mteb model-index region:us
---
tags:
- mteb
model-index:
- name: sent2vec_main_BERTtok_noPunct_normalise_True
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 78.41791044776119
    - type: ap
      value: 42.25569751541089
    - type: f1
      value: 72.43269265244831
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 61.3757
    - type: ap
      value: 57.04485974586232
    - type: f1
      value: 61.26466853396384
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.094
    - type: f1
      value: 30.785103843359906
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.772000000000002
    - type: map_at_10
      value: 33.863
    - type: map_at_100
      value: 35.071999999999996
    - type: map_at_1000
      value: 35.093
    - type: map_at_3
      value: 28.864
    - type: map_at_5
      value: 31.411
    - type: mrr_at_1
      value: 20.199
    - type: mrr_at_10
      value: 34.025
    - type: mrr_at_100
      value: 35.241
    - type: mrr_at_1000
      value: 35.263
    - type: mrr_at_3
      value: 29.03
    - type: mrr_at_5
      value: 31.545
    - type: ndcg_at_1
      value: 19.772000000000002
    - type: ndcg_at_10
      value: 42.408
    - type: ndcg_at_100
      value: 47.99
    - type: ndcg_at_1000
      value: 48.518
    - type: ndcg_at_3
      value: 31.861
    - type: ndcg_at_5
      value: 36.47
    - type: precision_at_1
      value: 19.772000000000002
    - type: precision_at_10
      value: 7.013
    - type: precision_at_100
      value: 0.955
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 13.514000000000001
    - type: precision_at_5
      value: 10.356
    - type: recall_at_1
      value: 19.772000000000002
    - type: recall_at_10
      value: 70.128
    - type: recall_at_100
      value: 95.519
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 40.541
    - type: recall_at_5
      value: 51.778
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.88029972847573
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 30.428577037304606
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 50.47113867778671
    - type: mrr
      value: 63.90735610957216
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 62.29174670648191
    - type: cos_sim_spearman
      value: 59.27183247662248
    - type: euclidean_pearson
      value: 61.72118923273273
    - type: euclidean_spearman
      value: 59.27183247662248
    - type: manhattan_pearson
      value: 60.783892648092696
    - type: manhattan_spearman
      value: 58.722422367578986
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.82142857142858
    - type: f1
      value: 66.92102518619261
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.329773772744545
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 26.226220147948837
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.81
    - type: map_at_10
      value: 24.413
    - type: map_at_100
      value: 25.496000000000002
    - type: map_at_1000
      value: 25.635
    - type: map_at_3
      value: 22.616
    - type: map_at_5
      value: 23.613
    - type: mrr_at_1
      value: 24.177
    - type: mrr_at_10
      value: 29.407
    - type: mrr_at_100
      value: 30.322
    - type: mrr_at_1000
      value: 30.403999999999996
    - type: mrr_at_3
      value: 27.682000000000002
    - type: mrr_at_5
      value: 28.754999999999995
    - type: ndcg_at_1
      value: 24.177
    - type: ndcg_at_10
      value: 28.375
    - type: ndcg_at_100
      value: 33.412
    - type: ndcg_at_1000
      value: 36.735
    - type: ndcg_at_3
      value: 25.661
    - type: ndcg_at_5
      value: 26.844
    - type: precision_at_1
      value: 24.177
    - type: precision_at_10
      value: 5.222
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 12.065
    - type: precision_at_5
      value: 8.555
    - type: recall_at_1
      value: 18.81
    - type: recall_at_10
      value: 35.197
    - type: recall_at_100
      value: 57.727
    - type: recall_at_1000
      value: 81.157
    - type: recall_at_3
      value: 26.354
    - type: recall_at_5
      value: 30.275999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.448
    - type: map_at_10
      value: 22.088
    - type: map_at_100
      value: 23.008
    - type: map_at_1000
      value: 23.132
    - type: map_at_3
      value: 20.455000000000002
    - type: map_at_5
      value: 21.254
    - type: mrr_at_1
      value: 21.337999999999997
    - type: mrr_at_10
      value: 26.791999999999998
    - type: mrr_at_100
      value: 27.528999999999996
    - type: mrr_at_1000
      value: 27.604
    - type: mrr_at_3
      value: 25.296999999999997
    - type: mrr_at_5
      value: 25.985000000000003
    - type: ndcg_at_1
      value: 21.337999999999997
    - type: ndcg_at_10
      value: 25.835
    - type: ndcg_at_100
      value: 29.959999999999997
    - type: ndcg_at_1000
      value: 32.927
    - type: ndcg_at_3
      value: 23.202
    - type: ndcg_at_5
      value: 24.126
    - type: precision_at_1
      value: 21.337999999999997
    - type: precision_at_10
      value: 4.8149999999999995
    - type: precision_at_100
      value: 0.886
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.274000000000001
    - type: precision_at_5
      value: 7.809000000000001
    - type: recall_at_1
      value: 16.448
    - type: recall_at_10
      value: 32.444
    - type: recall_at_100
      value: 50.44499999999999
    - type: recall_at_1000
      value: 71.193
    - type: recall_at_3
      value: 24.034
    - type: recall_at_5
      value: 26.950000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.152
    - type: map_at_10
      value: 31.480999999999998
    - type: map_at_100
      value: 32.454
    - type: map_at_1000
      value: 32.556000000000004
    - type: map_at_3
      value: 29.264000000000003
    - type: map_at_5
      value: 30.497999999999998
    - type: mrr_at_1
      value: 27.586
    - type: mrr_at_10
      value: 34.353
    - type: mrr_at_100
      value: 35.166
    - type: mrr_at_1000
      value: 35.237
