
      value: 12.577
    - type: mrr_at_10
      value: 16.256999999999998
    - type: mrr_at_100
      value: 16.830000000000002
    - type: mrr_at_1000
      value: 16.909
    - type: mrr_at_3
      value: 15.031
    - type: mrr_at_5
      value: 15.613
    - type: ndcg_at_1
      value: 12.577
    - type: ndcg_at_10
      value: 16.81
    - type: ndcg_at_100
      value: 20.085
    - type: ndcg_at_1000
      value: 22.684
    - type: ndcg_at_3
      value: 14.471
    - type: ndcg_at_5
      value: 15.384
    - type: precision_at_1
      value: 12.577
    - type: precision_at_10
      value: 2.8529999999999998
    - type: precision_at_100
      value: 0.49699999999999994
    - 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: 10.612
    - type: recall_at_10
      value: 22.983999999999998
    - type: recall_at_100
      value: 38.745000000000005
    - type: recall_at_1000
      value: 58.886
    - type: recall_at_3
      value: 15.982
    - type: recall_at_5
      value: 18.433
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.04
    - type: map_at_10
      value: 10.277
    - type: map_at_100
      value: 10.873
    - type: map_at_1000
      value: 10.989
    - type: map_at_3
      value: 9.243
    - type: map_at_5
      value: 9.843
    - type: mrr_at_1
      value: 8.774999999999999
    - type: mrr_at_10
      value: 12.468
    - type: mrr_at_100
      value: 13.084999999999999
    - type: mrr_at_1000
      value: 13.184000000000001
    - type: mrr_at_3
      value: 11.293000000000001
    - type: mrr_at_5
      value: 12.034
    - type: ndcg_at_1
      value: 8.774999999999999
    - type: ndcg_at_10
      value: 12.527
    - type: ndcg_at_100
      value: 15.939
    - type: ndcg_at_1000
      value: 19.383
    - type: ndcg_at_3
      value: 10.565
    - type: ndcg_at_5
      value: 11.555
    - type: precision_at_1
      value: 8.774999999999999
    - type: precision_at_10
      value: 2.3640000000000003
    - type: precision_at_100
      value: 0.49
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 5.047
    - type: precision_at_5
      value: 3.8129999999999997
    - type: recall_at_1
      value: 7.04
    - type: recall_at_10
      value: 17.193
    - type: recall_at_100
      value: 33.33
    - type: recall_at_1000
      value: 59.134
    - type: recall_at_3
      value: 11.859
    - type: recall_at_5
      value: 14.243
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.381
    - type: map_at_10
      value: 15.676000000000002
    - type: map_at_100
      value: 16.448999999999998
    - type: map_at_1000
      value: 16.563
    - type: map_at_3
      value: 14.313
    - type: map_at_5
      value: 15.010000000000002
    - type: mrr_at_1
      value: 14.086000000000002
    - type: mrr_at_10
      value: 18.621
    - type: mrr_at_100
      value: 19.41
    - type: mrr_at_1000
      value: 19.506999999999998
    - type: mrr_at_3
      value: 17.149
    - type: mrr_at_5
      value: 17.918
    - type: ndcg_at_1
      value: 14.086000000000002
    - type: ndcg_at_10
      value: 18.647
    - type: ndcg_at_100
      value: 22.823
    - type: ndcg_at_1000
      value: 26.207
    - type: ndcg_at_3
      value: 15.986
    - type: ndcg_at_5
      value: 17.108
    - type: precision_at_1
      value: 14.086000000000002
    - type: precision_at_10
      value: 3.218
    - type: precision_at_100
      value: 0.585
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 7.369000000000001
    - type: precision_at_5
      value: 5.187
    - type: recall_at_1
      value: 11.381
    - type: recall_at_10
      value: 25.008999999999997
    - type: recall_at_100
      value: 44.368
    - type: recall_at_1000
      value: 69.587
    - type: recall_at_3
      value: 17.612
    - type: recall_at_5
      value: 20.506
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.641
    - type: map_at_10
      value: 19.067
    - type: map_at_100
      value: 20.046
    - type: map_at_1000
      value: 20.221
    - type: map_at_3
      value: 17.699
    - type: map_at_5
      value: 18.458
    - type: mrr_at_1
      value: 16.008
    - type: mrr_at_10
      value: 22.526
    - type: mrr_at_100
      value: 23.307
    - type: mrr_at_1000
      value: 23.391000000000002
