mteb model-index region:us
---
tags:
- mteb
model-index:
- name: e5-small-v2
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 76.65671641791046
    - type: ap
      value: 40.16054083847425
    - type: f1
      value: 70.73805260085523
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 46.431999999999995
    - type: f1
      value: 44.4239364840113
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 24.182000000000002
    - type: map_at_10
      value: 38.53
    - type: map_at_100
      value: 39.574999999999996
    - type: map_at_1000
      value: 39.593
    - type: map_at_3
      value: 33.796
    - type: map_at_5
      value: 36.406
    - type: mrr_at_1
      value: 24.964
    - type: mrr_at_10
      value: 38.829
    - type: mrr_at_100
      value: 39.867000000000004
    - type: mrr_at_1000
      value: 39.885999999999996
    - type: mrr_at_3
      value: 34.092
    - type: mrr_at_5
      value: 36.713
    - type: ndcg_at_1
      value: 24.182000000000002
    - type: ndcg_at_10
      value: 46.865
    - type: ndcg_at_100
      value: 51.611
    - type: ndcg_at_1000
      value: 52.137
    - type: ndcg_at_3
      value: 37.036
    - type: ndcg_at_5
      value: 41.715999999999994
    - type: precision_at_1
      value: 24.182000000000002
    - type: precision_at_10
      value: 7.367999999999999
    - type: precision_at_100
      value: 0.951
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 15.481
    - type: precision_at_5
      value: 11.55
    - type: recall_at_1
      value: 24.182000000000002
    - type: recall_at_10
      value: 73.68400000000001
    - type: recall_at_100
      value: 95.092
    - type: recall_at_1000
      value: 99.289
    - type: recall_at_3
      value: 46.444
    - type: recall_at_5
      value: 57.752
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 43.243157093430476
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 36.48617956618108
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 57.6915668741631
    - type: mrr
      value: 70.97832300048366
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.25177125617765
    - type: cos_sim_spearman
      value: 82.19042698150236
    - type: euclidean_pearson
      value: 81.39677961271671
    - type: euclidean_spearman
      value: 82.19042698150236
    - type: manhattan_pearson
      value: 81.83582953195571
    - type: manhattan_spearman
      value: 82.20127060207557
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.73701298701299
    - type: f1
      value: 72.68295178070956
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.55562814544096
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 31.024495399036073
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 31.356
    - type: map_at_10
      value: 41.583
    - type: map_at_100
      value: 42.931999999999995
    - type: map_at_1000
      value: 43.059999999999995
    - type: map_at_3
      value: 38.572
    - type: map_at_5
      value: 40.184999999999995
    - type: mrr_at_1
      value: 39.485
    - type: mrr_at_10
      value: 48.325
    - type: mrr_at_100
      value: 49.044
    - type: mrr_at_1000
      value: 49.095
    - type: mrr_at_3
      value: 45.97
    - type: mrr_at_5
      value: 47.38
    - type: ndcg_at_1
      value: 39.485
    - type: ndcg_at_10
      value: 47.689
    - type: ndcg_at_100
      value: 52.611
    - type: ndcg_at_1000
      value: 54.75600000000001
    - type: ndcg_at_3
      value: 43.675000000000004
    - type: ndcg_at_5
      value: 45.305
    - type: precision_at_1
      value: 39.485
    - type: precision_at_10
      value: 9.142
    - type: precision_at_100
      value: 1.4460000000000002
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 21.364
    - type: precision_at_5
      value: 15.021
    - type: recall_at_1
      value: 31.356
    - type: recall_at_10
      value: 58.338
    - type: recall_at_100
      value: 79.23400000000001
    - type: recall_at_1000
      value: 93.4
    - type: recall_at_3
      value: 45.224
    - type: recall_at_5
      value: 50.719
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 25.988
    - type: map_at_10
      value: 34.314
    - type: map_at_100
      value: 35.323
    - type: map_at_1000
      value: 35.453
    - type: map_at_3
      value: 31.855
    - type: map_at_5
      value: 33.317
    - type: mrr_at_1
      value: 32.675
    - type: mrr_at_10
      value: 40.199
    - type: mrr_at_100
      value: 40.912
    - type: mrr_at_1000
      value: 40.964
    - type: mrr_at_3
      value: 38.132
    - type: mrr_at_5
      value: 39.421
    - type: ndcg_at_1
      value: 32.675
    - type: ndcg_at_10
      value: 39.346
    - type: ndcg_at_100
      value: 43.578
    - type: ndcg_at_1000
      value: 45.975
    - type: ndcg_at_3
      value: 35.75
    - type: ndcg_at_5
      value: 37.578
    - type: precision_at_1
      value: 32.675
    - type: precision_at_10
      value: 7.228999999999999
    - type: precision_at_100
      value: 1.204
    - type: precision_at_1000
      value: 0.172
    - type: precision_at_3
      value: 17.113
    - type: precision_at_5
      value: 12.166
    - type: recall_at_1
      value: 25.988
    - type: recall_at_10
      value: 47.943000000000005
    - type: recall_at_100
      value: 66.326
    - type: recall_at_1000
      value: 82.02000000000001
    - type: recall_at_3
      value: 37.169999999999995
    - type: recall_at_5
      value: 42.356
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 38.536
    - type: map_at_10
      value: 49.514
    - type: map_at_100
      value: 50.55500000000001
    - type: map_at_1000
      value: 50.615
    - type: map_at_3
      value: 46.329
    - type: map_at_5
      value: 48.278
    - type: mrr_at_1
      value: 43.887
    - type: mrr_at_10
      value: 52.900999999999996
    - type: mrr_at_100
      value: 53.63099999999999
    - type: mrr_at_1000
