mteb model-index region:us
---
tags:
- mteb
model-index:
- name: sbert_mpnet_main
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 65.02985074626866
    - type: ap
      value: 28.095796191623712
    - type: f1
      value: 59.03206708265084
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.13292500000001
    - type: ap
      value: 61.62083391211699
    - type: f1
      value: 66.94133235148541
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.436000000000003
    - type: f1
      value: 30.964288269346714
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 23.186
    - type: map_at_10
      value: 37.692
    - type: map_at_100
      value: 38.986
    - type: map_at_1000
      value: 38.991
    - type: map_at_3
      value: 32.622
    - type: map_at_5
      value: 35.004999999999995
    - type: mrr_at_1
      value: 23.613
    - type: mrr_at_10
      value: 37.846999999999994
    - type: mrr_at_100
      value: 39.153
    - type: mrr_at_1000
      value: 39.159
    - type: mrr_at_3
      value: 32.871
    - type: mrr_at_5
      value: 35.186
    - type: ndcg_at_1
      value: 23.186
    - type: ndcg_at_10
      value: 46.521
    - type: ndcg_at_100
      value: 51.954
    - type: ndcg_at_1000
      value: 52.087
    - type: ndcg_at_3
      value: 35.849
    - type: ndcg_at_5
      value: 40.12
    - type: precision_at_1
      value: 23.186
    - type: precision_at_10
      value: 7.510999999999999
    - type: precision_at_100
      value: 0.9860000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.078
    - type: precision_at_5
      value: 11.110000000000001
    - type: recall_at_1
      value: 23.186
    - type: recall_at_10
      value: 75.107
    - type: recall_at_100
      value: 98.649
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 45.235
    - type: recall_at_5
      value: 55.547999999999995
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 48.12285764391798
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 39.354603484421816
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 65.85199009344481
    - type: mrr
      value: 78.47700391329201
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 84.47737521407541
    - type: cos_sim_spearman
      value: 80.43195317854409
    - type: euclidean_pearson
      value: 82.20496682380606
    - type: euclidean_spearman
      value: 80.43195317854409
    - type: manhattan_pearson
      value: 81.48366733626929
    - type: manhattan_spearman
      value: 79.65904400101908
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 81.68181818181817
    - type: f1
      value: 81.10883180364475
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.31959997412176
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 34.81993134410802
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 36.036
    - type: map_at_10
      value: 49.302
    - type: map_at_100
      value: 50.956
    - type: map_at_1000
      value: 51.080000000000005
    - type: map_at_3
      value: 45.237
    - type: map_at_5
      value: 47.353
    - type: mrr_at_1
      value: 45.207
    - type: mrr_at_10
      value: 56.055
    - type: mrr_at_100
      value: 56.652
    - type: mrr_at_1000
      value: 56.688
    - type: mrr_at_3
      value: 53.672
    - type: mrr_at_5
      value: 55.123999999999995
    - type: ndcg_at_1
      value: 45.207
    - type: ndcg_at_10
      value: 56.485
    - type: ndcg_at_100
      value: 61.413
    - type: ndcg_at_1000
      value: 62.870000000000005
    - type: ndcg_at_3
      value: 51.346000000000004
    - type: ndcg_at_5
      value: 53.486
    - type: precision_at_1
      value: 45.207
    - type: precision_at_10
      value: 11.144
    - type: precision_at_100
      value: 1.735
    - type: precision_at_1000
      value: 0.22100000000000003
    - type: precision_at_3
      value: 24.94
    - type: precision_at_5
      value: 17.997
    - type: recall_at_1
      value: 36.036
    - type: recall_at_10
      value: 69.191
    - type: recall_at_100
      value: 89.423
    - type: recall_at_1000
      value: 98.425
    - type: recall_at_3
      value: 53.849999999999994
    - type: recall_at_5
      value: 60.107
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 32.92
    - type: map_at_10
      value: 45.739999999999995
    - type: map_at_100
      value: 47.309
    - type: map_at_1000
      value: 47.443000000000005
    - type: map_at_3
      value: 42.154
    - type: map_at_5
      value: 44.207
    - type: mrr_at_1
      value: 42.229
    - type: mrr_at_10
      value: 51.910999999999994
    - type: mrr_at_100
      value: 52.549
    - type: mrr_at_1000
      value: 52.586999999999996
    - type: mrr_at_3
      value: 49.427
    - type: mrr_at_5
      value: 50.93299999999999
    - type: ndcg_at_1
      value: 42.229
    - type: ndcg_at_10
      value: 52.288999999999994
    - type: ndcg_at_100
      value: 57.04900000000001
    - type: ndcg_at_1000
      value: 58.788
    - type: ndcg_at_3
      value: 47.531
    - type: ndcg_at_5
      value: 49.861
    - type: precision_at_1
      value: 42.229
    - type: precision_at_10
      value: 10.299
    - type: precision_at_100
      value: 1.68
    - type: precision_at_1000
      value: 0.213
    - type: precision_at_3
      value: 23.673
    - type: precision_at_5
      value: 17.006
    - type: recall_at_1
      value: 32.92
    - type: recall_at_10
      value: 63.865
    - type: recall_at_100
      value: 84.06700000000001
    - type: recall_at_1000
      value: 94.536
    - type: recall_at_3
      value: 49.643
    - type: recall_at_5
      value: 56.119
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 40.695
    - type: map_at_10
      value: 53.787
    - type: map_at_100
      value: 54.778000000000006
    - type: map_at_1000
      value: 54.827000000000005
    - type: map_at_3
      value: 50.151999999999994
    - type: map_at_5
      value: 52.207
    - type: mrr_at_1
      value: 46.52
    - type: mrr_at_10
      value: 57.068
    - type: mrr_at_100
      value: 57.656
    - type: mrr_at_1000