    - type: mrr_at_3
      value: 21.047
    - type: mrr_at_5
      value: 21.956999999999997
    - type: ndcg_at_1
      value: 16.008
    - type: ndcg_at_10
      value: 23.029
    - type: ndcg_at_100
      value: 27.533
    - type: ndcg_at_1000
      value: 31.096
    - type: ndcg_at_3
      value: 20.806
    - type: ndcg_at_5
      value: 21.859
    - type: precision_at_1
      value: 16.008
    - type: precision_at_10
      value: 4.605
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 10.408000000000001
    - type: precision_at_5
      value: 7.470000000000001
    - type: recall_at_1
      value: 12.641
    - type: recall_at_10
      value: 30.236
    - type: recall_at_100
      value: 51.543000000000006
    - type: recall_at_1000
      value: 76.265
    - type: recall_at_3
      value: 23.677999999999997
    - type: recall_at_5
      value: 26.456000000000003
  - 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: 15.101
    - type: map_at_100
      value: 15.725
    - type: map_at_1000
      value: 15.840000000000002
    - type: map_at_3
      value: 13.614
    - type: map_at_5
      value: 14.394000000000002
    - type: mrr_at_1
      value: 12.753999999999998
    - type: mrr_at_10
      value: 16.665
    - type: mrr_at_100
      value: 17.288
    - type: mrr_at_1000
      value: 17.393
    - type: mrr_at_3
      value: 15.096000000000002
    - type: mrr_at_5
      value: 15.974
    - type: ndcg_at_1
      value: 12.753999999999998
    - type: ndcg_at_10
      value: 17.821
    - type: ndcg_at_100
      value: 21.544
    - type: ndcg_at_1000
      value: 24.965
    - type: ndcg_at_3
      value: 14.789
    - type: ndcg_at_5
      value: 16.163
    - type: precision_at_1
      value: 12.753999999999998
    - type: precision_at_10
      value: 2.884
    - type: precision_at_100
      value: 0.518
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 6.346
    - type: precision_at_5
      value: 4.621
    - type: recall_at_1
      value: 11.288
    - type: recall_at_10
      value: 24.941
    - type: recall_at_100
      value: 43.339
    - type: recall_at_1000
      value: 69.813
    - type: recall_at_3
      value: 16.679
    - type: recall_at_5
      value: 19.982
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.319
    - type: map_at_10
      value: 9.538
    - type: map_at_100
      value: 10.786
    - type: map_at_1000
      value: 10.979
    - type: map_at_3
      value: 7.693999999999999
    - type: map_at_5
      value: 8.623
    - type: mrr_at_1
      value: 11.922
    - type: mrr_at_10
      value: 19.683
    - type: mrr_at_100
      value: 20.881
    - type: mrr_at_1000
      value: 20.961
    - type: mrr_at_3
      value: 17.014000000000003
    - type: mrr_at_5
      value: 18.47
    - type: ndcg_at_1
      value: 11.922
    - type: ndcg_at_10
      value: 14.517
    - type: ndcg_at_100
      value: 20.541999999999998
    - type: ndcg_at_1000
      value: 24.648999999999997
    - type: ndcg_at_3
      value: 10.975
    - type: ndcg_at_5
      value: 12.276
    - type: precision_at_1
      value: 11.922
    - type: precision_at_10
      value: 4.893
    - type: precision_at_100
      value: 1.129
    - type: precision_at_1000
      value: 0.187
    - type: precision_at_3
      value: 8.382000000000001
    - type: precision_at_5
      value: 6.801
    - type: recall_at_1
      value: 5.319
    - type: recall_at_10
      value: 18.593
    - type: recall_at_100
      value: 39.957
    - type: recall_at_1000
      value: 63.748000000000005
    - type: recall_at_3
      value: 10.314
    - type: recall_at_5
      value: 13.564000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.819
    - type: map_at_10
      value: 7.771999999999999
    - type: map_at_100
      value: 10.424999999999999
    - type: map_at_1000
      value: 11.165
    - type: map_at_3
      value: 5.586
    - type: map_at_5
      value: 6.524000000000001
    - type: mrr_at_1
      value: 34.75
    - type: mrr_at_10
      value: 43.289
    - type: mrr_at_100
      value: 44.184
    - type: mrr_at_1000
      value: 44.239
    - type: mrr_at_3
      value: 40.75
    - type: mrr_at_5
      value: 42.175000000000004
    - type: ndcg_at_1
