mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mpnet_main_noabtt
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 68.01492537313432
    - type: ap
      value: 29.926088215432827
    - type: f1
      value: 61.543829186658314
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 66.03607500000001
    - type: ap
      value: 60.89551858560106
    - type: f1
      value: 65.80068648160709
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.78199999999999
    - type: f1
      value: 34.250938954862356
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.266
    - type: map_at_10
      value: 35.196
    - type: map_at_100
      value: 36.387
    - type: map_at_1000
      value: 36.416
    - type: map_at_3
      value: 30.773
    - type: map_at_5
      value: 33.163
    - type: mrr_at_1
      value: 22.048000000000002
    - type: mrr_at_10
      value: 35.481
    - type: mrr_at_100
      value: 36.665
    - type: mrr_at_1000
      value: 36.693999999999996
    - type: mrr_at_3
      value: 31.069000000000003
    - type: mrr_at_5
      value: 33.455
    - type: ndcg_at_1
      value: 21.266
    - type: ndcg_at_10
      value: 43.114000000000004
    - type: ndcg_at_100
      value: 48.61
    - type: ndcg_at_1000
      value: 49.334
    - type: ndcg_at_3
      value: 33.951
    - type: ndcg_at_5
      value: 38.257999999999996
    - type: precision_at_1
      value: 21.266
    - type: precision_at_10
      value: 6.848999999999999
    - type: precision_at_100
      value: 0.935
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.391000000000002
    - type: precision_at_5
      value: 10.725
    - type: recall_at_1
      value: 21.266
    - type: recall_at_10
      value: 68.49199999999999
    - type: recall_at_100
      value: 93.528
    - type: recall_at_1000
      value: 99.14699999999999
    - type: recall_at_3
      value: 43.172
    - type: recall_at_5
      value: 53.627
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 36.01511495124908
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 26.77906639415867
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.32809895348082
    - type: mrr
      value: 68.93109967902211
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.61413947741643
    - type: cos_sim_spearman
      value: 75.72702669649405
    - type: euclidean_pearson
      value: 77.72961558201939
    - type: euclidean_spearman
      value: 75.72702669649405
    - type: manhattan_pearson
      value: 78.63299657922013
    - type: manhattan_spearman
      value: 77.19874697762698
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.92857142857143
    - type: f1
      value: 72.1661081571387
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.19795849293594
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.13940168273952
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.384999999999998
    - type: map_at_10
      value: 29.628
    - type: map_at_100
      value: 30.781
    - type: map_at_1000
      value: 30.933
    - type: map_at_3
      value: 26.889000000000003
    - type: map_at_5
      value: 28.388999999999996
    - type: mrr_at_1
      value: 28.183000000000003
    - type: mrr_at_10
      value: 34.952
    - type: mrr_at_100
      value: 35.774
    - type: mrr_at_1000
      value: 35.843
    - type: mrr_at_3
      value: 32.499
    - type: mrr_at_5
      value: 33.829
    - type: ndcg_at_1
      value: 28.183000000000003
    - type: ndcg_at_10
      value: 34.614
    - type: ndcg_at_100
      value: 39.737
    - type: ndcg_at_1000
      value: 42.742999999999995
    - type: ndcg_at_3
      value: 30.328
    - type: ndcg_at_5
      value: 32.23
    - type: precision_at_1
      value: 28.183000000000003
    - type: precision_at_10
      value: 6.723999999999999
    - type: precision_at_100
      value: 1.172
    - type: precision_at_1000
      value: 0.181
    - type: precision_at_3
      value: 14.402000000000001
    - type: precision_at_5
      value: 10.587
    - type: recall_at_1
      value: 22.384999999999998
    - type: recall_at_10
      value: 43.537
    - type: recall_at_100
      value: 66.37100000000001
    - type: recall_at_1000
      value: 86.978
    - type: recall_at_3
      value: 30.874000000000002
    - type: recall_at_5
      value: 36.358000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.145
    - type: map_at_10
      value: 20.992
    - type: map_at_100
      value: 21.951999999999998
    - type: map_at_1000
      value: 22.076999999999998
    - type: map_at_3
      value: 19.211
    - type: map_at_5
      value: 20.233999999999998
    - type: mrr_at_1
      value: 19.363
    - type: mrr_at_10
      value: 24.97
    - type: mrr_at_100
      value: 25.818
    - type: mrr_at_1000
      value: 25.895000000000003
    - type: mrr_at_3
      value: 23.238
    - type: mrr_at_5
      value: 24.288999999999998
    - type: ndcg_at_1
      value: 19.363
    - type: ndcg_at_10
      value: 24.665
    - type: ndcg_at_100
      value: 29.122999999999998
    - type: ndcg_at_1000
      value: 32.06
    - type: ndcg_at_3
      value: 21.729000000000003
    - type: ndcg_at_5
      value: 23.148
    - type: precision_at_1
      value: 19.363
    - type: precision_at_10
      value: 4.643
    - type: precision_at_100
      value: 0.864
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 10.51
    - type: precision_at_5
      value: 7.617999999999999
    - type: recall_at_1
      value: 15.145
    - type: recall_at_10
      value: 31.653
    - type: recall_at_100
      value: 51.344
    - type: recall_at_1000
      value: 71.352
    - type: recall_at_3
      value: 22.892000000000003
    - type: recall_at_5
      value: 26.878999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.68
    - type: map_at_10
      value: 33.0
    - type: map_at_100
      value: 34.095
    - type: map_at_1000
      value: 34.193
    - type: map_at_3
      value: 30.444
    - type: map_at_5
      value: 31.691999999999997
    - type: mrr_at_1
      value: 28.527
    - type: mrr_at_10