      value: 53.664
    - type: mrr_at_3
      value: 50.502
    - type: mrr_at_5
      value: 52.063
    - type: ndcg_at_1
      value: 43.887
    - type: ndcg_at_10
      value: 54.847
    - type: ndcg_at_100
      value: 59.163
    - type: ndcg_at_1000
      value: 60.44199999999999
    - type: ndcg_at_3
      value: 49.6
    - type: ndcg_at_5
      value: 52.493
    - type: precision_at_1
      value: 43.887
    - type: precision_at_10
      value: 8.677
    - type: precision_at_100
      value: 1.176
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 21.797
    - type: precision_at_5
      value: 15.146999999999998
    - type: recall_at_1
      value: 38.536
    - type: recall_at_10
      value: 67.23
    - type: recall_at_100
      value: 86.095
    - type: recall_at_1000
      value: 95.26400000000001
    - type: recall_at_3
      value: 53.388000000000005
    - type: recall_at_5
      value: 60.4
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 23.488
    - type: map_at_10
      value: 30.375000000000004
    - type: map_at_100
      value: 31.343
    - type: map_at_1000
      value: 31.447999999999997
    - type: map_at_3
      value: 28.017999999999997
    - type: map_at_5
      value: 29.415999999999997
    - type: mrr_at_1
      value: 25.085
    - type: mrr_at_10
      value: 31.935000000000002
    - type: mrr_at_100
      value: 32.843
    - type: mrr_at_1000
      value: 32.929
    - type: mrr_at_3
      value: 29.548000000000002
    - type: mrr_at_5
      value: 31.04
    - type: ndcg_at_1
      value: 25.085
    - type: ndcg_at_10
      value: 34.48
    - type: ndcg_at_100
      value: 39.501
    - type: ndcg_at_1000
      value: 42.141
    - type: ndcg_at_3
      value: 29.831000000000003
    - type: ndcg_at_5
      value: 32.312999999999995
    - type: precision_at_1
      value: 25.085
    - type: precision_at_10
      value: 5.153
    - type: precision_at_100
      value: 0.815
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 12.09
    - type: precision_at_5
      value: 8.701
    - type: recall_at_1
      value: 23.488
    - type: recall_at_10
      value: 45.671
    - type: recall_at_100
      value: 69.062
    - type: recall_at_1000
      value: 88.82
    - type: recall_at_3
      value: 33.376
    - type: recall_at_5
      value: 39.311
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 12.879999999999999
    - type: map_at_10
      value: 18.873
    - type: map_at_100
      value: 20.097
    - type: map_at_1000
      value: 20.222
    - type: map_at_3
      value: 16.982
    - type: map_at_5
      value: 17.902
    - type: mrr_at_1
      value: 15.920000000000002
    - type: mrr_at_10
      value: 22.71
    - type: mrr_at_100
      value: 23.818
    - type: mrr_at_1000
      value: 23.898
    - type: mrr_at_3
      value: 20.626
    - type: mrr_at_5
      value: 21.733
    - type: ndcg_at_1
      value: 15.920000000000002
    - type: ndcg_at_10
      value: 22.959
    - type: ndcg_at_100
      value: 29.270000000000003
    - type: ndcg_at_1000
      value: 32.448
    - type: ndcg_at_3
      value: 19.356
    - type: ndcg_at_5
      value: 20.816000000000003
    - type: precision_at_1
      value: 15.920000000000002
    - type: precision_at_10
      value: 4.328
    - type: precision_at_100
      value: 0.8710000000000001
    - type: precision_at_1000
      value: 0.127
    - type: precision_at_3
      value: 9.203999999999999
    - type: precision_at_5
      value: 6.5920000000000005
    - type: recall_at_1
      value: 12.879999999999999
    - type: recall_at_10
      value: 31.724999999999998
    - type: recall_at_100
      value: 60.049
    - type: recall_at_1000
      value: 83.133
    - type: recall_at_3
      value: 21.981
    - type: recall_at_5
      value: 25.668999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 22.774
    - type: map_at_10
      value: 31.312
    - type: map_at_100
      value: 32.487
    - type: map_at_1000
      value: 32.609
    - type: map_at_3
      value: 28.589
    - type: map_at_5
      value: 30.142999999999997
    - type: mrr_at_1
      value: 28.393
    - type: mrr_at_10
      value: 36.813
    - type: mrr_at_100
      value: 37.724999999999994
    - type: mrr_at_1000
      value: 37.789
    - type: mrr_at_3
      value: 34.392
    - type: mrr_at_5
      value: 35.893
    - type: ndcg_at_1
      value: 28.393
    - type: ndcg_at_10
      value: 36.835
    - type: ndcg_at_100
      value: 42.192
    - type: ndcg_at_1000
      value: 44.812000000000005
    - type: ndcg_at_3
      value: 32.268
    - type: ndcg_at_5
      value: 34.515
    - type: precision_at_1
      value: 28.393
    - type: precision_at_10
      value: 6.737
    - type: precision_at_100
      value: 1.114
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 15.399
    - type: precision_at_5
      value: 10.991
    - type: recall_at_1
      value: 22.774
    - type: recall_at_10
      value: 48.136
    - type: recall_at_100
      value: 71.0
    - type: recall_at_1000
      value: 88.74
    - type: recall_at_3
      value: 35.098
    - type: recall_at_5
      value: 41.134
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 23.669
    - type: map_at_10
      value: 32.554
    - type: map_at_100
      value: 33.886
    - type: map_at_1000
      value: 34.004
    - type: map_at_3
      value: 29.944
    - type: map_at_5
      value: 31.330999999999996
    - type: mrr_at_1
      value: 29.110000000000003
    - type: mrr_at_10
      value: 37.234
    - type: mrr_at_100
      value: 38.151
    - type: mrr_at_1000
      value: 38.218999999999994
    - type: mrr_at_3
      value: 35.046
    - type: mrr_at_5
      value: 36.056
    - type: ndcg_at_1
      value: 29.110000000000003
    - type: ndcg_at_10
      value: 37.743
    - type: ndcg_at_100
      value: 43.413000000000004
    - type: ndcg_at_1000
      value: 46.06
    - type: ndcg_at_3