    - type: mrr_at_3
      value: 32.226
    - type: mrr_at_5
      value: 33.527
    - type: ndcg_at_1
      value: 27.586
    - type: ndcg_at_10
      value: 35.782000000000004
    - type: ndcg_at_100
      value: 40.466
    - type: ndcg_at_1000
      value: 42.856
    - type: ndcg_at_3
      value: 31.627
    - type: ndcg_at_5
      value: 33.637
    - type: precision_at_1
      value: 27.586
    - type: precision_at_10
      value: 5.755
    - type: precision_at_100
      value: 0.8920000000000001
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 13.898
    - type: precision_at_5
      value: 9.705
    - type: recall_at_1
      value: 24.152
    - type: recall_at_10
      value: 46.039
    - type: recall_at_100
      value: 67.241
    - type: recall_at_1000
      value: 84.48
    - type: recall_at_3
      value: 34.71
    - type: recall_at_5
      value: 39.667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 9.925
    - type: map_at_10
      value: 13.233
    - type: map_at_100
      value: 13.937
    - type: map_at_1000
      value: 14.036000000000001
    - type: map_at_3
      value: 11.745
    - type: map_at_5
      value: 12.497
    - type: mrr_at_1
      value: 10.621
    - type: mrr_at_10
      value: 14.072999999999999
    - type: mrr_at_100
      value: 14.811
    - type: mrr_at_1000
      value: 14.901
    - type: mrr_at_3
      value: 12.617999999999999
    - type: mrr_at_5
      value: 13.358
    - type: ndcg_at_1
      value: 10.621
    - type: ndcg_at_10
      value: 15.537
    - type: ndcg_at_100
      value: 19.493
    - type: ndcg_at_1000
      value: 22.517
    - type: ndcg_at_3
      value: 12.533
    - type: ndcg_at_5
      value: 13.819999999999999
    - type: precision_at_1
      value: 10.621
    - type: precision_at_10
      value: 2.554
    - type: precision_at_100
      value: 0.479
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 5.235
    - type: precision_at_5
      value: 3.91
    - type: recall_at_1
      value: 9.925
    - type: recall_at_10
      value: 21.977
    - type: recall_at_100
      value: 41.128
    - type: recall_at_1000
      value: 64.911
    - type: recall_at_3
      value: 13.861
    - type: recall_at_5
      value: 16.798
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.345
    - type: map_at_10
      value: 8.312
    - type: map_at_100
      value: 9.051
    - type: map_at_1000
      value: 9.171999999999999
    - type: map_at_3
      value: 7.148000000000001
    - type: map_at_5
      value: 7.837
    - type: mrr_at_1
      value: 7.463
    - type: mrr_at_10
      value: 10.921
    - type: mrr_at_100
      value: 11.677999999999999
    - type: mrr_at_1000
      value: 11.777
    - type: mrr_at_3
      value: 9.515
    - type: mrr_at_5
      value: 10.224
    - type: ndcg_at_1
      value: 7.463
    - type: ndcg_at_10
      value: 10.671999999999999
    - type: ndcg_at_100
      value: 14.802000000000001
    - type: ndcg_at_1000
      value: 18.385
    - type: ndcg_at_3
      value: 8.382000000000001
    - type: ndcg_at_5
      value: 9.467
    - type: precision_at_1
      value: 7.463
    - type: precision_at_10
      value: 2.214
    - type: precision_at_100
      value: 0.504
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.312
    - type: precision_at_5
      value: 3.3329999999999997
    - type: recall_at_1
      value: 5.345
    - type: recall_at_10
      value: 15.528
    - type: recall_at_100
      value: 34.575
    - type: recall_at_1000
      value: 61.358999999999995
    - type: recall_at_3
      value: 9.207
    - type: recall_at_5
      value: 11.974
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.695
    - type: map_at_10
      value: 23.62
    - type: map_at_100
      value: 24.758
    - type: map_at_1000
      value: 24.893
    - type: map_at_3
      value: 21.747
    - type: map_at_5
      value: 22.701
    - type: mrr_at_1
      value: 22.425
    - type: mrr_at_10
      value: 27.628999999999998
    - type: mrr_at_100
      value: 28.603
    - type: mrr_at_1000
      value: 28.686
    - type: mrr_at_3
      value: 25.794
    - type: mrr_at_5
      value: 26.728
    - type: ndcg_at_1
      value: 22.425
    - type: ndcg_at_10
      value: 27.336
    - type: ndcg_at_100
      value: 33.155
    - type: ndcg_at_1000
      value: 36.335
    - type: ndcg_at_3
      value: 24.048
    - type: ndcg_at_5
      value: 25.4
    - type: precision_at_1
      value: 22.425
    - type: precision_at_10
      value: 4.841
    - type: precision_at_100
      value: 0.9209999999999999
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_3
      value: 10.876
    - type: precision_at_5
      value: 7.642
    - type: recall_at_1
      value: 18.695
    - type: recall_at_10
      value: 34.659
    - type: recall_at_100
      value: 60.94199999999999
    - type: recall_at_1000
      value: 83.005
    - type: recall_at_3
      value: 25.255
    - type: recall_at_5
      value: 28.882
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.322999999999999
    - type: map_at_10
      value: 17.906
    - type: map_at_100
      value: 18.986
    - type: map_at_1000
      value: 19.121
    - type: map_at_3
      value: 16.441
    - type: map_at_5
      value: 17.149
    - type: mrr_at_1
      value: 16.438
    - type: mrr_at_10
      value: 21.108
    - type: mrr_at_100
      value: 22.144
    - type: mrr_at_1000
      value: 22.235
    - type: mrr_at_3
      value: 19.73
    - type: mrr_at_5
      value: 20.358
    - type: ndcg_at_1
      value: 16.438
    - type: ndcg_at_10
      value: 20.952
    - type: ndcg_at_100
      value: 26.39
    - type: ndcg_at_1000
      value: 29.892999999999997
    - type: ndcg_at_3
      value: 18.374
    - type: ndcg_at_5
      value: 19.276
    - type: precision_at_1
      value: 16.438
    - type: precision_at_10
      value: 3.7670000000000003
    - type: precision_at_100
      value: 0.768
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 8.676
    - type: precision_at_5
      value: 6.0729999999999995