      value: 36.162
    - type: mrr_at_100
      value: 37.064
    - type: mrr_at_1000
      value: 37.124
    - type: mrr_at_3
      value: 33.866
    - type: mrr_at_5
      value: 35.026
    - type: ndcg_at_1
      value: 28.527
    - type: ndcg_at_10
      value: 37.893
    - type: ndcg_at_100
      value: 43.082
    - type: ndcg_at_1000
      value: 45.366
    - type: ndcg_at_3
      value: 33.062000000000005
    - type: ndcg_at_5
      value: 35.007
    - type: precision_at_1
      value: 28.527
    - type: precision_at_10
      value: 6.276
    - type: precision_at_100
      value: 0.966
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 14.879999999999999
    - type: precision_at_5
      value: 10.206999999999999
    - type: recall_at_1
      value: 24.68
    - type: recall_at_10
      value: 49.8
    - type: recall_at_100
      value: 73.27900000000001
    - type: recall_at_1000
      value: 89.761
    - type: recall_at_3
      value: 36.428
    - type: recall_at_5
      value: 41.284
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.674
    - type: map_at_10
      value: 17.466
    - type: map_at_100
      value: 18.309
    - type: map_at_1000
      value: 18.415
    - type: map_at_3
      value: 16.072
    - type: map_at_5
      value: 16.835
    - type: mrr_at_1
      value: 13.672
    - type: mrr_at_10
      value: 18.602
    - type: mrr_at_100
      value: 19.434
    - type: mrr_at_1000
      value: 19.526
    - type: mrr_at_3
      value: 17.213
    - type: mrr_at_5
      value: 17.942
    - type: ndcg_at_1
      value: 13.672
    - type: ndcg_at_10
      value: 20.339
    - type: ndcg_at_100
      value: 24.979000000000003
    - type: ndcg_at_1000
      value: 28.186
    - type: ndcg_at_3
      value: 17.5
    - type: ndcg_at_5
      value: 18.791
    - type: precision_at_1
      value: 13.672
    - type: precision_at_10
      value: 3.209
    - type: precision_at_100
      value: 0.5890000000000001
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 7.571
    - type: precision_at_5
      value: 5.311
    - type: recall_at_1
      value: 12.674
    - type: recall_at_10
      value: 28.096
    - type: recall_at_100
      value: 50.444
    - type: recall_at_1000
      value: 75.581
    - type: recall_at_3
      value: 20.330000000000002
    - type: recall_at_5
      value: 23.384
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.537
    - type: map_at_10
      value: 9.889000000000001
    - type: map_at_100
      value: 10.775
    - type: map_at_1000
      value: 10.902000000000001
    - type: map_at_3
      value: 8.639
    - type: map_at_5
      value: 9.264
    - type: mrr_at_1
      value: 8.706
    - type: mrr_at_10
      value: 12.606
    - type: mrr_at_100
      value: 13.455
    - type: mrr_at_1000
      value: 13.557
    - type: mrr_at_3
      value: 11.111
    - type: mrr_at_5
      value: 11.801
    - type: ndcg_at_1
      value: 8.706
    - type: ndcg_at_10
      value: 12.617999999999999
    - type: ndcg_at_100
      value: 17.34
    - type: ndcg_at_1000
      value: 20.905
    - type: ndcg_at_3
      value: 10.027999999999999
    - type: ndcg_at_5
      value: 11.063
    - type: precision_at_1
      value: 8.706
    - type: precision_at_10
      value: 2.45
    - type: precision_at_100
      value: 0.573
    - type: precision_at_1000
      value: 0.10200000000000001
    - type: precision_at_3
      value: 4.934
    - type: precision_at_5
      value: 3.6319999999999997
    - type: recall_at_1
      value: 6.537
    - type: recall_at_10
      value: 18.593
    - type: recall_at_100
      value: 39.922999999999995
    - type: recall_at_1000
      value: 66.08000000000001
    - type: recall_at_3
      value: 11.27
    - type: recall_at_5
      value: 13.996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.319
    - type: map_at_10
      value: 24.237000000000002
    - type: map_at_100
      value: 25.406000000000002
    - type: map_at_1000
      value: 25.554
    - type: map_at_3
      value: 22.032
    - type: map_at_5
      value: 23.258000000000003
    - type: mrr_at_1
      value: 22.522000000000002
    - type: mrr_at_10
      value: 28.764
    - type: mrr_at_100
      value: 29.692
    - type: mrr_at_1000
      value: 29.781999999999996
    - type: mrr_at_3
      value: 26.468000000000004
    - type: mrr_at_5
      value: 27.801
    - type: ndcg_at_1
      value: 22.522000000000002
    - type: ndcg_at_10
      value: 28.549999999999997
    - type: ndcg_at_100
      value: 34.126
    - type: ndcg_at_1000
      value: 37.471
    - type: ndcg_at_3
      value: 24.643
    - type: ndcg_at_5
      value: 26.537
    - type: precision_at_1
      value: 22.522000000000002
    - type: precision_at_10
      value: 5.2940000000000005
    - type: precision_at_100
      value: 0.97
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 11.485
    - type: precision_at_5
      value: 8.508000000000001
    - type: recall_at_1
      value: 18.319
    - type: recall_at_10
      value: 37.061
    - type: recall_at_100
      value: 61.68
    - type: recall_at_1000
      value: 84.885
    - type: recall_at_3
      value: 26.117
    - type: recall_at_5
      value: 30.939
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.307
    - type: map_at_10
      value: 17.764
    - type: map_at_100
      value: 18.843
    - type: map_at_1000
      value: 18.983
    - type: map_at_3
      value: 15.774
    - type: map_at_5
      value: 16.872999999999998
    - type: mrr_at_1
      value: 15.753
    - type: mrr_at_10
      value: 21.42
    - type: mrr_at_100
      value: 22.351
    - type: mrr_at_1000
      value: 22.448999999999998
    - type: mrr_at_3
      value: 19.368
    - type: mrr_at_5
      value: 20.527
    - type: ndcg_at_1
      value: 15.753
    - type: ndcg_at_10
      value: 21.573
    - type: ndcg_at_100
      value: 26.994
    - type: ndcg_at_1000
      value: 30.407
    - type: ndcg_at_3
      value: 17.968
    - type: ndcg_at_5
      value: 19.669
    - type: precision_at_1