      value: 33.501999999999995
    - type: ndcg_at_5
      value: 35.175
    - type: precision_at_1
      value: 29.110000000000003
    - type: precision_at_10
      value: 6.872
    - type: precision_at_100
      value: 1.129
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 16.02
    - type: precision_at_5
      value: 11.21
    - type: recall_at_1
      value: 23.669
    - type: recall_at_10
      value: 48.615
    - type: recall_at_100
      value: 72.708
    - type: recall_at_1000
      value: 90.96300000000001
    - type: recall_at_3
      value: 36.373
    - type: recall_at_5
      value: 41.06
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 21.364
    - type: map_at_10
      value: 27.208
    - type: map_at_100
      value: 28.083000000000002
    - type: map_at_1000
      value: 28.182000000000002
    - type: map_at_3
      value: 25.448999999999998
    - type: map_at_5
      value: 26.397
    - type: mrr_at_1
      value: 24.233
    - type: mrr_at_10
      value: 29.802
    - type: mrr_at_100
      value: 30.595
    - type: mrr_at_1000
      value: 30.660999999999998
    - type: mrr_at_3
      value: 28.17
    - type: mrr_at_5
      value: 28.967
    - type: ndcg_at_1
      value: 24.233
    - type: ndcg_at_10
      value: 30.774
    - type: ndcg_at_100
      value: 35.414
    - type: ndcg_at_1000
      value: 37.962
    - type: ndcg_at_3
      value: 27.497
    - type: ndcg_at_5
      value: 28.957
    - type: precision_at_1
      value: 24.233
    - type: precision_at_10
      value: 4.755
    - type: precision_at_100
      value: 0.775
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 11.860999999999999
    - type: precision_at_5
      value: 8.097999999999999
    - type: recall_at_1
      value: 21.364
    - type: recall_at_10
      value: 39.291
    - type: recall_at_100
      value: 60.907
    - type: recall_at_1000
      value: 79.786
    - type: recall_at_3
      value: 30.257
    - type: recall_at_5
      value: 33.924
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 15.139
    - type: map_at_10
      value: 21.063000000000002
    - type: map_at_100
      value: 22.070999999999998
    - type: map_at_1000
      value: 22.203999999999997
    - type: map_at_3
      value: 19.204
    - type: map_at_5
      value: 20.185
    - type: mrr_at_1
      value: 18.445
    - type: mrr_at_10
      value: 24.698999999999998
    - type: mrr_at_100
      value: 25.569999999999997
    - type: mrr_at_1000
      value: 25.659
    - type: mrr_at_3
      value: 22.866
    - type: mrr_at_5
      value: 23.868000000000002
    - type: ndcg_at_1
      value: 18.445
    - type: ndcg_at_10
      value: 24.998
    - type: ndcg_at_100
      value: 29.982999999999997
    - type: ndcg_at_1000
      value: 33.271
    - type: ndcg_at_3
      value: 21.692
    - type: ndcg_at_5
      value: 23.102
    - type: precision_at_1
      value: 18.445
    - type: precision_at_10
      value: 4.542
    - type: precision_at_100
      value: 0.84
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 10.381
    - type: precision_at_5
      value: 7.356999999999999
    - type: recall_at_1
      value: 15.139
    - type: recall_at_10
      value: 33.268
    - type: recall_at_100
      value: 55.87
    - type: recall_at_1000
      value: 79.841
    - type: recall_at_3
      value: 23.629
    - type: recall_at_5
      value: 27.541
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 24.317
    - type: map_at_10
      value: 31.661
    - type: map_at_100
      value: 32.844
    - type: map_at_1000
      value: 32.952
    - type: map_at_3
      value: 29.118
    - type: map_at_5
      value: 30.410999999999998
    - type: mrr_at_1
      value: 28.544999999999998
    - type: mrr_at_10
      value: 36.059999999999995
    - type: mrr_at_100
      value: 36.983
    - type: mrr_at_1000
      value: 37.047999999999995
    - type: mrr_at_3
      value: 33.738
    - type: mrr_at_5
      value: 34.871
    - type: ndcg_at_1
      value: 28.544999999999998
    - type: ndcg_at_10
      value: 36.546
    - type: ndcg_at_100
      value: 42.039
    - type: ndcg_at_1000
      value: 44.61
    - type: ndcg_at_3
      value: 31.835
    - type: ndcg_at_5
      value: 33.755
    - type: precision_at_1
      value: 28.544999999999998
    - type: precision_at_10
      value: 6.0729999999999995
    - type: precision_at_100
      value: 0.991
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 13.993
    - type: precision_at_5
      value: 9.795
    - type: recall_at_1
      value: 24.317
    - type: recall_at_10
      value: 47.227000000000004
    - type: recall_at_100
      value: 71.245
    - type: recall_at_1000
      value: 89.584
    - type: recall_at_3
      value: 34.292
    - type: recall_at_5
      value: 39.129000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 24.169999999999998
    - type: map_at_10
      value: 32.669
    - type: map_at_100
      value: 34.195
    - type: map_at_1000
      value: 34.438
    - type: map_at_3
      value: 30.264000000000003
    - type: map_at_5
      value: 31.694
    - type: mrr_at_1
      value: 29.249000000000002
    - type: mrr_at_10
      value: 37.230999999999995
    - type: mrr_at_100
      value: 38.216
    - type: mrr_at_1000
      value: 38.291
    - type: mrr_at_3
      value: 35.178
    - type: mrr_at_5
      value: 36.453
    - type: ndcg_at_1
      value: 29.249000000000002
    - type: ndcg_at_10
      value: 37.967
    - type: ndcg_at_100
      value: 43.514
    - type: ndcg_at_1000
      value: 46.63
    - type: ndcg_at_3
      value: 34.437
    - type: ndcg_at_5
      value: 36.299
    - type: precision_at_1
      value: 29.249000000000002
    - type: precision_at_10
      value: 7.055
    - type: precision_at_100
      value: 1.431
    - type: precision_at_1000
      value: 0.23800000000000002
    - type: precision_at_3
      value: 16.469
    - type: precision_at_5