    - type: recall_at_1
      value: 13.322999999999999
    - type: recall_at_10
      value: 27.127000000000002
    - type: recall_at_100
      value: 51.18899999999999
    - type: recall_at_1000
      value: 76.281
    - type: recall_at_3
      value: 19.84
    - type: recall_at_5
      value: 22.183
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.133333333333333
    - type: map_at_10
      value: 17.423833333333334
    - type: map_at_100
      value: 18.282916666666665
    - type: map_at_1000
      value: 18.404833333333336
    - type: map_at_3
      value: 15.924583333333336
    - type: map_at_5
      value: 16.736416666666663
    - type: mrr_at_1
      value: 15.967
    - type: mrr_at_10
      value: 20.30225
    - type: mrr_at_100
      value: 21.10133333333333
    - type: mrr_at_1000
      value: 21.189833333333333
    - type: mrr_at_3
      value: 18.80633333333333
    - type: mrr_at_5
      value: 19.632250000000003
    - type: ndcg_at_1
      value: 15.967
    - type: ndcg_at_10
      value: 20.442083333333333
    - type: ndcg_at_100
      value: 24.815083333333334
    - type: ndcg_at_1000
      value: 28.00433333333333
    - type: ndcg_at_3
      value: 17.737916666666667
    - type: ndcg_at_5
      value: 18.947750000000003
    - type: precision_at_1
      value: 15.967
    - type: precision_at_10
      value: 3.606833333333333
    - type: precision_at_100
      value: 0.6947500000000001
    - type: precision_at_1000
      value: 0.11408333333333331
    - type: precision_at_3
      value: 8.130083333333333
    - type: precision_at_5
      value: 5.840583333333333
    - type: recall_at_1
      value: 13.133333333333333
    - type: recall_at_10
      value: 26.80541666666667
    - type: recall_at_100
      value: 46.90025
    - type: recall_at_1000
      value: 70.29883333333335
    - type: recall_at_3
      value: 19.008583333333338
    - type: recall_at_5
      value: 22.206583333333338
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.577
    - type: map_at_10
      value: 13.016
    - type: map_at_100
      value: 13.746
    - type: map_at_1000
      value: 13.841999999999999
    - type: map_at_3
      value: 11.713999999999999
    - type: map_at_5
      value: 12.416
    - type: mrr_at_1
      value: 11.503
    - type: mrr_at_10
      value: 15.018
    - type: mrr_at_100
      value: 15.786
    - type: mrr_at_1000
      value: 15.870999999999999
    - type: mrr_at_3
      value: 13.855
    - type: mrr_at_5
      value: 14.438
    - type: ndcg_at_1
      value: 11.503
    - type: ndcg_at_10
      value: 15.464
    - type: ndcg_at_100
      value: 19.461000000000002
    - type: ndcg_at_1000
      value: 22.226000000000003
    - type: ndcg_at_3
      value: 13.092
    - type: ndcg_at_5
      value: 14.129
    - type: precision_at_1
      value: 11.503
    - type: precision_at_10
      value: 2.699
    - type: precision_at_100
      value: 0.505
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 5.982
    - type: precision_at_5
      value: 4.356
    - type: recall_at_1
      value: 9.577
    - type: recall_at_10
      value: 21.171
    - type: recall_at_100
      value: 40.012
    - type: recall_at_1000
      value: 61.024
    - type: recall_at_3
      value: 14.399000000000001
    - type: recall_at_5
      value: 17.101
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.856
    - type: map_at_10
      value: 9.584
    - type: map_at_100
      value: 10.174999999999999
    - type: map_at_1000
      value: 10.285
    - type: map_at_3
      value: 8.588
    - type: map_at_5
      value: 9.061
    - type: mrr_at_1
      value: 8.878
    - type: mrr_at_10
      value: 11.779
    - type: mrr_at_100
      value: 12.403
    - type: mrr_at_1000
      value: 12.494
    - type: mrr_at_3
      value: 10.742
    - type: mrr_at_5
      value: 11.258
    - type: ndcg_at_1
      value: 8.878
    - type: ndcg_at_10
      value: 11.703
    - type: ndcg_at_100
      value: 14.921999999999999
    - type: ndcg_at_1000
      value: 18.199
    - type: ndcg_at_3
      value: 9.838
    - type: ndcg_at_5
      value: 10.533
    - type: precision_at_1
      value: 8.878
    - type: precision_at_10
      value: 2.223
    - type: precision_at_100
      value: 0.466
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 4.68
    - type: precision_at_5
      value: 3.4000000000000004
    - type: recall_at_1
      value: 6.856
    - type: recall_at_10
      value: 16.051000000000002
    - type: recall_at_100
      value: 31.025000000000002
    - type: recall_at_1000
      value: 55.723
    - type: recall_at_3
      value: 10.607999999999999
    - type: recall_at_5
      value: 12.492
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.244
    - type: map_at_10
      value: 14.343
    - type: map_at_100
      value: 15.042
    - type: map_at_1000
      value: 15.152
    - type: map_at_3
      value: 13.153
    - type: map_at_5
      value: 13.811000000000002
    - type: mrr_at_1
      value: 13.433
    - type: mrr_at_10
      value: 16.703000000000003
    - type: mrr_at_100
      value: 17.433
    - type: mrr_at_1000
      value: 17.531
    - type: mrr_at_3
      value: 15.454
    - type: mrr_at_5
      value: 16.191
    - type: ndcg_at_1
      value: 13.433
    - type: ndcg_at_10
      value: 16.704
    - type: ndcg_at_100
      value: 20.66
    - type: ndcg_at_1000
      value: 23.927
    - type: ndcg_at_3
      value: 14.454
    - type: ndcg_at_5
      value: 15.512999999999998
    - type: precision_at_1
      value: 13.433
    - type: precision_at_10
      value: 2.743
    - type: precision_at_100
      value: 0.53
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.436999999999999
    - type: precision_at_5
      value: 4.552
    - type: recall_at_1
      value: 11.244
    - type: recall_at_10
      value: 21.833
    - type: recall_at_100
      value: 40.5
    - type: recall_at_1000
      value: 64.981
    - type: recall_at_3
      value: 15.442
    - type: recall_at_5
      value: 18.264