      value: 15.753
    - type: precision_at_10
      value: 4.144
    - type: precision_at_100
      value: 0.826
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 8.638
    - type: precision_at_5
      value: 6.575
    - type: recall_at_1
      value: 12.307
    - type: recall_at_10
      value: 29.615000000000002
    - type: recall_at_100
      value: 53.729000000000006
    - type: recall_at_1000
      value: 77.751
    - type: recall_at_3
      value: 19.584
    - type: recall_at_5
      value: 23.923
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.978749999999998
    - type: map_at_10
      value: 19.17908333333333
    - type: map_at_100
      value: 20.128416666666666
    - type: map_at_1000
      value: 20.25808333333333
    - type: map_at_3
      value: 17.398
    - type: map_at_5
      value: 18.342999999999996
    - type: mrr_at_1
      value: 17.03141666666667
    - type: mrr_at_10
      value: 22.300083333333333
    - type: mrr_at_100
      value: 23.13458333333334
    - type: mrr_at_1000
      value: 23.222583333333333
    - type: mrr_at_3
      value: 20.495749999999997
    - type: mrr_at_5
      value: 21.48033333333333
    - type: ndcg_at_1
      value: 17.03141666666667
    - type: ndcg_at_10
      value: 22.739833333333337
    - type: ndcg_at_100
      value: 27.511749999999996
    - type: ndcg_at_1000
      value: 30.706333333333337
    - type: ndcg_at_3
      value: 19.47566666666667
    - type: ndcg_at_5
      value: 20.91025
    - type: precision_at_1
      value: 17.03141666666667
    - type: precision_at_10
      value: 4.118166666666667
    - type: precision_at_100
      value: 0.7796666666666667
    - type: precision_at_1000
      value: 0.12458333333333332
    - type: precision_at_3
      value: 9.0545
    - type: precision_at_5
      value: 6.56175
    - type: recall_at_1
      value: 13.978749999999998
    - type: recall_at_10
      value: 30.441333333333333
    - type: recall_at_100
      value: 52.37841666666667
    - type: recall_at_1000
      value: 75.46725
    - type: recall_at_3
      value: 21.12483333333333
    - type: recall_at_5
      value: 24.88366666666667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.685
    - type: map_at_10
      value: 14.92
    - type: map_at_100
      value: 15.620000000000001
    - type: map_at_1000
      value: 15.702
    - type: map_at_3
      value: 13.327
    - type: map_at_5
      value: 14.148
    - type: mrr_at_1
      value: 12.73
    - type: mrr_at_10
      value: 16.999
    - type: mrr_at_100
      value: 17.727999999999998
    - type: mrr_at_1000
      value: 17.799
    - type: mrr_at_3
      value: 15.440000000000001
    - type: mrr_at_5
      value: 16.299
    - type: ndcg_at_1
      value: 12.73
    - type: ndcg_at_10
      value: 17.892
    - type: ndcg_at_100
      value: 21.819
    - type: ndcg_at_1000
      value: 24.238
    - type: ndcg_at_3
      value: 14.865999999999998
    - type: ndcg_at_5
      value: 16.157
    - type: precision_at_1
      value: 12.73
    - type: precision_at_10
      value: 3.16
    - type: precision_at_100
      value: 0.563
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 6.902
    - type: precision_at_5
      value: 5.031
    - type: recall_at_1
      value: 10.685
    - type: recall_at_10
      value: 25.291999999999998
    - type: recall_at_100
      value: 43.815
    - type: recall_at_1000
      value: 62.278
    - type: recall_at_3
      value: 16.481
    - type: recall_at_5
      value: 19.869
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.295
    - type: map_at_10
      value: 10.568
    - type: map_at_100
      value: 11.224
    - type: map_at_1000
      value: 11.354000000000001
    - type: map_at_3
      value: 9.41
    - type: map_at_5
      value: 10.055
    - type: mrr_at_1
      value: 9.36
    - type: mrr_at_10
      value: 12.956000000000001
    - type: mrr_at_100
      value: 13.628000000000002
    - type: mrr_at_1000
      value: 13.735
    - type: mrr_at_3
      value: 11.608
    - type: mrr_at_5
      value: 12.367
    - type: ndcg_at_1
      value: 9.36
    - type: ndcg_at_10
      value: 12.992
    - type: ndcg_at_100
      value: 16.681
    - type: ndcg_at_1000
      value: 20.355
    - type: ndcg_at_3
      value: 10.756
    - type: ndcg_at_5
      value: 11.805
    - type: precision_at_1
      value: 9.36
    - type: precision_at_10
      value: 2.46
    - type: precision_at_100
      value: 0.523
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 5.1499999999999995
    - type: precision_at_5
      value: 3.882
    - type: recall_at_1
      value: 7.295
    - type: recall_at_10
      value: 18.109
    - type: recall_at_100
      value: 35.382000000000005
    - type: recall_at_1000
      value: 62.734
    - type: recall_at_3
      value: 11.906
    - type: recall_at_5
      value: 14.524999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.784999999999998
    - type: map_at_10
      value: 16.897000000000002
    - type: map_at_100
      value: 17.804000000000002
    - type: map_at_1000
      value: 17.925
    - type: map_at_3
      value: 15.494
    - type: map_at_5
      value: 16.223000000000003
    - type: mrr_at_1
      value: 15.485
    - type: mrr_at_10
      value: 20.007
    - type: mrr_at_100
      value: 20.882
    - type: mrr_at_1000
      value: 20.979
    - type: mrr_at_3
      value: 18.392
    - type: mrr_at_5
      value: 19.320999999999998
    - type: ndcg_at_1
      value: 15.485
    - type: ndcg_at_10
      value: 19.993
    - type: ndcg_at_100
      value: 24.945999999999998
    - type: ndcg_at_1000
      value: 28.233000000000004
    - type: ndcg_at_3
      value: 17.19
    - type: ndcg_at_5
      value: 18.404999999999998
    - type: precision_at_1
      value: 15.485
    - type: precision_at_10
      value: 3.3680000000000003
    - type: precision_at_100
      value: 0.654
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 7.805
    - type: precision_at_5
      value: 5.56
    - type: recall_at_1
      value: 12.784999999999998