      value: 11.897
    - type: recall_at_1
      value: 24.169999999999998
    - type: recall_at_10
      value: 47.577000000000005
    - type: recall_at_100
      value: 72.375
    - type: recall_at_1000
      value: 92.711
    - type: recall_at_3
      value: 36.551
    - type: recall_at_5
      value: 41.739
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 18.306
    - type: map_at_10
      value: 24.882
    - type: map_at_100
      value: 25.898
    - type: map_at_1000
      value: 25.991999999999997
    - type: map_at_3
      value: 22.506999999999998
    - type: map_at_5
      value: 23.708000000000002
    - type: mrr_at_1
      value: 20.148
    - type: mrr_at_10
      value: 27.014
    - type: mrr_at_100
      value: 27.886
    - type: mrr_at_1000
      value: 27.955999999999996
    - type: mrr_at_3
      value: 24.553
    - type: mrr_at_5
      value: 25.801000000000002
    - type: ndcg_at_1
      value: 20.148
    - type: ndcg_at_10
      value: 29.211
    - type: ndcg_at_100
      value: 34.307
    - type: ndcg_at_1000
      value: 36.875
    - type: ndcg_at_3
      value: 24.333
    - type: ndcg_at_5
      value: 26.455000000000002
    - type: precision_at_1
      value: 20.148
    - type: precision_at_10
      value: 4.713
    - type: precision_at_100
      value: 0.784
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 10.290000000000001
    - type: precision_at_5
      value: 7.394
    - type: recall_at_1
      value: 18.306
    - type: recall_at_10
      value: 40.591
    - type: recall_at_100
      value: 64.18199999999999
    - type: recall_at_1000
      value: 83.646
    - type: recall_at_3
      value: 27.528999999999996
    - type: recall_at_5
      value: 32.619
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 7.872999999999999
    - type: map_at_10
      value: 13.361999999999998
    - type: map_at_100
      value: 15.024999999999999
    - type: map_at_1000
      value: 15.254000000000001
    - type: map_at_3
      value: 10.895000000000001
    - type: map_at_5
      value: 12.131
    - type: mrr_at_1
      value: 16.743
    - type: mrr_at_10
      value: 26.033
    - type: mrr_at_100
      value: 27.290999999999997
    - type: mrr_at_1000
      value: 27.356
    - type: mrr_at_3
      value: 22.573
    - type: mrr_at_5
      value: 24.336
    - type: ndcg_at_1
      value: 16.743
    - type: ndcg_at_10
      value: 19.675
    - type: ndcg_at_100
      value: 27.345000000000002
    - type: ndcg_at_1000
      value: 31.685999999999996
    - type: ndcg_at_3
      value: 15.036
    - type: ndcg_at_5
      value: 16.643
    - type: precision_at_1
      value: 16.743
    - type: precision_at_10
      value: 6.43
    - type: precision_at_100
      value: 1.4749999999999999
    - type: precision_at_1000
      value: 0.22599999999999998
    - type: precision_at_3
      value: 11.01
    - type: precision_at_5
      value: 8.924999999999999
    - type: recall_at_1
      value: 7.872999999999999
    - type: recall_at_10
      value: 25.026
    - type: recall_at_100
      value: 52.245
    - type: recall_at_1000
      value: 76.949
    - type: recall_at_3
      value: 13.962
    - type: recall_at_5
      value: 18.085
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 8.586
    - type: map_at_10
      value: 17.098
    - type: map_at_100
      value: 23.857
    - type: map_at_1000
      value: 25.357000000000003
    - type: map_at_3
      value: 12.574
    - type: map_at_5
      value: 14.374999999999998
    - type: mrr_at_1
      value: 59.5
    - type: mrr_at_10
      value: 68.199
    - type: mrr_at_100
      value: 68.699
    - type: mrr_at_1000
      value: 68.71199999999999
    - type: mrr_at_3
      value: 65.958
    - type: mrr_at_5
      value: 67.38300000000001
    - type: ndcg_at_1
      value: 48.625
    - type: ndcg_at_10
      value: 36.064
    - type: ndcg_at_100
      value: 41.137
    - type: ndcg_at_1000
      value: 49.08
    - type: ndcg_at_3
      value: 39.615
    - type: ndcg_at_5
      value: 37.080999999999996
    - type: precision_at_1
      value: 59.5
    - type: precision_at_10
      value: 28.050000000000004
    - type: precision_at_100
      value: 9.133
    - type: precision_at_1000
      value: 1.8960000000000001
    - type: precision_at_3
      value: 42.75
    - type: precision_at_5
      value: 35.25
    - type: recall_at_1
      value: 8.586
    - type: recall_at_10
      value: 23.148
    - type: recall_at_100
      value: 48.479
    - type: recall_at_1000
      value: 73.75500000000001
    - type: recall_at_3
      value: 13.718
    - type: recall_at_5
      value: 16.862
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 47.440000000000005
    - type: f1
      value: 40.19931464357708
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 50.544
    - type: map_at_10
      value: 63.495000000000005
    - type: map_at_100
      value: 64.005
    - type: map_at_1000
      value: 64.023
    - type: map_at_3
      value: 60.937
    - type: map_at_5
      value: 62.556
    - type: mrr_at_1
      value: 54.379999999999995
    - type: mrr_at_10
      value: 67.266
    - type: mrr_at_100
      value: 67.647
    - type: mrr_at_1000
      value: 67.65299999999999
    - type: mrr_at_3
      value: 64.85600000000001
    - type: mrr_at_5
      value: 66.402
    - type: ndcg_at_1
      value: 54.379999999999995
    - type: ndcg_at_10
      value: 69.977
    - type: ndcg_at_100
      value: 72.045
    - type: ndcg_at_1000
      value: 72.404
    - type: ndcg_at_3
      value: 65.12299999999999
    - type: ndcg_at_5
      value: 67.843
    - type: precision_at_1
      value: 54.379999999999995
    - type: precision_at_10
      value: 9.469
    - type: precision_at_100
      value: 1.0670000000000002
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 26.533
    - type: precision_at_5
      value: 17.441000000000003
    - type: recall_at_1