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.008000000000001
    - type: map_at_10
      value: 18.439
    - type: map_at_100
      value: 19.403000000000002
    - type: map_at_1000
      value: 19.593
    - type: map_at_3
      value: 16.975
    - type: map_at_5
      value: 17.947
    - type: mrr_at_1
      value: 17.391000000000002
    - type: mrr_at_10
      value: 21.95
    - type: mrr_at_100
      value: 22.755
    - type: mrr_at_1000
      value: 22.852
    - type: mrr_at_3
      value: 20.224
    - type: mrr_at_5
      value: 21.459
    - type: ndcg_at_1
      value: 17.391000000000002
    - type: ndcg_at_10
      value: 21.795
    - type: ndcg_at_100
      value: 25.939
    - type: ndcg_at_1000
      value: 29.677
    - type: ndcg_at_3
      value: 19.309
    - type: ndcg_at_5
      value: 20.907
    - type: precision_at_1
      value: 17.391000000000002
    - type: precision_at_10
      value: 3.972
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.174
    - type: precision_at_3
      value: 8.827
    - type: precision_at_5
      value: 6.7589999999999995
    - type: recall_at_1
      value: 14.008000000000001
    - type: recall_at_10
      value: 27.717000000000002
    - type: recall_at_100
      value: 46.787
    - type: recall_at_1000
      value: 72.724
    - type: recall_at_3
      value: 20.179
    - type: recall_at_5
      value: 24.288999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.217
    - type: map_at_10
      value: 12.651000000000002
    - type: map_at_100
      value: 13.339
    - type: map_at_1000
      value: 13.441
    - type: map_at_3
      value: 11.249
    - type: map_at_5
      value: 12.052999999999999
    - type: mrr_at_1
      value: 10.351
    - type: mrr_at_10
      value: 13.894
    - type: mrr_at_100
      value: 14.585999999999999
    - type: mrr_at_1000
      value: 14.686
    - type: mrr_at_3
      value: 12.539
    - type: mrr_at_5
      value: 13.306000000000001
    - type: ndcg_at_1
      value: 10.351
    - type: ndcg_at_10
      value: 15.15
    - type: ndcg_at_100
      value: 19.121
    - type: ndcg_at_1000
      value: 22.375
    - type: ndcg_at_3
      value: 12.335
    - type: ndcg_at_5
      value: 13.721
    - type: precision_at_1
      value: 10.351
    - type: precision_at_10
      value: 2.477
    - type: precision_at_100
      value: 0.484
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 5.299
    - type: precision_at_5
      value: 3.993
    - type: recall_at_1
      value: 9.217
    - type: recall_at_10
      value: 21.922
    - type: recall_at_100
      value: 41.232
    - type: recall_at_1000
      value: 66.74799999999999
    - type: recall_at_3
      value: 14.213999999999999
    - type: recall_at_5
      value: 17.602999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.405
    - type: map_at_10
      value: 13.173000000000002
    - type: map_at_100
      value: 14.824000000000002
    - type: map_at_1000
      value: 15.052
    - type: map_at_3
      value: 10.634
    - type: map_at_5
      value: 11.877
    - type: mrr_at_1
      value: 16.743
    - type: mrr_at_10
      value: 26.816000000000003
    - type: mrr_at_100
      value: 28.005000000000003
    - type: mrr_at_1000
      value: 28.064
    - type: mrr_at_3
      value: 23.344
    - type: mrr_at_5
      value: 25.324999999999996
    - type: ndcg_at_1
      value: 16.743
    - type: ndcg_at_10
      value: 19.874
    - type: ndcg_at_100
      value: 27.168999999999997
    - type: ndcg_at_1000
      value: 31.406
    - type: ndcg_at_3
      value: 15.219
    - type: ndcg_at_5
      value: 16.85
    - type: precision_at_1
      value: 16.743
    - type: precision_at_10
      value: 6.691
    - type: precision_at_100
      value: 1.4409999999999998
    - type: precision_at_1000
      value: 0.22100000000000003
    - type: precision_at_3
      value: 11.618
    - type: precision_at_5
      value: 9.42
    - type: recall_at_1
      value: 7.405
    - type: recall_at_10
      value: 25.295
    - type: recall_at_100
      value: 51.123
    - type: recall_at_1000
      value: 75.141
    - type: recall_at_3
      value: 14.14
    - type: recall_at_5
      value: 18.506
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.697
    - type: map_at_10
      value: 9.717
    - type: map_at_100
      value: 14.616999999999999
    - type: map_at_1000
      value: 15.794
    - type: map_at_3
      value: 6.671
    - type: map_at_5
      value: 7.9399999999999995
    - type: mrr_at_1
      value: 39.25
    - type: mrr_at_10
      value: 49.867
    - type: mrr_at_100
      value: 50.724000000000004
    - type: mrr_at_1000
      value: 50.747
    - type: mrr_at_3
      value: 47.583
    - type: mrr_at_5
      value: 49.083
    - type: ndcg_at_1
      value: 28.375
    - type: ndcg_at_10
      value: 24.157
    - type: ndcg_at_100
      value: 28.707
    - type: ndcg_at_1000
      value: 36.187999999999995
    - type: ndcg_at_3
      value: 26.237
    - type: ndcg_at_5
      value: 25.043
    - type: precision_at_1
      value: 39.25
    - type: precision_at_10
      value: 22.35
    - type: precision_at_100
      value: 7.580000000000001
    - type: precision_at_1000
      value: 1.559
    - type: precision_at_3
      value: 32.583
    - type: precision_at_5
      value: 28.449999999999996
    - type: recall_at_1
      value: 3.697
    - type: recall_at_10
      value: 14.566
    - type: recall_at_100
      value: 36.595
    - type: recall_at_1000
      value: 62.83
    - type: recall_at_3
      value: 8.268
    - type: recall_at_5
      value: 10.700999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 32.065
    - type: f1
      value: 29.16832120500216
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 15.042
    - type: map_at_10
      value: 23.017000000000003
    - type: map_at_100
      value: 24.038999999999998
    - type: map_at_1000
      value: 24.115000000000002
    - type: map_at_3
      value: 20.185
    - type: map_at_5
      value: 21.801000000000002