    - type: recall_at_10
      value: 26.740000000000002
    - type: recall_at_100
      value: 49.907000000000004
    - type: recall_at_1000
      value: 73.85000000000001
    - type: recall_at_3
      value: 18.741
    - type: recall_at_5
      value: 21.894
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.253
    - type: map_at_10
      value: 20.666999999999998
    - type: map_at_100
      value: 21.809
    - type: map_at_1000
      value: 22.012
    - type: map_at_3
      value: 18.754
    - type: map_at_5
      value: 19.743
    - type: mrr_at_1
      value: 19.17
    - type: mrr_at_10
      value: 24.614
    - type: mrr_at_100
      value: 25.487
    - type: mrr_at_1000
      value: 25.575
    - type: mrr_at_3
      value: 22.759999999999998
    - type: mrr_at_5
      value: 23.818
    - type: ndcg_at_1
      value: 19.17
    - type: ndcg_at_10
      value: 24.685000000000002
    - type: ndcg_at_100
      value: 29.84
    - type: ndcg_at_1000
      value: 33.548
    - type: ndcg_at_3
      value: 21.569
    - type: ndcg_at_5
      value: 22.842000000000002
    - type: precision_at_1
      value: 19.17
    - type: precision_at_10
      value: 4.862
    - type: precision_at_100
      value: 1.105
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 10.277
    - type: precision_at_5
      value: 7.431
    - type: recall_at_1
      value: 15.253
    - type: recall_at_10
      value: 31.858999999999998
    - type: recall_at_100
      value: 56.477999999999994
    - type: recall_at_1000
      value: 81.56099999999999
    - type: recall_at_3
      value: 22.11
    - type: recall_at_5
      value: 26.003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.68
    - type: map_at_10
      value: 14.121
    - type: map_at_100
      value: 14.923
    - type: map_at_1000
      value: 15.046999999999999
    - type: map_at_3
      value: 12.73
    - type: map_at_5
      value: 13.402
    - type: mrr_at_1
      value: 10.906
    - type: mrr_at_10
      value: 15.549
    - type: mrr_at_100
      value: 16.302
    - type: mrr_at_1000
      value: 16.407
    - type: mrr_at_3
      value: 13.986
    - type: mrr_at_5
      value: 14.743999999999998
    - type: ndcg_at_1
      value: 10.906
    - type: ndcg_at_10
      value: 17.064
    - type: ndcg_at_100
      value: 21.474
    - type: ndcg_at_1000
      value: 24.964
    - type: ndcg_at_3
      value: 14.069
    - type: ndcg_at_5
      value: 15.268999999999998
    - type: precision_at_1
      value: 10.906
    - type: precision_at_10
      value: 2.828
    - type: precision_at_100
      value: 0.551
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.1
    - type: precision_at_5
      value: 4.399
    - type: recall_at_1
      value: 9.68
    - type: recall_at_10
      value: 24.941
    - type: recall_at_100
      value: 46.189
    - type: recall_at_1000
      value: 72.796
    - type: recall_at_3
      value: 16.765
    - type: recall_at_5
      value: 19.55
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.151
    - type: map_at_10
      value: 11.699
    - type: map_at_100
      value: 13.213
    - type: map_at_1000
      value: 13.441
    - type: map_at_3
      value: 9.356
    - type: map_at_5
      value: 10.456999999999999
    - type: mrr_at_1
      value: 13.29
    - type: mrr_at_10
      value: 23.102
    - type: mrr_at_100
      value: 24.262
    - type: mrr_at_1000
      value: 24.332
    - type: mrr_at_3
      value: 19.75
    - type: mrr_at_5
      value: 21.490000000000002
    - type: ndcg_at_1
      value: 13.29
    - type: ndcg_at_10
      value: 17.761
    - type: ndcg_at_100
      value: 24.587
    - type: ndcg_at_1000
      value: 29.004
    - type: ndcg_at_3
      value: 13.247
    - type: ndcg_at_5
      value: 14.776
    - type: precision_at_1
      value: 13.29
    - type: precision_at_10
      value: 6.104
    - type: precision_at_100
      value: 1.343
    - type: precision_at_1000
      value: 0.213
    - type: precision_at_3
      value: 10.315000000000001
    - type: precision_at_5
      value: 8.352
    - type: recall_at_1
      value: 6.151
    - type: recall_at_10
      value: 23.374
    - type: recall_at_100
      value: 47.381
    - type: recall_at_1000
      value: 72.707
    - type: recall_at_3
      value: 12.709000000000001
    - type: recall_at_5
      value: 16.575
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.2969999999999997
    - type: map_at_10
      value: 8.185
    - type: map_at_100
      value: 11.555
    - type: map_at_1000
      value: 12.506
    - type: map_at_3
      value: 5.63
    - type: map_at_5
      value: 6.851
    - type: mrr_at_1
      value: 37.5
    - type: mrr_at_10
      value: 47.846
    - type: mrr_at_100
      value: 48.595
    - type: mrr_at_1000
      value: 48.619
    - type: mrr_at_3
      value: 44.792
    - type: mrr_at_5
      value: 46.367000000000004
    - type: ndcg_at_1
      value: 27.375
    - type: ndcg_at_10
      value: 21.753
    - type: ndcg_at_100
      value: 24.714
    - type: ndcg_at_1000
      value: 31.426
    - type: ndcg_at_3
      value: 23.781
    - type: ndcg_at_5
      value: 22.808
    - type: precision_at_1
      value: 37.5
    - type: precision_at_10
      value: 19.775000000000002
    - type: precision_at_100
      value: 6.45
    - type: precision_at_1000
      value: 1.434
    - type: precision_at_3
      value: 28.333000000000002
    - type: precision_at_5
      value: 24.95
    - type: recall_at_1
      value: 3.2969999999999997
    - type: recall_at_10
      value: 12.861
    - type: recall_at_100
      value: 31.055
    - type: recall_at_1000
      value: 53.855
    - type: recall_at_3
      value: 6.848999999999999
    - type: recall_at_5
      value: 9.328
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 45.91
    - type: f1
      value: 41.614000185716236
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.413
    - type: map_at_10
      value: 21.197
    - type: map_at_100
      value: 22.116
    - type: map_at_1000
      value: 22.186
