mteb model-index region:us
---
tags:
- mteb
model-index:
- name: llama3_STSprompt_new
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 76.76119402985076
    - type: ap
      value: 39.59339434775403
    - type: f1
      value: 70.4551858327582
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 60.84025
    - type: ap
      value: 56.82293339927369
    - type: f1
      value: 60.461296544029764
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.786
    - type: f1
      value: 31.584406207778038
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.407999999999998
    - type: map_at_10
      value: 36.149
    - type: map_at_100
      value: 37.397000000000006
    - type: map_at_1000
      value: 37.415
    - type: map_at_3
      value: 31.117
    - type: map_at_5
      value: 33.851
    - type: mrr_at_1
      value: 21.834999999999997
    - type: mrr_at_10
      value: 36.334
    - type: mrr_at_100
      value: 37.574999999999996
    - type: mrr_at_1000
      value: 37.592
    - type: mrr_at_3
      value: 31.283
    - type: mrr_at_5
      value: 34.046
    - type: ndcg_at_1
      value: 21.407999999999998
    - type: ndcg_at_10
      value: 44.786
    - type: ndcg_at_100
      value: 50.169
    - type: ndcg_at_1000
      value: 50.566
    - type: ndcg_at_3
      value: 34.319
    - type: ndcg_at_5
      value: 39.259
    - type: precision_at_1
      value: 21.407999999999998
    - type: precision_at_10
      value: 7.2620000000000005
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.533
    - type: precision_at_5
      value: 11.124
    - type: recall_at_1
      value: 21.407999999999998
    - type: recall_at_10
      value: 72.617
    - type: recall_at_100
      value: 96.30199999999999
    - type: recall_at_1000
      value: 99.289
    - type: recall_at_3
      value: 43.599
    - type: recall_at_5
      value: 55.619
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.204388842106965
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.528430856566054
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.435706376344065
    - type: mrr
      value: 68.46535197643232
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 80.75947376350628
    - type: cos_sim_spearman
      value: 78.76866226728414
    - type: euclidean_pearson
      value: 79.77815732635439
    - type: euclidean_spearman
      value: 78.76866226728414
    - type: manhattan_pearson
      value: 77.27913529620776
    - type: manhattan_spearman
      value: 76.785484549114
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.85714285714285
    - type: f1
      value: 72.12088062707018
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.91654959096841
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.40685330251096
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 23.343
    - type: map_at_10
      value: 30.634
    - type: map_at_100
      value: 31.904
    - type: map_at_1000
      value: 32.056000000000004
    - type: map_at_3
      value: 27.988000000000003
    - type: map_at_5
      value: 29.604000000000003
    - type: mrr_at_1
      value: 29.471000000000004
    - type: mrr_at_10
      value: 36.76
    - type: mrr_at_100
      value: 37.569
    - type: mrr_at_1000
      value: 37.637
    - type: mrr_at_3
      value: 34.406
    - type: mrr_at_5
      value: 35.900999999999996
    - type: ndcg_at_1
      value: 29.471000000000004
    - type: ndcg_at_10
      value: 35.754000000000005
    - type: ndcg_at_100
      value: 41.185
    - type: ndcg_at_1000
      value: 44.132
    - type: ndcg_at_3
      value: 31.791000000000004
    - type: ndcg_at_5
      value: 33.867000000000004
    - type: precision_at_1
      value: 29.471000000000004
    - type: precision_at_10
      value: 6.7379999999999995
    - type: precision_at_100
      value: 1.192
    - type: precision_at_1000
      value: 0.17600000000000002
    - type: precision_at_3
      value: 15.212
    - type: precision_at_5
      value: 11.245
    - type: recall_at_1
      value: 23.343
    - type: recall_at_10
      value: 44.596999999999994
    - type: recall_at_100
      value: 68.522
    - type: recall_at_1000
      value: 88.539
    - type: recall_at_3
      value: 32.592
    - type: recall_at_5
      value: 38.479
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 19.200999999999997
    - type: map_at_10
      value: 26.07
    - type: map_at_100
      value: 27.145999999999997
    - type: map_at_1000
      value: 27.265
    - type: map_at_3
      value: 23.952
    - type: map_at_5
      value: 25.083
    - type: mrr_at_1
      value: 24.459
    - type: mrr_at_10
      value: 30.769000000000002
    - type: mrr_at_100
      value: 31.595000000000002
    - type: mrr_at_1000
      value: 31.659
    - type: mrr_at_3
      value: 28.769
    - type: mrr_at_5
      value: 29.902
    - type: ndcg_at_1
      value: 24.459
    - type: ndcg_at_10
      value: 30.387999999999998
    - type: ndcg_at_100
      value: 35.17
    - type: ndcg_at_1000
      value: 37.852999999999994
    - type: ndcg_at_3
      value: 26.893
    - type: ndcg_at_5
      value: 28.43
    - type: precision_at_1
      value: 24.459
    - type: precision_at_10
      value: 5.599
    - type: precision_at_100
      value: 1.018
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 12.972
    - type: precision_at_5
      value: 9.159
    - type: recall_at_1
      value: 19.200999999999997
    - type: recall_at_10
      value: 38.721
    - type: recall_at_100
      value: 59.278
    - type: recall_at_1000
      value: 77.7
    - type: recall_at_3
      value: 28.402
    - type: recall_at_5
      value: 32.778
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.450000000000003
    - type: map_at_10
      value: 36.176
    - type: map_at_100
      value: 37.291000000000004
    - type: map_at_1000
      value: 37.388
    - type: map_at_3
      value: 33.525
    - type: map_at_5
      value: 35.128
    - type: mrr_at_1
      value: 31.661
    - type: mrr_at_10
      value: 39.306999999999995
    - type: mrr_at_100
      value: 40.256