    - type: mrr_at_1
      value: 15.992
    - type: mrr_at_10
      value: 24.396
    - type: mrr_at_100
      value: 25.405
    - type: mrr_at_1000
      value: 25.47
    - type: mrr_at_3
      value: 21.45
    - type: mrr_at_5
      value: 23.13
    - type: ndcg_at_1
      value: 15.992
    - type: ndcg_at_10
      value: 28.060000000000002
    - type: ndcg_at_100
      value: 33.217
    - type: ndcg_at_1000
      value: 35.283
    - type: ndcg_at_3
      value: 22.198999999999998
    - type: ndcg_at_5
      value: 25.112000000000002
    - type: precision_at_1
      value: 15.992
    - type: precision_at_10
      value: 4.6370000000000005
    - type: precision_at_100
      value: 0.741
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 9.586
    - type: precision_at_5
      value: 7.2940000000000005
    - type: recall_at_1
      value: 15.042
    - type: recall_at_10
      value: 42.653
    - type: recall_at_100
      value: 66.649
    - type: recall_at_1000
      value: 82.531
    - type: recall_at_3
      value: 26.778999999999996
    - type: recall_at_5
      value: 33.728
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.313000000000001
    - type: map_at_10
      value: 10.087
    - type: map_at_100
      value: 11.245
    - type: map_at_1000
      value: 11.42
    - type: map_at_3
      value: 8.462
    - type: map_at_5
      value: 9.325
    - type: mrr_at_1
      value: 12.5
    - type: mrr_at_10
      value: 18.041
    - type: mrr_at_100
      value: 19.017999999999997
    - type: mrr_at_1000
      value: 19.124
    - type: mrr_at_3
      value: 15.972
    - type: mrr_at_5
      value: 17.122
    - type: ndcg_at_1
      value: 12.5
    - type: ndcg_at_10
      value: 14.165
    - type: ndcg_at_100
      value: 19.7
    - type: ndcg_at_1000
      value: 23.897
    - type: ndcg_at_3
      value: 11.66
    - type: ndcg_at_5
      value: 12.616
    - type: precision_at_1
      value: 12.5
    - type: precision_at_10
      value: 4.275
    - type: precision_at_100
      value: 0.972
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 7.767
    - type: precision_at_5
      value: 6.389
    - type: recall_at_1
      value: 6.313000000000001
    - type: recall_at_10
      value: 18.147
    - type: recall_at_100
      value: 40.111000000000004
    - type: recall_at_1000
      value: 66.507
    - type: recall_at_3
      value: 10.617
    - type: recall_at_5
      value: 13.577
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 17.016000000000002
    - type: map_at_10
      value: 24.376
    - type: map_at_100
      value: 25.365
    - type: map_at_1000
      value: 25.485000000000003
    - type: map_at_3
      value: 22.288
    - type: map_at_5
      value: 23.432
    - type: mrr_at_1
      value: 34.031
    - type: mrr_at_10
      value: 41.53
    - type: mrr_at_100
      value: 42.28
    - type: mrr_at_1000
      value: 42.333
    - type: mrr_at_3
      value: 39.48
    - type: mrr_at_5
      value: 40.654
    - type: ndcg_at_1
      value: 34.031
    - type: ndcg_at_10
      value: 31.326999999999998
    - type: ndcg_at_100
      value: 35.845
    - type: ndcg_at_1000
      value: 38.635999999999996
    - type: ndcg_at_3
      value: 27.364
    - type: ndcg_at_5
      value: 29.284
    - type: precision_at_1
      value: 34.031
    - type: precision_at_10
      value: 7.005
    - type: precision_at_100
      value: 1.0619999999999998
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_3
      value: 17.385
    - type: precision_at_5
      value: 11.956999999999999
    - type: recall_at_1
      value: 17.016000000000002
    - type: recall_at_10
      value: 35.024
    - type: recall_at_100
      value: 53.113
    - type: recall_at_1000
      value: 71.776
    - type: recall_at_3
      value: 26.077
    - type: recall_at_5
      value: 29.892000000000003
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 59.41600000000001
    - type: ap
      value: 55.7436036225634
    - type: f1
      value: 59.054381876483475
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 4.468
    - type: map_at_10
      value: 7.446999999999999
    - type: map_at_100
      value: 8.178
    - type: map_at_1000
      value: 8.283
    - type: map_at_3
      value: 6.321000000000001
    - type: map_at_5
      value: 6.895
    - type: mrr_at_1
      value: 4.542
    - type: mrr_at_10
      value: 7.6240000000000006
    - type: mrr_at_100
      value: 8.361
    - type: mrr_at_1000
      value: 8.464
    - type: mrr_at_3
      value: 6.468
    - type: mrr_at_5
      value: 7.062
    - type: ndcg_at_1
      value: 4.542
    - type: ndcg_at_10
      value: 9.363000000000001
    - type: ndcg_at_100
      value: 13.533000000000001
    - type: ndcg_at_1000
      value: 16.775000000000002
    - type: ndcg_at_3
      value: 6.98
    - type: ndcg_at_5
      value: 8.02
    - type: precision_at_1
      value: 4.542
    - type: precision_at_10
      value: 1.599
    - type: precision_at_100
      value: 0.379
    - type: precision_at_1000
      value: 0.066
    - type: precision_at_3
      value: 3.004
    - type: precision_at_5
      value: 2.327
    - type: recall_at_1
      value: 4.468
    - type: recall_at_10
      value: 15.351999999999999
    - type: recall_at_100
      value: 36.035000000000004
    - type: recall_at_1000
      value: 62.18
    - type: recall_at_3
      value: 8.744
    - type: recall_at_5
      value: 11.242
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.19334245326037
    - type: f1
      value: 86.53113330755195
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 62.968536251709985
    - type: f1
      value: 41.745605561498856
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.725622057834556
    - type: f1
      value: 56.7455479326888
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.08271687962339
    - type: f1
      value: 64.50271836543025
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.29414331190791
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.743625453318558