    - type: map_at_3
      value: 18.867
    - type: map_at_5
      value: 20.154
    - type: mrr_at_1
      value: 15.302
    - type: mrr_at_10
      value: 22.462
    - type: mrr_at_100
      value: 23.391000000000002
    - type: mrr_at_1000
      value: 23.452
    - type: mrr_at_3
      value: 20.012
    - type: mrr_at_5
      value: 21.38
    - type: ndcg_at_1
      value: 15.302
    - type: ndcg_at_10
      value: 25.458
    - type: ndcg_at_100
      value: 30.144
    - type: ndcg_at_1000
      value: 32.124
    - type: ndcg_at_3
      value: 20.638
    - type: ndcg_at_5
      value: 22.964000000000002
    - type: precision_at_1
      value: 15.302
    - type: precision_at_10
      value: 4.086
    - type: precision_at_100
      value: 0.662
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 8.806
    - type: precision_at_5
      value: 6.514
    - type: recall_at_1
      value: 14.413
    - type: recall_at_10
      value: 37.682
    - type: recall_at_100
      value: 59.521
    - type: recall_at_1000
      value: 74.95100000000001
    - type: recall_at_3
      value: 24.618000000000002
    - type: recall_at_5
      value: 30.186
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.948
    - type: map_at_10
      value: 11.461
    - type: map_at_100
      value: 12.565000000000001
    - type: map_at_1000
      value: 12.76
    - type: map_at_3
      value: 9.679
    - type: map_at_5
      value: 10.59
    - type: mrr_at_1
      value: 13.58
    - type: mrr_at_10
      value: 19.377
    - type: mrr_at_100
      value: 20.435
    - type: mrr_at_1000
      value: 20.526
    - type: mrr_at_3
      value: 17.000999999999998
    - type: mrr_at_5
      value: 18.374
    - type: ndcg_at_1
      value: 13.58
    - type: ndcg_at_10
      value: 15.756999999999998
    - type: ndcg_at_100
      value: 21.529999999999998
    - type: ndcg_at_1000
      value: 25.956000000000003
    - type: ndcg_at_3
      value: 12.848
    - type: ndcg_at_5
      value: 13.998
    - type: precision_at_1
      value: 13.58
    - type: precision_at_10
      value: 4.491
    - type: precision_at_100
      value: 1.035
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 8.385
    - type: precision_at_5
      value: 6.6049999999999995
    - type: recall_at_1
      value: 6.948
    - type: recall_at_10
      value: 20.569000000000003
    - type: recall_at_100
      value: 43.488
    - type: recall_at_1000
      value: 70.87400000000001
    - type: recall_at_3
      value: 12.17
    - type: recall_at_5
      value: 15.495999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 14.854999999999999
    - type: map_at_10
      value: 21.003
    - type: map_at_100
      value: 21.797
    - type: map_at_1000
      value: 21.904
    - type: map_at_3
      value: 19.258
    - type: map_at_5
      value: 20.188
    - type: mrr_at_1
      value: 29.709999999999997
    - type: mrr_at_10
      value: 36.414
    - type: mrr_at_100
      value: 37.113
    - type: mrr_at_1000
      value: 37.179
    - type: mrr_at_3
      value: 34.542
    - type: mrr_at_5
      value: 35.619
    - type: ndcg_at_1
      value: 29.709999999999997
    - type: ndcg_at_10
      value: 27.198
    - type: ndcg_at_100
      value: 31.052999999999997
    - type: ndcg_at_1000
      value: 33.757
    - type: ndcg_at_3
      value: 23.775
    - type: ndcg_at_5
      value: 25.399
    - type: precision_at_1
      value: 29.709999999999997
    - type: precision_at_10
      value: 6.078
    - type: precision_at_100
      value: 0.919
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 15.093
    - type: precision_at_5
      value: 10.344000000000001
    - type: recall_at_1
      value: 14.854999999999999
    - type: recall_at_10
      value: 30.392000000000003
    - type: recall_at_100
      value: 45.949
    - type: recall_at_1000
      value: 64.078
    - type: recall_at_3
      value: 22.64
    - type: recall_at_5
      value: 25.861
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 66.3596
    - type: ap
      value: 60.91255566890042
    - type: f1
      value: 66.1523853101571
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.046
    - type: map_at_10
      value: 10.651
    - type: map_at_100
      value: 11.505
    - type: map_at_1000
      value: 11.61
    - type: map_at_3
      value: 8.959999999999999
    - type: map_at_5
      value: 9.843
    - type: mrr_at_1
      value: 6.261
    - type: mrr_at_10
      value: 10.934000000000001
    - type: mrr_at_100
      value: 11.795
    - type: mrr_at_1000
      value: 11.897
    - type: mrr_at_3
      value: 9.205
    - type: mrr_at_5
      value: 10.112
    - type: ndcg_at_1
      value: 6.246
    - type: ndcg_at_10
      value: 13.559
    - type: ndcg_at_100
      value: 18.291
    - type: ndcg_at_1000
      value: 21.503
    - type: ndcg_at_3
      value: 10.012
    - type: ndcg_at_5
      value: 11.605
    - type: precision_at_1
      value: 6.246
    - type: precision_at_10
      value: 2.357
    - type: precision_at_100
      value: 0.481
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_3
      value: 4.436
    - type: precision_at_5
      value: 3.4610000000000003
    - type: recall_at_1
      value: 6.046
    - type: recall_at_10
      value: 22.621
    - type: recall_at_100
      value: 45.829
    - type: recall_at_1000
      value: 71.735
    - type: recall_at_3
      value: 12.826
    - type: recall_at_5
      value: 16.658
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.10989512083903
    - type: f1
      value: 87.64152476625755
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 57.87505699954399
    - type: f1
      value: 40.00822983589675
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.21788836583726
    - type: f1
      value: 61.64373490787742
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.50168123739071
    - type: f1
      value: 71.25047204682383
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.30894849088611
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.369395178404975