    - type: mrr_at_1000
      value: 40.314
    - type: mrr_at_3
      value: 36.928
    - type: mrr_at_5
      value: 38.342
    - type: ndcg_at_1
      value: 31.661
    - type: ndcg_at_10
      value: 40.942
    - type: ndcg_at_100
      value: 46.225
    - type: ndcg_at_1000
      value: 48.369
    - type: ndcg_at_3
      value: 36.131
    - type: ndcg_at_5
      value: 38.646
    - type: precision_at_1
      value: 31.661
    - type: precision_at_10
      value: 6.596
    - type: precision_at_100
      value: 1.014
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 15.967
    - type: precision_at_5
      value: 11.298
    - type: recall_at_1
      value: 27.450000000000003
    - type: recall_at_10
      value: 52.268
    - type: recall_at_100
      value: 76.02499999999999
    - type: recall_at_1000
      value: 91.365
    - type: recall_at_3
      value: 39.377
    - type: recall_at_5
      value: 45.537
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.808000000000002
    - type: map_at_10
      value: 18.166
    - type: map_at_100
      value: 19.005
    - type: map_at_1000
      value: 19.127
    - type: map_at_3
      value: 16.821
    - type: map_at_5
      value: 17.407
    - type: mrr_at_1
      value: 15.254000000000001
    - type: mrr_at_10
      value: 19.505
    - type: mrr_at_100
      value: 20.337
    - type: mrr_at_1000
      value: 20.444000000000003
    - type: mrr_at_3
      value: 18.192
    - type: mrr_at_5
      value: 18.746
    - type: ndcg_at_1
      value: 15.254000000000001
    - type: ndcg_at_10
      value: 20.926000000000002
    - type: ndcg_at_100
      value: 25.363999999999997
    - type: ndcg_at_1000
      value: 28.986
    - type: ndcg_at_3
      value: 18.151999999999997
    - type: ndcg_at_5
      value: 19.154
    - type: precision_at_1
      value: 15.254000000000001
    - type: precision_at_10
      value: 3.209
    - type: precision_at_100
      value: 0.5760000000000001
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.5329999999999995
    - type: precision_at_5
      value: 5.13
    - type: recall_at_1
      value: 13.808000000000002
    - type: recall_at_10
      value: 28.301
    - type: recall_at_100
      value: 49.118
    - type: recall_at_1000
      value: 77.371
    - type: recall_at_3
      value: 20.625
    - type: recall_at_5
      value: 23.064
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.545
    - type: map_at_10
      value: 11.065999999999999
    - type: map_at_100
      value: 12.009
    - type: map_at_1000
      value: 12.145999999999999
    - type: map_at_3
      value: 9.862
    - type: map_at_5
      value: 10.458
    - type: mrr_at_1
      value: 9.826
    - type: mrr_at_10
      value: 13.819
    - type: mrr_at_100
      value: 14.760000000000002
    - type: mrr_at_1000
      value: 14.863999999999999
    - type: mrr_at_3
      value: 12.520999999999999
    - type: mrr_at_5
      value: 13.062000000000001
    - type: ndcg_at_1
      value: 9.826
    - type: ndcg_at_10
      value: 13.713000000000001
    - type: ndcg_at_100
      value: 18.834999999999997
    - type: ndcg_at_1000
      value: 22.567
    - type: ndcg_at_3
      value: 11.358
    - type: ndcg_at_5
      value: 12.212
    - type: precision_at_1
      value: 9.826
    - type: precision_at_10
      value: 2.637
    - type: precision_at_100
      value: 0.621
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 5.514
    - type: precision_at_5
      value: 3.9800000000000004
    - type: recall_at_1
      value: 7.545
    - type: recall_at_10
      value: 19.229
    - type: recall_at_100
      value: 42.588
    - type: recall_at_1000
      value: 70.111
    - type: recall_at_3
      value: 12.617999999999999
    - type: recall_at_5
      value: 14.777999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 19.002
    - type: map_at_10
      value: 25.330000000000002
    - type: map_at_100
      value: 26.561
    - type: map_at_1000
      value: 26.704
    - type: map_at_3
      value: 23.1
    - type: map_at_5
      value: 24.426000000000002
    - type: mrr_at_1
      value: 23.388
    - type: mrr_at_10
      value: 29.847
    - type: mrr_at_100
      value: 30.847
    - type: mrr_at_1000
      value: 30.932
    - type: mrr_at_3
      value: 27.687
    - type: mrr_at_5
      value: 29.000999999999998
    - type: ndcg_at_1
      value: 23.388
    - type: ndcg_at_10
      value: 29.721999999999998
    - type: ndcg_at_100
      value: 35.549
    - type: ndcg_at_1000
      value: 38.815
    - type: ndcg_at_3
      value: 25.887
    - type: ndcg_at_5
      value: 27.858
    - type: precision_at_1
      value: 23.388
    - type: precision_at_10
      value: 5.409
    - type: precision_at_100
      value: 0.983
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 11.902
    - type: precision_at_5
      value: 8.738999999999999
    - type: recall_at_1
      value: 19.002
    - type: recall_at_10
      value: 38.507000000000005
    - type: recall_at_100
      value: 64.043
    - type: recall_at_1000
      value: 86.97500000000001
    - type: recall_at_3
      value: 27.477
    - type: recall_at_5
      value: 32.719
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 14.74
    - type: map_at_10
      value: 21.048000000000002
    - type: map_at_100
      value: 22.172
    - type: map_at_1000
      value: 22.319
    - type: map_at_3
      value: 18.658
    - type: map_at_5
      value: 19.962
    - type: mrr_at_1
      value: 18.265
    - type: mrr_at_10
      value: 24.971
    - type: mrr_at_100
      value: 25.834000000000003
    - type: mrr_at_1000
      value: 25.929000000000002
    - type: mrr_at_3
      value: 22.66
    - type: mrr_at_5
      value: 23.955000000000002
    - type: ndcg_at_1
      value: 18.265
    - type: ndcg_at_10
      value: 25.404
    - type: ndcg_at_100
      value: 30.519000000000002
    - type: ndcg_at_1000
      value: 34.109
    - type: ndcg_at_3
      value: 21.104
    - type: ndcg_at_5
      value: 23.044
    - type: precision_at_1
      value: 18.265
    - type: precision_at_10
