mteb model-index region:us
---
tags:
- mteb
model-index:
- name: gte-base-en-v1.5_embs_nofiltering_sortlenTrue_phrase2sent_15epoch_15epoch__adam0.001_accum1_best_epoch_3863037_bs128_result
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.71641791044777
    - type: ap
      value: 35.599140186230734
    - type: f1
      value: 66.72372354326045
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 72.7823
    - type: ap
      value: 66.88980427652794
    - type: f1
      value: 72.60105018624591
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 38.483999999999995
    - type: f1
      value: 37.867826932045745
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.195
    - type: map_at_10
      value: 35.876999999999995
    - type: map_at_100
      value: 37.147999999999996
    - type: map_at_1000
      value: 37.165
    - type: map_at_3
      value: 31.342
    - type: map_at_5
      value: 33.764
    - type: mrr_at_1
      value: 21.906
    - type: mrr_at_10
      value: 36.128
    - type: mrr_at_100
      value: 37.397999999999996
    - type: mrr_at_1000
      value: 37.416
    - type: mrr_at_3
      value: 31.555
    - type: mrr_at_5
      value: 34.001999999999995
    - type: ndcg_at_1
      value: 21.195
    - type: ndcg_at_10
      value: 44.207
    - type: ndcg_at_100
      value: 49.88
    - type: ndcg_at_1000
      value: 50.298
    - type: ndcg_at_3
      value: 34.755
    - type: ndcg_at_5
      value: 39.135
    - type: precision_at_1
      value: 21.195
    - type: precision_at_10
      value: 7.091
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 14.889
    - type: precision_at_5
      value: 11.067
    - type: recall_at_1
      value: 21.195
    - type: recall_at_10
      value: 70.91
    - type: recall_at_100
      value: 96.30199999999999
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 44.666
    - type: recall_at_5
      value: 55.334
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 38.289190023047105
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 28.15017802770073
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.677327183831046
    - type: mrr
      value: 68.2003253748406
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.79485923763309
    - type: cos_sim_spearman
      value: 79.71265968052003
    - type: euclidean_pearson
      value: 80.78575386279923
    - type: euclidean_spearman
      value: 79.71265968052003
    - type: manhattan_pearson
      value: 81.12300703450198
    - type: manhattan_spearman
      value: 81.23377867759768
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.04870129870129
    - type: f1
      value: 74.29090714638184
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.18202629628483
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.419352316577875
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.305
    - type: map_at_10
      value: 28.046
    - type: map_at_100
      value: 29.174
    - type: map_at_1000
      value: 29.326999999999998
    - type: map_at_3
      value: 25.464
    - type: map_at_5
      value: 26.874
    - type: mrr_at_1
      value: 26.179999999999996
    - type: mrr_at_10
      value: 34.0
    - type: mrr_at_100
      value: 34.797
    - type: mrr_at_1000
      value: 34.864
    - type: mrr_at_3
      value: 31.784000000000002
    - type: mrr_at_5
      value: 32.992
    - type: ndcg_at_1
      value: 26.179999999999996
    - type: ndcg_at_10
      value: 33.46
    - type: ndcg_at_100
      value: 38.539
    - type: ndcg_at_1000
      value: 41.619
    - type: ndcg_at_3
      value: 29.471000000000004
    - type: ndcg_at_5
      value: 31.169999999999998
    - type: precision_at_1
      value: 26.179999999999996
    - type: precision_at_10
      value: 6.680999999999999
    - type: precision_at_100
      value: 1.15
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 14.591999999999999
    - type: precision_at_5
      value: 10.73
    - type: recall_at_1
      value: 20.305
    - type: recall_at_10
      value: 43.199
    - type: recall_at_100
      value: 66.46
    - type: recall_at_1000
      value: 87.469
    - type: recall_at_3
      value: 30.94
    - type: recall_at_5
      value: 35.927
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 18.265
    - type: map_at_10
      value: 24.661
    - type: map_at_100
      value: 25.739
    - type: map_at_1000
      value: 25.86
    - type: map_at_3
      value: 22.775000000000002
    - type: map_at_5
      value: 23.814
    - type: mrr_at_1
      value: 23.185
    - type: mrr_at_10
      value: 29.067
    - type: mrr_at_100
      value: 29.939
    - type: mrr_at_1000
      value: 30.007
    - type: mrr_at_3
      value: 27.197
    - type: mrr_at_5
      value: 28.248
    - type: ndcg_at_1
      value: 23.185
    - type: ndcg_at_10
      value: 28.638
    - type: ndcg_at_100
      value: 33.341
    - type: ndcg_at_1000
      value: 36.11
    - type: ndcg_at_3
      value: 25.599
    - type: ndcg_at_5
      value: 26.901999999999997
    - type: precision_at_1
      value: 23.185
    - type: precision_at_10
      value: 5.306
    - type: precision_at_100
      value: 0.959
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 12.442
    - type: precision_at_5
      value: 8.764
    - type: recall_at_1
      value: 18.265
    - type: recall_at_10
      value: 36.055
    - type: recall_at_100
      value: 56.419
    - type: recall_at_1000
      value: 75.25500000000001
    - type: recall_at_3
      value: 26.906999999999996
    - type: recall_at_5
      value: 30.637999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.065
    - type: map_at_10
      value: 35.952
    - type: map_at_100
      value: 37.092999999999996
    - type: map_at_1000
      value: 37.19
    - type: map_at_3
      value: 33.410000000000004
    - type: map_at_5
      value: 34.743
    - type: mrr_at_1
      value: 31.223
    - type: mrr_at_10
      value: 39.174
    - type: mrr_at_100
      value: 40.091
    - type: mrr_at_1000
      value: 40.152
    - type: mrr_at_3
      value: 37.011
    - type: mrr_at_5