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.225892079841838
    - type: mrr
      value: 31.239259568046673
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.115
    - type: map_at_10
      value: 7.8149999999999995
    - type: map_at_100
      value: 9.962
    - type: map_at_1000
      value: 11.253
    - type: map_at_3
      value: 6.014
    - type: map_at_5
      value: 6.874
    - type: mrr_at_1
      value: 32.198
    - type: mrr_at_10
      value: 42.025
    - type: mrr_at_100
      value: 42.875
    - type: mrr_at_1000
      value: 42.925999999999995
    - type: mrr_at_3
      value: 39.318999999999996
    - type: mrr_at_5
      value: 41.192
    - type: ndcg_at_1
      value: 30.186
    - type: ndcg_at_10
      value: 24.194
    - type: ndcg_at_100
      value: 23.426
    - type: ndcg_at_1000
      value: 32.955
    - type: ndcg_at_3
      value: 27.528999999999996
    - type: ndcg_at_5
      value: 26.295
    - type: precision_at_1
      value: 32.198
    - type: precision_at_10
      value: 17.740000000000002
    - type: precision_at_100
      value: 6.433
    - type: precision_at_1000
      value: 1.9609999999999999
    - type: precision_at_3
      value: 26.006
    - type: precision_at_5
      value: 22.786
    - type: recall_at_1
      value: 4.115
    - type: recall_at_10
      value: 11.774
    - type: recall_at_100
      value: 26.046999999999997
    - type: recall_at_1000
      value: 60.171
    - type: recall_at_3
      value: 6.935
    - type: recall_at_5
      value: 8.958
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.959
    - type: map_at_10
      value: 13.771
    - type: map_at_100
      value: 14.954
    - type: map_at_1000
      value: 15.061
    - type: map_at_3
      value: 11.548
    - type: map_at_5
      value: 12.686
    - type: mrr_at_1
      value: 9.067
    - type: mrr_at_10
      value: 15.262
    - type: mrr_at_100
      value: 16.358
    - type: mrr_at_1000
      value: 16.447
    - type: mrr_at_3
      value: 12.895999999999999
    - type: mrr_at_5
      value: 14.13
    - type: ndcg_at_1
      value: 9.067
    - type: ndcg_at_10
      value: 17.711
    - type: ndcg_at_100
      value: 23.771
    - type: ndcg_at_1000
      value: 26.695
    - type: ndcg_at_3
      value: 13.04
    - type: ndcg_at_5
      value: 15.098
    - type: precision_at_1
      value: 9.067
    - type: precision_at_10
      value: 3.36
    - type: precision_at_100
      value: 0.6819999999999999
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 6.132
    - type: precision_at_5
      value: 4.832
    - type: recall_at_1
      value: 7.959
    - type: recall_at_10
      value: 28.529
    - type: recall_at_100
      value: 56.747
    - type: recall_at_1000
      value: 79.251
    - type: recall_at_3
      value: 16.066
    - type: recall_at_5
      value: 20.836
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.468999999999994
    - type: map_at_10
      value: 76.363
    - type: map_at_100
      value: 77.13799999999999
    - type: map_at_1000
      value: 77.169
    - type: map_at_3
      value: 73.303
    - type: map_at_5
      value: 75.139
    - type: mrr_at_1
      value: 73.09
    - type: mrr_at_10
      value: 80.379
    - type: mrr_at_100
      value: 80.632
    - type: mrr_at_1000
      value: 80.637
    - type: mrr_at_3
      value: 78.9
    - type: mrr_at_5
      value: 79.83200000000001
    - type: ndcg_at_1
      value: 73.14
    - type: ndcg_at_10
      value: 80.99
    - type: ndcg_at_100
      value: 83.086
    - type: ndcg_at_1000
      value: 83.421
    - type: ndcg_at_3
      value: 77.263
    - type: ndcg_at_5
      value: 79.175
    - type: precision_at_1
      value: 73.14
    - type: precision_at_10
      value: 12.324
    - type: precision_at_100
      value: 1.469
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.562999999999995
    - type: precision_at_5
      value: 22.259999999999998
    - type: recall_at_1
      value: 63.468999999999994
    - type: recall_at_10
      value: 89.997
    - type: recall_at_100
      value: 97.87
    - type: recall_at_1000
      value: 99.714
    - type: recall_at_3
      value: 79.45100000000001
    - type: recall_at_5
      value: 84.652
    - type: map_at_1
      value: 3.118
    - type: map_at_10
      value: 7.127999999999999
    - type: map_at_100
      value: 8.551
    - type: map_at_1000
      value: 8.819
    - type: map_at_3
      value: 5.269
    - type: map_at_5
      value: 6.136
    - type: mrr_at_1
      value: 15.299999999999999
    - type: mrr_at_10
      value: 23.138
    - type: mrr_at_100
      value: 24.354
    - type: mrr_at_1000
      value: 24.449
    - type: mrr_at_3
      value: 20.349999999999998
    - type: mrr_at_5
      value: 21.875
    - type: ndcg_at_1
      value: 15.299999999999999
    - type: ndcg_at_10
      value: 12.7
    - type: ndcg_at_100
      value: 19.177
    - type: ndcg_at_1000
      value: 24.578
    - type: ndcg_at_3
      value: 12.076
    - type: ndcg_at_5
      value: 10.446
    - type: precision_at_1
      value: 15.299999999999999
    - type: precision_at_10
      value: 6.5600000000000005
    - type: precision_at_100
      value: 1.598
    - type: precision_at_1000
      value: 0.29
    - type: precision_at_3
      value: 11.200000000000001
    - type: precision_at_5
      value: 9.04
    - type: recall_at_1
      value: 3.118
    - type: recall_at_10
      value: 13.297999999999998
    - type: recall_at_100
      value: 32.427
    - type: recall_at_1000
      value: 58.885
    - type: recall_at_3
      value: 6.827999999999999
    - type: recall_at_5
      value: 9.173
    - type: map_at_1
      value: 0.146
    - type: map_at_10
      value: 0.9169999999999999
    - type: map_at_100
      value: 4.661
    - type: map_at_1000
      value: 11.487
    - type: map_at_3
      value: 0.332
    - type: map_at_5
      value: 0.503
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 66.813
    - type: mrr_at_100
      value: 67.338
    - type: mrr_at_1000
