mteb model-index region:us
---
tags:
- mteb
model-index:
- name: sup-simcse
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.3134328358209
    - type: ap
      value: 38.04095408812765
    - type: f1
      value: 69.18544755163924
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 62.44112500000001
    - type: ap
      value: 57.817235716985074
    - type: f1
      value: 62.37720459608907
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.09000000000001
    - type: f1
      value: 31.64639321293789
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 17.994
    - type: map_at_10
      value: 31.223
    - type: map_at_100
      value: 32.557
    - type: map_at_1000
      value: 32.589
    - type: map_at_3
      value: 26.919999999999998
    - type: map_at_5
      value: 29.25
    - type: mrr_at_1
      value: 18.492
    - type: mrr_at_10
      value: 31.413000000000004
    - type: mrr_at_100
      value: 32.747
    - type: mrr_at_1000
      value: 32.779
    - type: mrr_at_3
      value: 27.073999999999998
    - type: mrr_at_5
      value: 29.429
    - type: ndcg_at_1
      value: 17.994
    - type: ndcg_at_10
      value: 38.903999999999996
    - type: ndcg_at_100
      value: 45.172000000000004
    - type: ndcg_at_1000
      value: 45.989000000000004
    - type: ndcg_at_3
      value: 29.969
    - type: ndcg_at_5
      value: 34.147
    - type: precision_at_1
      value: 17.994
    - type: precision_at_10
      value: 6.358
    - type: precision_at_100
      value: 0.924
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 12.945
    - type: precision_at_5
      value: 9.786999999999999
    - type: recall_at_1
      value: 17.994
    - type: recall_at_10
      value: 63.585
    - type: recall_at_100
      value: 92.39
    - type: recall_at_1000
      value: 98.72
    - type: recall_at_3
      value: 38.834
    - type: recall_at_5
      value: 48.933
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 31.91520053343146
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.737264050164082
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 51.46910611293683
    - type: mrr
      value: 65.14081255771006
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 74.4730319095045
    - type: cos_sim_spearman
      value: 73.39685311998065
    - type: euclidean_pearson
      value: 73.54538639388942
    - type: euclidean_spearman
      value: 73.39685311998065
    - type: manhattan_pearson
      value: 75.5608385430094
    - type: manhattan_spearman
      value: 76.07643224829802
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.97402597402598
    - type: f1
      value: 66.9475406749266
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 29.885798705312226
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 21.675278900147095
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.625
    - type: map_at_10
      value: 25.241999999999997
    - type: map_at_100
      value: 26.105
    - type: map_at_1000
      value: 26.230999999999998
    - type: map_at_3
      value: 23.24
    - type: map_at_5
      value: 24.465999999999998
    - type: mrr_at_1
      value: 23.176
    - type: mrr_at_10
      value: 29.841
    - type: mrr_at_100
      value: 30.586999999999996
    - type: mrr_at_1000
      value: 30.659999999999997
    - type: mrr_at_3
      value: 27.992
    - type: mrr_at_5
      value: 29.137
    - type: ndcg_at_1
      value: 23.176
    - type: ndcg_at_10
      value: 29.517
    - type: ndcg_at_100
      value: 33.798
    - type: ndcg_at_1000
      value: 36.839
    - type: ndcg_at_3
      value: 26.464
    - type: ndcg_at_5
      value: 27.971
    - type: precision_at_1
      value: 23.176
    - type: precision_at_10
      value: 5.6370000000000005
    - type: precision_at_100
      value: 0.9400000000000001
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 12.684999999999999
    - type: precision_at_5
      value: 9.099
    - type: recall_at_1
      value: 18.625
    - type: recall_at_10
      value: 37.151
    - type: recall_at_100
      value: 57.02199999999999
    - type: recall_at_1000
      value: 78.295
    - type: recall_at_3
      value: 28.112
    - type: recall_at_5
      value: 32.562999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.832
    - type: map_at_10
      value: 22.323999999999998
    - type: map_at_100
      value: 23.204
    - type: map_at_1000
      value: 23.316
    - type: map_at_3
      value: 20.631
    - type: map_at_5
      value: 21.587
    - type: mrr_at_1
      value: 21.274
    - type: mrr_at_10
      value: 26.705000000000002
    - type: mrr_at_100
      value: 27.427
    - type: mrr_at_1000
      value: 27.498
    - type: mrr_at_3
      value: 24.979000000000003
    - type: mrr_at_5
      value: 26.003999999999998
    - type: ndcg_at_1
      value: 21.274
    - type: ndcg_at_10
      value: 26.003999999999998
    - type: ndcg_at_100
      value: 30.196
    - type: ndcg_at_1000
      value: 33.011
    - type: ndcg_at_3
      value: 23.083000000000002
    - type: ndcg_at_5
      value: 24.455
    - type: precision_at_1
      value: 21.274
    - type: precision_at_10
      value: 4.764
    - type: precision_at_100
      value: 0.864
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 11.04
    - type: precision_at_5
      value: 7.8469999999999995
    - type: recall_at_1
      value: 16.832
    - type: recall_at_10
      value: 32.729
    - type: recall_at_100
      value: 51.341
    - type: recall_at_1000
      value: 70.96900000000001
    - type: recall_at_3
      value: 24.229
    - type: recall_at_5
      value: 27.974
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 22.171
    - type: map_at_10
      value: 29.671999999999997
    - type: map_at_100
      value: 30.613
    - type: map_at_1000
      value: 30.705
    - type: map_at_3
      value: 27.331
    - type: map_at_5
      value: 28.743000000000002
    - type: mrr_at_1
      value: 25.705
    - type: mrr_at_10
      value: 32.637
    - type: mrr_at_100
      value: 33.428999999999995
    - type: mrr_at_1000