      value: 4.909
    - type: precision_at_100
      value: 0.89
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 10.046
    - type: precision_at_5
      value: 7.6259999999999994
    - type: recall_at_1
      value: 14.74
    - type: recall_at_10
      value: 34.69
    - type: recall_at_100
      value: 56.674
    - type: recall_at_1000
      value: 82.37
    - type: recall_at_3
      value: 22.924
    - type: recall_at_5
      value: 27.72
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 15.725666666666669
    - type: map_at_10
      value: 21.168583333333334
    - type: map_at_100
      value: 22.158666666666665
    - type: map_at_1000
      value: 22.29175
    - type: map_at_3
      value: 19.335833333333337
    - type: map_at_5
      value: 20.32875
    - type: mrr_at_1
      value: 18.944333333333336
    - type: mrr_at_10
      value: 24.424
    - type: mrr_at_100
      value: 25.27591666666667
    - type: mrr_at_1000
      value: 25.36416666666667
    - type: mrr_at_3
      value: 22.627416666666665
    - type: mrr_at_5
      value: 23.61191666666667
    - type: ndcg_at_1
      value: 18.944333333333336
    - type: ndcg_at_10
      value: 24.833083333333335
    - type: ndcg_at_100
      value: 29.647666666666666
    - type: ndcg_at_1000
      value: 32.913333333333334
    - type: ndcg_at_3
      value: 21.536166666666663
    - type: ndcg_at_5
      value: 23.013250000000003
    - type: precision_at_1
      value: 18.944333333333336
    - type: precision_at_10
      value: 4.4035
    - type: precision_at_100
      value: 0.8164999999999999
    - type: precision_at_1000
      value: 0.1284166666666667
    - type: precision_at_3
      value: 9.893416666666667
    - type: precision_at_5
      value: 7.1185
    - type: recall_at_1
      value: 15.725666666666669
    - type: recall_at_10
      value: 32.66266666666667
    - type: recall_at_100
      value: 54.48908333333333
    - type: recall_at_1000
      value: 78.27425
    - type: recall_at_3
      value: 23.251916666666666
    - type: recall_at_5
      value: 27.12425
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 12.077
    - type: map_at_10
      value: 16.801
    - type: map_at_100
      value: 17.655
    - type: map_at_1000
      value: 17.751
    - type: map_at_3
      value: 15.509
    - type: map_at_5
      value: 16.162000000000003
    - type: mrr_at_1
      value: 13.804
    - type: mrr_at_10
      value: 18.745
    - type: mrr_at_100
      value: 19.599
    - type: mrr_at_1000
      value: 19.678
    - type: mrr_at_3
      value: 17.434
    - type: mrr_at_5
      value: 18.101
    - type: ndcg_at_1
      value: 13.804
    - type: ndcg_at_10
      value: 19.698999999999998
    - type: ndcg_at_100
      value: 24.254
    - type: ndcg_at_1000
      value: 27.083000000000002
    - type: ndcg_at_3
      value: 17.21
    - type: ndcg_at_5
      value: 18.240000000000002
    - type: precision_at_1
      value: 13.804
    - type: precision_at_10
      value: 3.313
    - type: precision_at_100
      value: 0.618
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.872999999999999
    - type: precision_at_5
      value: 5.399
    - type: recall_at_1
      value: 12.077
    - type: recall_at_10
      value: 26.668999999999997
    - type: recall_at_100
      value: 47.831
    - type: recall_at_1000
      value: 69.413
    - type: recall_at_3
      value: 19.49
    - type: recall_at_5
      value: 22.225
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.115
    - type: map_at_10
      value: 11.722000000000001
    - type: map_at_100
      value: 12.348
    - type: map_at_1000
      value: 12.481
    - type: map_at_3
      value: 10.426
    - type: map_at_5
      value: 11.182
    - type: mrr_at_1
      value: 10.255
    - type: mrr_at_10
      value: 14.277999999999999
    - type: mrr_at_100
      value: 14.899999999999999
    - type: mrr_at_1000
      value: 15.009
    - type: mrr_at_3
      value: 12.91
    - type: mrr_at_5
      value: 13.712
    - type: ndcg_at_1
      value: 10.255
    - type: ndcg_at_10
      value: 14.35
    - type: ndcg_at_100
      value: 17.784
    - type: ndcg_at_1000
      value: 21.539
    - type: ndcg_at_3
      value: 11.967
    - type: ndcg_at_5
      value: 13.126
    - type: precision_at_1
      value: 10.255
    - type: precision_at_10
      value: 2.719
    - type: precision_at_100
      value: 0.53
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 5.781
    - type: precision_at_5
      value: 4.329000000000001
    - type: recall_at_1
      value: 8.115
    - type: recall_at_10
      value: 19.848
    - type: recall_at_100
      value: 35.974000000000004
    - type: recall_at_1000
      value: 63.839
    - type: recall_at_3
      value: 13.073
    - type: recall_at_5
      value: 16.109
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 14.966
    - type: map_at_10
      value: 18.857
    - type: map_at_100
      value: 19.723
    - type: map_at_1000
      value: 19.845
    - type: map_at_3
      value: 17.207
    - type: map_at_5
      value: 17.97
    - type: mrr_at_1
      value: 17.444000000000003
    - type: mrr_at_10
      value: 21.769
    - type: mrr_at_100
      value: 22.58
    - type: mrr_at_1000
      value: 22.676
    - type: mrr_at_3
      value: 20.04
    - type: mrr_at_5
      value: 20.852
    - type: ndcg_at_1
      value: 17.444000000000003
    - type: ndcg_at_10
      value: 22.020999999999997
    - type: ndcg_at_100
      value: 26.573999999999998
    - type: ndcg_at_1000
      value: 30.047
    - type: ndcg_at_3
      value: 18.673000000000002
    - type: ndcg_at_5
      value: 19.927
    - type: precision_at_1
      value: 17.444000000000003
    - type: precision_at_10
      value: 3.6380000000000003
    - type: precision_at_100
      value: 0.659
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 8.116
    - type: precision_at_5
      value: 5.7090000000000005
    - type: recall_at_1
      value: 14.966
    - type: recall_at_10
      value: 29.195
    - type: recall_at_100
      value: 50.092999999999996