      value: 38.115
    - type: ndcg_at_1
      value: 31.223
    - type: ndcg_at_10
      value: 40.871
    - type: ndcg_at_100
      value: 46.068
    - type: ndcg_at_1000
      value: 48.295
    - type: ndcg_at_3
      value: 36.285000000000004
    - type: ndcg_at_5
      value: 38.25
    - type: precision_at_1
      value: 31.223
    - type: precision_at_10
      value: 6.639
    - type: precision_at_100
      value: 1.014
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 16.092000000000002
    - type: precision_at_5
      value: 11.047
    - type: recall_at_1
      value: 27.065
    - type: recall_at_10
      value: 52.605000000000004
    - type: recall_at_100
      value: 75.653
    - type: recall_at_1000
      value: 91.724
    - type: recall_at_3
      value: 40.150999999999996
    - type: recall_at_5
      value: 44.979
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.692999999999998
    - type: map_at_10
      value: 17.427
    - type: map_at_100
      value: 18.235
    - type: map_at_1000
      value: 18.355
    - type: map_at_3
      value: 16.144
    - type: map_at_5
      value: 16.81
    - type: mrr_at_1
      value: 13.672
    - type: mrr_at_10
      value: 18.633
    - type: mrr_at_100
      value: 19.447
    - type: mrr_at_1000
      value: 19.554
    - type: mrr_at_3
      value: 17.401
    - type: mrr_at_5
      value: 17.983
    - type: ndcg_at_1
      value: 13.672
    - type: ndcg_at_10
      value: 20.212
    - type: ndcg_at_100
      value: 24.66
    - type: ndcg_at_1000
      value: 28.265
    - type: ndcg_at_3
      value: 17.625
    - type: ndcg_at_5
      value: 18.728
    - type: precision_at_1
      value: 13.672
    - type: precision_at_10
      value: 3.141
    - type: precision_at_100
      value: 0.569
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 7.5329999999999995
    - type: precision_at_5
      value: 5.220000000000001
    - type: recall_at_1
      value: 12.692999999999998
    - type: recall_at_10
      value: 27.656
    - type: recall_at_100
      value: 48.927
    - type: recall_at_1000
      value: 77.113
    - type: recall_at_3
      value: 20.54
    - type: recall_at_5
      value: 23.177
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.814
    - type: map_at_10
      value: 11.472
    - type: map_at_100
      value: 12.283
    - type: map_at_1000
      value: 12.407
    - type: map_at_3
      value: 9.892
    - type: map_at_5
      value: 10.525
    - type: mrr_at_1
      value: 9.950000000000001
    - type: mrr_at_10
      value: 13.947999999999999
    - type: mrr_at_100
      value: 14.790000000000001
    - type: mrr_at_1000
      value: 14.893999999999998
    - type: mrr_at_3
      value: 12.189
    - type: mrr_at_5
      value: 12.91
    - type: ndcg_at_1
      value: 9.950000000000001
    - type: ndcg_at_10
      value: 14.481
    - type: ndcg_at_100
      value: 18.999
    - type: ndcg_at_1000
      value: 22.519
    - type: ndcg_at_3
      value: 11.212
    - type: ndcg_at_5
      value: 12.238
    - type: precision_at_1
      value: 9.950000000000001
    - type: precision_at_10
      value: 2.861
    - type: precision_at_100
      value: 0.607
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 5.224
    - type: precision_at_5
      value: 3.856
    - type: recall_at_1
      value: 7.814
    - type: recall_at_10
      value: 21.507
    - type: recall_at_100
      value: 42.067
    - type: recall_at_1000
      value: 68.059
    - type: recall_at_3
      value: 12.489
    - type: recall_at_5
      value: 14.973
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.572
    - type: map_at_10
      value: 24.854000000000003
    - type: map_at_100
      value: 26.029000000000003
    - type: map_at_1000
      value: 26.177
    - type: map_at_3
      value: 22.417
    - type: map_at_5
      value: 23.612
    - type: mrr_at_1
      value: 22.907
    - type: mrr_at_10
      value: 29.643000000000004
    - type: mrr_at_100
      value: 30.499
    - type: mrr_at_1000
      value: 30.586999999999996
    - type: mrr_at_3
      value: 27.108999999999998
    - type: mrr_at_5
      value: 28.355999999999998
    - type: ndcg_at_1
      value: 22.907
    - type: ndcg_at_10
      value: 29.601
    - type: ndcg_at_100
      value: 35.11
    - type: ndcg_at_1000
      value: 38.433
    - type: ndcg_at_3
      value: 25.068
    - type: ndcg_at_5
      value: 26.828000000000003
    - type: precision_at_1
      value: 22.907
    - type: precision_at_10
      value: 5.525
    - type: precision_at_100
      value: 1.002
    - type: precision_at_1000
      value: 0.149
    - type: precision_at_3
      value: 11.389000000000001
    - type: precision_at_5
      value: 8.354000000000001
    - type: recall_at_1
      value: 18.572
    - type: recall_at_10
      value: 39.499
    - type: recall_at_100
      value: 63.46000000000001
    - type: recall_at_1000
      value: 86.52499999999999
    - type: recall_at_3
      value: 26.699
    - type: recall_at_5
      value: 31.175000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 14.918000000000001
    - type: map_at_10
      value: 20.223
    - type: map_at_100
      value: 21.429000000000002
    - type: map_at_1000
      value: 21.578
    - type: map_at_3
      value: 18.278
    - type: map_at_5
      value: 19.312
    - type: mrr_at_1
      value: 18.037
    - type: mrr_at_10
      value: 23.75
    - type: mrr_at_100
      value: 24.804000000000002
    - type: mrr_at_1000
      value: 24.898
    - type: mrr_at_3
      value: 21.842
    - type: mrr_at_5
      value: 22.755
    - type: ndcg_at_1
      value: 18.037
    - type: ndcg_at_10
      value: 23.907
    - type: ndcg_at_100
      value: 29.663
    - type: ndcg_at_1000
      value: 33.245000000000005
    - type: ndcg_at_3
      value: 20.379
    - type: ndcg_at_5
      value: 21.799
    - type: precision_at_1
      value: 18.037
    - type: precision_at_10
      value: 4.452
    - type: precision_at_100
      value: 0.881
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 9.513
    - type: precision_at_5