      value: 33.497
    - type: mrr_at_3
      value: 30.418
    - type: mrr_at_5
      value: 31.794
    - type: ndcg_at_1
      value: 25.705
    - type: ndcg_at_10
      value: 34.03
    - type: ndcg_at_100
      value: 38.663
    - type: ndcg_at_1000
      value: 41.071999999999996
    - type: ndcg_at_3
      value: 29.64
    - type: ndcg_at_5
      value: 31.953
    - type: precision_at_1
      value: 25.705
    - type: precision_at_10
      value: 5.542
    - type: precision_at_100
      value: 0.86
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 13.145000000000001
    - type: precision_at_5
      value: 9.442
    - type: recall_at_1
      value: 22.171
    - type: recall_at_10
      value: 44.439
    - type: recall_at_100
      value: 65.658
    - type: recall_at_1000
      value: 83.578
    - type: recall_at_3
      value: 32.681
    - type: recall_at_5
      value: 38.273
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 9.415999999999999
    - type: map_at_10
      value: 13.023000000000001
    - type: map_at_100
      value: 13.776
    - type: map_at_1000
      value: 13.882
    - type: map_at_3
      value: 11.834999999999999
    - type: map_at_5
      value: 12.472
    - type: mrr_at_1
      value: 10.282
    - type: mrr_at_10
      value: 14.069999999999999
    - type: mrr_at_100
      value: 14.802999999999999
    - type: mrr_at_1000
      value: 14.902999999999999
    - type: mrr_at_3
      value: 12.825000000000001
    - type: mrr_at_5
      value: 13.508000000000001
    - type: ndcg_at_1
      value: 10.282
    - type: ndcg_at_10
      value: 15.305
    - type: ndcg_at_100
      value: 19.234
    - type: ndcg_at_1000
      value: 22.368
    - type: ndcg_at_3
      value: 12.852
    - type: ndcg_at_5
      value: 13.985
    - type: precision_at_1
      value: 10.282
    - type: precision_at_10
      value: 2.407
    - type: precision_at_100
      value: 0.45799999999999996
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 5.386
    - type: precision_at_5
      value: 3.842
    - type: recall_at_1
      value: 9.415999999999999
    - type: recall_at_10
      value: 21.465999999999998
    - type: recall_at_100
      value: 40.026
    - type: recall_at_1000
      value: 64.36699999999999
    - type: recall_at_3
      value: 14.849
    - type: recall_at_5
      value: 17.541999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.739
    - type: map_at_10
      value: 8.01
    - type: map_at_100
      value: 8.545
    - type: map_at_1000
      value: 8.649
    - type: map_at_3
      value: 7.059
    - type: map_at_5
      value: 7.558
    - type: mrr_at_1
      value: 7.587000000000001
    - type: mrr_at_10
      value: 10.222000000000001
    - type: mrr_at_100
      value: 10.817
    - type: mrr_at_1000
      value: 10.904
    - type: mrr_at_3
      value: 9.142
    - type: mrr_at_5
      value: 9.652
    - type: ndcg_at_1
      value: 7.587000000000001
    - type: ndcg_at_10
      value: 9.923
    - type: ndcg_at_100
      value: 13.29
    - type: ndcg_at_1000
      value: 16.607
    - type: ndcg_at_3
      value: 8.043
    - type: ndcg_at_5
      value: 8.827
    - type: precision_at_1
      value: 7.587000000000001
    - type: precision_at_10
      value: 1.8780000000000001
    - type: precision_at_100
      value: 0.428
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 3.814
    - type: precision_at_5
      value: 2.861
    - type: recall_at_1
      value: 5.739
    - type: recall_at_10
      value: 13.776
    - type: recall_at_100
      value: 29.828
    - type: recall_at_1000
      value: 54.825
    - type: recall_at_3
      value: 8.6
    - type: recall_at_5
      value: 10.566
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.172
    - type: map_at_10
      value: 21.865000000000002
    - type: map_at_100
      value: 22.857
    - type: map_at_1000
      value: 22.985
    - type: map_at_3
      value: 20.326
    - type: map_at_5
      value: 21.175
    - type: mrr_at_1
      value: 20.693
    - type: mrr_at_10
      value: 25.716
    - type: mrr_at_100
      value: 26.576
    - type: mrr_at_1000
      value: 26.66
    - type: mrr_at_3
      value: 24.093999999999998
    - type: mrr_at_5
      value: 25.037
    - type: ndcg_at_1
      value: 20.693
    - type: ndcg_at_10
      value: 25.186999999999998
    - type: ndcg_at_100
      value: 30.259000000000004
    - type: ndcg_at_1000
      value: 33.424
    - type: ndcg_at_3
      value: 22.582
    - type: ndcg_at_5
      value: 23.783
    - type: precision_at_1
      value: 20.693
    - type: precision_at_10
      value: 4.427
    - type: precision_at_100
      value: 0.8410000000000001
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 10.33
    - type: precision_at_5
      value: 7.315
    - type: recall_at_1
      value: 17.172
    - type: recall_at_10
      value: 31.494
    - type: recall_at_100
      value: 54.008
    - type: recall_at_1000
      value: 76.591
    - type: recall_at_3
      value: 23.851
    - type: recall_at_5
      value: 27.065
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.777
    - type: map_at_10
      value: 16.028000000000002
    - type: map_at_100
      value: 16.908
    - type: map_at_1000
      value: 17.026
    - type: map_at_3
      value: 14.623
    - type: map_at_5
      value: 15.309000000000001
    - type: mrr_at_1
      value: 14.498
    - type: mrr_at_10
      value: 19.3
    - type: mrr_at_100
      value: 20.125
    - type: mrr_at_1000
      value: 20.211000000000002
    - type: mrr_at_3
      value: 17.808
    - type: mrr_at_5
      value: 18.584
    - type: ndcg_at_1
      value: 14.498
    - type: ndcg_at_10
      value: 19.087
    - type: ndcg_at_100
      value: 23.651
    - type: ndcg_at_1000
      value: 26.838
    - type: ndcg_at_3
      value: 16.534
    - type: ndcg_at_5
      value: 17.546
    - type: precision_at_1
      value: 14.498
    - type: precision_at_10
      value: 3.4819999999999998
    - type: precision_at_100
      value: 0.687