      value: 25.5
    - type: ndcg_at_10
      value: 19.994
    - type: ndcg_at_100
      value: 21.802
    - type: ndcg_at_1000
      value: 28.086
    - type: ndcg_at_3
      value: 22.279
    - type: ndcg_at_5
      value: 20.986
    - type: precision_at_1
      value: 34.75
    - type: precision_at_10
      value: 17.65
    - type: precision_at_100
      value: 5.317
    - type: precision_at_1000
      value: 1.146
    - type: precision_at_3
      value: 25.75
    - type: precision_at_5
      value: 22.400000000000002
    - type: recall_at_1
      value: 3.819
    - type: recall_at_10
      value: 11.533
    - type: recall_at_100
      value: 26.484999999999996
    - type: recall_at_1000
      value: 47.63
    - type: recall_at_3
      value: 6.268999999999999
    - type: recall_at_5
      value: 8.218
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.69500000000001
    - type: f1
      value: 39.81935458907266
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 10.544
    - type: map_at_10
      value: 16.105
    - type: map_at_100
      value: 16.91
    - type: map_at_1000
      value: 16.993
    - type: map_at_3
      value: 14.273
    - type: map_at_5
      value: 15.259
    - type: mrr_at_1
      value: 11.206000000000001
    - type: mrr_at_10
      value: 17.129
    - type: mrr_at_100
      value: 17.955
    - type: mrr_at_1000
      value: 18.032999999999998
    - type: mrr_at_3
      value: 15.214
    - type: mrr_at_5
      value: 16.249
    - type: ndcg_at_1
      value: 11.206000000000001
    - type: ndcg_at_10
      value: 19.546
    - type: ndcg_at_100
      value: 23.934
    - type: ndcg_at_1000
      value: 26.356
    - type: ndcg_at_3
      value: 15.706999999999999
    - type: ndcg_at_5
      value: 17.488999999999997
    - type: precision_at_1
      value: 11.206000000000001
    - type: precision_at_10
      value: 3.195
    - type: precision_at_100
      value: 0.557
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 6.7860000000000005
    - type: precision_at_5
      value: 4.997999999999999
    - type: recall_at_1
      value: 10.544
    - type: recall_at_10
      value: 29.421999999999997
    - type: recall_at_100
      value: 50.54
    - type: recall_at_1000
      value: 69.53200000000001
    - type: recall_at_3
      value: 18.901
    - type: recall_at_5
      value: 23.183999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.688
    - type: map_at_10
      value: 9.454
    - type: map_at_100
      value: 10.459
    - type: map_at_1000
      value: 10.645
    - type: map_at_3
      value: 7.914000000000001
    - type: map_at_5
      value: 8.622
    - type: mrr_at_1
      value: 11.42
    - type: mrr_at_10
      value: 16.608
    - type: mrr_at_100
      value: 17.566000000000003
    - type: mrr_at_1000
      value: 17.675
    - type: mrr_at_3
      value: 14.712
    - type: mrr_at_5
      value: 15.638
    - type: ndcg_at_1
      value: 11.42
    - type: ndcg_at_10
      value: 13.293
    - type: ndcg_at_100
      value: 18.289
    - type: ndcg_at_1000
      value: 22.781000000000002
    - type: ndcg_at_3
      value: 10.835
    - type: ndcg_at_5
      value: 11.576
    - type: precision_at_1
      value: 11.42
    - type: precision_at_10
      value: 3.997
    - type: precision_at_100
      value: 0.897
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_3
      value: 7.356
    - type: precision_at_5
      value: 5.772
    - type: recall_at_1
      value: 5.688
    - type: recall_at_10
      value: 17.544
    - type: recall_at_100
      value: 37.358999999999995
    - type: recall_at_1000
      value: 65.735
    - type: recall_at_3
      value: 9.987
    - type: recall_at_5
      value: 12.337
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.248
    - type: map_at_10
      value: 18.584
    - type: map_at_100
      value: 19.348000000000003
    - type: map_at_1000
      value: 19.457
    - type: map_at_3
      value: 16.962
    - type: map_at_5
      value: 17.862000000000002
    - type: mrr_at_1
      value: 26.496
    - type: mrr_at_10
      value: 32.580999999999996
    - type: mrr_at_100
      value: 33.314
    - type: mrr_at_1000
      value: 33.387
    - type: mrr_at_3
      value: 30.808000000000003