      value: 57.679
    - type: mrr_at_3
      value: 54.211
    - type: mrr_at_5
      value: 55.97
    - type: ndcg_at_1
      value: 46.52
    - type: ndcg_at_10
      value: 60.026
    - type: ndcg_at_100
      value: 63.81099999999999
    - type: ndcg_at_1000
      value: 64.741
    - type: ndcg_at_3
      value: 53.83
    - type: ndcg_at_5
      value: 56.928999999999995
    - type: precision_at_1
      value: 46.52
    - type: precision_at_10
      value: 9.754999999999999
    - type: precision_at_100
      value: 1.2670000000000001
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 24.096
    - type: precision_at_5
      value: 16.689999999999998
    - type: recall_at_1
      value: 40.695
    - type: recall_at_10
      value: 75.181
    - type: recall_at_100
      value: 91.479
    - type: recall_at_1000
      value: 98.06899999999999
    - type: recall_at_3
      value: 58.707
    - type: recall_at_5
      value: 66.295
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 29.024
    - type: map_at_10
      value: 38.438
    - type: map_at_100
      value: 39.576
    - type: map_at_1000
      value: 39.645
    - type: map_at_3
      value: 34.827999999999996
    - type: map_at_5
      value: 36.947
    - type: mrr_at_1
      value: 31.299
    - type: mrr_at_10
      value: 40.514
    - type: mrr_at_100
      value: 41.455
    - type: mrr_at_1000
      value: 41.504000000000005
    - type: mrr_at_3
      value: 37.1
    - type: mrr_at_5
      value: 39.162
    - type: ndcg_at_1
      value: 31.299
    - type: ndcg_at_10
      value: 44.268
    - type: ndcg_at_100
      value: 49.507
    - type: ndcg_at_1000
      value: 51.205999999999996
    - type: ndcg_at_3
      value: 37.248999999999995
    - type: ndcg_at_5
      value: 40.861999999999995
    - type: precision_at_1
      value: 31.299
    - type: precision_at_10
      value: 6.949
    - type: precision_at_100
      value: 1.012
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 15.518
    - type: precision_at_5
      value: 11.366999999999999
    - type: recall_at_1
      value: 29.024
    - type: recall_at_10
      value: 60.404
    - type: recall_at_100
      value: 83.729
    - type: recall_at_1000
      value: 96.439
    - type: recall_at_3
      value: 41.65
    - type: recall_at_5
      value: 50.263999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 17.774
    - type: map_at_10
      value: 28.099
    - type: map_at_100
      value: 29.603
    - type: map_at_1000
      value: 29.709999999999997
    - type: map_at_3
      value: 25.036
    - type: map_at_5
      value: 26.657999999999998
    - type: mrr_at_1
      value: 22.139
    - type: mrr_at_10
      value: 32.482
    - type: mrr_at_100
      value: 33.632
    - type: mrr_at_1000
      value: 33.683
    - type: mrr_at_3
      value: 29.706
    - type: mrr_at_5
      value: 31.291000000000004
    - type: ndcg_at_1
      value: 22.139
    - type: ndcg_at_10
      value: 34.205999999999996
    - type: ndcg_at_100
      value: 40.844
    - type: ndcg_at_1000
      value: 43.144
    - type: ndcg_at_3
      value: 28.732999999999997
    - type: ndcg_at_5
      value: 31.252000000000002
    - type: precision_at_1
      value: 22.139
    - type: precision_at_10
      value: 6.567
    - type: precision_at_100
      value: 1.147
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 14.386
    - type: precision_at_5
      value: 10.423
    - type: recall_at_1
      value: 17.774
    - type: recall_at_10
      value: 48.32
    - type: recall_at_100
      value: 76.373
    - type: recall_at_1000
      value: 92.559
    - type: recall_at_3
      value: 33.478
    - type: recall_at_5
      value: 39.872
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 31.885
    - type: map_at_10
      value: 44.289
    - type: map_at_100
      value: 45.757999999999996
    - type: map_at_1000
      value: 45.86
    - type: map_at_3
      value: 40.459
    - type: map_at_5
      value: 42.662
    - type: mrr_at_1
      value: 39.75
    - type: mrr_at_10
      value: 50.056999999999995
    - type: mrr_at_100
      value: 50.849999999999994
    - type: mrr_at_1000
      value: 50.883
    - type: mrr_at_3
      value: 47.482
    - type: mrr_at_5
      value: 48.964
    - type: ndcg_at_1
      value: 39.75
    - type: ndcg_at_10
      value: 50.975
    - type: ndcg_at_100
      value: 56.528999999999996
    - type: ndcg_at_1000
      value: 58.06099999999999
    - type: ndcg_at_3
      value: 45.327
    - type: ndcg_at_5
      value: 48.041
    - type: precision_at_1
      value: 39.75
    - type: precision_at_10
      value: 9.557
    - type: precision_at_100
      value: 1.469
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 22.073
    - type: precision_at_5
      value: 15.765
    - type: recall_at_1
      value: 31.885
    - type: recall_at_10
      value: 64.649
    - type: recall_at_100
      value: 87.702
    - type: recall_at_1000
      value: 97.327
    - type: recall_at_3
      value: 48.61
    - type: recall_at_5
      value: 55.882
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 26.454
    - type: map_at_10
      value: 37.756
    - type: map_at_100
      value: 39.225
    - type: map_at_1000
      value: 39.332
    - type: map_at_3
      value: 34.115
    - type: map_at_5
      value: 35.942
    - type: mrr_at_1
      value: 32.42
    - type: mrr_at_10
      value: 42.659000000000006
    - type: mrr_at_100
      value: 43.625
    - type: mrr_at_1000
      value: 43.672
    - type: mrr_at_3
      value: 39.878
    - type: mrr_at_5
      value: 41.482
    - type: ndcg_at_1
      value: 32.42
    - type: ndcg_at_10
      value: 44.165
    - type: ndcg_at_100
      value: 50.202000000000005
    - type: ndcg_at_1000
      value: 52.188
    - type: ndcg_at_3
      value: 38.381
    - type: ndcg_at_5
      value: 40.849000000000004
    - type: precision_at_1
      value: 32.42
    - type: precision_at_10
      value: 8.482000000000001
    - type: precision_at_100
      value: 1.332
    - type: precision_at_1000