      value: 6.895
    - type: recall_at_1
      value: 14.918000000000001
    - type: recall_at_10
      value: 31.503999999999998
    - type: recall_at_100
      value: 56.354000000000006
    - type: recall_at_1000
      value: 81.774
    - type: recall_at_3
      value: 21.819
    - type: recall_at_5
      value: 25.459
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.668083333333332
    - type: map_at_10
      value: 20.24666666666667
    - type: map_at_100
      value: 21.21025
    - type: map_at_1000
      value: 21.340666666666664
    - type: map_at_3
      value: 18.417083333333334
    - type: map_at_5
      value: 19.366833333333332
    - type: mrr_at_1
      value: 17.777833333333334
    - type: mrr_at_10
      value: 23.403333333333336
    - type: mrr_at_100
      value: 24.25408333333333
    - type: mrr_at_1000
      value: 24.34333333333333
    - type: mrr_at_3
      value: 21.6155
    - type: mrr_at_5
      value: 22.521
    - type: ndcg_at_1
      value: 17.777833333333334
    - type: ndcg_at_10
      value: 23.933500000000002
    - type: ndcg_at_100
      value: 28.714749999999995
    - type: ndcg_at_1000
      value: 31.968833333333336
    - type: ndcg_at_3
      value: 20.60758333333333
    - type: ndcg_at_5
      value: 21.982416666666666
    - type: precision_at_1
      value: 17.777833333333334
    - type: precision_at_10
      value: 4.3180000000000005
    - type: precision_at_100
      value: 0.8045833333333333
    - type: precision_at_1000
      value: 0.12691666666666668
    - type: precision_at_3
      value: 9.535000000000002
    - type: precision_at_5
      value: 6.825916666666666
    - type: recall_at_1
      value: 14.668083333333332
    - type: recall_at_10
      value: 31.930916666666665
    - type: recall_at_100
      value: 53.753249999999994
    - type: recall_at_1000
      value: 77.43366666666667
    - type: recall_at_3
      value: 22.524250000000002
    - type: recall_at_5
      value: 26.094916666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.096
    - type: map_at_10
      value: 15.190999999999999
    - type: map_at_100
      value: 15.922
    - type: map_at_1000
      value: 16.017
    - type: map_at_3
      value: 13.664000000000001
    - type: map_at_5
      value: 14.446
    - type: mrr_at_1
      value: 12.117
    - type: mrr_at_10
      value: 17.294
    - type: mrr_at_100
      value: 18.074
    - type: mrr_at_1000
      value: 18.153
    - type: mrr_at_3
      value: 15.823
    - type: mrr_at_5
      value: 16.59
    - type: ndcg_at_1
      value: 12.117
    - type: ndcg_at_10
      value: 18.248
    - type: ndcg_at_100
      value: 22.418
    - type: ndcg_at_1000
      value: 25.271
    - type: ndcg_at_3
      value: 15.368
    - type: ndcg_at_5
      value: 16.614
    - type: precision_at_1
      value: 12.117
    - type: precision_at_10
      value: 3.206
    - type: precision_at_100
      value: 0.583
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 7.106
    - type: precision_at_5
      value: 5.061
    - type: recall_at_1
      value: 10.096
    - type: recall_at_10
      value: 25.624000000000002
    - type: recall_at_100
      value: 45.49
    - type: recall_at_1000
      value: 67.392
    - type: recall_at_3
      value: 17.68
    - type: recall_at_5
      value: 20.823
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.7780000000000005
    - type: map_at_10
      value: 11.493
    - type: map_at_100
      value: 12.200999999999999
    - type: map_at_1000
      value: 12.324
    - type: map_at_3
      value: 10.244
    - type: map_at_5
      value: 10.899000000000001
    - type: mrr_at_1
      value: 9.876
    - type: mrr_at_10
      value: 14.001
    - type: mrr_at_100
      value: 14.701
    - type: mrr_at_1000
      value: 14.799999999999999
    - type: mrr_at_3
      value: 12.583
    - type: mrr_at_5
      value: 13.325000000000001
    - type: ndcg_at_1
      value: 9.876
    - type: ndcg_at_10
      value: 14.158000000000001
    - type: ndcg_at_100
      value: 18.038999999999998
    - type: ndcg_at_1000
      value: 21.58
    - type: ndcg_at_3
      value: 11.722000000000001
    - type: ndcg_at_5
      value: 12.769
    - type: precision_at_1
      value: 9.876
    - type: precision_at_10
      value: 2.705
    - type: precision_at_100
      value: 0.555
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 5.666
    - type: precision_at_5
      value: 4.178
    - type: recall_at_1
      value: 7.7780000000000005
    - type: recall_at_10
      value: 19.86
    - type: recall_at_100
      value: 38.0
    - type: recall_at_1000
      value: 64.331
    - type: recall_at_3
      value: 13.117999999999999
    - type: recall_at_5
      value: 15.783
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.088
    - type: map_at_10
      value: 17.759
    - type: map_at_100
      value: 18.597
    - type: map_at_1000
      value: 18.718
    - type: map_at_3
      value: 16.232
    - type: map_at_5
      value: 17.129
    - type: mrr_at_1
      value: 15.672
    - type: mrr_at_10
      value: 20.676
    - type: mrr_at_100
      value: 21.505
    - type: mrr_at_1000
      value: 21.605
    - type: mrr_at_3
      value: 18.999
    - type: mrr_at_5
      value: 19.932
    - type: ndcg_at_1
      value: 15.672
    - type: ndcg_at_10
      value: 21.035
    - type: ndcg_at_100
      value: 25.52
    - type: ndcg_at_1000
      value: 28.875
    - type: ndcg_at_3
      value: 18.015
    - type: ndcg_at_5
      value: 19.476
    - type: precision_at_1
      value: 15.672
    - type: precision_at_10
      value: 3.535
    - type: precision_at_100
      value: 0.652
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 8.24
    - type: precision_at_5
      value: 5.821
    - type: recall_at_1
      value: 13.088
    - type: recall_at_10
      value: 28.414
    - type: recall_at_100
      value: 48.949999999999996
    - type: recall_at_1000
      value: 73.67399999999999
    - type: recall_at_3
      value: 19.893
    - type: recall_at_5
      value: 23.718