    - type: recall_at_1000
      value: 75.858
    - type: recall_at_3
      value: 19.695
    - type: recall_at_5
      value: 22.979
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 17.05
    - type: map_at_10
      value: 22.636
    - type: map_at_100
      value: 23.860999999999997
    - type: map_at_1000
      value: 24.078
    - type: map_at_3
      value: 20.922
    - type: map_at_5
      value: 21.886
    - type: mrr_at_1
      value: 20.751
    - type: mrr_at_10
      value: 26.348
    - type: mrr_at_100
      value: 27.354
    - type: mrr_at_1000
      value: 27.447
    - type: mrr_at_3
      value: 24.671000000000003
    - type: mrr_at_5
      value: 25.728
    - type: ndcg_at_1
      value: 20.751
    - type: ndcg_at_10
      value: 26.684
    - type: ndcg_at_100
      value: 31.863999999999997
    - type: ndcg_at_1000
      value: 35.515
    - type: ndcg_at_3
      value: 24.035
    - type: ndcg_at_5
      value: 25.308000000000003
    - type: precision_at_1
      value: 20.751
    - type: precision_at_10
      value: 5.099
    - type: precision_at_100
      value: 1.154
    - type: precision_at_1000
      value: 0.208
    - type: precision_at_3
      value: 11.397
    - type: precision_at_5
      value: 8.261000000000001
    - type: recall_at_1
      value: 17.05
    - type: recall_at_10
      value: 33.784
    - type: recall_at_100
      value: 58.012
    - type: recall_at_1000
      value: 82.789
    - type: recall_at_3
      value: 25.393
    - type: recall_at_5
      value: 29.035
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.411
    - type: map_at_10
      value: 15.517
    - type: map_at_100
      value: 16.229
    - type: map_at_1000
      value: 16.341
    - type: map_at_3
      value: 14.06
    - type: map_at_5
      value: 14.677000000000001
    - type: mrr_at_1
      value: 12.753999999999998
    - type: mrr_at_10
      value: 16.97
    - type: mrr_at_100
      value: 17.68
    - type: mrr_at_1000
      value: 17.781
    - type: mrr_at_3
      value: 15.311
    - type: mrr_at_5
      value: 16.041
    - type: ndcg_at_1
      value: 12.753999999999998
    - type: ndcg_at_10
      value: 18.394
    - type: ndcg_at_100
      value: 22.448999999999998
    - type: ndcg_at_1000
      value: 25.945
    - type: ndcg_at_3
      value: 15.232999999999999
    - type: ndcg_at_5
      value: 16.347
    - type: precision_at_1
      value: 12.753999999999998
    - type: precision_at_10
      value: 2.976
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 6.4079999999999995
    - type: precision_at_5
      value: 4.547
    - type: recall_at_1
      value: 11.411
    - type: recall_at_10
      value: 26.143
    - type: recall_at_100
      value: 45.711
    - type: recall_at_1000
      value: 72.961
    - type: recall_at_3
      value: 17.357
    - type: recall_at_5
      value: 20.068
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.674
    - type: map_at_10
      value: 14.216000000000001
    - type: map_at_100
      value: 15.751999999999999
    - type: map_at_1000
      value: 15.967999999999998
    - type: map_at_3
      value: 11.283
    - type: map_at_5
      value: 12.837000000000002
    - type: mrr_at_1
      value: 17.915
    - type: mrr_at_10
      value: 28.315
    - type: mrr_at_100
      value: 29.328
    - type: mrr_at_1000
      value: 29.387999999999998
    - type: mrr_at_3
      value: 24.636
    - type: mrr_at_5
      value: 26.773000000000003
    - type: ndcg_at_1
      value: 17.915
    - type: ndcg_at_10
      value: 21.224999999999998
    - type: ndcg_at_100
      value: 27.994000000000003
    - type: ndcg_at_1000
      value: 32.037
    - type: ndcg_at_3
      value: 15.984000000000002
    - type: ndcg_at_5
      value: 18.072
    - type: precision_at_1
      value: 17.915
    - type: precision_at_10
      value: 7.023
    - type: precision_at_100
      value: 1.438
    - type: precision_at_1000
      value: 0.217
    - type: precision_at_3
      value: 12.009
    - type: precision_at_5
      value: 10.084999999999999
    - type: recall_at_1
      value: 7.674
    - type: recall_at_10
      value: 27.153
    - type: recall_at_100
      value: 51.035
    - type: recall_at_1000
      value: 74.024
    - type: recall_at_3
      value: 14.862
    - type: recall_at_5
      value: 19.928
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.776
    - type: map_at_10
      value: 10.783
    - type: map_at_100
      value: 15.287999999999998
    - type: map_at_1000
      value: 16.328
    - type: map_at_3
      value: 7.401000000000001
    - type: map_at_5
      value: 8.993
    - type: mrr_at_1
      value: 45.75
    - type: mrr_at_10
      value: 54.373000000000005
    - type: mrr_at_100
      value: 55.068
    - type: mrr_at_1000
      value: 55.096000000000004
    - type: mrr_at_3
      value: 51.792
    - type: mrr_at_5
      value: 53.32900000000001
    - type: ndcg_at_1
      value: 33.5
    - type: ndcg_at_10
      value: 25.586
    - type: ndcg_at_100
      value: 29.076999999999998
    - type: ndcg_at_1000
      value: 36.24
    - type: ndcg_at_3
      value: 28.259
    - type: ndcg_at_5
      value: 27.315
    - type: precision_at_1
      value: 45.75
    - type: precision_at_10
      value: 22.425
    - type: precision_at_100
      value: 6.978
    - type: precision_at_1000
      value: 1.409
    - type: precision_at_3
      value: 33.583
    - type: precision_at_5
      value: 29.4
    - type: recall_at_1
      value: 4.776
    - type: recall_at_10
      value: 15.557000000000002
    - type: recall_at_100
      value: 36.02
    - type: recall_at_1000
      value: 60.653
    - type: recall_at_3
      value: 8.562
    - type: recall_at_5
      value: 11.487
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 47.910000000000004
    - type: f1
      value: 45.27010147379218
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 19.009
    - type: map_at_10
      value: 28.401
    - type: map_at_100
      value: 29.377
    - type: map_at_1000
      value: 29.444
    - type: map_at_3
      value: 25.533