      value: 0.169
    - type: precision_at_3
      value: 18.683
    - type: precision_at_5
      value: 13.539000000000001
    - type: recall_at_1
      value: 26.454
    - type: recall_at_10
      value: 57.937000000000005
    - type: recall_at_100
      value: 83.76
    - type: recall_at_1000
      value: 96.82600000000001
    - type: recall_at_3
      value: 41.842
    - type: recall_at_5
      value: 48.285
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.743666666666673
    - type: map_at_10
      value: 38.75416666666667
    - type: map_at_100
      value: 40.13325
    - type: map_at_1000
      value: 40.24616666666667
    - type: map_at_3
      value: 35.267250000000004
    - type: map_at_5
      value: 37.13275
    - type: mrr_at_1
      value: 33.14358333333334
    - type: mrr_at_10
      value: 42.96625
    - type: mrr_at_100
      value: 43.845666666666666
    - type: mrr_at_1000
      value: 43.89225
    - type: mrr_at_3
      value: 40.18900000000001
    - type: mrr_at_5
      value: 41.7585
    - type: ndcg_at_1
      value: 33.14358333333334
    - type: ndcg_at_10
      value: 44.959166666666675
    - type: ndcg_at_100
      value: 50.463750000000005
    - type: ndcg_at_1000
      value: 52.35508333333334
    - type: ndcg_at_3
      value: 39.17883333333334
    - type: ndcg_at_5
      value: 41.797250000000005
    - type: precision_at_1
      value: 33.14358333333334
    - type: precision_at_10
      value: 8.201083333333333
    - type: precision_at_100
      value: 1.3085
    - type: precision_at_1000
      value: 0.1665833333333333
    - type: precision_at_3
      value: 18.405583333333336
    - type: precision_at_5
      value: 13.233166666666666
    - type: recall_at_1
      value: 27.743666666666673
    - type: recall_at_10
      value: 58.91866666666667
    - type: recall_at_100
      value: 82.76216666666669
    - type: recall_at_1000
      value: 95.56883333333333
    - type: recall_at_3
      value: 42.86925
    - type: recall_at_5
      value: 49.553333333333335
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 25.244
    - type: map_at_10
      value: 33.464
    - type: map_at_100
      value: 34.633
    - type: map_at_1000
      value: 34.721999999999994
    - type: map_at_3
      value: 30.784
    - type: map_at_5
      value: 32.183
    - type: mrr_at_1
      value: 28.681
    - type: mrr_at_10
      value: 36.15
    - type: mrr_at_100
      value: 37.151
    - type: mrr_at_1000
      value: 37.211
    - type: mrr_at_3
      value: 33.845
    - type: mrr_at_5
      value: 35.095
    - type: ndcg_at_1
      value: 28.681
    - type: ndcg_at_10
      value: 38.149
    - type: ndcg_at_100
      value: 43.856
    - type: ndcg_at_1000
      value: 46.026
    - type: ndcg_at_3
      value: 33.318
    - type: ndcg_at_5
      value: 35.454
    - type: precision_at_1
      value: 28.681
    - type: precision_at_10
      value: 6.304
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 14.673
    - type: precision_at_5
      value: 10.245
    - type: recall_at_1
      value: 25.244
    - type: recall_at_10
      value: 49.711
    - type: recall_at_100
      value: 75.928
    - type: recall_at_1000
      value: 91.79899999999999
    - type: recall_at_3
      value: 36.325
    - type: recall_at_5
      value: 41.752
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 18.857
    - type: map_at_10
      value: 27.794
    - type: map_at_100
      value: 29.186
    - type: map_at_1000
      value: 29.323
    - type: map_at_3
      value: 24.779
    - type: map_at_5
      value: 26.459
    - type: mrr_at_1
      value: 23.227999999999998
    - type: mrr_at_10
      value: 31.85
    - type: mrr_at_100
      value: 32.89
    - type: mrr_at_1000
      value: 32.961
    - type: mrr_at_3
      value: 29.112
    - type: mrr_at_5
      value: 30.673000000000002
    - type: ndcg_at_1
      value: 23.227999999999998
    - type: ndcg_at_10
      value: 33.353
    - type: ndcg_at_100
      value: 39.598
    - type: ndcg_at_1000
      value: 42.268
    - type: ndcg_at_3
      value: 28.054000000000002
    - type: ndcg_at_5
      value: 30.566
    - type: precision_at_1
      value: 23.227999999999998
    - type: precision_at_10
      value: 6.397
    - type: precision_at_100
      value: 1.129
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 13.616
    - type: precision_at_5
      value: 10.116999999999999
    - type: recall_at_1
      value: 18.857
    - type: recall_at_10
      value: 45.797
    - type: recall_at_100
      value: 73.615
    - type: recall_at_1000
      value: 91.959
    - type: recall_at_3
      value: 31.129
    - type: recall_at_5
      value: 37.565
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 27.486
    - type: map_at_10
      value: 39.164
    - type: map_at_100
      value: 40.543
    - type: map_at_1000
      value: 40.636
    - type: map_at_3
      value: 35.52
    - type: map_at_5
      value: 37.355
    - type: mrr_at_1
      value: 32.275999999999996
    - type: mrr_at_10
      value: 42.882
    - type: mrr_at_100
      value: 43.883
    - type: mrr_at_1000
      value: 43.926
    - type: mrr_at_3
      value: 40.065
    - type: mrr_at_5
      value: 41.549
    - type: ndcg_at_1
      value: 32.275999999999996
    - type: ndcg_at_10
      value: 45.414
    - type: ndcg_at_100
      value: 51.254
    - type: ndcg_at_1000
      value: 53.044000000000004
    - type: ndcg_at_3
      value: 39.324999999999996
    - type: ndcg_at_5
      value: 41.835
    - type: precision_at_1
      value: 32.275999999999996
    - type: precision_at_10
      value: 8.144
    - type: precision_at_100
      value: 1.237
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 18.501
    - type: precision_at_5
      value: 13.134
    - type: recall_at_1
      value: 27.486
    - type: recall_at_10
      value: 60.449
    - type: recall_at_100
      value: 85.176
    - type: recall_at_1000
      value: 97.087
    - type: recall_at_3
      value: 43.59
    - type: recall_at_5
      value: 50.08899999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 26.207