    - type: mrr_at_5
      value: 31.805
    - type: ndcg_at_1
      value: 26.496
    - type: ndcg_at_10
      value: 24.198
    - type: ndcg_at_100
      value: 28.017999999999997
    - type: ndcg_at_1000
      value: 30.839
    - type: ndcg_at_3
      value: 21.002000000000002
    - type: ndcg_at_5
      value: 22.547
    - type: precision_at_1
      value: 26.496
    - type: precision_at_10
      value: 5.415
    - type: precision_at_100
      value: 0.8500000000000001
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 13.234000000000002
    - type: precision_at_5
      value: 9.164
    - type: recall_at_1
      value: 13.248
    - type: recall_at_10
      value: 27.076
    - type: recall_at_100
      value: 42.512
    - type: recall_at_1000
      value: 61.41799999999999
    - type: recall_at_3
      value: 19.851
    - type: recall_at_5
      value: 22.91
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.98560000000001
    - type: ap
      value: 59.217561950701445
    - type: f1
      value: 63.818409911217046
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.179
    - type: map_at_10
      value: 9.055
    - type: map_at_100
      value: 9.814
    - type: map_at_1000
      value: 9.911
    - type: map_at_3
      value: 7.631
    - type: map_at_5
      value: 8.415000000000001
    - type: mrr_at_1
      value: 5.3580000000000005
    - type: mrr_at_10
      value: 9.302000000000001
    - type: mrr_at_100
      value: 10.075000000000001
    - type: mrr_at_1000
      value: 10.169
    - type: mrr_at_3
      value: 7.856000000000001
    - type: mrr_at_5
      value: 8.654
    - type: ndcg_at_1
      value: 5.33
    - type: ndcg_at_10
      value: 11.491
    - type: ndcg_at_100
      value: 15.735
    - type: ndcg_at_1000
      value: 18.721
    - type: ndcg_at_3
      value: 8.522
    - type: ndcg_at_5
      value: 9.943
    - type: precision_at_1
      value: 5.33
    - type: precision_at_10
      value: 1.983
    - type: precision_at_100
      value: 0.42
    - type: precision_at_1000
      value: 0.068
    - type: precision_at_3
      value: 3.763
    - type: precision_at_5
      value: 2.9770000000000003
    - type: recall_at_1
      value: 5.179
    - type: recall_at_10
      value: 19.069
    - type: recall_at_100
      value: 39.946
    - type: recall_at_1000
      value: 64.031
    - type: recall_at_3
      value: 10.91
    - type: recall_at_5
      value: 14.334
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.25444596443229
    - type: f1
      value: 88.34114464691379
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.3251253989968
    - type: f1
      value: 39.879870396124964
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.90316072629455
    - type: f1
      value: 59.6419867903448
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.5474108944183
    - type: f1
      value: 67.13260105586494
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.08360278577924
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.539985814012603
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.52217790319968
    - type: mrr
      value: 29.375037759331086
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.202
    - type: map_at_10
      value: 6.216
    - type: map_at_100
      value: 7.902000000000001
    - type: map_at_1000
      value: 9.114
    - type: map_at_3
      value: 4.752
    - type: map_at_5
      value: 5.414
    - type: mrr_at_1
      value: 31.269000000000002
    - type: mrr_at_10
      value: 39.649
    - type: mrr_at_100
      value: 40.261
    - type: mrr_at_1000
      value: 40.338
    - type: mrr_at_3
      value: 37.049
    - type: mrr_at_5
      value: 38.643
    - type: ndcg_at_1
      value: 29.412
    - type: ndcg_at_10
      value: 21.224
    - type: ndcg_at_100
      value: 19.897000000000002
    - type: ndcg_at_1000
      value: 29.53
    - type: ndcg_at_3
      value: 24.635
    - type: ndcg_at_5
      value: 23.114
    - type: precision_at_1
      value: 31.269000000000002
    - type: precision_at_10
      value: 15.697
    - type: precision_at_100
      value: 5.842
    - type: precision_at_1000
      value: 1.8880000000000001
    - type: precision_at_3
      value: 23.013