    - type: map_at_5
      value: 27.193
    - type: mrr_at_1
      value: 20.297
    - type: mrr_at_10
      value: 30.075000000000003
    - type: mrr_at_100
      value: 31.019999999999996
    - type: mrr_at_1000
      value: 31.075000000000003
    - type: mrr_at_3
      value: 27.088
    - type: mrr_at_5
      value: 28.83
    - type: ndcg_at_1
      value: 20.297
    - type: ndcg_at_10
      value: 33.949
    - type: ndcg_at_100
      value: 38.79
    - type: ndcg_at_1000
      value: 40.619
    - type: ndcg_at_3
      value: 28.077
    - type: ndcg_at_5
      value: 31.055
    - type: precision_at_1
      value: 20.297
    - type: precision_at_10
      value: 5.42
    - type: precision_at_100
      value: 0.8049999999999999
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 12.161
    - type: precision_at_5
      value: 8.869
    - type: recall_at_1
      value: 19.009
    - type: recall_at_10
      value: 49.716
    - type: recall_at_100
      value: 72.032
    - type: recall_at_1000
      value: 86.136
    - type: recall_at_3
      value: 33.821
    - type: recall_at_5
      value: 40.983999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.593
    - type: map_at_10
      value: 12.928999999999998
    - type: map_at_100
      value: 14.167
    - type: map_at_1000
      value: 14.374
    - type: map_at_3
      value: 10.908
    - type: map_at_5
      value: 12.030000000000001
    - type: mrr_at_1
      value: 15.432000000000002
    - type: mrr_at_10
      value: 21.886
    - type: mrr_at_100
      value: 23.018
    - type: mrr_at_1000
      value: 23.115
    - type: mrr_at_3
      value: 19.599
    - type: mrr_at_5
      value: 21.003
    - type: ndcg_at_1
      value: 15.432000000000002
    - type: ndcg_at_10
      value: 17.781
    - type: ndcg_at_100
      value: 23.669
    - type: ndcg_at_1000
      value: 28.384999999999998
    - type: ndcg_at_3
      value: 14.912
    - type: ndcg_at_5
      value: 16.119
    - type: precision_at_1
      value: 15.432000000000002
    - type: precision_at_10
      value: 5.154
    - type: precision_at_100
      value: 1.103
    - type: precision_at_1000
      value: 0.193
    - type: precision_at_3
      value: 9.927999999999999
    - type: precision_at_5
      value: 7.654
    - type: recall_at_1
      value: 7.593
    - type: recall_at_10
      value: 22.942999999999998
    - type: recall_at_100
      value: 45.762
    - type: recall_at_1000
      value: 74.97
    - type: recall_at_3
      value: 14.108
    - type: recall_at_5
      value: 18.195
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 19.622
    - type: map_at_10
      value: 27.953
    - type: map_at_100
      value: 28.932999999999996
    - type: map_at_1000
      value: 29.042
    - type: map_at_3
      value: 25.657000000000004
    - type: map_at_5
      value: 26.951000000000004
    - type: mrr_at_1
      value: 39.244
    - type: mrr_at_10
      value: 46.881
    - type: mrr_at_100
      value: 47.568
    - type: mrr_at_1000
      value: 47.617
    - type: mrr_at_3
      value: 44.882
    - type: mrr_at_5
      value: 46.013999999999996
    - type: ndcg_at_1
      value: 39.244
    - type: ndcg_at_10
      value: 35.43
    - type: ndcg_at_100
      value: 39.783
    - type: ndcg_at_1000
      value: 42.32
    - type: ndcg_at_3
      value: 31.238
    - type: ndcg_at_5
      value: 33.29
    - type: precision_at_1
      value: 39.244
    - type: precision_at_10
      value: 7.811
    - type: precision_at_100
      value: 1.129
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_3
      value: 19.725
    - type: precision_at_5
      value: 13.458
    - type: recall_at_1
      value: 19.622
    - type: recall_at_10
      value: 39.055
    - type: recall_at_100
      value: 56.442
    - type: recall_at_1000
      value: 73.383
    - type: recall_at_3
      value: 29.587999999999997
    - type: recall_at_5
      value: 33.646
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 59.50080000000001
    - type: ap
      value: 55.788718834100095
    - type: f1
      value: 59.31886351889661
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.361
    - type: map_at_10
      value: 11.3
    - type: map_at_100
      value: 12.23
    - type: map_at_1000
      value: 12.344
    - type: map_at_3
      value: 9.475
    - type: map_at_5
      value: 10.402000000000001
    - type: mrr_at_1
      value: 6.5040000000000004
    - type: mrr_at_10
      value: 11.554
    - type: mrr_at_100
      value: 12.486
    - type: mrr_at_1000
      value: 12.595
    - type: mrr_at_3
      value: 9.692
    - type: mrr_at_5
      value: 10.639
    - type: ndcg_at_1
      value: 6.519
    - type: ndcg_at_10
      value: 14.435999999999998
    - type: ndcg_at_100
      value: 19.442
    - type: ndcg_at_1000
      value: 22.834
    - type: ndcg_at_3
      value: 10.578
    - type: ndcg_at_5
      value: 12.248000000000001
    - type: precision_at_1
      value: 6.519
    - type: precision_at_10
      value: 2.52
    - type: precision_at_100
      value: 0.511
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 4.642
    - type: precision_at_5
      value: 3.633
    - type: recall_at_1
      value: 6.361
    - type: recall_at_10
      value: 24.273
    - type: recall_at_100
      value: 48.545
    - type: recall_at_1000
      value: 75.789
    - type: recall_at_3
      value: 13.567000000000002
    - type: recall_at_5
      value: 17.562
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 90.02963976288191
    - type: f1
      value: 88.93893646570741
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.592795257637945
    - type: f1
      value: 42.681889382124076
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.47612642905178
    - type: f1
      value: 60.06479567610216
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.64156018829858
    - type: f1
      value: 67.51582950719383
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.59174951459128
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.506220008220637
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.293104746926446