    - type: map_at_10
      value: 37.255
    - type: map_at_100
      value: 39.043
    - type: map_at_1000
      value: 39.273
    - type: map_at_3
      value: 33.487
    - type: map_at_5
      value: 35.441
    - type: mrr_at_1
      value: 31.423000000000002
    - type: mrr_at_10
      value: 41.693999999999996
    - type: mrr_at_100
      value: 42.678
    - type: mrr_at_1000
      value: 42.71
    - type: mrr_at_3
      value: 38.472
    - type: mrr_at_5
      value: 40.231
    - type: ndcg_at_1
      value: 31.423000000000002
    - type: ndcg_at_10
      value: 44.235
    - type: ndcg_at_100
      value: 50.49
    - type: ndcg_at_1000
      value: 52.283
    - type: ndcg_at_3
      value: 37.602000000000004
    - type: ndcg_at_5
      value: 40.518
    - type: precision_at_1
      value: 31.423000000000002
    - type: precision_at_10
      value: 8.715
    - type: precision_at_100
      value: 1.7590000000000001
    - type: precision_at_1000
      value: 0.257
    - type: precision_at_3
      value: 17.523
    - type: precision_at_5
      value: 13.161999999999999
    - type: recall_at_1
      value: 26.207
    - type: recall_at_10
      value: 59.17099999999999
    - type: recall_at_100
      value: 86.166
    - type: recall_at_1000
      value: 96.54700000000001
    - type: recall_at_3
      value: 41.18
    - type: recall_at_5
      value: 48.083999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 20.342
    - type: map_at_10
      value: 29.962
    - type: map_at_100
      value: 30.989
    - type: map_at_1000
      value: 31.102999999999998
    - type: map_at_3
      value: 26.656000000000002
    - type: map_at_5
      value: 28.179
    - type: mrr_at_1
      value: 22.551
    - type: mrr_at_10
      value: 32.273
    - type: mrr_at_100
      value: 33.127
    - type: mrr_at_1000
      value: 33.202999999999996
    - type: mrr_at_3
      value: 29.298000000000002
    - type: mrr_at_5
      value: 30.628
    - type: ndcg_at_1
      value: 22.551
    - type: ndcg_at_10
      value: 35.945
    - type: ndcg_at_100
      value: 41.012
    - type: ndcg_at_1000
      value: 43.641999999999996
    - type: ndcg_at_3
      value: 29.45
    - type: ndcg_at_5
      value: 31.913999999999998
    - type: precision_at_1
      value: 22.551
    - type: precision_at_10
      value: 6.1
    - type: precision_at_100
      value: 0.943
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 13.184999999999999
    - type: precision_at_5
      value: 9.353
    - type: recall_at_1
      value: 20.342
    - type: recall_at_10
      value: 52.349000000000004
    - type: recall_at_100
      value: 75.728
    - type: recall_at_1000
      value: 95.253
    - type: recall_at_3
      value: 34.427
    - type: recall_at_5
      value: 40.326
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.71
    - type: map_at_10
      value: 14.81
    - type: map_at_100
      value: 16.536
    - type: map_at_1000
      value: 16.744999999999997
    - type: map_at_3
      value: 12.109
    - type: map_at_5
      value: 13.613
    - type: mrr_at_1
      value: 18.046
    - type: mrr_at_10
      value: 29.341
    - type: mrr_at_100
      value: 30.48
    - type: mrr_at_1000
      value: 30.535
    - type: mrr_at_3
      value: 25.765
    - type: mrr_at_5
      value: 27.935
    - type: ndcg_at_1
      value: 18.046
    - type: ndcg_at_10
      value: 21.971
    - type: ndcg_at_100
      value: 29.468
    - type: ndcg_at_1000
      value: 33.428999999999995
    - type: ndcg_at_3
      value: 17.227999999999998
    - type: ndcg_at_5
      value: 19.189999999999998
    - type: precision_at_1
      value: 18.046
    - type: precision_at_10
      value: 7.192
    - type: precision_at_100
      value: 1.51
    - type: precision_at_1000
      value: 0.22499999999999998
    - type: precision_at_3
      value: 13.312
    - type: precision_at_5
      value: 10.775
    - type: recall_at_1
      value: 7.71
    - type: recall_at_10
      value: 27.908
    - type: recall_at_100
      value: 54.452
    - type: recall_at_1000
      value: 76.764
    - type: recall_at_3
      value: 16.64
    - type: recall_at_5
      value: 21.631
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 6.8180000000000005
    - type: map_at_10
      value: 14.591000000000001
    - type: map_at_100
      value: 19.855999999999998
    - type: map_at_1000
      value: 21.178
    - type: map_at_3
      value: 10.345
    - type: map_at_5
      value: 12.367
    - type: mrr_at_1
      value: 49.5
    - type: mrr_at_10
      value: 61.414
    - type: mrr_at_100
      value: 61.974
    - type: mrr_at_1000
      value: 61.985
    - type: mrr_at_3
      value: 59.62499999999999
    - type: mrr_at_5
      value: 60.575
    - type: ndcg_at_1
      value: 39.25
    - type: ndcg_at_10
      value: 32.088
    - type: ndcg_at_100
      value: 36.019
    - type: ndcg_at_1000
      value: 43.649
    - type: ndcg_at_3
      value: 35.132999999999996
    - type: ndcg_at_5
      value: 33.777
    - type: precision_at_1
      value: 49.5
    - type: precision_at_10
      value: 25.624999999999996
    - type: precision_at_100
      value: 8.043
    - type: precision_at_1000
      value: 1.7409999999999999
    - type: precision_at_3
      value: 38.417
    - type: precision_at_5
      value: 33.2
    - type: recall_at_1
      value: 6.8180000000000005
    - type: recall_at_10
      value: 20.399
    - type: recall_at_100
      value: 42.8
    - type: recall_at_1000
      value: 68.081
    - type: recall_at_3
      value: 11.928999999999998
    - type: recall_at_5
      value: 15.348999999999998
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 42.205000000000005
    - type: f1
      value: 37.531846125752075
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 31.901000000000003
    - type: map_at_10
      value: 44.156
    - type: map_at_100
      value: 44.901
    - type: map_at_1000
      value: 44.939
    - type: map_at_3
      value: 41.008
    - type: map_at_5
      value: 42.969