    - type: precision_at_5
      value: 19.628
    - type: recall_at_1
      value: 3.202
    - type: recall_at_10
      value: 9.889000000000001
    - type: recall_at_100
      value: 21.366
    - type: recall_at_1000
      value: 56.267999999999994
    - type: recall_at_3
      value: 5.7459999999999996
    - type: recall_at_5
      value: 7.473000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.892
    - type: map_at_10
      value: 13.358999999999998
    - type: map_at_100
      value: 14.396
    - type: map_at_1000
      value: 14.499
    - type: map_at_3
      value: 11.335
    - type: map_at_5
      value: 12.375
    - type: mrr_at_1
      value: 8.98
    - type: mrr_at_10
      value: 14.762
    - type: mrr_at_100
      value: 15.787
    - type: mrr_at_1000
      value: 15.873000000000001
    - type: mrr_at_3
      value: 12.65
    - type: mrr_at_5
      value: 13.761000000000001
    - type: ndcg_at_1
      value: 8.98
    - type: ndcg_at_10
      value: 17.013
    - type: ndcg_at_100
      value: 22.582
    - type: ndcg_at_1000
      value: 25.546000000000003
    - type: ndcg_at_3
      value: 12.765
    - type: ndcg_at_5
      value: 14.662
    - type: precision_at_1
      value: 8.98
    - type: precision_at_10
      value: 3.152
    - type: precision_at_100
      value: 0.636
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 5.997
    - type: precision_at_5
      value: 4.652
    - type: recall_at_1
      value: 7.892
    - type: recall_at_10
      value: 27.081
    - type: recall_at_100
      value: 53.36300000000001
    - type: recall_at_1000
      value: 76.419
    - type: recall_at_3
      value: 15.623999999999999
    - type: recall_at_5
      value: 20.104
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.224999999999994
    - type: map_at_10
      value: 73.768
    - type: map_at_100
      value: 74.54899999999999
    - type: map_at_1000
      value: 74.588
    - type: map_at_3
      value: 70.845
    - type: map_at_5
      value: 72.61
    - type: mrr_at_1
      value: 70.63000000000001
    - type: mrr_at_10
      value: 78.204
    - type: mrr_at_100
      value: 78.469
    - type: mrr_at_1000
      value: 78.477
    - type: mrr_at_3
      value: 76.67500000000001
    - type: mrr_at_5
      value: 77.644
    - type: ndcg_at_1
      value: 70.61
    - type: ndcg_at_10
      value: 78.586
    - type: ndcg_at_100
      value: 80.852
    - type: ndcg_at_1000
      value: 81.32000000000001
    - type: ndcg_at_3
      value: 74.902
    - type: ndcg_at_5
      value: 76.787
    - type: precision_at_1
      value: 70.61
    - type: precision_at_10
      value: 11.904
    - type: precision_at_100
      value: 1.438
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 32.503
    - type: precision_at_5
      value: 21.526
    - type: recall_at_1
      value: 61.224999999999994
    - type: recall_at_10
      value: 87.908
    - type: recall_at_100
      value: 96.63000000000001
    - type: recall_at_1000
      value: 99.367
    - type: recall_at_3
      value: 77.358
    - type: recall_at_5
      value: 82.584
    - type: map_at_1
      value: 2.585
    - type: map_at_10
      value: 5.988
    - type: map_at_100
      value: 7.21
    - type: map_at_1000
      value: 7.449999999999999
    - type: map_at_3
      value: 4.372
    - type: map_at_5
      value: 5.194
    - type: mrr_at_1
      value: 12.8
    - type: mrr_at_10
      value: 19.963
    - type: mrr_at_100
      value: 21.195
    - type: mrr_at_1000
      value: 21.29
    - type: mrr_at_3
      value: 17.533
    - type: mrr_at_5
      value: 18.853
    - type: ndcg_at_1
      value: 12.8
    - type: ndcg_at_10
      value: 10.874
    - type: ndcg_at_100
      value: 16.695
    - type: ndcg_at_1000
      value: 21.762999999999998
    - type: ndcg_at_3
      value: 10.209
    - type: ndcg_at_5
      value: 8.999
    - type: precision_at_1
      value: 12.8
    - type: precision_at_10
      value: 5.65
    - type: precision_at_100
      value: 1.411
    - type: precision_at_1000
      value: 0.264
    - type: precision_at_3
      value: 9.433
    - type: precision_at_5
      value: 7.88
    - type: recall_at_1
      value: 2.585
    - type: recall_at_10
      value: 11.455