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.433
    - type: map_at_10
      value: 19.926
    - type: map_at_100
      value: 21.11
    - type: map_at_1000
      value: 21.302
    - type: map_at_3
      value: 17.991
    - type: map_at_5
      value: 19.078999999999997
    - type: mrr_at_1
      value: 17.391000000000002
    - type: mrr_at_10
      value: 23.433999999999997
    - type: mrr_at_100
      value: 24.41
    - type: mrr_at_1000
      value: 24.501
    - type: mrr_at_3
      value: 21.706
    - type: mrr_at_5
      value: 22.684
    - type: ndcg_at_1
      value: 17.391000000000002
    - type: ndcg_at_10
      value: 24.11
    - type: ndcg_at_100
      value: 29.500999999999998
    - type: ndcg_at_1000
      value: 33.093
    - type: ndcg_at_3
      value: 21.037
    - type: ndcg_at_5
      value: 22.439
    - type: precision_at_1
      value: 17.391000000000002
    - type: precision_at_10
      value: 4.881
    - type: precision_at_100
      value: 1.138
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 10.277
    - type: precision_at_5
      value: 7.549
    - type: recall_at_1
      value: 13.433
    - type: recall_at_10
      value: 32.029
    - type: recall_at_100
      value: 57.727
    - type: recall_at_1000
      value: 82.536
    - type: recall_at_3
      value: 22.914
    - type: recall_at_5
      value: 26.844
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.99
    - type: map_at_10
      value: 15.956000000000001
    - type: map_at_100
      value: 16.711000000000002
    - type: map_at_1000
      value: 16.833000000000002
    - type: map_at_3
      value: 14.494000000000002
    - type: map_at_5
      value: 15.159
    - type: mrr_at_1
      value: 13.123999999999999
    - type: mrr_at_10
      value: 17.22
    - type: mrr_at_100
      value: 17.992
    - type: mrr_at_1000
      value: 18.105
    - type: mrr_at_3
      value: 15.742
    - type: mrr_at_5
      value: 16.362
    - type: ndcg_at_1
      value: 13.123999999999999
    - type: ndcg_at_10
      value: 18.481
    - type: ndcg_at_100
      value: 22.719
    - type: ndcg_at_1000
      value: 26.321
    - type: ndcg_at_3
      value: 15.509999999999998
    - type: ndcg_at_5
      value: 16.576
    - type: precision_at_1
      value: 13.123999999999999
    - type: precision_at_10
      value: 2.884
    - type: precision_at_100
      value: 0.545
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 6.346
    - type: precision_at_5
      value: 4.436
    - type: recall_at_1
      value: 11.99
    - type: recall_at_10
      value: 25.219
    - type: recall_at_100
      value: 45.532000000000004
    - type: recall_at_1000
      value: 73.35199999999999
    - type: recall_at_3
      value: 17.141000000000002
    - type: recall_at_5
      value: 19.643
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.6240000000000006
    - type: map_at_10
      value: 13.211999999999998
    - type: map_at_100
      value: 14.82
    - type: map_at_1000
      value: 15.039
    - type: map_at_3
      value: 10.793999999999999
    - type: map_at_5
      value: 12.035
    - type: mrr_at_1
      value: 17.459
    - type: mrr_at_10
      value: 26.590000000000003
    - type: mrr_at_100
      value: 27.792
    - type: mrr_at_1000
      value: 27.851
    - type: mrr_at_3
      value: 23.268
    - type: mrr_at_5
      value: 25.192999999999998
    - type: ndcg_at_1
      value: 17.459
    - type: ndcg_at_10
      value: 19.606
    - type: ndcg_at_100
      value: 26.87
    - type: ndcg_at_1000
      value: 31.080000000000002
    - type: ndcg_at_3
      value: 15.190000000000001
    - type: ndcg_at_5
      value: 16.85
    - type: precision_at_1
      value: 17.459
    - type: precision_at_10
      value: 6.45
    - type: precision_at_100
      value: 1.421
    - type: precision_at_1000
      value: 0.219
    - type: precision_at_3
      value: 11.488
    - type: precision_at_5
      value: 9.316
    - type: recall_at_1
      value: 7.6240000000000006
    - type: recall_at_10
      value: 24.593
    - type: recall_at_100
      value: 50.300999999999995
    - type: recall_at_1000
      value: 74.439
    - type: recall_at_3
      value: 14.097000000000001
    - type: recall_at_5
      value: 18.362000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.456
    - type: map_at_10
      value: 9.995
    - type: map_at_100
      value: 14.196
    - type: map_at_1000
      value: 15.284
    - type: map_at_3
      value: 7.02
    - type: map_at_5
      value: 8.341
    - type: mrr_at_1
      value: 43.25
    - type: mrr_at_10
      value: 52.626
    - type: mrr_at_100
      value: 53.361000000000004
    - type: mrr_at_1000
      value: 53.396
    - type: mrr_at_3
      value: 50.208
    - type: mrr_at_5
      value: 51.696
    - type: ndcg_at_1
      value: 31.75
    - type: ndcg_at_10
      value: 24.557000000000002
    - type: ndcg_at_100
      value: 28.179
    - type: ndcg_at_1000
      value: 35.42
    - type: ndcg_at_3
      value: 27.05
    - type: ndcg_at_5
      value: 25.938
    - type: precision_at_1
      value: 43.25
    - type: precision_at_10
      value: 21.95
    - type: precision_at_100
      value: 7.21
    - type: precision_at_1000
      value: 1.5310000000000001
    - type: precision_at_3
      value: 32.25
    - type: precision_at_5
      value: 28.050000000000004
    - type: recall_at_1
      value: 4.456
    - type: recall_at_10
      value: 14.808
    - type: recall_at_100
      value: 35.062
    - type: recall_at_1000
      value: 60.111000000000004
    - type: recall_at_3
      value: 8.333
    - type: recall_at_5
      value: 10.847999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 48.275
    - type: f1
      value: 44.11697299626323
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.512
    - type: map_at_10
      value: 25.102000000000004
    - type: map_at_100
      value: 26.14
    - type: map_at_1000
      value: 26.212000000000003
    - type: map_at_3
      value: 22.531000000000002
    - type: map_at_5
      value: 23.959
    - type: mrr_at_1
      value: 17.642