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.22281471544121
    - type: mrr
      value: 30.160864819580873
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.392
    - type: map_at_10
      value: 7.062
    - type: map_at_100
      value: 9.11
    - type: map_at_1000
      value: 10.464
    - type: map_at_3
      value: 5.389
    - type: map_at_5
      value: 6.213
    - type: mrr_at_1
      value: 29.412
    - type: mrr_at_10
      value: 39.061
    - type: mrr_at_100
      value: 39.948
    - type: mrr_at_1000
      value: 39.993
    - type: mrr_at_3
      value: 35.759
    - type: mrr_at_5
      value: 38.127
    - type: ndcg_at_1
      value: 28.019
    - type: ndcg_at_10
      value: 22.771
    - type: ndcg_at_100
      value: 21.962
    - type: ndcg_at_1000
      value: 31.907999999999998
    - type: ndcg_at_3
      value: 25.093
    - type: ndcg_at_5
      value: 24.5
    - type: precision_at_1
      value: 29.412
    - type: precision_at_10
      value: 17.121
    - type: precision_at_100
      value: 6.279
    - type: precision_at_1000
      value: 1.9800000000000002
    - type: precision_at_3
      value: 23.529
    - type: precision_at_5
      value: 21.486
    - type: recall_at_1
      value: 3.392
    - type: recall_at_10
      value: 11.437
    - type: recall_at_100
      value: 25.005
    - type: recall_at_1000
      value: 59.95399999999999
    - type: recall_at_3
      value: 6.75
    - type: recall_at_5
      value: 8.891
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.077
    - type: map_at_10
      value: 14.743
    - type: map_at_100
      value: 16.127
    - type: map_at_1000
      value: 16.247
    - type: map_at_3
      value: 12.029
    - type: map_at_5
      value: 13.623
    - type: mrr_at_1
      value: 9.328
    - type: mrr_at_10
      value: 16.439
    - type: mrr_at_100
      value: 17.701
    - type: mrr_at_1000
      value: 17.799
    - type: mrr_at_3
      value: 13.62
    - type: mrr_at_5
      value: 15.290000000000001
    - type: ndcg_at_1
      value: 9.328
    - type: ndcg_at_10
      value: 19.331
    - type: ndcg_at_100
      value: 26.301000000000002
    - type: ndcg_at_1000
      value: 29.461
    - type: ndcg_at_3
      value: 13.761000000000001
    - type: ndcg_at_5
      value: 16.633
    - type: precision_at_1
      value: 9.328
    - type: precision_at_10
      value: 3.734
    - type: precision_at_100
      value: 0.77
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 6.586
    - type: precision_at_5
      value: 5.521
    - type: recall_at_1
      value: 8.077
    - type: recall_at_10
      value: 32.007999999999996
    - type: recall_at_100
      value: 64.327
    - type: recall_at_1000
      value: 88.374
    - type: recall_at_3
      value: 17.277
    - type: recall_at_5
      value: 24.008
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 50.542
    - type: map_at_10
      value: 62.251999999999995
    - type: map_at_100
      value: 63.21
    - type: map_at_1000
      value: 63.260000000000005
    - type: map_at_3
      value: 59.134
    - type: map_at_5
      value: 60.965
    - type: mrr_at_1
      value: 58.13
    - type: mrr_at_10
      value: 66.899
    - type: mrr_at_100
      value: 67.36
    - type: mrr_at_1000
      value: 67.377
    - type: mrr_at_3
      value: 64.825
    - type: mrr_at_5
      value: 66.103
    - type: ndcg_at_1
      value: 58.13
    - type: ndcg_at_10
      value: 67.713
    - type: ndcg_at_100
      value: 71.039
    - type: ndcg_at_1000
      value: 71.84700000000001
    - type: ndcg_at_3
      value: 63.102000000000004
    - type: ndcg_at_5
      value: 65.416
    - type: precision_at_1
      value: 58.13
    - type: precision_at_10
      value: 10.504
    - type: precision_at_100
      value: 1.353
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 27.439999999999998
    - type: precision_at_5
      value: 18.509999999999998
    - type: recall_at_1
      value: 50.542
    - type: recall_at_10
      value: 79.107
    - type: recall_at_100
      value: 92.632
    - type: recall_at_1000
      value: 97.84
    - type: recall_at_3
      value: 66.28500000000001
    - type: recall_at_5
      value: 72.342
    - type: map_at_1
      value: 2.563
    - type: map_at_10
      value: 6.265999999999999
    - type: map_at_100
      value: 7.577
    - type: map_at_1000
      value: 7.847999999999999
    - type: map_at_3
      value: 4.643
    - type: map_at_5
      value: 5.442
    - type: mrr_at_1
      value: 12.6
    - type: mrr_at_10
      value: 20.934
    - type: mrr_at_100
      value: 22.141
    - type: mrr_at_1000
      value: 22.23
    - type: mrr_at_3
      value: 18.3
    - type: mrr_at_5
      value: 19.759999999999998
    - type: ndcg_at_1
      value: 12.6
    - type: ndcg_at_10
      value: 11.494
    - type: ndcg_at_100
      value: 17.775
    - type: ndcg_at_1000
      value: 23.173
    - type: ndcg_at_3
      value: 10.905
    - type: ndcg_at_5
      value: 9.532
    - type: precision_at_1
      value: 12.6
    - type: precision_at_10
      value: 6.01
    - type: precision_at_100
      value: 1.528
    - type: precision_at_1000
      value: 0.28300000000000003
    - type: precision_at_3
      value: 10.366999999999999
    - type: precision_at_5
      value: 8.48
    - type: recall_at_1
      value: 2.563
    - type: recall_at_10
      value: 12.182
    - type: recall_at_100
      value: 31.038
    - type: recall_at_1000
      value: 57.56
    - type: recall_at_3
      value: 6.317
    - type: recall_at_5
      value: 8.597000000000001
    - type: map_at_1
      value: 0.13
    - type: map_at_10
      value: 0.735
    - type: map_at_100
      value: 4.331
    - type: map_at_1000
      value: 11.176
    - type: map_at_3
      value: 0.295
    - type: map_at_5
      value: 0.42
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 65.96
    - type: mrr_at_100
      value: 66.31
    - type: mrr_at_1000
      value: 66.31
    - type: mrr_at_3
      value: 62.333000000000006