    - type: recall_at_100
      value: 28.665000000000003
    - type: recall_at_1000
      value: 53.547999999999995
    - type: recall_at_3
      value: 5.748
    - type: recall_at_5
      value: 7.983
    - type: map_at_1
      value: 0.133
    - type: map_at_10
      value: 0.707
    - type: map_at_100
      value: 3.759
    - type: map_at_1000
      value: 9.02
    - type: map_at_3
      value: 0.27399999999999997
    - type: map_at_5
      value: 0.4
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 61.147
    - type: mrr_at_100
      value: 62.076
    - type: mrr_at_1000
      value: 62.076
    - type: mrr_at_3
      value: 57.99999999999999
    - type: mrr_at_5
      value: 59.3
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 36.039
    - type: ndcg_at_100
      value: 28.122999999999998
    - type: ndcg_at_1000
      value: 25.650000000000002
    - type: ndcg_at_3
      value: 38.173
    - type: ndcg_at_5
      value: 37.35
    - type: precision_at_1
      value: 52.0
    - type: precision_at_10
      value: 39.4
    - type: precision_at_100
      value: 29.82
    - type: precision_at_1000
      value: 12.690000000000001
    - type: precision_at_3
      value: 42.0
    - type: precision_at_5
      value: 40.400000000000006
    - type: recall_at_1
      value: 0.133
    - type: recall_at_10
      value: 0.897
    - type: recall_at_100
      value: 6.336
    - type: recall_at_1000
      value: 24.990000000000002
    - type: recall_at_3
      value: 0.301
    - type: recall_at_5
      value: 0.462
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 33.05951893381823
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 42.691497046210955
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.47089854443493
    - type: cos_sim_spearman
      value: 67.65881641628117
    - type: euclidean_pearson
      value: 72.75220596907191
    - type: euclidean_spearman
      value: 67.65881507675402
    - type: manhattan_pearson
      value: 71.2932268352905
    - type: manhattan_spearman
      value: 66.28937203768146
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 73.59904123111602
    - type: cos_sim_spearman
      value: 66.64191118455778
    - type: euclidean_pearson
      value: 70.031991407929
    - type: euclidean_spearman
      value: 66.64312867708462
    - type: manhattan_pearson
      value: 70.87113974670322
    - type: manhattan_spearman
      value: 67.87998624470126
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.1868454480634
    - type: cos_sim_spearman
      value: 78.5663631376088
    - type: euclidean_pearson
      value: 78.1441330499307
    - type: euclidean_spearman
      value: 78.5663753212518
    - type: manhattan_pearson
      value: 78.7258747377543
    - type: manhattan_spearman
      value: 79.24251325682667
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.39709143417873
    - type: cos_sim_spearman
      value: 74.33024682805708
    - type: euclidean_pearson
      value: 76.65457389990631
    - type: euclidean_spearman
      value: 74.33023713728515
    - type: manhattan_pearson
      value: 76.73342787471654
    - type: manhattan_spearman
      value: 74.74461118652161
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.9395037638594
    - type: cos_sim_spearman
      value: 81.01819776486752
    - type: euclidean_pearson
      value: 81.03043241994847
    - type: euclidean_spearman
      value: 81.01819627953365
    - type: manhattan_pearson
      value: 81.68968136619384
    - type: manhattan_spearman
      value: 81.82363999592259
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.243504336461
    - type: cos_sim_spearman
      value: 76.61917655422197
    - type: euclidean_pearson
      value: 76.26910712210864
    - type: euclidean_spearman
      value: 76.62000560376505
    - type: manhattan_pearson
      value: 76.91613259757325
    - type: manhattan_spearman
      value: 77.4215820608173
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.99178286054092
    - type: cos_sim_spearman
      value: 84.2361483019332
    - type: euclidean_pearson
      value: 84.30885968598922
    - type: euclidean_spearman
      value: 84.23702233300253
    - type: manhattan_pearson
      value: 84.64734537899606