    - type: mrr
      value: 31.267960016056946
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.619
    - type: map_at_10
      value: 10.05
    - type: map_at_100
      value: 13.109000000000002
    - type: map_at_1000
      value: 14.657
    - type: map_at_3
      value: 7.438000000000001
    - type: map_at_5
      value: 8.64
    - type: mrr_at_1
      value: 36.842000000000006
    - type: mrr_at_10
      value: 47.339999999999996
    - type: mrr_at_100
      value: 48.089999999999996
    - type: mrr_at_1000
      value: 48.141
    - type: mrr_at_3
      value: 44.891999999999996
    - type: mrr_at_5
      value: 46.238
    - type: ndcg_at_1
      value: 35.138999999999996
    - type: ndcg_at_10
      value: 29.275000000000002
    - type: ndcg_at_100
      value: 28.326
    - type: ndcg_at_1000
      value: 37.551
    - type: ndcg_at_3
      value: 32.97
    - type: ndcg_at_5
      value: 31.452999999999996
    - type: precision_at_1
      value: 36.842000000000006
    - type: precision_at_10
      value: 21.95
    - type: precision_at_100
      value: 7.870000000000001
    - type: precision_at_1000
      value: 2.131
    - type: precision_at_3
      value: 31.579
    - type: precision_at_5
      value: 27.245
    - type: recall_at_1
      value: 4.619
    - type: recall_at_10
      value: 14.347999999999999
    - type: recall_at_100
      value: 30.683
    - type: recall_at_1000
      value: 63.588
    - type: recall_at_3
      value: 8.552
    - type: recall_at_5
      value: 11.205
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.099
    - type: map_at_10
      value: 16.035
    - type: map_at_100
      value: 17.333000000000002
    - type: map_at_1000
      value: 17.442
    - type: map_at_3
      value: 13.264000000000001
    - type: map_at_5
      value: 14.751
    - type: mrr_at_1
      value: 10.342
    - type: mrr_at_10
      value: 17.718
    - type: mrr_at_100
      value: 18.883
    - type: mrr_at_1000
      value: 18.973000000000003
    - type: mrr_at_3
      value: 14.909
    - type: mrr_at_5
      value: 16.442999999999998
    - type: ndcg_at_1
      value: 10.342
    - type: ndcg_at_10
      value: 20.698
    - type: ndcg_at_100
      value: 27.167
    - type: ndcg_at_1000
      value: 30.070999999999998
    - type: ndcg_at_3
      value: 15.018999999999998
    - type: ndcg_at_5
      value: 17.659
    - type: precision_at_1
      value: 10.342
    - type: precision_at_10
      value: 3.9539999999999997
    - type: precision_at_100
      value: 0.761
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 7.106999999999999
    - type: precision_at_5
      value: 5.776
    - type: recall_at_1
      value: 9.099
    - type: recall_at_10
      value: 33.596
    - type: recall_at_100
      value: 63.562
    - type: recall_at_1000
      value: 85.72999999999999
    - type: recall_at_3
      value: 18.472
    - type: recall_at_5
      value: 24.585
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.827
    - type: map_at_10
      value: 76.964
    - type: map_at_100
      value: 77.704
    - type: map_at_1000
      value: 77.735
    - type: map_at_3
      value: 73.934
    - type: map_at_5
      value: 75.82600000000001
    - type: mrr_at_1
      value: 73.48
    - type: mrr_at_10
      value: 81.093
    - type: mrr_at_100
      value: 81.317
    - type: mrr_at_1000
      value: 81.32000000000001
    - type: mrr_at_3
      value: 79.657
    - type: mrr_at_5
      value: 80.63
    - type: ndcg_at_1
      value: 73.56
    - type: ndcg_at_10
      value: 81.65599999999999
    - type: ndcg_at_100
      value: 83.65
    - type: ndcg_at_1000
      value: 83.953
    - type: ndcg_at_3
      value: 78.051
    - type: ndcg_at_5
      value: 80.022
    - type: precision_at_1
      value: 73.56
    - type: precision_at_10
      value: 12.367
    - type: precision_at_100
      value: 1.465
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.907
    - type: precision_at_5
      value: 22.494
    - type: recall_at_1
      value: 63.827
    - type: recall_at_10
      value: 90.716
    - type: recall_at_100
      value: 98.15700000000001
    - type: recall_at_1000
      value: 99.75
    - type: recall_at_3
      value: 80.58800000000001
    - type: recall_at_5
      value: 85.94500000000001
    - type: map_at_1
      value: 3.013
    - type: map_at_10
      value: 7.526
    - type: map_at_100
      value: 9.064
    - type: map_at_1000
      value: 9.334000000000001
    - type: map_at_3
      value: 5.372
    - type: map_at_5
      value: 6.547
    - type: mrr_at_1
      value: 14.799999999999999
    - type: mrr_at_10
      value: 23.24
    - type: mrr_at_100
      value: 24.552
    - type: mrr_at_1000
      value: 24.623
    - type: mrr_at_3
      value: 19.967
    - type: mrr_at_5
      value: 21.917
    - type: ndcg_at_1
      value: 14.799999999999999
    - type: ndcg_at_10
      value: 13.34
    - type: ndcg_at_100
      value: 20.208000000000002
    - type: ndcg_at_1000
      value: 25.352999999999998
    - type: ndcg_at_3
      value: 12.161
    - type: ndcg_at_5
      value: 11.05
    - type: precision_at_1
      value: 14.799999999999999
    - type: precision_at_10
      value: 7.049999999999999
    - type: precision_at_100
      value: 1.703
    - type: precision_at_1000
      value: 0.294
    - type: precision_at_3
      value: 11.4
    - type: precision_at_5
      value: 9.959999999999999
    - type: recall_at_1
      value: 3.013
    - type: recall_at_10
      value: 14.298
    - type: recall_at_100
      value: 34.583000000000006
    - type: recall_at_1000
      value: 59.772999999999996
    - type: recall_at_3
      value: 6.948
    - type: recall_at_5
      value: 10.088
    - type: map_at_1
      value: 0.105
    - type: map_at_10
      value: 0.721
    - type: map_at_100
      value: 4.549
    - type: map_at_1000
      value: 12.995999999999999
    - type: map_at_3
      value: 0.28400000000000003
    - type: map_at_5
      value: 0.41700000000000004
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 60.319