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 7.800999999999999
    - type: precision_at_5
      value: 5.525
    - type: recall_at_1
      value: 11.777
    - type: recall_at_10
      value: 25.151
    - type: recall_at_100
      value: 45.653
    - type: recall_at_1000
      value: 68.569
    - type: recall_at_3
      value: 18.063000000000002
    - type: recall_at_5
      value: 20.757
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.363666666666665
    - type: map_at_10
      value: 16.769583333333333
    - type: map_at_100
      value: 17.52825
    - type: map_at_1000
      value: 17.63925
    - type: map_at_3
      value: 15.336083333333333
    - type: map_at_5
      value: 16.122083333333332
    - type: mrr_at_1
      value: 14.978166666666667
    - type: mrr_at_10
      value: 19.563416666666665
    - type: mrr_at_100
      value: 20.268500000000003
    - type: mrr_at_1000
      value: 20.353
    - type: mrr_at_3
      value: 18.08591666666667
    - type: mrr_at_5
      value: 18.910083333333333
    - type: ndcg_at_1
      value: 14.978166666666667
    - type: ndcg_at_10
      value: 19.7445
    - type: ndcg_at_100
      value: 23.696083333333334
    - type: ndcg_at_1000
      value: 26.728
    - type: ndcg_at_3
      value: 17.140833333333333
    - type: ndcg_at_5
      value: 18.317750000000004
    - type: precision_at_1
      value: 14.978166666666667
    - type: precision_at_10
      value: 3.4974166666666666
    - type: precision_at_100
      value: 0.6443333333333334
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 7.916749999999999
    - type: precision_at_5
      value: 5.668166666666666
    - type: recall_at_1
      value: 12.363666666666665
    - type: recall_at_10
      value: 26.023833333333336
    - type: recall_at_100
      value: 44.30291666666666
    - type: recall_at_1000
      value: 66.63566666666667
    - type: recall_at_3
      value: 18.639416666666666
    - type: recall_at_5
      value: 21.716833333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 8.491
    - type: map_at_10
      value: 11.84
    - type: map_at_100
      value: 12.489
    - type: map_at_1000
      value: 12.558
    - type: map_at_3
      value: 10.619
    - type: map_at_5
      value: 11.350999999999999
    - type: mrr_at_1
      value: 10.276
    - type: mrr_at_10
      value: 13.855999999999998
    - type: mrr_at_100
      value: 14.487
    - type: mrr_at_1000
      value: 14.549999999999999
    - type: mrr_at_3
      value: 12.679000000000002
    - type: mrr_at_5
      value: 13.4
    - type: ndcg_at_1
      value: 10.276
    - type: ndcg_at_10
      value: 14.185
    - type: ndcg_at_100
      value: 17.654
    - type: ndcg_at_1000
      value: 19.813
    - type: ndcg_at_3
      value: 11.912
    - type: ndcg_at_5
      value: 13.061
    - type: precision_at_1
      value: 10.276
    - type: precision_at_10
      value: 2.5
    - type: precision_at_100
      value: 0.45599999999999996
    - type: precision_at_1000
      value: 0.06999999999999999
    - type: precision_at_3
      value: 5.521
    - type: precision_at_5
      value: 4.08
    - type: recall_at_1
      value: 8.491
    - type: recall_at_10
      value: 19.528000000000002
    - type: recall_at_100
      value: 35.942
    - type: recall_at_1000
      value: 52.614000000000004
    - type: recall_at_3
      value: 13.092
    - type: recall_at_5
      value: 15.988
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.343999999999999
    - type: map_at_10
      value: 9.16
    - type: map_at_100
      value: 9.693999999999999
    - type: map_at_1000
      value: 9.794
    - type: map_at_3
      value: 8.32
    - type: map_at_5
      value: 8.662
    - type: mrr_at_1
      value: 7.983
    - type: mrr_at_10
      value: 11.277
    - type: mrr_at_100
      value: 11.825
    - type: mrr_at_1000
      value: 11.914
    - type: mrr_at_3
      value: 10.323
    - type: mrr_at_5
      value: 10.735999999999999
    - type: ndcg_at_1
      value: 7.983
    - type: ndcg_at_10
      value: 11.231
    - type: ndcg_at_100
      value: 14.202
    - type: ndcg_at_1000
      value: 17.22
    - type: ndcg_at_3
      value: 9.600999999999999
    - type: ndcg_at_5
      value: 10.086
    - type: precision_at_1
      value: 7.983
    - type: precision_at_10
      value: 2.116
    - type: precision_at_100
      value: 0.432
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 4.691
    - type: precision_at_5
      value: 3.2419999999999995
    - type: recall_at_1
      value: 6.343999999999999
    - type: recall_at_10
      value: 15.526000000000002
    - type: recall_at_100
      value: 29.496
    - type: recall_at_1000
      value: 52.088
    - type: recall_at_3
      value: 10.665
    - type: recall_at_5
      value: 12.055
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 10.299999999999999
    - type: map_at_10
      value: 13.899000000000001
    - type: map_at_100
      value: 14.575
    - type: map_at_1000
      value: 14.677999999999999
    - type: map_at_3
      value: 12.672
    - type: map_at_5
      value: 13.302
    - type: mrr_at_1
      value: 12.313
    - type: mrr_at_10
      value: 16.139
    - type: mrr_at_100
      value: 16.858
    - type: mrr_at_1000
      value: 16.957
    - type: mrr_at_3
      value: 14.77
    - type: mrr_at_5
      value: 15.459999999999999
    - type: ndcg_at_1
      value: 12.313
    - type: ndcg_at_10
      value: 16.408
    - type: ndcg_at_100
      value: 19.991
    - type: ndcg_at_1000
      value: 23.236
    - type: ndcg_at_3
      value: 13.980999999999998
    - type: ndcg_at_5
      value: 14.976999999999999
    - type: precision_at_1
      value: 12.313
    - type: precision_at_10
      value: 2.771
    - type: precision_at_100
      value: 0.504
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 6.281000000000001
    - type: precision_at_5
      value: 4.44
    - type: recall_at_1
      value: 10.299999999999999
    - type: recall_at_10
      value: 22.096
    - type: recall_at_100
      value: 38.515
    - type: recall_at_1000
      value: 63.157