    - type: manhattan_spearman
      value: 84.71355882886535
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.18741235485141
    - type: cos_sim_spearman
      value: 60.873579764468225
    - type: euclidean_pearson
      value: 63.18427359110471
    - type: euclidean_spearman
      value: 60.873579764468225
    - type: manhattan_pearson
      value: 63.443408253414354
    - type: manhattan_spearman
      value: 61.5997912341628
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.15144919426055
    - type: cos_sim_spearman
      value: 75.76050778643061
    - type: euclidean_pearson
      value: 77.30073366013343
    - type: euclidean_spearman
      value: 75.76052625455534
    - type: manhattan_pearson
      value: 77.41746598074477
    - type: manhattan_spearman
      value: 75.98770131791319
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.66070662385174
    - type: mrr
      value: 90.05894523051387
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 31.139
    - type: map_at_10
      value: 38.127
    - type: map_at_100
      value: 39.216
    - type: map_at_1000
      value: 39.290000000000006
    - type: map_at_3
      value: 35.667
    - type: map_at_5
      value: 37.317
    - type: mrr_at_1
      value: 33.333
    - type: mrr_at_10
      value: 39.972
    - type: mrr_at_100
      value: 40.892
    - type: mrr_at_1000
      value: 40.955000000000005
    - type: mrr_at_3
      value: 37.889
    - type: mrr_at_5
      value: 39.222
    - type: ndcg_at_1
      value: 33.333
    - type: ndcg_at_10
      value: 42.177
    - type: ndcg_at_100
      value: 47.772999999999996
    - type: ndcg_at_1000
      value: 49.738
    - type: ndcg_at_3
      value: 37.568
    - type: ndcg_at_5
      value: 40.294999999999995
    - type: precision_at_1
      value: 33.333
    - type: precision_at_10
      value: 5.867
    - type: precision_at_100
      value: 0.903
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 14.777999999999999
    - type: precision_at_5
      value: 10.4
    - type: recall_at_1
      value: 31.139
    - type: recall_at_10
      value: 53.056000000000004
    - type: recall_at_100
      value: 79.60000000000001
    - type: recall_at_1000
      value: 95.133
    - type: recall_at_3
      value: 40.75
    - type: recall_at_5
      value: 47.417
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.63663366336634
    - type: cos_sim_ap
      value: 87.41569381811651
    - type: cos_sim_f1
      value: 80.8154730789336
    - type: cos_sim_precision
      value: 84.66593647316539
    - type: cos_sim_recall
      value: 77.3
    - type: dot_accuracy
      value: 99.63663366336634
    - type: dot_ap
      value: 87.41569381811651
    - type: dot_f1
      value: 80.8154730789336
    - type: dot_precision
      value: 84.66593647316539
    - type: dot_recall
      value: 77.3
    - type: euclidean_accuracy
      value: 99.63663366336634
    - type: euclidean_ap
      value: 87.41569381811651
    - type: euclidean_f1
      value: 80.8154730789336
    - type: euclidean_precision
      value: 84.66593647316539
    - type: euclidean_recall
      value: 77.3
    - type: manhattan_accuracy
      value: 99.6930693069307
    - type: manhattan_ap
      value: 90.67306262109962
    - type: manhattan_f1
      value: 84.03707518022657
    - type: manhattan_precision
      value: 86.62420382165605
    - type: manhattan_recall
      value: 81.6
    - type: max_accuracy
      value: 99.6930693069307
    - type: max_ap
      value: 90.67306262109962
    - type: max_f1
      value: 84.03707518022657
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 36.46819467809413
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.142679626551587
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.08118718504021
    - type: mrr
      value: 43.547356442577026
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.26989671913281
    - type: cos_sim_spearman
      value: 30.01993799277349
    - type: dot_pearson
      value: 30.26989672303903
    - type: dot_spearman
      value: 30.03106981258351
  - 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: 8.95
    - type: map_at_100
      value: 14.699000000000002
    - type: map_at_1000