    - type: mrr_at_10
      value: 26.665
    - type: mrr_at_100
      value: 27.700000000000003
    - type: mrr_at_1000
      value: 27.762999999999998
    - type: mrr_at_3
      value: 24.03
    - type: mrr_at_5
      value: 25.501
    - type: ndcg_at_1
      value: 17.642
    - type: ndcg_at_10
      value: 30.162
    - type: ndcg_at_100
      value: 35.393
    - type: ndcg_at_1000
      value: 37.370999999999995
    - type: ndcg_at_3
      value: 24.878
    - type: ndcg_at_5
      value: 27.426000000000002
    - type: precision_at_1
      value: 17.642
    - type: precision_at_10
      value: 4.845
    - type: precision_at_100
      value: 0.765
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 10.876
    - type: precision_at_5
      value: 7.864
    - type: recall_at_1
      value: 16.512
    - type: recall_at_10
      value: 44.528
    - type: recall_at_100
      value: 68.794
    - type: recall_at_1000
      value: 84.055
    - type: recall_at_3
      value: 30.151
    - type: recall_at_5
      value: 36.244
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.548
    - type: map_at_10
      value: 11.365
    - type: map_at_100
      value: 12.659
    - type: map_at_1000
      value: 12.870999999999999
    - type: map_at_3
      value: 9.238
    - type: map_at_5
      value: 10.295
    - type: mrr_at_1
      value: 13.735
    - type: mrr_at_10
      value: 19.666
    - type: mrr_at_100
      value: 20.848
    - type: mrr_at_1000
      value: 20.951
    - type: mrr_at_3
      value: 17.335
    - type: mrr_at_5
      value: 18.616
    - type: ndcg_at_1
      value: 13.735
    - type: ndcg_at_10
      value: 15.923000000000002
    - type: ndcg_at_100
      value: 22.23
    - type: ndcg_at_1000
      value: 26.893
    - type: ndcg_at_3
      value: 12.756
    - type: ndcg_at_5
      value: 13.883999999999999
    - type: precision_at_1
      value: 13.735
    - type: precision_at_10
      value: 4.7379999999999995
    - type: precision_at_100
      value: 1.086
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 8.436
    - type: precision_at_5
      value: 6.7589999999999995
    - type: recall_at_1
      value: 6.548
    - type: recall_at_10
      value: 21.267
    - type: recall_at_100
      value: 46.07
    - type: recall_at_1000
      value: 74.868
    - type: recall_at_3
      value: 11.611
    - type: recall_at_5
      value: 15.284
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 17.387
    - type: map_at_10
      value: 24.564
    - type: map_at_100
      value: 25.503999999999998
    - type: map_at_1000
      value: 25.619999999999997
    - type: map_at_3
      value: 22.496
    - type: map_at_5
      value: 23.646
    - type: mrr_at_1
      value: 34.774
    - type: mrr_at_10
      value: 41.935
    - type: mrr_at_100
      value: 42.679
    - type: mrr_at_1000
      value: 42.737
    - type: mrr_at_3
      value: 39.883
    - type: mrr_at_5
      value: 41.063
    - type: ndcg_at_1
      value: 34.774
    - type: ndcg_at_10
      value: 31.456
    - type: ndcg_at_100
      value: 35.827
    - type: ndcg_at_1000
      value: 38.627
    - type: ndcg_at_3
      value: 27.534999999999997
    - type: ndcg_at_5
      value: 29.452
    - type: precision_at_1
      value: 34.774
    - type: precision_at_10
      value: 6.97
    - type: precision_at_100
      value: 1.048
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 17.349
    - type: precision_at_5
      value: 11.924
    - type: recall_at_1
      value: 17.387
    - type: recall_at_10
      value: 34.848
    - type: recall_at_100
      value: 52.384
    - type: recall_at_1000
      value: 71.134
    - type: recall_at_3
      value: 26.023000000000003
    - type: recall_at_5
      value: 29.811
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 69.98119999999999
    - type: ap
      value: 64.17725086855937
    - type: f1
      value: 69.78928359055172
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.372999999999999
    - type: map_at_10
      value: 11.145
    - type: map_at_100
      value: 12.055
    - type: map_at_1000
      value: 12.17
    - type: map_at_3
      value: 9.391
    - type: map_at_5
      value: 10.270999999999999
    - type: mrr_at_1
      value: 6.561999999999999
    - type: mrr_at_10
      value: 11.446000000000002
    - type: mrr_at_100
      value: 12.359
    - type: mrr_at_1000
      value: 12.47
    - type: mrr_at_3
      value: 9.654
    - type: mrr_at_5
      value: 10.566
    - type: ndcg_at_1
      value: 6.5329999999999995
    - type: ndcg_at_10
      value: 14.174000000000001
    - type: ndcg_at_100
      value: 19.168
    - type: ndcg_at_1000
      value: 22.579
    - type: ndcg_at_3
      value: 10.465
    - type: ndcg_at_5
      value: 12.057
    - type: precision_at_1
      value: 6.5329999999999995
    - type: precision_at_10
      value: 2.451
    - type: precision_at_100
      value: 0.506
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 4.58
    - type: precision_at_5
      value: 3.553
    - type: recall_at_1
      value: 6.372999999999999
    - type: recall_at_10
      value: 23.639
    - type: recall_at_100
      value: 48.012
    - type: recall_at_1000
      value: 75.368
    - type: recall_at_3
      value: 13.333
    - type: recall_at_5
      value: 17.147000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.3953488372093
    - type: f1
      value: 90.47618297254341
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 61.249430004559954
    - type: f1
      value: 42.242289025471344
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.15131136516476
    - type: f1
      value: 62.8508450491576
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.9670477471419
    - type: f1
      value: 70.83719077833712
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.27049656570754
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.8992311215977
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.216583547389536
    - type: mrr
      value: 32.31147129597184
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.651000000000001