      value: 50.544
    - type: recall_at_10
      value: 86.253
    - type: recall_at_100
      value: 94.92699999999999
    - type: recall_at_1000
      value: 97.301
    - type: recall_at_3
      value: 73.215
    - type: recall_at_5
      value: 79.81899999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 18.027
    - type: map_at_10
      value: 28.347
    - type: map_at_100
      value: 30.123
    - type: map_at_1000
      value: 30.284
    - type: map_at_3
      value: 24.862000000000002
    - type: map_at_5
      value: 26.698
    - type: mrr_at_1
      value: 34.105000000000004
    - type: mrr_at_10
      value: 42.747
    - type: mrr_at_100
      value: 43.672
    - type: mrr_at_1000
      value: 43.723
    - type: mrr_at_3
      value: 40.303
    - type: mrr_at_5
      value: 41.6
    - type: ndcg_at_1
      value: 34.105000000000004
    - type: ndcg_at_10
      value: 35.495
    - type: ndcg_at_100
      value: 42.447
    - type: ndcg_at_1000
      value: 45.537
    - type: ndcg_at_3
      value: 31.911
    - type: ndcg_at_5
      value: 32.995999999999995
    - type: precision_at_1
      value: 34.105000000000004
    - type: precision_at_10
      value: 9.738
    - type: precision_at_100
      value: 1.687
    - type: precision_at_1000
      value: 0.22399999999999998
    - type: precision_at_3
      value: 20.988
    - type: precision_at_5
      value: 15.432000000000002
    - type: recall_at_1
      value: 18.027
    - type: recall_at_10
      value: 41.897
    - type: recall_at_100
      value: 67.949
    - type: recall_at_1000
      value: 86.735
    - type: recall_at_3
      value: 29.342000000000002
    - type: recall_at_5
      value: 34.365
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 35.409
    - type: map_at_10
      value: 55.894
    - type: map_at_100
      value: 56.838
    - type: map_at_1000
      value: 56.901999999999994
    - type: map_at_3
      value: 52.074
    - type: map_at_5
      value: 54.429
    - type: mrr_at_1
      value: 70.817
    - type: mrr_at_10
      value: 78.532
    - type: mrr_at_100
      value: 78.755
    - type: mrr_at_1000
      value: 78.763
    - type: mrr_at_3
      value: 77.171
    - type: mrr_at_5
      value: 78.03
    - type: ndcg_at_1
      value: 70.817
    - type: ndcg_at_10
      value: 64.995
    - type: ndcg_at_100
      value: 68.27499999999999
    - type: ndcg_at_1000
      value: 69.525
    - type: ndcg_at_3
      value: 59.401
    - type: ndcg_at_5
      value: 62.471
    - type: precision_at_1
      value: 70.817
    - type: precision_at_10
      value: 13.957
    - type: precision_at_100
      value: 1.651
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 38.267
    - type: precision_at_5
      value: 25.385999999999996
    - type: recall_at_1
      value: 35.409
    - type: recall_at_10
      value: 69.784
    - type: recall_at_100
      value: 82.54599999999999
    - type: recall_at_1000
      value: 90.824
    - type: recall_at_3
      value: 57.4
    - type: recall_at_5
      value: 63.464
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 79.54679999999999
    - type: ap
      value: 73.47419341239319
    - type: f1
      value: 79.4507801491805
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: test
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 2.465
    - type: map_at_10
      value: 15.237
    - type: map_at_100
      value: 39.974
    - type: map_at_1000
      value: 47.487
    - type: map_at_3
      value: 6.798
    - type: map_at_5
      value: 9.635
    - type: mrr_at_1
      value: 93.023
    - type: mrr_at_10
      value: 94.961
    - type: mrr_at_100
      value: 95.041
    - type: mrr_at_1000
      value: 95.041
    - type: mrr_at_3
      value: 94.961
    - type: mrr_at_5
      value: 94.961
    - type: ndcg_at_1
      value: 75.194
    - type: ndcg_at_10
      value: 68.715
    - type: ndcg_at_100
      value: 64.191
    - type: ndcg_at_1000
      value: 71.192
    - type: ndcg_at_3
      value: 73.085
    - type: ndcg_at_5
      value: 72.817
    - type: precision_at_1
      value: 93.023
    - type: precision_at_10
      value: 76.512
    - type: precision_at_100
      value: 37.698
    - type: precision_at_1000
      value: 6.851
    - type: precision_at_3
      value: 88.372
    - type: precision_at_5
      value: 84.651
    - type: recall_at_1
      value: 2.465
    - type: recall_at_10
      value: 16.181
    - type: recall_at_100
      value: 52.515
    - type: recall_at_1000
      value: 77.483
    - type: recall_at_3
      value: 6.922000000000001
    - type: recall_at_5
      value: 9.945
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 90.48335613315092
    - type: f1
      value: 90.3575395041569
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 58.10533515731875
    - type: f1
      value: 41.93379347349137
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.60524546065906
    - type: f1
      value: 62.37255545904355
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.049092131809
    - type: f1
      value: 70.19452987909062
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.698383065423773
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.763066538701253
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.320838995172895
    - type: mrr
      value: 31.223609863654694
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 5.127000000000001
    - type: map_at_10
      value: 11.395
    - type: map_at_100
      value: 14.252999999999998
    - type: map_at_1000
      value: 15.601
    - type: map_at_3
      value: 8.327
    - type: map_at_5
      value: 9.637
    - type: mrr_at_1
      value: 42.105
    - type: mrr_at_10
      value: 50.495000000000005
    - type: mrr_at_100
      value: 51.175000000000004
    - type: mrr_at_1000
      value: 51.217999999999996
    - type: mrr_at_3
      value: 48.452
    - type: mrr_at_5