      value: 67.338
    - type: mrr_at_3
      value: 64.333
    - type: mrr_at_5
      value: 65.833
    - type: ndcg_at_1
      value: 50.0
    - type: ndcg_at_10
      value: 45.345
    - type: ndcg_at_100
      value: 34.175
    - type: ndcg_at_1000
      value: 31.346
    - type: ndcg_at_3
      value: 47.038999999999994
    - type: ndcg_at_5
      value: 47.219
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 50.0
    - type: precision_at_100
      value: 36.24
    - type: precision_at_1000
      value: 15.129999999999999
    - type: precision_at_3
      value: 52.666999999999994
    - type: precision_at_5
      value: 52.0
    - type: recall_at_1
      value: 0.146
    - type: recall_at_10
      value: 1.216
    - type: recall_at_100
      value: 7.892
    - type: recall_at_1000
      value: 30.56
    - type: recall_at_3
      value: 0.379
    - type: recall_at_5
      value: 0.61
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 40.96803215988553
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 44.76290891260663
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.43930654983161
    - type: cos_sim_spearman
      value: 64.67852678771158
    - type: euclidean_pearson
      value: 71.3061879333313
    - type: euclidean_spearman
      value: 64.67866157468679
    - type: manhattan_pearson
      value: 69.51075530995897
    - type: manhattan_spearman
      value: 63.82662313156165
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 73.65362279607574
    - type: cos_sim_spearman
      value: 64.97375169407779
    - type: euclidean_pearson
      value: 70.50786081642359
    - type: euclidean_spearman
      value: 64.97517508701773
    - type: manhattan_pearson
      value: 69.51012145127774
    - type: manhattan_spearman
      value: 64.81905653953442
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.02560272667618
    - type: cos_sim_spearman
      value: 76.85285173868739
    - type: euclidean_pearson
      value: 76.51659956643294
    - type: euclidean_spearman
      value: 76.85288956038684
    - type: manhattan_pearson
      value: 77.15391795740369
    - type: manhattan_spearman
      value: 77.55482712197826
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 75.88413419187634
    - type: cos_sim_spearman
      value: 71.81224584659623
    - type: euclidean_pearson
      value: 75.30536428389317
    - type: euclidean_spearman
      value: 71.81223615883246
    - type: manhattan_pearson
      value: 74.49619807839628
    - type: manhattan_spearman
      value: 71.45719514379861
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 78.17595987680231
    - type: cos_sim_spearman
      value: 79.69244239201231
    - type: euclidean_pearson
      value: 79.76482765319105
    - type: euclidean_spearman
      value: 79.69243514352287
    - type: manhattan_pearson
      value: 78.95938461387554
    - type: manhattan_spearman
      value: 79.12374541215064
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.19691031147148
    - type: cos_sim_spearman
      value: 75.6670693739496
    - type: euclidean_pearson
      value: 75.83043624320031
    - type: euclidean_spearman
      value: 75.66761977438898
    - type: manhattan_pearson
      value: 75.77299348357039
    - type: manhattan_spearman
      value: 75.55171542186395
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 81.6132447770844
    - type: cos_sim_spearman
      value: 82.86761864975185
    - type: euclidean_pearson
      value: 82.79978751053565
    - type: euclidean_spearman
      value: 82.8684934691074
    - type: manhattan_pearson
      value: 82.34063577443474
    - type: manhattan_spearman
      value: 82.44500370747792
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 57.122789236461344
    - type: cos_sim_spearman
      value: 59.32471385840999
    - type: euclidean_pearson
      value: 60.436929454793386
    - type: euclidean_spearman
      value: 59.32471385840999
    - type: manhattan_pearson
      value: 62.55817551321529
    - type: manhattan_spearman
      value: 60.72936294004832
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 75.51421130475329
    - type: cos_sim_spearman
      value: 74.18767551459518
    - type: euclidean_pearson
      value: 76.30778235018026
    - type: euclidean_spearman
      value: 74.18769398451926
    - type: manhattan_pearson
      value: 75.98020747073735
    - type: manhattan_spearman
      value: 74.1108346690318
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.72194768168208
    - type: mrr
      value: 91.43610293120096
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 30.528
    - type: map_at_10
      value: 39.351
    - type: map_at_100
      value: 40.461000000000006
    - type: map_at_1000
      value: 40.535
    - type: map_at_3
      value: 36.741
    - type: map_at_5
      value: 38.588
    - type: mrr_at_1
      value: 32.667
    - type: mrr_at_10
      value: 41.123
    - type: mrr_at_100
      value: 42.135
    - type: mrr_at_1000
      value: 42.197
    - type: mrr_at_3
      value: 38.944
    - type: mrr_at_5
      value: 40.528
    - type: ndcg_at_1
      value: 32.667
    - type: ndcg_at_10
      value: 44.06
    - type: ndcg_at_100
      value: 49.599
    - type: ndcg_at_1000
      value: 51.573
    - type: ndcg_at_3
      value: 39.373999999999995
    - type: ndcg_at_5
      value: 42.393
    - type: precision_at_1
      value: 32.667
    - type: precision_at_10
      value: 6.267
    - type: precision_at_100
      value: 0.9329999999999999
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 16.111
    - type: precision_at_5
      value: 11.267000000000001
    - type: recall_at_1
      value: 30.528
    - type: recall_at_10
      value: 56.77799999999999
    - type: recall_at_100
      value: 82.73899999999999
    - type: recall_at_1000
      value: 98.2
    - type: recall_at_3
      value: 44.806000000000004
    - type: recall_at_5
      value: 52.0
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.71386138613862
    - type: cos_sim_ap