    - type: map_at_10
      value: 8.924999999999999
    - type: map_at_100
      value: 11.43
    - type: map_at_1000
      value: 12.879999999999999
    - type: map_at_3
      value: 6.718
    - type: map_at_5
      value: 7.727
    - type: mrr_at_1
      value: 37.461
    - type: mrr_at_10
      value: 46.018
    - type: mrr_at_100
      value: 46.649
    - type: mrr_at_1000
      value: 46.713
    - type: mrr_at_3
      value: 43.55
    - type: mrr_at_5
      value: 44.928000000000004
    - type: ndcg_at_1
      value: 36.378
    - type: ndcg_at_10
      value: 27.193
    - type: ndcg_at_100
      value: 25.840000000000003
    - type: ndcg_at_1000
      value: 35.382999999999996
    - type: ndcg_at_3
      value: 31.054
    - type: ndcg_at_5
      value: 29.523
    - type: precision_at_1
      value: 37.461
    - type: precision_at_10
      value: 19.875999999999998
    - type: precision_at_100
      value: 7.198
    - type: precision_at_1000
      value: 2.069
    - type: precision_at_3
      value: 28.38
    - type: precision_at_5
      value: 25.386999999999997
    - type: recall_at_1
      value: 4.651000000000001
    - type: recall_at_10
      value: 13.517999999999999
    - type: recall_at_100
      value: 28.475
    - type: recall_at_1000
      value: 61.861999999999995
    - type: recall_at_3
      value: 7.657
    - type: recall_at_5
      value: 9.76
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.456000000000001
    - type: map_at_10
      value: 16.392
    - type: map_at_100
      value: 17.730999999999998
    - type: map_at_1000
      value: 17.835
    - type: map_at_3
      value: 13.743
    - type: map_at_5
      value: 15.262999999999998
    - type: mrr_at_1
      value: 10.776
    - type: mrr_at_10
      value: 18.163999999999998
    - type: mrr_at_100
      value: 19.403000000000002
    - type: mrr_at_1000
      value: 19.489
    - type: mrr_at_3
      value: 15.464
    - type: mrr_at_5
      value: 17.035
    - type: ndcg_at_1
      value: 10.776
    - type: ndcg_at_10
      value: 20.959
    - type: ndcg_at_100
      value: 27.589000000000002
    - type: ndcg_at_1000
      value: 30.416999999999998
    - type: ndcg_at_3
      value: 15.552
    - type: ndcg_at_5
      value: 18.275
    - type: precision_at_1
      value: 10.776
    - type: precision_at_10
      value: 3.94
    - type: precision_at_100
      value: 0.763
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 7.396999999999999
    - type: precision_at_5
      value: 5.933
    - type: recall_at_1
      value: 9.456000000000001
    - type: recall_at_10
      value: 33.394
    - type: recall_at_100
      value: 63.915
    - type: recall_at_1000
      value: 85.598
    - type: recall_at_3
      value: 19.098000000000003
    - type: recall_at_5
      value: 25.466
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 64.744
    - type: map_at_10
      value: 77.86
    - type: map_at_100
      value: 78.58800000000001
    - type: map_at_1000
      value: 78.617
    - type: map_at_3
      value: 74.788
    - type: map_at_5
      value: 76.716
    - type: mrr_at_1
      value: 74.49
    - type: mrr_at_10
      value: 81.843
    - type: mrr_at_100
      value: 82.035
    - type: mrr_at_1000
      value: 82.038
    - type: mrr_at_3
      value: 80.39
    - type: mrr_at_5
      value: 81.372
    - type: ndcg_at_1
      value: 74.59
    - type: ndcg_at_10
      value: 82.459
    - type: ndcg_at_100
      value: 84.34899999999999
    - type: ndcg_at_1000
      value: 84.626
    - type: ndcg_at_3
      value: 78.821
    - type: ndcg_at_5
      value: 80.83500000000001
    - type: precision_at_1
      value: 74.59
    - type: precision_at_10
      value: 12.494
    - type: precision_at_100
      value: 1.477
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 34.233000000000004
    - type: precision_at_5
      value: 22.747999999999998
    - type: recall_at_1
      value: 64.744
    - type: recall_at_10
      value: 91.355
    - type: recall_at_100
      value: 98.30799999999999
    - type: recall_at_1000
      value: 99.766
    - type: recall_at_3
      value: 81.109
    - type: recall_at_5
      value: 86.572
    - type: map_at_1
      value: 2.868
    - type: map_at_10
      value: 7.155
    - type: map_at_100
      value: 8.651
    - type: map_at_1000
      value: 8.921
    - type: map_at_3
      value: 5.197
    - type: map_at_5
      value: 6.168
    - type: mrr_at_1
      value: 14.099999999999998
    - type: mrr_at_10
      value: 22.528000000000002
    - type: mrr_at_100
      value: 23.730999999999998
    - type: mrr_at_1000
      value: 23.827
    - type: mrr_at_3
      value: 19.683
    - type: mrr_at_5
      value: 21.233
    - type: ndcg_at_1
      value: 14.099999999999998
    - type: ndcg_at_10
      value: 12.756
    - type: ndcg_at_100
      value: 19.49
    - type: ndcg_at_1000
      value: 24.942
    - type: ndcg_at_3
      value: 11.905000000000001
    - type: ndcg_at_5
      value: 10.474
    - type: precision_at_1
      value: 14.099999999999998
    - type: precision_at_10
      value: 6.7299999999999995
    - type: precision_at_100
      value: 1.657
    - type: precision_at_1000
      value: 0.297
    - type: precision_at_3
      value: 11.200000000000001
    - type: precision_at_5
      value: 9.3
    - type: recall_at_1
      value: 2.868
    - type: recall_at_10
      value: 13.613
    - type: recall_at_100
      value: 33.645
    - type: recall_at_1000
      value: 60.372
    - type: recall_at_3
      value: 6.808
    - type: recall_at_5
      value: 9.418
    - type: map_at_1
      value: 0.157
    - type: map_at_10
      value: 0.989
    - type: map_at_100
      value: 5.3580000000000005
    - type: map_at_1000
      value: 13.614999999999998
    - type: map_at_3
      value: 0.391
    - type: map_at_5
      value: 0.557
    - type: mrr_at_1
      value: 57.99999999999999
    - type: mrr_at_10
      value: 69.039
    - type: mrr_at_100
      value: 69.618
    - type: mrr_at_1000
      value: 69.618
    - type: mrr_at_3
      value: 67.667