      value: 49.830000000000005
    - type: ndcg_at_1
      value: 40.093
    - type: ndcg_at_10
      value: 31.806
    - type: ndcg_at_100
      value: 28.949
    - type: ndcg_at_1000
      value: 37.655
    - type: ndcg_at_3
      value: 36.692
    - type: ndcg_at_5
      value: 34.348
    - type: precision_at_1
      value: 41.486000000000004
    - type: precision_at_10
      value: 23.777
    - type: precision_at_100
      value: 7.457999999999999
    - type: precision_at_1000
      value: 2.018
    - type: precision_at_3
      value: 34.572
    - type: precision_at_5
      value: 29.536
    - type: recall_at_1
      value: 5.127000000000001
    - type: recall_at_10
      value: 15.427
    - type: recall_at_100
      value: 29.206
    - type: recall_at_1000
      value: 60.716
    - type: recall_at_3
      value: 9.261999999999999
    - type: recall_at_5
      value: 11.677999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 29.275000000000002
    - type: map_at_10
      value: 44.374
    - type: map_at_100
      value: 45.405
    - type: map_at_1000
      value: 45.437
    - type: map_at_3
      value: 40.028000000000006
    - type: map_at_5
      value: 42.492999999999995
    - type: mrr_at_1
      value: 32.966
    - type: mrr_at_10
      value: 46.905
    - type: mrr_at_100
      value: 47.699999999999996
    - type: mrr_at_1000
      value: 47.721000000000004
    - type: mrr_at_3
      value: 43.308
    - type: mrr_at_5
      value: 45.458
    - type: ndcg_at_1
      value: 32.966
    - type: ndcg_at_10
      value: 52.151
    - type: ndcg_at_100
      value: 56.565
    - type: ndcg_at_1000
      value: 57.315000000000005
    - type: ndcg_at_3
      value: 43.973
    - type: ndcg_at_5
      value: 48.125
    - type: precision_at_1
      value: 32.966
    - type: precision_at_10
      value: 8.72
    - type: precision_at_100
      value: 1.121
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 20.085
    - type: precision_at_5
      value: 14.45
    - type: recall_at_1
      value: 29.275000000000002
    - type: recall_at_10
      value: 73.288
    - type: recall_at_100
      value: 92.56
    - type: recall_at_1000
      value: 98.139
    - type: recall_at_3
      value: 52.11
    - type: recall_at_5
      value: 61.696
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 67.537
    - type: map_at_10
      value: 80.879
    - type: map_at_100
      value: 81.577
    - type: map_at_1000
      value: 81.602
    - type: map_at_3
      value: 77.981
    - type: map_at_5
      value: 79.768
    - type: mrr_at_1
      value: 77.69
    - type: mrr_at_10
      value: 84.417
    - type: mrr_at_100
      value: 84.59299999999999
    - type: mrr_at_1000
      value: 84.596
    - type: mrr_at_3
      value: 83.26
    - type: mrr_at_5
      value: 84.023
    - type: ndcg_at_1
      value: 77.72
    - type: ndcg_at_10
      value: 85.021
    - type: ndcg_at_100
      value: 86.66199999999999
    - type: ndcg_at_1000
      value: 86.87700000000001
    - type: ndcg_at_3
      value: 81.90899999999999
    - type: ndcg_at_5
      value: 83.55
    - type: precision_at_1
      value: 77.72
    - type: precision_at_10
      value: 12.876999999999999
    - type: precision_at_100
      value: 1.498
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 35.653
    - type: precision_at_5
      value: 23.476
    - type: recall_at_1
      value: 67.537
    - type: recall_at_10
      value: 92.878
    - type: recall_at_100
      value: 98.786
    - type: recall_at_1000
      value: 99.892
    - type: recall_at_3
      value: 83.968
    - type: recall_at_5
      value: 88.571
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 49.16241148820256
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 61.54900278834193
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 4.173
    - type: map_at_10
      value: 10.120999999999999
    - type: map_at_100
      value: 11.956
    - type: map_at_1000
      value: 12.219
    - type: map_at_3
      value: 7.3580000000000005
    - type: map_at_5
      value: 8.799
    - type: mrr_at_1
      value: 20.599999999999998
    - type: mrr_at_10
      value: 30.326999999999998
    - type: mrr_at_100
      value: 31.412000000000003
    - type: mrr_at_1000
      value: 31.480000000000004
    - type: mrr_at_3
      value: 26.983
    - type: mrr_at_5
      value: 28.938000000000002
    - type: ndcg_at_1
      value: 20.599999999999998
    - type: ndcg_at_10
      value: 17.365
    - type: ndcg_at_100
      value: 24.623
    - type: ndcg_at_1000
      value: 29.65
    - type: ndcg_at_3
      value: 16.509999999999998
    - type: ndcg_at_5
      value: 14.542
    - type: precision_at_1
      value: 20.599999999999998
    - type: precision_at_10
      value: 8.98
    - type: precision_at_100
      value: 1.939
    - type: precision_at_1000
      value: 0.315
    - type: precision_at_3
      value: 15.4
    - type: precision_at_5
      value: 12.8
    - type: recall_at_1
      value: 4.173
    - type: recall_at_10
      value: 18.212999999999997
    - type: recall_at_100
      value: 39.363
    - type: recall_at_1000
      value: 63.94499999999999
    - type: recall_at_3
      value: 9.373
    - type: recall_at_5
      value: 13.008000000000001
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 83.87431570350371
    - type: cos_sim_spearman
      value: 79.25074443392982
    - type: euclidean_pearson
      value: 80.9080554083112
    - type: euclidean_spearman
      value: 79.2507399109411
    - type: manhattan_pearson
      value: 80.90956765983888
    - type: manhattan_spearman
      value: 79.20576643481074
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 83.48662954870734
    - type: cos_sim_spearman
      value: 73.70799073411621
    - type: euclidean_pearson
      value: 80.49103960387095
    - type: euclidean_spearman
      value: 73.7055087532169
    - type: manhattan_pearson