    - type: mrr_at_100
      value: 60.885999999999996
    - type: mrr_at_1000
      value: 60.885999999999996
    - type: mrr_at_3
      value: 57.333
    - type: mrr_at_5
      value: 59.833000000000006
    - type: ndcg_at_1
      value: 44.0
    - type: ndcg_at_10
      value: 40.998000000000005
    - type: ndcg_at_100
      value: 33.910000000000004
    - type: ndcg_at_1000
      value: 33.009
    - type: ndcg_at_3
      value: 44.061
    - type: ndcg_at_5
      value: 42.599
    - type: precision_at_1
      value: 46.0
    - type: precision_at_10
      value: 44.0
    - type: precision_at_100
      value: 36.5
    - type: precision_at_1000
      value: 16.332
    - type: precision_at_3
      value: 47.333
    - type: precision_at_5
      value: 46.400000000000006
    - type: recall_at_1
      value: 0.105
    - type: recall_at_10
      value: 0.966
    - type: recall_at_100
      value: 7.939
    - type: recall_at_1000
      value: 32.742
    - type: recall_at_3
      value: 0.332
    - type: recall_at_5
      value: 0.524
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 37.97924574250143
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 48.71752191180725
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 74.07986021045129
    - type: cos_sim_spearman
      value: 64.67577113468512
    - type: euclidean_pearson
      value: 68.68990414597263
    - type: euclidean_spearman
      value: 64.6758531649771
    - type: manhattan_pearson
      value: 64.11188923174566
    - type: manhattan_spearman
      value: 61.592371585956954
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.27146005453507
    - type: cos_sim_spearman
      value: 65.93558276183687
    - type: euclidean_pearson
      value: 69.43586842102822
    - type: euclidean_spearman
      value: 65.93703144865253
    - type: manhattan_pearson
      value: 69.6516644189866
    - type: manhattan_spearman
      value: 67.20730340507434
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 74.13479779206598
    - type: cos_sim_spearman
      value: 75.25854160622782
    - type: euclidean_pearson
      value: 75.03898639719446
    - type: euclidean_spearman
      value: 75.25855381633339
    - type: manhattan_pearson
      value: 75.14786852843275
    - type: manhattan_spearman
      value: 75.52670123327891
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.3585600169152
    - type: cos_sim_spearman
      value: 73.17704515393254
    - type: euclidean_pearson
      value: 74.891448527922
    - type: euclidean_spearman
      value: 73.1770354645383
    - type: manhattan_pearson
      value: 72.00352080759266
    - type: manhattan_spearman
      value: 71.33088649793352
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.2547221125337
    - type: cos_sim_spearman
      value: 81.56092496306586
    - type: euclidean_pearson
      value: 81.231224879122
    - type: euclidean_spearman
      value: 81.5609157140913
    - type: manhattan_pearson
      value: 79.39410985986596
    - type: manhattan_spearman
      value: 80.14350013562763
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.57832167022859
    - type: cos_sim_spearman
      value: 76.32409937204893
    - type: euclidean_pearson
      value: 75.69939675596083
    - type: euclidean_spearman
      value: 76.32464971104763
    - type: manhattan_pearson
      value: 75.37942909301383
    - type: manhattan_spearman
      value: 75.89813657924768
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.96852885219164
    - type: cos_sim_spearman
      value: 85.48862854621792
    - type: euclidean_pearson
      value: 84.50084962774064
    - type: euclidean_spearman
      value: 85.48950185584661
    - type: manhattan_pearson
      value: 79.54278385586173
    - type: manhattan_spearman
      value: 80.17022136076748
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 64.76167399937835
    - type: cos_sim_spearman
      value: 62.00631665062863
    - type: euclidean_pearson
      value: 63.93004336582023
    - type: euclidean_spearman
      value: 62.00631665062863
    - type: manhattan_pearson
      value: 63.57713263161092
    - type: manhattan_spearman
      value: 61.927941480246915
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 79.23095984093324
    - type: cos_sim_spearman
      value: 77.53643283015238
    - type: euclidean_pearson
      value: 78.32103757433086
    - type: euclidean_spearman
      value: 77.53645129624546
    - type: manhattan_pearson
      value: 74.68643604195545
    - type: manhattan_spearman
      value: 74.12436119957579
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 73.00659666541951
    - type: mrr
      value: 91.75728411022529
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 40.278000000000006
    - type: map_at_10
      value: 48.849
    - type: map_at_100
      value: 49.895
    - type: map_at_1000
      value: 49.946
    - type: map_at_3
      value: 46.431
    - type: map_at_5
      value: 47.544
    - type: mrr_at_1
      value: 42.667
    - type: mrr_at_10
      value: 50.517999999999994
    - type: mrr_at_100
      value: 51.354
    - type: mrr_at_1000
      value: 51.403
    - type: mrr_at_3
      value: 48.443999999999996
    - type: mrr_at_5
      value: 49.311
    - type: ndcg_at_1
      value: 42.667
    - type: ndcg_at_10
      value: 53.688
    - type: ndcg_at_100
      value: 58.342000000000006
    - type: ndcg_at_1000
      value: 59.719
    - type: ndcg_at_3
      value: 48.85
    - type: ndcg_at_5
      value: 50.699000000000005
    - type: precision_at_1
      value: 42.667
    - type: precision_at_10
      value: 7.467
    - type: precision_at_100
      value: 1.0070000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 19.333
    - type: precision_at_5
      value: 12.733
    - type: recall_at_1
      value: 40.278000000000006
    - type: recall_at_10
      value: 67.27199999999999
    - type: recall_at_100
      value: 88.1
    - type: recall_at_1000
      value: 99.0
    - type: recall_at_3
      value: 53.917
    - type: recall_at_5