    - type: mrr_at_5
      value: 68.56700000000001
    - type: ndcg_at_1
      value: 55.00000000000001
    - type: ndcg_at_10
      value: 48.394
    - type: ndcg_at_100
      value: 37.158
    - type: ndcg_at_1000
      value: 34.204
    - type: ndcg_at_3
      value: 53.754000000000005
    - type: ndcg_at_5
      value: 50.712999999999994
    - type: precision_at_1
      value: 57.99999999999999
    - type: precision_at_10
      value: 51.800000000000004
    - type: precision_at_100
      value: 39.26
    - type: precision_at_1000
      value: 16.503999999999998
    - type: precision_at_3
      value: 57.333
    - type: precision_at_5
      value: 52.800000000000004
    - type: recall_at_1
      value: 0.157
    - type: recall_at_10
      value: 1.238
    - type: recall_at_100
      value: 8.674
    - type: recall_at_1000
      value: 33.222
    - type: recall_at_3
      value: 0.436
    - type: recall_at_5
      value: 0.643
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 46.254882422464526
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 50.94989318333412
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 77.98965504956827
    - type: cos_sim_spearman
      value: 68.28460263921258
    - type: euclidean_pearson
      value: 73.50270698016448
    - type: euclidean_spearman
      value: 68.28468403646217
    - type: manhattan_pearson
      value: 72.8261914195885
    - type: manhattan_spearman
      value: 67.86873546122553
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.14830947681742
    - type: cos_sim_spearman
      value: 68.60266030636393
    - type: euclidean_pearson
      value: 72.88451477994006
    - type: euclidean_spearman
      value: 68.60389167221209
    - type: manhattan_pearson
      value: 71.89880964464528
    - type: manhattan_spearman
      value: 68.11051648970675
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.72037928360238
    - type: cos_sim_spearman
      value: 79.74389537608737
    - type: euclidean_pearson
      value: 79.39980926218213
    - type: euclidean_spearman
      value: 79.74393317465844
    - type: manhattan_pearson
      value: 78.7481714360194
    - type: manhattan_spearman
      value: 79.05784658583435
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 79.20839429694983
    - type: cos_sim_spearman
      value: 75.75758249233702
    - type: euclidean_pearson
      value: 78.2593144118954
    - type: euclidean_spearman
      value: 75.7575727998599
    - type: manhattan_pearson
      value: 77.98797449902915
    - type: manhattan_spearman
      value: 75.58570762607603
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 82.38797626966284
    - type: cos_sim_spearman
      value: 83.0821006142509
    - type: euclidean_pearson
      value: 82.89995084283936
    - type: euclidean_spearman
      value: 83.08209908184749
    - type: manhattan_pearson
      value: 82.6019409098804
    - type: manhattan_spearman
      value: 82.76534947735776
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.80219740466768
    - type: cos_sim_spearman
      value: 79.07336247296158
    - type: euclidean_pearson
      value: 78.34175159212086
    - type: euclidean_spearman
      value: 79.07335507859334
    - type: manhattan_pearson
      value: 78.146156004842
    - type: manhattan_spearman
      value: 78.85783029933849
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.74773705987958
    - type: cos_sim_spearman
      value: 85.73402749289298
    - type: euclidean_pearson
      value: 85.18510280404286
    - type: euclidean_spearman
      value: 85.73490066116952
    - type: manhattan_pearson
      value: 84.93638596678905
    - type: manhattan_spearman
      value: 85.5315548466084
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 59.17015437324628
    - type: cos_sim_spearman
      value: 59.75467857816752
    - type: euclidean_pearson
      value: 60.812443155269534
    - type: euclidean_spearman
      value: 59.75467857816752
    - type: manhattan_pearson
      value: 59.950493146979255
    - type: manhattan_spearman
      value: 58.932105528273645
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 80.46948132600193
    - type: cos_sim_spearman
      value: 79.10069645170242
    - type: euclidean_pearson
      value: 80.31463403998292
    - type: euclidean_spearman
      value: 79.10071491600597
    - type: manhattan_pearson
      value: 80.01917165738134
    - type: manhattan_spearman
      value: 78.86150076844012
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.0368453616957
    - type: mrr
      value: 91.42105987694224
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 37.083
    - type: map_at_10
      value: 45.626
    - type: map_at_100
      value: 46.741
    - type: map_at_1000
      value: 46.796
    - type: map_at_3
      value: 43.397999999999996
    - type: map_at_5
      value: 44.098
    - type: mrr_at_1
      value: 39.333
    - type: mrr_at_10
      value: 47.424
    - type: mrr_at_100
      value: 48.365
    - type: mrr_at_1000
      value: 48.413000000000004
    - type: mrr_at_3
      value: 45.444
    - type: mrr_at_5
      value: 46.011
    - type: ndcg_at_1
      value: 39.333
    - type: ndcg_at_10
      value: 50.324999999999996
    - type: ndcg_at_100
      value: 55.74400000000001
    - type: ndcg_at_1000
      value: 57.092
    - type: ndcg_at_3
      value: 45.805
    - type: ndcg_at_5
      value: 46.826
    - type: precision_at_1
      value: 39.333
    - type: precision_at_10
      value: 6.9
    - type: precision_at_100
      value: 0.993
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 18.111
    - type: precision_at_5
      value: 11.466999999999999
    - type: recall_at_1
      value: 37.083
    - type: recall_at_10
      value: 63.444
    - type: recall_at_100
      value: 88.617
    - type: recall_at_1000
      value: 98.867
    - type: recall_at_3
      value: 50.556
    - type: recall_at_5
      value: 53.056000000000004
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.66039603960397
    - type: cos_sim_ap