      value: 80.5783519196888
    - type: manhattan_spearman
      value: 73.90297846138822
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 80.70595293210951
    - type: cos_sim_spearman
      value: 82.31727223815786
    - type: euclidean_pearson
      value: 81.5306062072953
    - type: euclidean_spearman
      value: 82.31721735735299
    - type: manhattan_pearson
      value: 81.43418231655517
    - type: manhattan_spearman
      value: 82.20026619822572
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 81.24706825802423
    - type: cos_sim_spearman
      value: 80.06920825678749
    - type: euclidean_pearson
      value: 80.48334698932342
    - type: euclidean_spearman
      value: 80.06918911208002
    - type: manhattan_pearson
      value: 80.40681414406772
    - type: manhattan_spearman
      value: 80.0102866792831
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.16929217014857
    - type: cos_sim_spearman
      value: 87.2100080395613
    - type: euclidean_pearson
      value: 86.4066737251256
    - type: euclidean_spearman
      value: 87.20998056215564
    - type: manhattan_pearson
      value: 86.39080868256596
    - type: manhattan_spearman
      value: 87.1927937048571
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 80.53662089031329
    - type: cos_sim_spearman
      value: 82.33056272292711
    - type: euclidean_pearson
      value: 81.40056519211387
    - type: euclidean_spearman
      value: 82.33056272292711
    - type: manhattan_pearson
      value: 81.27845573928735
    - type: manhattan_spearman
      value: 82.22192854693785
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 87.66415281856406
    - type: cos_sim_spearman
      value: 87.58094863633612
    - type: euclidean_pearson
      value: 88.25085288996081
    - type: euclidean_spearman
      value: 87.58094863633612
    - type: manhattan_pearson
      value: 88.34016528668018
    - type: manhattan_spearman
      value: 87.67773968789653
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 65.91354529556227
    - type: cos_sim_spearman
      value: 66.29904599827411
    - type: euclidean_pearson
      value: 66.99135025654104
    - type: euclidean_spearman
      value: 66.29904599827411
    - type: manhattan_pearson
      value: 67.29167796154489
    - type: manhattan_spearman
      value: 66.54035688112117
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 83.17371544155577
    - type: cos_sim_spearman
      value: 84.91600230031912
    - type: euclidean_pearson
      value: 84.58535536355062
    - type: euclidean_spearman
      value: 84.91603828194314
    - type: manhattan_pearson
      value: 84.52786631260929
    - type: manhattan_spearman
      value: 84.8279451537192
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.90931256553237
    - type: mrr
      value: 94.55430462783404
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 52.233
    - type: map_at_10
      value: 63.135
    - type: map_at_100
      value: 63.766999999999996
    - type: map_at_1000
      value: 63.788999999999994
    - type: map_at_3
      value: 60.374
    - type: map_at_5
      value: 62.11600000000001
    - type: mrr_at_1
      value: 54.333
    - type: mrr_at_10
      value: 64.208
    - type: mrr_at_100
      value: 64.687
    - type: mrr_at_1000
      value: 64.705
    - type: mrr_at_3
      value: 62.166999999999994
    - type: mrr_at_5
      value: 63.532999999999994
    - type: ndcg_at_1
      value: 54.333
    - type: ndcg_at_10
      value: 67.965
    - type: ndcg_at_100
      value: 70.709
    - type: ndcg_at_1000
      value: 71.221
    - type: ndcg_at_3
      value: 63.376
    - type: ndcg_at_5
      value: 65.977
    - type: precision_at_1
      value: 54.333
    - type: precision_at_10
      value: 9.167
    - type: precision_at_100
      value: 1.0630000000000002
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 25.0
    - type: precision_at_5
      value: 16.733
    - type: recall_at_1
      value: 52.233
    - type: recall_at_10
      value: 81.289
    - type: recall_at_100
      value: 93.767
    - type: recall_at_1000
      value: 97.667
    - type: recall_at_3
      value: 69.294
    - type: recall_at_5
      value: 75.64999999999999
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.8069306930693
    - type: cos_sim_ap
      value: 95.01715408250185
    - type: cos_sim_f1
      value: 90.27431421446383
    - type: cos_sim_precision
      value: 90.04975124378109
    - type: cos_sim_recall
      value: 90.5
    - type: dot_accuracy
      value: 99.8069306930693
    - type: dot_ap
      value: 95.01715420720572
    - type: dot_f1
      value: 90.27431421446383
    - type: dot_precision
      value: 90.04975124378109
    - type: dot_recall
      value: 90.5
    - type: euclidean_accuracy
      value: 99.8069306930693
    - type: euclidean_ap
      value: 95.01715408250185
    - type: euclidean_f1
      value: 90.27431421446383
    - type: euclidean_precision
      value: 90.04975124378109
    - type: euclidean_recall
      value: 90.5
    - type: manhattan_accuracy
      value: 99.8108910891089
    - type: manhattan_ap
      value: 95.08344895081773
    - type: manhattan_f1
      value: 90.2672718103883
    - type: manhattan_precision
      value: 91.04781281790437
    - type: manhattan_recall
      value: 89.5
    - type: max_accuracy
      value: 99.8108910891089
    - type: max_ap
      value: 95.08344895081773
    - type: max_f1
      value: 90.27431421446383
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 56.77496100801627
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.03980982336066
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 49.92590367093363
    - type: mrr
      value: 50.72744249214838
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.873523128424296
    - type: cos_sim_spearman
      value: 29.77696422152863
    - type: dot_pearson