      value: 58.443999999999996
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.74455445544554
    - type: cos_sim_ap
      value: 92.6197642156122
    - type: cos_sim_f1
      value: 86.78481012658227
    - type: cos_sim_precision
      value: 87.8974358974359
    - type: cos_sim_recall
      value: 85.7
    - type: dot_accuracy
      value: 99.74455445544554
    - type: dot_ap
      value: 92.6197642156122
    - type: dot_f1
      value: 86.78481012658227
    - type: dot_precision
      value: 87.8974358974359
    - type: dot_recall
      value: 85.7
    - type: euclidean_accuracy
      value: 99.74455445544554
    - type: euclidean_ap
      value: 92.6197642156122
    - type: euclidean_f1
      value: 86.78481012658227
    - type: euclidean_precision
      value: 87.8974358974359
    - type: euclidean_recall
      value: 85.7
    - type: manhattan_accuracy
      value: 99.76237623762376
    - type: manhattan_ap
      value: 93.22739174872532
    - type: manhattan_f1
      value: 87.87878787878789
    - type: manhattan_precision
      value: 88.77551020408163
    - type: manhattan_recall
      value: 87.0
    - type: max_accuracy
      value: 99.76237623762376
    - type: max_ap
      value: 93.22739174872532
    - type: max_f1
      value: 87.87878787878789
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 34.40384098107476
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.79004125896283
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.544704411607
    - type: mrr
      value: 43.00333959341312
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 27.97500813769544
    - type: cos_sim_spearman
      value: 27.944732299630086
    - type: dot_pearson
      value: 27.97500812408448
    - type: dot_spearman
      value: 27.91532727171099
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.327
    - type: map_at_10
      value: 7.445
    - type: map_at_100
      value: 14.402999999999999
    - type: map_at_1000
      value: 16.102
    - type: map_at_3
      value: 3.689
    - type: map_at_5
      value: 5.305
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 38.279
    - type: mrr_at_100
      value: 39.434999999999995
    - type: mrr_at_1000
      value: 39.451
    - type: mrr_at_3
      value: 33.672999999999995
    - type: mrr_at_5
      value: 36.939
    - type: ndcg_at_1
      value: 20.408
    - type: ndcg_at_10
      value: 21.571
    - type: ndcg_at_100
      value: 35.510000000000005
    - type: ndcg_at_1000
      value: 47.25
    - type: ndcg_at_3
      value: 22.866
    - type: ndcg_at_5
      value: 23.951
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 21.224
    - type: precision_at_100
      value: 8.449
    - type: precision_at_1000
      value: 1.59
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 26.531
    - type: recall_at_1
      value: 1.327
    - type: recall_at_10
      value: 13.715
    - type: recall_at_100
      value: 49.903
    - type: recall_at_1000
      value: 86.25
    - type: recall_at_3
      value: 5.0040000000000004
    - type: recall_at_5
      value: 7.959
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 75.24119999999999
    - type: ap
      value: 16.333693949079212
    - type: f1
      value: 57.95963832110142
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 50.80362195812111
    - type: f1
      value: 51.07007731951286
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 38.237341017271426
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.87536508314956
    - type: cos_sim_ap
      value: 62.453427699972195
    - type: cos_sim_f1
      value: 60.47918683446273
    - type: cos_sim_precision
      value: 55.85605721949038
    - type: cos_sim_recall
      value: 65.93667546174143
    - type: dot_accuracy
      value: 82.87536508314956
    - type: dot_ap
      value: 62.453427699972195
    - type: dot_f1
      value: 60.47918683446273
    - type: dot_precision
      value: 55.85605721949038
    - type: dot_recall
      value: 65.93667546174143
    - type: euclidean_accuracy
      value: 82.87536508314956
    - type: euclidean_ap
      value: 62.453427699972195
    - type: euclidean_f1
      value: 60.47918683446273
    - type: euclidean_precision
      value: 55.85605721949038
    - type: euclidean_recall
      value: 65.93667546174143
    - type: manhattan_accuracy
      value: 80.44942480777254
    - type: manhattan_ap
      value: 54.51058097426563
    - type: manhattan_f1
      value: 53.99701556171392
    - type: manhattan_precision
      value: 45.29685264663805
    - type: manhattan_recall
      value: 66.83377308707124
    - type: max_accuracy
      value: 82.87536508314956
    - type: max_ap
      value: 62.453427699972195
    - type: max_f1
      value: 60.47918683446273
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.47622928552023
    - type: cos_sim_ap
      value: 82.95452704175317
    - type: cos_sim_f1
      value: 75.16585581601062
    - type: cos_sim_precision
      value: 72.0941742081448
    - type: cos_sim_recall
      value: 78.51093316907914
    - type: dot_accuracy
      value: 87.47622928552023
    - type: dot_ap
      value: 82.95452715549013
    - type: dot_f1
      value: 75.16585581601062
    - type: dot_precision
      value: 72.0941742081448
    - type: dot_recall
      value: 78.51093316907914
    - type: euclidean_accuracy
      value: 87.47622928552023
    - type: euclidean_ap
      value: 82.95452684622329
    - type: euclidean_f1
      value: 75.16585581601062
    - type: euclidean_precision
      value: 72.0941742081448
    - type: euclidean_recall
      value: 78.51093316907914
    - type: manhattan_accuracy
      value: 87.0396243256879
    - type: manhattan_ap
      value: 81.90067228921978
    - type: manhattan_f1
      value: 74.29892820437529
    - type: manhattan_precision
      value: 70.99466891133558
    - type: manhattan_recall
      value: 77.9257776408993
    - type: max_accuracy
      value: 87.47622928552023
    - type: max_ap
      value: 82.95452715549013
    - type: max_f1
      value: 75.16585581601062
---