    - type: recall_at_3
      value: 15.193000000000001
    - type: recall_at_5
      value: 17.807000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.791
    - type: map_at_10
      value: 17.625
    - type: map_at_100
      value: 18.448999999999998
    - type: map_at_1000
      value: 18.626
    - type: map_at_3
      value: 16.176
    - type: map_at_5
      value: 17.018
    - type: mrr_at_1
      value: 15.415000000000001
    - type: mrr_at_10
      value: 20.612
    - type: mrr_at_100
      value: 21.305
    - type: mrr_at_1000
      value: 21.410999999999998
    - type: mrr_at_3
      value: 18.939
    - type: mrr_at_5
      value: 19.928
    - type: ndcg_at_1
      value: 15.415000000000001
    - type: ndcg_at_10
      value: 20.819
    - type: ndcg_at_100
      value: 24.814
    - type: ndcg_at_1000
      value: 28.693
    - type: ndcg_at_3
      value: 18.495
    - type: ndcg_at_5
      value: 19.645000000000003
    - type: precision_at_1
      value: 15.415000000000001
    - type: precision_at_10
      value: 3.913
    - type: precision_at_100
      value: 0.804
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 8.762
    - type: precision_at_5
      value: 6.4430000000000005
    - type: recall_at_1
      value: 12.791
    - type: recall_at_10
      value: 26.791999999999998
    - type: recall_at_100
      value: 45.705
    - type: recall_at_1000
      value: 72.547
    - type: recall_at_3
      value: 19.902
    - type: recall_at_5
      value: 23.019000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.706
    - type: map_at_10
      value: 12.547
    - type: map_at_100
      value: 13.123999999999999
    - type: map_at_1000
      value: 13.221
    - type: map_at_3
      value: 11.201
    - type: map_at_5
      value: 11.822000000000001
    - type: mrr_at_1
      value: 10.536
    - type: mrr_at_10
      value: 14.386
    - type: mrr_at_100
      value: 14.982999999999999
    - type: mrr_at_1000
      value: 15.071000000000002
    - type: mrr_at_3
      value: 13.062000000000001
    - type: mrr_at_5
      value: 13.681
    - type: ndcg_at_1
      value: 10.536
    - type: ndcg_at_10
      value: 15.238
    - type: ndcg_at_100
      value: 18.601
    - type: ndcg_at_1000
      value: 21.615000000000002
    - type: ndcg_at_3
      value: 12.503
    - type: ndcg_at_5
      value: 13.524
    - type: precision_at_1
      value: 10.536
    - type: precision_at_10
      value: 2.532
    - type: precision_at_100
      value: 0.45799999999999996
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 5.545
    - type: precision_at_5
      value: 3.882
    - type: recall_at_1
      value: 8.706
    - type: recall_at_10
      value: 22.137999999999998
    - type: recall_at_100
      value: 38.440999999999995
    - type: recall_at_1000
      value: 62.028000000000006
    - type: recall_at_3
      value: 14.435999999999998
    - type: recall_at_5
      value: 16.993
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.991
    - type: map_at_10
      value: 10.279
    - type: map_at_100
      value: 11.522
    - type: map_at_1000
      value: 11.725
    - type: map_at_3
      value: 8.358
    - type: map_at_5
      value: 9.168999999999999
    - type: mrr_at_1
      value: 12.899
    - type: mrr_at_10
      value: 20.954
    - type: mrr_at_100
      value: 22.005
    - type: mrr_at_1000
      value: 22.076
    - type: mrr_at_3
      value: 17.849999999999998
    - type: mrr_at_5
      value: 19.534000000000002
    - type: ndcg_at_1
      value: 12.899
    - type: ndcg_at_10
      value: 15.591
    - type: ndcg_at_100
      value: 21.558
    - type: ndcg_at_1000
      value: 25.795
    - type: ndcg_at_3
      value: 11.662
    - type: ndcg_at_5
      value: 12.916
    - type: precision_at_1
      value: 12.899
    - type: precision_at_10
      value: 5.218
    - type: precision_at_100
      value: 1.164
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 8.708
    - type: precision_at_5
      value: 6.997000000000001
    - type: recall_at_1
      value: 5.991
    - type: recall_at_10
      value: 20.165
    - type: recall_at_100
      value: 41.479
    - type: recall_at_1000
      value: 66.014
    - type: recall_at_3
      value: 10.915
    - type: recall_at_5
      value: 14.033000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.752
    - type: map_at_10
      value: 6.859
    - type: map_at_100
      value: 9.745
    - type: map_at_1000
      value: 10.549
    - type: map_at_3
      value: 4.707
    - type: map_at_5
      value: 5.7059999999999995
    - type: mrr_at_1
      value: 35.0
    - type: mrr_at_10
      value: 44.019999999999996
    - type: mrr_at_100
      value: 44.773
    - type: mrr_at_1000
      value: 44.812999999999995
    - type: mrr_at_3
      value: 40.583000000000006
    - type: mrr_at_5
      value: 42.921
    - type: ndcg_at_1
      value: 25.124999999999996
    - type: ndcg_at_10
      value: 19.197
    - type: ndcg_at_100
      value: 21.688
    - type: ndcg_at_1000
      value: 27.944000000000003
    - type: ndcg_at_3
      value: 20.949
    - type: ndcg_at_5
      value: 20.333000000000002
    - type: precision_at_1
      value: 35.0
    - type: precision_at_10
      value: 17.549999999999997
    - type: precision_at_100
      value: 5.645
    - type: precision_at_1000
      value: 1.218
    - type: precision_at_3
      value: 25.0
    - type: precision_at_5
      value: 22.5
    - type: recall_at_1
      value: 2.752
    - type: recall_at_10
      value: 10.939
    - type: recall_at_100
      value: 27.250000000000004
    - type: recall_at_1000
      value: 48.545
    - type: recall_at_3
      value: 5.79
    - type: recall_at_5
      value: 7.981000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 40.695
    - type: f1
      value: 36.79470681884116
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.595999999999998
    - type: map_at_10
      value: 18.759999999999998
    - type: map_at_100
      value: 19.605
    - type: map_at_1000
      value: 19.68
    - type: map_at_3