      value: 29.873538265911392
    - type: dot_spearman
      value: 29.77696422152863
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.16
    - type: map_at_10
      value: 1.196
    - type: map_at_100
      value: 6.525
    - type: map_at_1000
      value: 17.379
    - type: map_at_3
      value: 0.43299999999999994
    - type: map_at_5
      value: 0.687
    - type: mrr_at_1
      value: 64.0
    - type: mrr_at_10
      value: 76.467
    - type: mrr_at_100
      value: 76.533
    - type: mrr_at_1000
      value: 76.533
    - type: mrr_at_3
      value: 73.667
    - type: mrr_at_5
      value: 75.467
    - type: ndcg_at_1
      value: 56.99999999999999
    - type: ndcg_at_10
      value: 52.614000000000004
    - type: ndcg_at_100
      value: 41.677
    - type: ndcg_at_1000
      value: 41.565000000000005
    - type: ndcg_at_3
      value: 55.765
    - type: ndcg_at_5
      value: 55.553
    - type: precision_at_1
      value: 64.0
    - type: precision_at_10
      value: 56.8
    - type: precision_at_100
      value: 43.18
    - type: precision_at_1000
      value: 19.016
    - type: precision_at_3
      value: 60.0
    - type: precision_at_5
      value: 60.4
    - type: recall_at_1
      value: 0.16
    - type: recall_at_10
      value: 1.4909999999999999
    - type: recall_at_100
      value: 10.238999999999999
    - type: recall_at_1000
      value: 40.492
    - type: recall_at_3
      value: 0.486
    - type: recall_at_5
      value: 0.8099999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.078
    - type: map_at_10
      value: 4.777
    - type: map_at_100
      value: 8.552
    - type: map_at_1000
      value: 9.831
    - type: map_at_3
      value: 2.33
    - type: map_at_5
      value: 3.102
    - type: mrr_at_1
      value: 14.285999999999998
    - type: mrr_at_10
      value: 25.688
    - type: mrr_at_100
      value: 27.211000000000002
    - type: mrr_at_1000
      value: 27.262999999999998
    - type: mrr_at_3
      value: 20.408
    - type: mrr_at_5
      value: 23.265
    - type: ndcg_at_1
      value: 13.264999999999999
    - type: ndcg_at_10
      value: 13.225999999999999
    - type: ndcg_at_100
      value: 23.873
    - type: ndcg_at_1000
      value: 35.357
    - type: ndcg_at_3
      value: 11.162999999999998
    - type: ndcg_at_5
      value: 12.202
    - type: precision_at_1
      value: 14.285999999999998
    - type: precision_at_10
      value: 13.469000000000001
    - type: precision_at_100
      value: 5.592
    - type: precision_at_1000
      value: 1.278
    - type: precision_at_3
      value: 12.245000000000001
    - type: precision_at_5
      value: 13.877999999999998
    - type: recall_at_1
      value: 1.078
    - type: recall_at_10
      value: 10.094
    - type: recall_at_100
      value: 35.723
    - type: recall_at_1000
      value: 70.161
    - type: recall_at_3
      value: 3.078
    - type: recall_at_5
      value: 5.171
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 63.526
    - type: ap
      value: 11.499475362455422
    - type: f1
      value: 49.007047166853305
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 61.77136389360498
    - type: f1
      value: 61.60711673348749
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 40.700597517044926
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 86.59474280264648
    - type: cos_sim_ap
      value: 75.2354882574253
    - type: cos_sim_f1
      value: 69.23641703377386
    - type: cos_sim_precision
      value: 64.55956184390689
    - type: cos_sim_recall
      value: 74.64379947229551
    - type: dot_accuracy
      value: 86.59474280264648
    - type: dot_ap
      value: 75.2355004100119
    - type: dot_f1
      value: 69.23641703377386
    - type: dot_precision
      value: 64.55956184390689
    - type: dot_recall
      value: 74.64379947229551
    - type: euclidean_accuracy
      value: 86.59474280264648
    - type: euclidean_ap
      value: 75.23549109559548
    - type: euclidean_f1
      value: 69.23641703377386
    - type: euclidean_precision
      value: 64.55956184390689
    - type: euclidean_recall
      value: 74.64379947229551
    - type: manhattan_accuracy
      value: 86.46361089586935
    - type: manhattan_ap
      value: 74.97783476285602
    - type: manhattan_f1
      value: 69.16030534351145
    - type: manhattan_precision
      value: 66.78132678132678
    - type: manhattan_recall
      value: 71.71503957783642
    - type: max_accuracy
      value: 86.59474280264648
    - type: max_ap
      value: 75.2355004100119
    - type: max_f1
      value: 69.23641703377386
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 89.03830480847596
    - type: cos_sim_ap
      value: 85.95577773962282
    - type: cos_sim_f1
      value: 78.27735233907043
    - type: cos_sim_precision
      value: 77.10231516056758
    - type: cos_sim_recall
      value: 79.48875885432707
    - type: dot_accuracy
      value: 89.03830480847596
    - type: dot_ap
      value: 85.95578535080806
    - type: dot_f1
      value: 78.27735233907043
    - type: dot_precision
      value: 77.10231516056758
    - type: dot_recall
      value: 79.48875885432707
    - type: euclidean_accuracy
      value: 89.03830480847596
    - type: euclidean_ap
      value: 85.95573921817162
    - type: euclidean_f1
      value: 78.27735233907043
    - type: euclidean_precision
      value: 77.10231516056758
    - type: euclidean_recall
      value: 79.48875885432707
    - type: manhattan_accuracy
      value: 88.9024721543059
    - type: manhattan_ap
      value: 85.89551017445959
    - type: manhattan_f1
      value: 78.19396487013964
    - type: manhattan_precision
      value: 76.28148799062683
    - type: manhattan_recall
      value: 80.20480443486295
    - type: max_accuracy
      value: 89.03830480847596
    - type: max_ap
      value: 85.95578535080806
    - type: max_f1
      value: 78.27735233907043
---