    - type: mrr_at_5
      value: 64.133
    - type: ndcg_at_1
      value: 46.0
    - type: ndcg_at_10
      value: 41.13
    - type: ndcg_at_100
      value: 32.284
    - type: ndcg_at_1000
      value: 30.653999999999996
    - type: ndcg_at_3
      value: 43.531
    - type: ndcg_at_5
      value: 41.765
    - type: precision_at_1
      value: 54.0
    - type: precision_at_10
      value: 44.6
    - type: precision_at_100
      value: 34.48
    - type: precision_at_1000
      value: 15.092
    - type: precision_at_3
      value: 48.0
    - type: precision_at_5
      value: 44.4
    - type: recall_at_1
      value: 0.13
    - type: recall_at_10
      value: 1.0070000000000001
    - type: recall_at_100
      value: 7.5520000000000005
    - type: recall_at_1000
      value: 30.467
    - type: recall_at_3
      value: 0.335
    - type: recall_at_5
      value: 0.492
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 40.637960737671726
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 45.03877757456517
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 70.97405006739949
    - type: cos_sim_spearman
      value: 63.227979902099165
    - type: euclidean_pearson
      value: 66.19721301612253
    - type: euclidean_spearman
      value: 63.22797557268851
    - type: manhattan_pearson
      value: 65.13067739221246
    - type: manhattan_spearman
      value: 62.606566921475135
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 61.8124029654452
    - type: cos_sim_spearman
      value: 54.20205145049397
    - type: euclidean_pearson
      value: 57.77673709166251
    - type: euclidean_spearman
      value: 54.20205145049397
    - type: manhattan_pearson
      value: 57.89405213238462
    - type: manhattan_spearman
      value: 54.629833623089596
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 64.32001417267017
    - type: cos_sim_spearman
      value: 65.6993785617677
    - type: euclidean_pearson
      value: 65.5446558919719
    - type: euclidean_spearman
      value: 65.6993785617677
    - type: manhattan_pearson
      value: 65.39435047355222
    - type: manhattan_spearman
      value: 65.47378838287605
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 68.92258658196903
    - type: cos_sim_spearman
      value: 65.99362560413196
    - type: euclidean_pearson
      value: 67.35844919653478
    - type: euclidean_spearman
      value: 65.99361325517108
    - type: manhattan_pearson
      value: 67.29865914012107
    - type: manhattan_spearman
      value: 65.98540675442793
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 76.94650869269346
    - type: cos_sim_spearman
      value: 77.15952881408424
    - type: euclidean_pearson
      value: 76.15238442977392
    - type: euclidean_spearman
      value: 77.15952881408424
    - type: manhattan_pearson
      value: 76.31567646432944
    - type: manhattan_spearman
      value: 77.57593105179275
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 69.51617147722006
    - type: cos_sim_spearman
      value: 69.92956219902182
    - type: euclidean_pearson
      value: 69.49066528233178
    - type: euclidean_spearman
      value: 69.92956219902182
    - type: manhattan_pearson
      value: 69.83632628879278
    - type: manhattan_spearman
      value: 70.34281119054346
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.36079159271515
    - type: cos_sim_spearman
      value: 83.14925676391923
    - type: euclidean_pearson
      value: 81.34579249878097
    - type: euclidean_spearman
      value: 83.14925676391923
    - type: manhattan_pearson
      value: 81.32200226343679
    - type: manhattan_spearman
      value: 83.0005721494159
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.64942893346429
    - type: cos_sim_spearman
      value: 61.84606669166541
    - type: euclidean_pearson
      value: 63.046912770456856
    - type: euclidean_spearman
      value: 61.84606669166541
    - type: manhattan_pearson
      value: 61.728865510770625
    - type: manhattan_spearman
      value: 60.03953122233777
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 71.3835068094255
    - type: cos_sim_spearman
      value: 68.66618434769194
    - type: euclidean_pearson
      value: 69.88526771287596
    - type: euclidean_spearman
      value: 68.66618434769194
    - type: manhattan_pearson
      value: 70.31797109978754
    - type: manhattan_spearman
      value: 69.14310993347732
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.69868794851263
    - type: mrr
      value: 90.33154572370259
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 28.028
    - type: map_at_10
      value: 35.251
    - type: map_at_100
      value: 36.258
    - type: map_at_1000
      value: 36.361
    - type: map_at_3
      value: 32.634
    - type: map_at_5
      value: 34.251
    - type: mrr_at_1
      value: 29.666999999999998
    - type: mrr_at_10
      value: 36.565
    - type: mrr_at_100
      value: 37.438
    - type: mrr_at_1000
      value: 37.527
    - type: mrr_at_3
      value: 34.111000000000004
    - type: mrr_at_5
      value: 35.644
    - type: ndcg_at_1
      value: 29.666999999999998
    - type: ndcg_at_10
      value: 39.405
    - type: ndcg_at_100
      value: 44.574999999999996
    - type: ndcg_at_1000
      value: 47.15
    - type: ndcg_at_3
      value: 34.416000000000004
    - type: ndcg_at_5
      value: 37.178
    - type: precision_at_1
      value: 29.666999999999998
    - type: precision_at_10
      value: 5.7
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 13.778000000000002
    - type: precision_at_5
      value: 9.733
    - type: recall_at_1
      value: 28.028
    - type: recall_at_10
      value: 51.0
    - type: recall_at_100
      value: 75.922
    - type: recall_at_1000
      value: 95.767
    - type: recall_at_3
      value: 37.917
    - type: recall_at_5
      value: 44.611000000000004
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.4881188118812
    - type: cos_sim_ap
      value: 76.35350792016202
    - type: cos_sim_f1