      value: 91.49236791906557
    - type: cos_sim_f1
      value: 85.24262131065534
    - type: cos_sim_precision
      value: 85.28528528528528
    - type: cos_sim_recall
      value: 85.2
    - type: dot_accuracy
      value: 99.71386138613862
    - type: dot_ap
      value: 91.49236791906557
    - type: dot_f1
      value: 85.24262131065534
    - type: dot_precision
      value: 85.28528528528528
    - type: dot_recall
      value: 85.2
    - type: euclidean_accuracy
      value: 99.71386138613862
    - type: euclidean_ap
      value: 91.49236791906557
    - type: euclidean_f1
      value: 85.24262131065534
    - type: euclidean_precision
      value: 85.28528528528528
    - type: euclidean_recall
      value: 85.2
    - type: manhattan_accuracy
      value: 99.74356435643564
    - type: manhattan_ap
      value: 92.92378153295812
    - type: manhattan_f1
      value: 86.91358024691358
    - type: manhattan_precision
      value: 85.85365853658537
    - type: manhattan_recall
      value: 88.0
    - type: max_accuracy
      value: 99.74356435643564
    - type: max_ap
      value: 92.92378153295812
    - type: max_f1
      value: 86.91358024691358
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 46.49650440995953
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.729040984470192
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.340961146720595
    - type: mrr
      value: 42.78318903318903
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.518691188419957
    - type: cos_sim_spearman
      value: 31.803967934264456
    - type: dot_pearson
      value: 31.518690928671965
    - type: dot_spearman
      value: 31.787757429064612
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.0140000000000002
    - type: map_at_10
      value: 6.574000000000001
    - type: map_at_100
      value: 12.025
    - type: map_at_1000
      value: 13.649000000000001
    - type: map_at_3
      value: 3.5450000000000004
    - type: map_at_5
      value: 4.903
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 40.943000000000005
    - type: mrr_at_100
      value: 42.535000000000004
    - type: mrr_at_1000
      value: 42.535000000000004
    - type: mrr_at_3
      value: 37.075
    - type: mrr_at_5
      value: 38.81
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 19.471
    - type: ndcg_at_100
      value: 32.823
    - type: ndcg_at_1000
      value: 44.644
    - type: ndcg_at_3
      value: 21.255
    - type: ndcg_at_5
      value: 21.438
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 17.347
    - type: precision_at_100
      value: 7.5920000000000005
    - type: precision_at_1000
      value: 1.508
    - type: precision_at_3
      value: 21.088
    - type: precision_at_5
      value: 21.633
    - type: recall_at_1
      value: 2.0140000000000002
    - type: recall_at_10
      value: 11.748
    - type: recall_at_100
      value: 46.436
    - type: recall_at_1000
      value: 82.16799999999999
    - type: recall_at_3
      value: 4.4990000000000006
    - type: recall_at_5
      value: 7.423
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.5234
    - type: ap
      value: 14.633576385764599
    - type: f1
      value: 54.63581892147792
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 56.57894736842105
    - type: f1
      value: 56.73891238797681
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 38.4061559598505
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.92900995410383
    - type: cos_sim_ap
      value: 62.43405323490786
    - type: cos_sim_f1
      value: 60.06760019314341
    - type: cos_sim_precision
      value: 55.36270582999555
    - type: cos_sim_recall
      value: 65.64643799472294
    - type: dot_accuracy
      value: 82.92900995410383
    - type: dot_ap
      value: 62.43405323490786
    - type: dot_f1
      value: 60.06760019314341
    - type: dot_precision
      value: 55.36270582999555
    - type: dot_recall
      value: 65.64643799472294
    - type: euclidean_accuracy
      value: 82.92900995410383
    - type: euclidean_ap
      value: 62.43405323490786
    - type: euclidean_f1
      value: 60.06760019314341
    - type: euclidean_precision
      value: 55.36270582999555
    - type: euclidean_recall
      value: 65.64643799472294
    - type: manhattan_accuracy
      value: 82.14221851344102
    - type: manhattan_ap
      value: 60.311627003336824
    - type: manhattan_f1
      value: 58.30150527971243
    - type: manhattan_precision
      value: 50.762910798122064
    - type: manhattan_recall
      value: 68.46965699208444
    - type: max_accuracy
      value: 82.92900995410383
    - type: max_ap
      value: 62.43405323490786
    - type: max_f1
      value: 60.06760019314341
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.08813598789149
    - type: cos_sim_ap
      value: 82.16719168081325
    - type: cos_sim_f1
      value: 74.65280302479458
    - type: cos_sim_precision
      value: 70.71910731505717
    - type: cos_sim_recall
      value: 79.04989220819218
    - type: dot_accuracy
      value: 87.08813598789149
    - type: dot_ap
      value: 82.16719168228374
    - type: dot_f1
      value: 74.65280302479458
    - type: dot_precision
      value: 70.71910731505717
    - type: dot_recall
      value: 79.04989220819218
    - type: euclidean_accuracy
      value: 87.08813598789149
    - type: euclidean_ap
      value: 82.16720008129118
    - type: euclidean_f1
      value: 74.65280302479458
    - type: euclidean_precision
      value: 70.71910731505717
    - type: euclidean_recall
      value: 79.04989220819218
    - type: manhattan_accuracy
      value: 87.16963558039352
    - type: manhattan_ap
      value: 82.17943816238372
    - type: manhattan_f1
      value: 74.91245171305823
    - type: manhattan_precision
      value: 70.52545714091497
    - type: manhattan_recall
      value: 79.88142901139513
    - type: max_accuracy
      value: 87.16963558039352
    - type: max_ap
      value: 82.17943816238372
    - type: max_f1
      value: 74.91245171305823
---