    - type: mrr_at_1
      value: 34.263
    - type: mrr_at_10
      value: 46.997
    - type: mrr_at_100
      value: 47.691
    - type: mrr_at_1000
      value: 47.717999999999996
    - type: mrr_at_3
      value: 43.836999999999996
    - type: mrr_at_5
      value: 45.816
    - type: ndcg_at_1
      value: 34.263
    - type: ndcg_at_10
      value: 50.863
    - type: ndcg_at_100
      value: 54.337
    - type: ndcg_at_1000
      value: 55.297
    - type: ndcg_at_3
      value: 44.644
    - type: ndcg_at_5
      value: 48.075
    - type: precision_at_1
      value: 34.263
    - type: precision_at_10
      value: 7.542999999999999
    - type: precision_at_100
      value: 0.9400000000000001
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 18.912000000000003
    - type: precision_at_5
      value: 13.177
    - type: recall_at_1
      value: 31.901000000000003
    - type: recall_at_10
      value: 68.872
    - type: recall_at_100
      value: 84.468
    - type: recall_at_1000
      value: 91.694
    - type: recall_at_3
      value: 52.272
    - type: recall_at_5
      value: 60.504999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 24.4
    - type: map_at_10
      value: 41.117
    - type: map_at_100
      value: 43.167
    - type: map_at_1000
      value: 43.323
    - type: map_at_3
      value: 35.744
    - type: map_at_5
      value: 38.708
    - type: mrr_at_1
      value: 49.074
    - type: mrr_at_10
      value: 58.229
    - type: mrr_at_100
      value: 58.861
    - type: mrr_at_1000
      value: 58.887
    - type: mrr_at_3
      value: 55.761
    - type: mrr_at_5
      value: 57.428000000000004
    - type: ndcg_at_1
      value: 49.074
    - type: ndcg_at_10
      value: 49.963
    - type: ndcg_at_100
      value: 56.564
    - type: ndcg_at_1000
      value: 58.931999999999995
    - type: ndcg_at_3
      value: 45.489000000000004
    - type: ndcg_at_5
      value: 47.133
    - type: precision_at_1
      value: 49.074
    - type: precision_at_10
      value: 13.889000000000001
    - type: precision_at_100
      value: 2.091
    - type: precision_at_1000
      value: 0.251
    - type: precision_at_3
      value: 30.658
    - type: precision_at_5
      value: 22.593
    - type: recall_at_1
      value: 24.4
    - type: recall_at_10
      value: 58.111999999999995
    - type: recall_at_100
      value: 81.96900000000001
    - type: recall_at_1000
      value: 96.187
    - type: recall_at_3
      value: 41.661
    - type: recall_at_5
      value: 49.24
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 22.262
    - type: map_at_10
      value: 31.266
    - type: map_at_100
      value: 32.202
    - type: map_at_1000
      value: 32.299
    - type: map_at_3
      value: 28.874
    - type: map_at_5
      value: 30.246000000000002
    - type: mrr_at_1
      value: 44.524
    - type: mrr_at_10
      value: 52.306
    - type: mrr_at_100
      value: 52.905
    - type: mrr_at_1000
      value: 52.949999999999996
    - type: mrr_at_3
      value: 50.302
    - type: mrr_at_5
      value: 51.476
    - type: ndcg_at_1
      value: 44.524
    - type: ndcg_at_10
      value: 39.294000000000004
    - type: ndcg_at_100
      value: 43.296
    - type: ndcg_at_1000
      value: 45.561
    - type: ndcg_at_3
      value: 35.013
    - type: ndcg_at_5
      value: 37.177
    - type: precision_at_1
      value: 44.524
    - type: precision_at_10
      value: 8.52
    - type: precision_at_100
      value: 1.169
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_3
      value: 22.003
    - type: precision_at_5
      value: 14.914
    - type: recall_at_1
      value: 22.262
    - type: recall_at_10
      value: 42.6
    - type: recall_at_100
      value: 58.46
    - type: recall_at_1000
      value: 73.565
    - type: recall_at_3
      value: 33.005
    - type: recall_at_5
      value: 37.286
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 71.1692
    - type: ap
      value: 65.20437904022796
    - type: f1
      value: 70.84877305815426
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.159
    - type: map_at_10
      value: 32.994
    - type: map_at_100
      value: 34.171
    - type: map_at_1000
      value: 34.221000000000004
    - type: map_at_3
      value: 29.267
    - type: map_at_5
      value: 31.335
    - type: mrr_at_1
      value: 21.762
    - type: mrr_at_10
      value: 33.622
    - type: mrr_at_100
      value: 34.733000000000004
    - type: mrr_at_1000
      value: 34.777
    - type: mrr_at_3
      value: 29.914
    - type: mrr_at_5
      value: 31.988
    - type: ndcg_at_1
      value: 21.762
    - type: ndcg_at_10
      value: 39.742
    - type: ndcg_at_100
      value: 45.481
    - type: ndcg_at_1000
      value: 46.73
    - type: ndcg_at_3
      value: 32.080999999999996
    - type: ndcg_at_5
      value: 35.787
    - type: precision_at_1
      value: 21.762
    - type: precision_at_10
      value: 6.324000000000001
    - type: precision_at_100
      value: 0.922
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 13.696
    - type: precision_at_5
      value: 10.100000000000001
    - type: recall_at_1
      value: 21.159
    - type: recall_at_10
      value: 60.488
    - type: recall_at_100
      value: 87.21900000000001
    - type: recall_at_1000
      value: 96.806
    - type: recall_at_3
      value: 39.582
    - type: recall_at_5
      value: 48.474000000000004
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.87870497036023
    - type: f1
      value: 91.83382088668456
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 68.25353397172822
    - type: f1
      value: 48.271392350964916
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 69.78816408876934
    - type: f1
      value: 67.9093645800099
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 75.67585743106926
    - type: f1
      value: 74.97929341799454
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 35.58814842333602
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 33.419043960776875
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.96770386785412