      value: 16.692
    - type: map_at_5
      value: 17.773
    - type: mrr_at_1
      value: 13.411000000000001
    - type: mrr_at_10
      value: 19.907
    - type: mrr_at_100
      value: 20.767
    - type: mrr_at_1000
      value: 20.837
    - type: mrr_at_3
      value: 17.762
    - type: mrr_at_5
      value: 18.895999999999997
    - type: ndcg_at_1
      value: 13.411000000000001
    - type: ndcg_at_10
      value: 22.647000000000002
    - type: ndcg_at_100
      value: 27.084999999999997
    - type: ndcg_at_1000
      value: 29.296
    - type: ndcg_at_3
      value: 18.326999999999998
    - type: ndcg_at_5
      value: 20.265
    - type: precision_at_1
      value: 13.411000000000001
    - type: precision_at_10
      value: 3.6740000000000004
    - type: precision_at_100
      value: 0.608
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 7.890999999999999
    - type: precision_at_5
      value: 5.755
    - type: recall_at_1
      value: 12.595999999999998
    - type: recall_at_10
      value: 33.836
    - type: recall_at_100
      value: 54.82
    - type: recall_at_1000
      value: 72.15599999999999
    - type: recall_at_3
      value: 21.961
    - type: recall_at_5
      value: 26.601999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.716
    - type: map_at_10
      value: 7.8340000000000005
    - type: map_at_100
      value: 8.652
    - type: map_at_1000
      value: 8.838
    - type: map_at_3
      value: 6.802999999999999
    - type: map_at_5
      value: 7.292999999999999
    - type: mrr_at_1
      value: 9.259
    - type: mrr_at_10
      value: 14.297
    - type: mrr_at_100
      value: 15.14
    - type: mrr_at_1000
      value: 15.260000000000002
    - type: mrr_at_3
      value: 12.834000000000001
    - type: mrr_at_5
      value: 13.483
    - type: ndcg_at_1
      value: 9.259
    - type: ndcg_at_10
      value: 11.083
    - type: ndcg_at_100
      value: 15.493000000000002
    - type: ndcg_at_1000
      value: 19.895
    - type: ndcg_at_3
      value: 9.494
    - type: ndcg_at_5
      value: 9.884
    - type: precision_at_1
      value: 9.259
    - type: precision_at_10
      value: 3.1329999999999996
    - type: precision_at_100
      value: 0.761
    - type: precision_at_1000
      value: 0.148
    - type: precision_at_3
      value: 6.379
    - type: precision_at_5
      value: 4.63
    - type: recall_at_1
      value: 4.716
    - type: recall_at_10
      value: 14.516000000000002
    - type: recall_at_100
      value: 31.980999999999998
    - type: recall_at_1000
      value: 59.891000000000005
    - type: recall_at_3
      value: 9.123000000000001
    - type: recall_at_5
      value: 10.975
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.977
    - type: map_at_10
      value: 19.313
    - type: map_at_100
      value: 20.09
    - type: map_at_1000
      value: 20.191
    - type: map_at_3
      value: 17.777
    - type: map_at_5
      value: 18.621
    - type: mrr_at_1
      value: 27.954
    - type: mrr_at_10
      value: 34.175
    - type: mrr_at_100
      value: 34.886
    - type: mrr_at_1000
      value: 34.953
    - type: mrr_at_3
      value: 32.471
    - type: mrr_at_5
      value: 33.383
    - type: ndcg_at_1
      value: 27.954
    - type: ndcg_at_10
      value: 25.102999999999998
    - type: ndcg_at_100
      value: 28.887
    - type: ndcg_at_1000
      value: 31.554
    - type: ndcg_at_3
      value: 22.06
    - type: ndcg_at_5
      value: 23.491999999999997
    - type: precision_at_1
      value: 27.954
    - type: precision_at_10
      value: 5.542
    - type: precision_at_100
      value: 0.859
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 13.886999999999999
    - type: precision_at_5
      value: 9.464
    - type: recall_at_1
      value: 13.977
    - type: recall_at_10
      value: 27.711000000000002
    - type: recall_at_100
      value: 42.93
    - type: recall_at_1000
      value: 60.864
    - type: recall_at_3
      value: 20.831
    - type: recall_at_5
      value: 23.66
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 62.92960000000001
    - type: ap
      value: 58.305412968174274
    - type: f1
      value: 62.79151880122965
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 4.644
    - type: map_at_10
      value: 8.189
    - type: map_at_100
      value: 8.941
    - type: map_at_1000
      value: 9.034
    - type: map_at_3
      value: 6.811
    - type: map_at_5
      value: 7.53
    - type: mrr_at_1
      value: 4.771
    - type: mrr_at_10
      value: 8.426
    - type: mrr_at_100
      value: 9.186
    - type: mrr_at_1000
      value: 9.276
    - type: mrr_at_3
      value: 7.031999999999999
    - type: mrr_at_5
      value: 7.7509999999999994
    - type: ndcg_at_1
      value: 4.742
    - type: ndcg_at_10
      value: 10.471
    - type: ndcg_at_100
      value: 14.651
    - type: ndcg_at_1000
      value: 17.529
    - type: ndcg_at_3
      value: 7.599
    - type: ndcg_at_5
      value: 8.886
    - type: precision_at_1
      value: 4.742
    - type: precision_at_10
      value: 1.83
    - type: precision_at_100
      value: 0.4
    - type: precision_at_1000
      value: 0.065
    - type: precision_at_3
      value: 3.3520000000000003
    - type: precision_at_5
      value: 2.653
    - type: recall_at_1
      value: 4.644
    - type: recall_at_10
      value: 17.592
    - type: recall_at_100
      value: 38.112
    - type: recall_at_1000
      value: 61.36000000000001
    - type: recall_at_3
      value: 9.672
    - type: recall_at_5
      value: 12.766
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 84.52120383036934
    - type: f1
      value: 84.02668015212832
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 57.425900592795266
    - type: f1
      value: 39.185902692178225
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.395427034297235
    - type: f1
      value: 59.07963466976405
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.7619367854741
    - type: f1
      value: 65.31589654283285
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.800219005224214