      value: 89.16346887114837
    - type: cos_sim_f1
      value: 83.18072289156628
    - type: cos_sim_precision
      value: 80.27906976744185
    - type: cos_sim_recall
      value: 86.3
    - type: dot_accuracy
      value: 99.66039603960397
    - type: dot_ap
      value: 89.16346887114837
    - type: dot_f1
      value: 83.18072289156628
    - type: dot_precision
      value: 80.27906976744185
    - type: dot_recall
      value: 86.3
    - type: euclidean_accuracy
      value: 99.66039603960397
    - type: euclidean_ap
      value: 89.16346887114837
    - type: euclidean_f1
      value: 83.18072289156628
    - type: euclidean_precision
      value: 80.27906976744185
    - type: euclidean_recall
      value: 86.3
    - type: manhattan_accuracy
      value: 99.66930693069307
    - type: manhattan_ap
      value: 89.13276894140405
    - type: manhattan_f1
      value: 83.46534653465346
    - type: manhattan_precision
      value: 82.6470588235294
    - type: manhattan_recall
      value: 84.3
    - type: max_accuracy
      value: 99.66930693069307
    - type: max_ap
      value: 89.16346887114837
    - type: max_f1
      value: 83.46534653465346
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 49.394155025012324
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.32321222461949
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.523517787741575
    - type: mrr
      value: 44.07447638146168
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.28542082978425
    - type: cos_sim_spearman
      value: 30.039804865964005
    - type: dot_pearson
      value: 31.28542082880828
    - type: dot_spearman
      value: 30.051397798547818
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.385
    - type: map_at_10
      value: 7.414
    - type: map_at_100
      value: 13.084999999999999
    - type: map_at_1000
      value: 14.765
    - type: map_at_3
      value: 3.5909999999999997
    - type: map_at_5
      value: 5.402
    - type: mrr_at_1
      value: 20.408
    - type: mrr_at_10
      value: 37.669000000000004
    - type: mrr_at_100
      value: 38.823
    - type: mrr_at_1000
      value: 38.823
    - type: mrr_at_3
      value: 33.672999999999995
    - type: mrr_at_5
      value: 35.612
    - type: ndcg_at_1
      value: 19.387999999999998
    - type: ndcg_at_10
      value: 19.288
    - type: ndcg_at_100
      value: 33.376
    - type: ndcg_at_1000
      value: 45.28
    - type: ndcg_at_3
      value: 20.511
    - type: ndcg_at_5
      value: 21.182000000000002
    - type: precision_at_1
      value: 20.408
    - type: precision_at_10
      value: 18.776
    - type: precision_at_100
      value: 8.061
    - type: precision_at_1000
      value: 1.5779999999999998
    - type: precision_at_3
      value: 23.810000000000002
    - type: precision_at_5
      value: 23.673
    - type: recall_at_1
      value: 1.385
    - type: recall_at_10
      value: 13.113
    - type: recall_at_100
      value: 48.345
    - type: recall_at_1000
      value: 85.087
    - type: recall_at_3
      value: 4.932
    - type: recall_at_5
      value: 8.4
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 79.2658
    - type: ap
      value: 19.45051650328674
    - type: f1
      value: 61.721255030714005
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 60.19524617996604
    - type: f1
      value: 60.47726202926952
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 42.20230019842334
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.32240567443525
    - type: cos_sim_ap
      value: 63.95052535841297
    - type: cos_sim_f1
      value: 60.78094302554028
    - type: cos_sim_precision
      value: 56.844281120808446
    - type: cos_sim_recall
      value: 65.30343007915567
    - type: dot_accuracy
      value: 83.32240567443525
    - type: dot_ap
      value: 63.95052535841297
    - type: dot_f1
      value: 60.78094302554028
    - type: dot_precision
      value: 56.844281120808446
    - type: dot_recall
      value: 65.30343007915567
    - type: euclidean_accuracy
      value: 83.32240567443525
    - type: euclidean_ap
      value: 63.95052535841297
    - type: euclidean_f1
      value: 60.78094302554028
    - type: euclidean_precision
      value: 56.844281120808446
    - type: euclidean_recall
      value: 65.30343007915567
    - type: manhattan_accuracy
      value: 83.30452405078381
    - type: manhattan_ap
      value: 63.82521079916541
    - type: manhattan_f1
      value: 60.567750833237554
    - type: manhattan_precision
      value: 53.65506006923234
    - type: manhattan_recall
      value: 69.52506596306068
    - type: max_accuracy
      value: 83.32240567443525
    - type: max_ap
      value: 63.95052535841297
    - type: max_f1
      value: 60.78094302554028
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.51309814879497
    - type: cos_sim_ap
      value: 83.04143677647984
    - type: cos_sim_f1
      value: 75.14412661109682
    - type: cos_sim_precision
      value: 71.82871182871183
    - type: cos_sim_recall
      value: 78.78041268863566
    - type: dot_accuracy
      value: 87.51309814879497
    - type: dot_ap
      value: 83.0414382592019
    - type: dot_f1
      value: 75.14412661109682
    - type: dot_precision
      value: 71.82871182871183
    - type: dot_recall
      value: 78.78041268863566
    - type: euclidean_accuracy
      value: 87.51309814879497
    - type: euclidean_ap
      value: 83.04144849399968
    - type: euclidean_f1
      value: 75.14412661109682
    - type: euclidean_precision
      value: 71.82871182871183
    - type: euclidean_recall
      value: 78.78041268863566
    - type: manhattan_accuracy
      value: 87.50921721581868
    - type: manhattan_ap
      value: 82.97187030449552
    - type: manhattan_f1
      value: 74.93584260051325
    - type: manhattan_precision
      value: 72.48003453485863
    - type: manhattan_recall
      value: 77.56390514320911
    - type: max_accuracy
      value: 87.51309814879497
    - type: max_ap
      value: 83.04144849399968
    - type: max_f1
      value: 75.14412661109682
---