    - type: mrr
      value: 31.93649596540149
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.938
    - type: map_at_10
      value: 12.034
    - type: map_at_100
      value: 15.675
    - type: map_at_1000
      value: 17.18
    - type: map_at_3
      value: 8.471
    - type: map_at_5
      value: 10.128
    - type: mrr_at_1
      value: 42.415000000000006
    - type: mrr_at_10
      value: 52.11900000000001
    - type: mrr_at_100
      value: 52.717999999999996
    - type: mrr_at_1000
      value: 52.754999999999995
    - type: mrr_at_3
      value: 50.0
    - type: mrr_at_5
      value: 51.285000000000004
    - type: ndcg_at_1
      value: 40.402
    - type: ndcg_at_10
      value: 33.289
    - type: ndcg_at_100
      value: 31.496000000000002
    - type: ndcg_at_1000
      value: 40.453
    - type: ndcg_at_3
      value: 37.841
    - type: ndcg_at_5
      value: 36.215
    - type: precision_at_1
      value: 41.796
    - type: precision_at_10
      value: 25.294
    - type: precision_at_100
      value: 8.381
    - type: precision_at_1000
      value: 2.1260000000000003
    - type: precision_at_3
      value: 36.429
    - type: precision_at_5
      value: 32.446000000000005
    - type: recall_at_1
      value: 4.938
    - type: recall_at_10
      value: 16.637
    - type: recall_at_100
      value: 33.853
    - type: recall_at_1000
      value: 66.07
    - type: recall_at_3
      value: 9.818
    - type: recall_at_5
      value: 12.544
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 27.124
    - type: map_at_10
      value: 42.418
    - type: map_at_100
      value: 43.633
    - type: map_at_1000
      value: 43.66
    - type: map_at_3
      value: 37.766
    - type: map_at_5
      value: 40.482
    - type: mrr_at_1
      value: 30.794
    - type: mrr_at_10
      value: 44.877
    - type: mrr_at_100
      value: 45.786
    - type: mrr_at_1000
      value: 45.805
    - type: mrr_at_3
      value: 40.967
    - type: mrr_at_5
      value: 43.342000000000006
    - type: ndcg_at_1
      value: 30.794
    - type: ndcg_at_10
      value: 50.449999999999996
    - type: ndcg_at_100
      value: 55.437999999999995
    - type: ndcg_at_1000
      value: 56.084
    - type: ndcg_at_3
      value: 41.678
    - type: ndcg_at_5
      value: 46.257
    - type: precision_at_1
      value: 30.794
    - type: precision_at_10
      value: 8.656
    - type: precision_at_100
      value: 1.141
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 19.37
    - type: precision_at_5
      value: 14.218
    - type: recall_at_1
      value: 27.124
    - type: recall_at_10
      value: 72.545
    - type: recall_at_100
      value: 93.938
    - type: recall_at_1000
      value: 98.788
    - type: recall_at_3
      value: 49.802
    - type: recall_at_5
      value: 60.426
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.33500000000001
    - type: map_at_10
      value: 83.553
    - type: map_at_100
      value: 84.237
    - type: map_at_1000
      value: 84.251
    - type: map_at_3
      value: 80.457
    - type: map_at_5
      value: 82.394
    - type: mrr_at_1
      value: 80.06
    - type: mrr_at_10
      value: 86.519
    - type: mrr_at_100
      value: 86.649
    - type: mrr_at_1000
      value: 86.651
    - type: mrr_at_3
      value: 85.518
    - type: mrr_at_5
      value: 86.217
    - type: ndcg_at_1
      value: 80.06
    - type: ndcg_at_10
      value: 87.46000000000001
    - type: ndcg_at_100
      value: 88.77199999999999
    - type: ndcg_at_1000
      value: 88.863
    - type: ndcg_at_3
      value: 84.439
    - type: ndcg_at_5
      value: 86.125
    - type: precision_at_1
      value: 80.06
    - type: precision_at_10
      value: 13.418
    - type: precision_at_100
      value: 1.536
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.107
    - type: precision_at_5
      value: 24.518
    - type: recall_at_1
      value: 69.33500000000001
    - type: recall_at_10
      value: 95.03200000000001
    - type: recall_at_100
      value: 99.559
    - type: recall_at_1000
      value: 99.98700000000001
    - type: recall_at_3
      value: 86.405
    - type: recall_at_5
      value: 91.122
    - type: map_at_1
      value: 5.192
    - type: map_at_10
      value: 14.426
    - type: map_at_100
      value: 17.18
    - type: map_at_1000
      value: 17.580000000000002
    - type: map_at_3
      value: 9.94
    - type: map_at_5
      value: 12.077
    - type: mrr_at_1
      value: 25.5
    - type: mrr_at_10
      value: 38.034
    - type: mrr_at_100
      value: 39.033
    - type: mrr_at_1000
      value: 39.07
    - type: mrr_at_3
      value: 34.117
    - type: mrr_at_5
      value: 36.427
    - type: ndcg_at_1
      value: 25.5
    - type: ndcg_at_10
      value: 23.765
    - type: ndcg_at_100
      value: 33.664
    - type: ndcg_at_1000
      value: 39.481
    - type: ndcg_at_3
      value: 21.813
    - type: ndcg_at_5
      value: 19.285
    - type: precision_at_1
      value: 25.5
    - type: precision_at_10
      value: 12.690000000000001
    - type: precision_at_100
      value: 2.71
    - type: precision_at_1000
      value: 0.409
    - type: precision_at_3
      value: 20.732999999999997
    - type: precision_at_5
      value: 17.24
    - type: recall_at_1
      value: 5.192
    - type: recall_at_10
      value: 25.712000000000003
    - type: recall_at_100
      value: 54.99699999999999
    - type: recall_at_1000
      value: 82.97200000000001
    - type: recall_at_3
      value: 12.631999999999998
    - type: recall_at_5
      value: 17.497
    - type: map_at_1
      value: 0.19499999999999998
    - type: map_at_10
      value: 1.218
    - type: map_at_100
      value: 7.061000000000001
    - type: map_at_1000
      value: 19.735
    - type: map_at_3
      value: 0.46499999999999997
    - type: map_at_5
      value: 0.672
    - type: mrr_at_1
      value: 66.0
    - type: mrr_at_10
      value: 75.44999999999999
    - type: mrr_at_100
      value: 75.762
    - type: mrr_at_1000
      value: 75.762