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.232953769516218
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.764776217338706
    - type: mrr
      value: 29.61488447099121
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.087
    - type: map_at_10
      value: 5.01
    - type: map_at_100
      value: 6.239
    - type: map_at_1000
      value: 7.2620000000000005
    - type: map_at_3
      value: 3.884
    - type: map_at_5
      value: 4.519
    - type: mrr_at_1
      value: 27.245
    - type: mrr_at_10
      value: 35.077000000000005
    - type: mrr_at_100
      value: 36.007
    - type: mrr_at_1000
      value: 36.087
    - type: mrr_at_3
      value: 32.405
    - type: mrr_at_5
      value: 34.2
    - type: ndcg_at_1
      value: 25.851000000000003
    - type: ndcg_at_10
      value: 17.534
    - type: ndcg_at_100
      value: 16.656000000000002
    - type: ndcg_at_1000
      value: 26.058999999999997
    - type: ndcg_at_3
      value: 20.155
    - type: ndcg_at_5
      value: 19.349
    - type: precision_at_1
      value: 27.245
    - type: precision_at_10
      value: 13.096
    - type: precision_at_100
      value: 4.723999999999999
    - type: precision_at_1000
      value: 1.73
    - type: precision_at_3
      value: 18.473
    - type: precision_at_5
      value: 16.718
    - type: recall_at_1
      value: 3.087
    - type: recall_at_10
      value: 7.555000000000001
    - type: recall_at_100
      value: 18.819
    - type: recall_at_1000
      value: 51.94
    - type: recall_at_3
      value: 4.387
    - type: recall_at_5
      value: 5.955
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.423
    - type: map_at_10
      value: 12.739
    - type: map_at_100
      value: 13.803
    - type: map_at_1000
      value: 13.905000000000001
    - type: map_at_3
      value: 10.796999999999999
    - type: map_at_5
      value: 11.785
    - type: mrr_at_1
      value: 8.459
    - type: mrr_at_10
      value: 14.205000000000002
    - type: mrr_at_100
      value: 15.213
    - type: mrr_at_1000
      value: 15.303
    - type: mrr_at_3
      value: 12.138
    - type: mrr_at_5
      value: 13.192
    - type: ndcg_at_1
      value: 8.459
    - type: ndcg_at_10
      value: 16.353
    - type: ndcg_at_100
      value: 21.83
    - type: ndcg_at_1000
      value: 24.768
    - type: ndcg_at_3
      value: 12.237
    - type: ndcg_at_5
      value: 14.033999999999999
    - type: precision_at_1
      value: 8.459
    - type: precision_at_10
      value: 3.053
    - type: precision_at_100
      value: 0.616
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 5.755
    - type: precision_at_5
      value: 4.455
    - type: recall_at_1
      value: 7.423
    - type: recall_at_10
      value: 26.226
    - type: recall_at_100
      value: 51.73799999999999
    - type: recall_at_1000
      value: 74.471
    - type: recall_at_3
      value: 15.134
    - type: recall_at_5
      value: 19.351
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 59.080999999999996
    - type: map_at_10
      value: 71.06700000000001
    - type: map_at_100
      value: 71.892
    - type: map_at_1000
      value: 71.935
    - type: map_at_3
      value: 68.291
    - type: map_at_5
      value: 69.93599999999999
    - type: mrr_at_1
      value: 68.04
    - type: mrr_at_10
      value: 75.777
    - type: mrr_at_100
      value: 76.095
    - type: mrr_at_1000
      value: 76.105
    - type: mrr_at_3
      value: 74.248
    - type: mrr_at_5
      value: 75.199
    - type: ndcg_at_1
      value: 68.08
    - type: ndcg_at_10
      value: 75.92999999999999
    - type: ndcg_at_100
      value: 78.467
    - type: ndcg_at_1000
      value: 79.08800000000001
    - type: ndcg_at_3
      value: 72.33800000000001
    - type: ndcg_at_5
      value: 74.117
    - type: precision_at_1
      value: 68.08
    - type: precision_at_10
      value: 11.453000000000001
    - type: precision_at_100
      value: 1.397
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 31.343
    - type: precision_at_5
      value: 20.663999999999998
    - type: recall_at_1
      value: 59.080999999999996
    - type: recall_at_10
      value: 85.235
    - type: recall_at_100
      value: 95.232
    - type: recall_at_1000
      value: 99.003
    - type: recall_at_3
      value: 74.857
    - type: recall_at_5
      value: 79.866
    - type: map_at_1
      value: 2.128
    - type: map_at_10
      value: 5.224
    - type: map_at_100
      value: 6.2
    - type: map_at_1000
      value: 6.41
    - type: map_at_3
      value: 3.7929999999999997
    - type: map_at_5
      value: 4.507
    - type: mrr_at_1
      value: 10.4
    - type: mrr_at_10
      value: 17.692
    - type: mrr_at_100
      value: 18.721
    - type: mrr_at_1000
      value: 18.828
    - type: mrr_at_3
      value: 15.283
    - type: mrr_at_5
      value: 16.673
    - type: ndcg_at_1
      value: 10.4
    - type: ndcg_at_10
      value: 9.673
    - type: ndcg_at_100
      value: 14.597
    - type: ndcg_at_1000
      value: 19.45
    - type: ndcg_at_3
      value: 8.924999999999999
    - type: ndcg_at_5
      value: 7.968999999999999
    - type: precision_at_1
      value: 10.4
    - type: precision_at_10
      value: 5.09
    - type: precision_at_100
      value: 1.239
    - type: precision_at_1000
      value: 0.242
    - type: precision_at_3
      value: 8.4
    - type: precision_at_5
      value: 7.08
    - type: recall_at_1
      value: 2.128
    - type: recall_at_10
      value: 10.355
    - type: recall_at_100
      value: 25.131999999999998
    - type: recall_at_1000
      value: 49.123
    - type: recall_at_3
      value: 5.148
    - type: recall_at_5
      value: 7.227
    - type: map_at_1
      value: 0.082
    - type: map_at_10
      value: 0.522
    - type: map_at_100
      value: 2.443
    - type: map_at_1000
      value: 6.104
    - type: map_at_3
      value: 0.21
    - type: map_at_5
      value: 0.335
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 52.908
    - type: mrr_at_100