      value: 16.275000000000002
    - type: map_at_3
      value: 4.963
    - type: map_at_5
      value: 6.707000000000001
    - type: mrr_at_1
      value: 36.735
    - type: mrr_at_10
      value: 48.016
    - type: mrr_at_100
      value: 48.826
    - type: mrr_at_1000
      value: 48.826
    - type: mrr_at_3
      value: 44.558
    - type: mrr_at_5
      value: 46.394999999999996
    - type: ndcg_at_1
      value: 33.672999999999995
    - type: ndcg_at_10
      value: 21.981
    - type: ndcg_at_100
      value: 35.227000000000004
    - type: ndcg_at_1000
      value: 46.428999999999995
    - type: ndcg_at_3
      value: 27.496
    - type: ndcg_at_5
      value: 24.886
    - type: precision_at_1
      value: 36.735
    - type: precision_at_10
      value: 19.184
    - type: precision_at_100
      value: 7.754999999999999
    - type: precision_at_1000
      value: 1.486
    - type: precision_at_3
      value: 27.891
    - type: precision_at_5
      value: 24.898
    - type: recall_at_1
      value: 2.664
    - type: recall_at_10
      value: 13.309999999999999
    - type: recall_at_100
      value: 46.727000000000004
    - type: recall_at_1000
      value: 81.158
    - type: recall_at_3
      value: 5.872
    - type: recall_at_5
      value: 8.694
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.86019999999999
    - type: ap
      value: 13.439585186117995
    - type: f1
      value: 53.53111224664294
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.539898132427844
    - type: f1
      value: 53.736121370681076
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.790329189415395
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.59063002920665
    - type: cos_sim_ap
      value: 65.1646758019036
    - type: cos_sim_f1
      value: 61.95799041886746
    - type: cos_sim_precision
      value: 57.96368650884855
    - type: cos_sim_recall
      value: 66.54353562005278
    - type: dot_accuracy
      value: 83.59063002920665
    - type: dot_ap
      value: 65.1646758019036
    - type: dot_f1
      value: 61.95799041886746
    - type: dot_precision
      value: 57.96368650884855
    - type: dot_recall
      value: 66.54353562005278
    - type: euclidean_accuracy
      value: 83.59063002920665
    - type: euclidean_ap
      value: 65.1646758019036
    - type: euclidean_f1
      value: 61.95799041886746
    - type: euclidean_precision
      value: 57.96368650884855
    - type: euclidean_recall
      value: 66.54353562005278
    - type: manhattan_accuracy
      value: 83.29856350956668
    - type: manhattan_ap
      value: 63.803561536283404
    - type: manhattan_f1
      value: 60.45279383429673
    - type: manhattan_precision
      value: 55.60478511298184
    - type: manhattan_recall
      value: 66.2269129287599
    - type: max_accuracy
      value: 83.59063002920665
    - type: max_ap
      value: 65.1646758019036
    - type: max_f1
      value: 61.95799041886746
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.46264602010324
    - type: cos_sim_ap
      value: 82.64331601180713
    - type: cos_sim_f1
      value: 74.66489420627008
    - type: cos_sim_precision
      value: 71.73774214148868
    - type: cos_sim_recall
      value: 77.8410840776101
    - type: dot_accuracy
      value: 87.46264602010324
    - type: dot_ap
      value: 82.64331811121104
    - type: dot_f1
      value: 74.66489420627008
    - type: dot_precision
      value: 71.73774214148868
    - type: dot_recall
      value: 77.8410840776101
    - type: euclidean_accuracy
      value: 87.46264602010324
    - type: euclidean_ap
      value: 82.64331792274162
    - type: euclidean_f1
      value: 74.66489420627008
    - type: euclidean_precision
      value: 71.73774214148868
    - type: euclidean_recall
      value: 77.8410840776101
    - type: manhattan_accuracy
      value: 87.35203943027904
    - type: manhattan_ap
      value: 82.69548093072707
    - type: manhattan_f1
      value: 74.90158915293776
    - type: manhattan_precision
      value: 71.1171096345515
    - type: manhattan_recall
      value: 79.11148752694795
    - type: max_accuracy
      value: 87.46264602010324
    - type: max_ap
      value: 82.69548093072707
    - type: max_f1
      value: 74.90158915293776
---