    - type: mrr_at_3
      value: 73.0
    - type: mrr_at_5
      value: 75.2
    - type: ndcg_at_1
      value: 60.0
    - type: ndcg_at_10
      value: 51.319
    - type: ndcg_at_100
      value: 41.738
    - type: ndcg_at_1000
      value: 43.221
    - type: ndcg_at_3
      value: 54.989
    - type: ndcg_at_5
      value: 52.774
    - type: precision_at_1
      value: 66.0
    - type: precision_at_10
      value: 55.60000000000001
    - type: precision_at_100
      value: 43.34
    - type: precision_at_1000
      value: 19.994
    - type: precision_at_3
      value: 59.333000000000006
    - type: precision_at_5
      value: 57.199999999999996
    - type: recall_at_1
      value: 0.19499999999999998
    - type: recall_at_10
      value: 1.473
    - type: recall_at_100
      value: 10.596
    - type: recall_at_1000
      value: 42.466
    - type: recall_at_3
      value: 0.49899999999999994
    - type: recall_at_5
      value: 0.76
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 54.6255780307404
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 56.59790381472837
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 84.00280883059669
    - type: cos_sim_spearman
      value: 80.5854073415301
    - type: euclidean_pearson
      value: 80.55974855788163
    - type: euclidean_spearman
      value: 80.58540915387199
    - type: manhattan_pearson
      value: 80.27294590630332
    - type: manhattan_spearman
      value: 80.33173697386924
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 83.28013517070231
    - type: cos_sim_spearman
      value: 72.63423278021162
    - type: euclidean_pearson
      value: 79.0134328937988
    - type: euclidean_spearman
      value: 72.6317208665704
    - type: manhattan_pearson
      value: 78.65900012611007
    - type: manhattan_spearman
      value: 72.2664461694106
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 83.20700541762768
    - type: cos_sim_spearman
      value: 83.48499016384896
    - type: euclidean_pearson
      value: 82.82555230041145
    - type: euclidean_spearman
      value: 83.48499008964005
    - type: manhattan_pearson
      value: 82.46034748646868
    - type: manhattan_spearman
      value: 83.0982395910203
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 82.27112967842054
    - type: cos_sim_spearman
      value: 78.00009897988296
    - type: euclidean_pearson
      value: 80.62651899334658
    - type: euclidean_spearman
      value: 78.00011049475123
    - type: manhattan_pearson
      value: 80.25786318469045
    - type: manhattan_spearman
      value: 77.68753745374089
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 84.98824087716352
    - type: cos_sim_spearman
      value: 85.66276030650279
    - type: euclidean_pearson
      value: 84.88733572125385
    - type: euclidean_spearman
      value: 85.66275954505593
    - type: manhattan_pearson
      value: 84.70100837758532
    - type: manhattan_spearman
      value: 85.50318725207696
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 78.82478680049049
    - type: cos_sim_spearman
      value: 80.03011315645662
    - type: euclidean_pearson
      value: 79.84794515389011
    - type: euclidean_spearman
      value: 80.03011258077692
    - type: manhattan_pearson
      value: 79.47012184458262
    - type: manhattan_spearman
      value: 79.60652985087651
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 90.90804308048635
    - type: cos_sim_spearman
      value: 90.59523263123734
    - type: euclidean_pearson
      value: 89.84669638887216
    - type: euclidean_spearman
      value: 90.59523263123734
    - type: manhattan_pearson
      value: 89.82268499045634
    - type: manhattan_spearman
      value: 90.68706496728889
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 67.34372229369944
    - type: cos_sim_spearman
      value: 68.38595785593503
    - type: euclidean_pearson
      value: 69.11395687585315
    - type: euclidean_spearman
      value: 68.38595785593503
    - type: manhattan_pearson
      value: 68.84995019201014
    - type: manhattan_spearman
      value: 68.04844816582818
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 84.03996039453689
    - type: cos_sim_spearman
      value: 83.421898505618
    - type: euclidean_pearson
      value: 83.78671191583726
    - type: euclidean_spearman
      value: 83.4219042133061
    - type: manhattan_pearson
      value: 83.44085796612015
    - type: manhattan_spearman
      value: 83.02900779808584
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 88.65396986895777
    - type: mrr
      value: 96.60209525405604
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 51.456
    - type: map_at_10
      value: 60.827
    - type: map_at_100
      value: 61.595
    - type: map_at_1000
      value: 61.629999999999995
    - type: map_at_3
      value: 57.518
    - type: map_at_5
      value: 59.435
    - type: mrr_at_1
      value: 53.333
    - type: mrr_at_10
      value: 61.773999999999994
    - type: mrr_at_100
      value: 62.370999999999995
    - type: mrr_at_1000
      value: 62.405
    - type: mrr_at_3
      value: 59.278
    - type: mrr_at_5
      value: 60.778
    - type: ndcg_at_1
      value: 53.333
    - type: ndcg_at_10
      value: 65.57
    - type: ndcg_at_100
      value: 68.911
    - type: ndcg_at_1000
      value: 69.65299999999999
    - type: ndcg_at_3
      value: 60.009
    - type: ndcg_at_5
      value: 62.803
    - type: precision_at_1
      value: 53.333
    - type: precision_at_10
      value: 8.933
    - type: precision_at_100
      value: 1.0699999999999998
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 23.333000000000002
    - type: precision_at_5
      value: 15.8
    - type: recall_at_1
      value: 51.456
    - type: recall_at_10
      value: 79.011
    - type: recall_at_100
      value: 94.167
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_3
      value: 64.506
    - type: recall_at_5
      value: 71.211
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.65940594059406
    - type: cos_sim_ap