      value: 53.563
    - type: mrr_at_1000
      value: 53.563
    - type: mrr_at_3
      value: 48.667
    - type: mrr_at_5
      value: 50.967
    - type: ndcg_at_1
      value: 36.0
    - type: ndcg_at_10
      value: 33.141
    - type: ndcg_at_100
      value: 23.552999999999997
    - type: ndcg_at_1000
      value: 21.127000000000002
    - type: ndcg_at_3
      value: 35.274
    - type: ndcg_at_5
      value: 35.374
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 35.8
    - type: precision_at_100
      value: 24.46
    - type: precision_at_1000
      value: 10.556000000000001
    - type: precision_at_3
      value: 38.667
    - type: precision_at_5
      value: 39.6
    - type: recall_at_1
      value: 0.082
    - type: recall_at_10
      value: 0.762
    - type: recall_at_100
      value: 5.053
    - type: recall_at_1000
      value: 20.758
    - type: recall_at_3
      value: 0.256
    - type: recall_at_5
      value: 0.428
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 32.60289362468036
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 40.4522615771674
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.367126208385
    - type: cos_sim_spearman
      value: 68.33460522353158
    - type: euclidean_pearson
      value: 72.82526651070455
    - type: euclidean_spearman
      value: 68.3346412251751
    - type: manhattan_pearson
      value: 69.54331108044752
    - type: manhattan_spearman
      value: 65.45302638171147
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 70.85977556465735
    - type: cos_sim_spearman
      value: 63.97433796108382
    - type: euclidean_pearson
      value: 67.10317546783216
    - type: euclidean_spearman
      value: 63.9755699230653
    - type: manhattan_pearson
      value: 65.52418699963135
    - type: manhattan_spearman
      value: 63.21258915122308
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 73.1838126630538
    - type: cos_sim_spearman
      value: 75.39011836536339
    - type: euclidean_pearson
      value: 74.9782801873135
    - type: euclidean_spearman
      value: 75.39015619876471
    - type: manhattan_pearson
      value: 74.93646082889957
    - type: manhattan_spearman
      value: 75.27860913964665
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 75.33602852852485
    - type: cos_sim_spearman
      value: 72.88610761015623
    - type: euclidean_pearson
      value: 74.74618127482613
    - type: euclidean_spearman
      value: 72.88609792110957
    - type: manhattan_pearson
      value: 74.00797719940813
    - type: manhattan_spearman
      value: 72.30319426143821
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 78.48344310675034
    - type: cos_sim_spearman
      value: 79.5602100440999
    - type: euclidean_pearson
      value: 79.6105408248732
    - type: euclidean_spearman
      value: 79.56019504416581
    - type: manhattan_pearson
      value: 79.94079490935202
    - type: manhattan_spearman
      value: 80.19729048900355
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.02545587458899
    - type: cos_sim_spearman
      value: 75.2780369994608
    - type: euclidean_pearson
      value: 74.81275720654355
    - type: euclidean_spearman
      value: 75.27802996000392
    - type: manhattan_pearson
      value: 75.365898594137
    - type: manhattan_spearman
      value: 75.99988657994446
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 83.37158192569701
    - type: cos_sim_spearman
      value: 84.53055784651096
    - type: euclidean_pearson
      value: 84.50120181859903
    - type: euclidean_spearman
      value: 84.53143170799756
    - type: manhattan_pearson
      value: 83.67777600066678
    - type: manhattan_spearman
      value: 84.30878918286747
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.60218549460609
    - type: cos_sim_spearman
      value: 60.4194432631911
    - type: euclidean_pearson
      value: 62.3707197693071
    - type: euclidean_spearman
      value: 60.4194432631911
    - type: manhattan_pearson
      value: 62.154998597530245
    - type: manhattan_spearman
      value: 60.670846068288775
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.44357753178365
    - type: cos_sim_spearman
      value: 75.1868455148921
    - type: euclidean_pearson
      value: 76.36802547145336
    - type: euclidean_spearman
      value: 75.1868639836731
    - type: manhattan_pearson
      value: 75.85844829336776
    - type: manhattan_spearman
      value: 74.88123489350302
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 68.51995354068147
    - type: mrr
      value: 88.515406162465
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 25.611
    - type: map_at_10
      value: 32.638
    - type: map_at_100
      value: 33.593
    - type: map_at_1000
      value: 33.672000000000004
    - type: map_at_3
      value: 30.166999999999998
    - type: map_at_5
      value: 31.306
    - type: mrr_at_1
      value: 27.0
    - type: mrr_at_10
      value: 34.104
    - type: mrr_at_100
      value: 34.98
    - type: mrr_at_1000
      value: 35.046
    - type: mrr_at_3
      value: 31.889
    - type: mrr_at_5
      value: 32.906
    - type: ndcg_at_1
      value: 27.0
    - type: ndcg_at_10
      value: 36.882999999999996
    - type: ndcg_at_100
      value: 41.941
    - type: ndcg_at_1000
      value: 44.341
    - type: ndcg_at_3
      value: 31.945
    - type: ndcg_at_5
      value: 33.833999999999996
    - type: precision_at_1
      value: 27.0
    - type: precision_at_10
      value: 5.367
    - type: precision_at_100
      value: 0.823
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 12.778
    - type: precision_at_5
      value: 8.733
    - type: recall_at_1
      value: 25.611
    - type: recall_at_10
      value: 48.888999999999996
    - type: recall_at_100
      value: 73.089
    - type: recall_at_1000
      value: 92.45
    - type: recall_at_3
      value: 35.25
    - type: recall_at_5
      value: 39.778000000000006
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.56732673267327
    - type: cos_sim_ap