      value: 71.3097713097713
    - type: cos_sim_precision
      value: 74.24242424242425
    - type: cos_sim_recall
      value: 68.60000000000001
    - type: dot_accuracy
      value: 99.4881188118812
    - type: dot_ap
      value: 76.35352166019477
    - type: dot_f1
      value: 71.3097713097713
    - type: dot_precision
      value: 74.24242424242425
    - type: dot_recall
      value: 68.60000000000001
    - type: euclidean_accuracy
      value: 99.4881188118812
    - type: euclidean_ap
      value: 76.35352166019477
    - type: euclidean_f1
      value: 71.3097713097713
    - type: euclidean_precision
      value: 74.24242424242425
    - type: euclidean_recall
      value: 68.60000000000001
    - type: manhattan_accuracy
      value: 99.52772277227723
    - type: manhattan_ap
      value: 78.50333575922221
    - type: manhattan_f1
      value: 73.3549083063646
    - type: manhattan_precision
      value: 79.62529274004683
    - type: manhattan_recall
      value: 68.0
    - type: max_accuracy
      value: 99.52772277227723
    - type: max_ap
      value: 78.50333575922221
    - type: max_f1
      value: 73.3549083063646
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 40.941911761240355
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.824455223894702
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 38.3470566823082
    - type: mrr
      value: 38.32813428401664
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.049953404273477
    - type: cos_sim_spearman
      value: 29.804596105979087
    - type: dot_pearson
      value: 29.049953900699947
    - type: dot_spearman
      value: 29.804596105979087
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.654
    - type: map_at_10
      value: 7.806
    - type: map_at_100
      value: 14.004
    - type: map_at_1000
      value: 15.620000000000001
    - type: map_at_3
      value: 3.2419999999999995
    - type: map_at_5
      value: 5.337
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 39.849000000000004
    - type: mrr_at_100
      value: 40.943000000000005
    - type: mrr_at_1000
      value: 40.961999999999996
    - type: mrr_at_3
      value: 34.694
    - type: mrr_at_5
      value: 38.673
    - type: ndcg_at_1
      value: 24.490000000000002
    - type: ndcg_at_10
      value: 22.093
    - type: ndcg_at_100
      value: 36.111
    - type: ndcg_at_1000
      value: 47.046
    - type: ndcg_at_3
      value: 21.179000000000002
    - type: ndcg_at_5
      value: 23.285
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 21.429000000000002
    - type: precision_at_100
      value: 8.49
    - type: precision_at_1000
      value: 1.5630000000000002
    - type: precision_at_3
      value: 21.769
    - type: precision_at_5
      value: 25.714
    - type: recall_at_1
      value: 1.654
    - type: recall_at_10
      value: 15.341
    - type: recall_at_100
      value: 50.41
    - type: recall_at_1000
      value: 85.14
    - type: recall_at_3
      value: 4.338
    - type: recall_at_5
      value: 8.687000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 67.91439999999999
    - type: ap
      value: 12.410354705209787
    - type: f1
      value: 51.88512351191456
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 47.5410299943407
    - type: f1
      value: 47.58958023479498
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.5181314197037
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.85611253501818
    - type: cos_sim_ap
      value: 58.113125405453545
    - type: cos_sim_f1
      value: 55.672823218997344
    - type: cos_sim_precision
      value: 51.033421284080916
    - type: cos_sim_recall
      value: 61.24010554089709
    - type: dot_accuracy
      value: 81.85611253501818
    - type: dot_ap
      value: 58.11310241068986
    - type: dot_f1
      value: 55.672823218997344
    - type: dot_precision
      value: 51.033421284080916
    - type: dot_recall
      value: 61.24010554089709
    - type: euclidean_accuracy
      value: 81.85611253501818
    - type: euclidean_ap
      value: 58.1131071609323
    - type: euclidean_f1
      value: 55.672823218997344
    - type: euclidean_precision
      value: 51.033421284080916
    - type: euclidean_recall
      value: 61.24010554089709
    - type: manhattan_accuracy
      value: 81.65345413363534
    - type: manhattan_ap
      value: 57.10449344464378
    - type: manhattan_f1
      value: 54.28008803428703
    - type: manhattan_precision
      value: 48.37910386124303
    - type: manhattan_recall
      value: 61.82058047493404
    - type: max_accuracy
      value: 81.85611253501818
    - type: max_ap
      value: 58.113125405453545
    - type: max_f1
      value: 55.672823218997344
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.07843365545077
    - type: cos_sim_ap
      value: 81.68445531153804
    - type: cos_sim_f1
      value: 74.29516577700925
    - type: cos_sim_precision
      value: 72.58704275011017
    - type: cos_sim_recall
      value: 76.08561749307053
    - type: dot_accuracy
      value: 87.07843365545077
    - type: dot_ap
      value: 81.6844546424336
    - type: dot_f1
      value: 74.29516577700925
    - type: dot_precision
      value: 72.58704275011017
    - type: dot_recall
      value: 76.08561749307053
    - type: euclidean_accuracy
      value: 87.07843365545077
    - type: euclidean_ap
      value: 81.6844533865009
    - type: euclidean_f1
      value: 74.29516577700925
    - type: euclidean_precision
      value: 72.58704275011017
    - type: euclidean_recall
      value: 76.08561749307053
    - type: manhattan_accuracy
      value: 87.01633872783017
    - type: manhattan_ap
      value: 81.4619306223648
    - type: manhattan_f1
      value: 74.21754285098278
    - type: manhattan_precision
      value: 69.58425982076679
    - type: manhattan_recall
      value: 79.51185709886049
    - type: max_accuracy
      value: 87.07843365545077
    - type: max_ap
      value: 81.68445531153804
    - type: max_f1
      value: 74.29516577700925
---