      value: 90.14551416831162
    - type: cos_sim_f1
      value: 82.26044226044226
    - type: cos_sim_precision
      value: 80.8695652173913
    - type: cos_sim_recall
      value: 83.7
    - type: dot_accuracy
      value: 99.65940594059406
    - type: dot_ap
      value: 90.14551416831162
    - type: dot_f1
      value: 82.26044226044226
    - type: dot_precision
      value: 80.8695652173913
    - type: dot_recall
      value: 83.7
    - type: euclidean_accuracy
      value: 99.65940594059406
    - type: euclidean_ap
      value: 90.14551416831162
    - type: euclidean_f1
      value: 82.26044226044226
    - type: euclidean_precision
      value: 80.8695652173913
    - type: euclidean_recall
      value: 83.7
    - type: manhattan_accuracy
      value: 99.64950495049504
    - type: manhattan_ap
      value: 89.549267663098
    - type: manhattan_f1
      value: 81.58280410356619
    - type: manhattan_precision
      value: 79.75167144221585
    - type: manhattan_recall
      value: 83.5
    - type: max_accuracy
      value: 99.65940594059406
    - type: max_ap
      value: 90.14551416831162
    - type: max_f1
      value: 82.26044226044226
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 53.653923131513245
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 34.2472395162543
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 51.97846886836596
    - type: mrr
      value: 52.861970545794065
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 28.364292988727772
    - type: cos_sim_spearman
      value: 27.485869639926136
    - type: dot_pearson
      value: 28.36429488492219
    - type: dot_spearman
      value: 27.485454060168806
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.997
    - type: map_at_10
      value: 7.5569999999999995
    - type: map_at_100
      value: 12.238
    - type: map_at_1000
      value: 13.773
    - type: map_at_3
      value: 4.334
    - type: map_at_5
      value: 5.5
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 40.799
    - type: mrr_at_100
      value: 41.915
    - type: mrr_at_1000
      value: 41.926
    - type: mrr_at_3
      value: 36.054
    - type: mrr_at_5
      value: 39.217999999999996
    - type: ndcg_at_1
      value: 22.448999999999998
    - type: ndcg_at_10
      value: 19.933999999999997
    - type: ndcg_at_100
      value: 30.525999999999996
    - type: ndcg_at_1000
      value: 43.147999999999996
    - type: ndcg_at_3
      value: 22.283
    - type: ndcg_at_5
      value: 21.224
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 17.551
    - type: precision_at_100
      value: 6.4079999999999995
    - type: precision_at_1000
      value: 1.463
    - type: precision_at_3
      value: 23.128999999999998
    - type: precision_at_5
      value: 20.816000000000003
    - type: recall_at_1
      value: 1.997
    - type: recall_at_10
      value: 13.001999999999999
    - type: recall_at_100
      value: 40.98
    - type: recall_at_1000
      value: 79.40899999999999
    - type: recall_at_3
      value: 5.380999999999999
    - type: recall_at_5
      value: 7.721
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 66.0898
    - type: ap
      value: 12.085385183980698
    - type: f1
      value: 50.795355262136766
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.028296547821164
    - type: f1
      value: 55.31088386514747
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 50.065510618285934
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 86.07617571675507
    - type: cos_sim_ap
      value: 73.85397891429963
    - type: cos_sim_f1
      value: 68.50702798531087
    - type: cos_sim_precision
      value: 65.86316045775506
    - type: cos_sim_recall
      value: 71.37203166226914
    - type: dot_accuracy
      value: 86.07617571675507
    - type: dot_ap
      value: 73.85397372247319
    - type: dot_f1
      value: 68.50702798531087
    - type: dot_precision
      value: 65.86316045775506
    - type: dot_recall
      value: 71.37203166226914
    - type: euclidean_accuracy
      value: 86.07617571675507
    - type: euclidean_ap
      value: 73.85397657756167
    - type: euclidean_f1
      value: 68.50702798531087
    - type: euclidean_precision
      value: 65.86316045775506
    - type: euclidean_recall
      value: 71.37203166226914
    - type: manhattan_accuracy
      value: 85.98676759849795
    - type: manhattan_ap
      value: 73.86876714443989
    - type: manhattan_f1
      value: 68.55096559662361
    - type: manhattan_precision
      value: 66.51774633904195
    - type: manhattan_recall
      value: 70.71240105540898
    - type: max_accuracy
      value: 86.07617571675507
    - type: max_ap
      value: 73.86876714443989
    - type: max_f1
      value: 68.55096559662361
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.51631932316529
    - type: cos_sim_ap
      value: 85.10832311156074
    - type: cos_sim_f1
      value: 77.14563397129186
    - type: cos_sim_precision
      value: 74.9709386806161
    - type: cos_sim_recall
      value: 79.45026178010471
    - type: dot_accuracy
      value: 88.51631932316529
    - type: dot_ap
      value: 85.10831793463562
    - type: dot_f1
      value: 77.14563397129186
    - type: dot_precision
      value: 74.9709386806161
    - type: dot_recall
      value: 79.45026178010471
    - type: euclidean_accuracy
      value: 88.51631932316529
    - type: euclidean_ap
      value: 85.10831981936006
    - type: euclidean_f1
      value: 77.14563397129186
    - type: euclidean_precision
      value: 74.9709386806161
    - type: euclidean_recall
      value: 79.45026178010471
    - type: manhattan_accuracy
      value: 88.50467652423643
    - type: manhattan_ap
      value: 85.0833090132178
    - type: manhattan_f1
      value: 77.11157455683002
    - type: manhattan_precision
      value: 74.67541834968263
    - type: manhattan_recall
      value: 79.71204188481676
    - type: max_accuracy
      value: 88.51631932316529
    - type: max_ap
      value: 85.10832311156074
    - type: max_f1
      value: 77.14563397129186
---