      value: 83.46633430421917
    - type: cos_sim_f1
      value: 76.71816728822589
    - type: cos_sim_precision
      value: 82.09806157354618
    - type: cos_sim_recall
      value: 72.0
    - type: dot_accuracy
      value: 99.56732673267327
    - type: dot_ap
      value: 83.46633430421917
    - type: dot_f1
      value: 76.71816728822589
    - type: dot_precision
      value: 82.09806157354618
    - type: dot_recall
      value: 72.0
    - type: euclidean_accuracy
      value: 99.56732673267327
    - type: euclidean_ap
      value: 83.46633430421917
    - type: euclidean_f1
      value: 76.71816728822589
    - type: euclidean_precision
      value: 82.09806157354618
    - type: euclidean_recall
      value: 72.0
    - type: manhattan_accuracy
      value: 99.67722772277227
    - type: manhattan_ap
      value: 89.71022888608738
    - type: manhattan_f1
      value: 82.66129032258065
    - type: manhattan_precision
      value: 83.33333333333334
    - type: manhattan_recall
      value: 82.0
    - type: max_accuracy
      value: 99.67722772277227
    - type: max_ap
      value: 89.71022888608738
    - type: max_f1
      value: 82.66129032258065
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 38.950459678791944
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.43306179999893
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.30089691776191
    - type: mrr
      value: 41.81213394448689
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.787391241122602
    - type: cos_sim_spearman
      value: 30.10535337344201
    - type: dot_pearson
      value: 29.787391177030514
    - type: dot_spearman
      value: 30.02195919678659
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.6310000000000002
    - type: map_at_10
      value: 5.423
    - type: map_at_100
      value: 9.573
    - type: map_at_1000
      value: 11.048
    - type: map_at_3
      value: 3.318
    - type: map_at_5
      value: 4.093999999999999
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 38.083
    - type: mrr_at_100
      value: 39.221000000000004
    - type: mrr_at_1000
      value: 39.227000000000004
    - type: mrr_at_3
      value: 34.694
    - type: mrr_at_5
      value: 35.510000000000005
    - type: ndcg_at_1
      value: 22.448999999999998
    - type: ndcg_at_10
      value: 17.093
    - type: ndcg_at_100
      value: 27.413999999999998
    - type: ndcg_at_1000
      value: 39.706
    - type: ndcg_at_3
      value: 19.91
    - type: ndcg_at_5
      value: 18.007
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 15.306000000000001
    - type: precision_at_100
      value: 6.327000000000001
    - type: precision_at_1000
      value: 1.392
    - type: precision_at_3
      value: 21.088
    - type: precision_at_5
      value: 17.959
    - type: recall_at_1
      value: 1.6310000000000002
    - type: recall_at_10
      value: 10.459
    - type: recall_at_100
      value: 38.216
    - type: recall_at_1000
      value: 75.151
    - type: recall_at_3
      value: 4.634
    - type: recall_at_5
      value: 6.0409999999999995
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.7038
    - type: ap
      value: 14.220727052200816
    - type: f1
      value: 54.464733589173576
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.478777589134125
    - type: f1
      value: 52.650244129490055
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.99931902240702
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.52965369255529
    - type: cos_sim_ap
      value: 62.51268142006894
    - type: cos_sim_f1
      value: 59.800097513408105
    - type: cos_sim_precision
      value: 55.57317625736293
    - type: cos_sim_recall
      value: 64.72295514511873
    - type: dot_accuracy
      value: 82.52965369255529
    - type: dot_ap
      value: 62.51268142006894
    - type: dot_f1
      value: 59.800097513408105
    - type: dot_precision
      value: 55.57317625736293
    - type: dot_recall
      value: 64.72295514511873
    - type: euclidean_accuracy
      value: 82.52965369255529
    - type: euclidean_ap
      value: 62.51268142006894
    - type: euclidean_f1
      value: 59.800097513408105
    - type: euclidean_precision
      value: 55.57317625736293
    - type: euclidean_recall
      value: 64.72295514511873
    - type: manhattan_accuracy
      value: 81.77862549919533
    - type: manhattan_ap
      value: 59.21825218726623
    - type: manhattan_f1
      value: 56.64351333183957
    - type: manhattan_precision
      value: 49.22118380062305
    - type: manhattan_recall
      value: 66.7018469656992
    - type: max_accuracy
      value: 82.52965369255529
    - type: max_ap
      value: 62.51268142006894
    - type: max_f1
      value: 59.800097513408105
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.01051732836575
    - type: cos_sim_ap
      value: 82.14373850939549
    - type: cos_sim_f1
      value: 74.26138467234358
    - type: cos_sim_precision
      value: 71.52332049636286
    - type: cos_sim_recall
      value: 77.21743147520789
    - type: dot_accuracy
      value: 87.01051732836575
    - type: dot_ap
      value: 82.14374565499902
    - type: dot_f1
      value: 74.26138467234358
    - type: dot_precision
      value: 71.52332049636286
    - type: dot_recall
      value: 77.21743147520789
    - type: euclidean_accuracy
      value: 87.01051732836575
    - type: euclidean_ap
      value: 82.14373956027772
    - type: euclidean_f1
      value: 74.26138467234358
    - type: euclidean_precision
      value: 71.52332049636286
    - type: euclidean_recall
      value: 77.21743147520789
    - type: manhattan_accuracy
      value: 87.06290992354562
    - type: manhattan_ap
      value: 82.16999565860169
    - type: manhattan_f1
      value: 74.21972757498838
    - type: manhattan_precision
      value: 69.27851565107122
    - type: manhattan_recall
      value: 79.91992608561749
    - type: max_accuracy
      value: 87.06290992354562
    - type: max_ap
      value: 82.16999565860169
    - type: max_f1
      value: 74.26138467234358
---
