mteb model-index region:us
---
tags:
- mteb
model-index:
- name: mpnet_main_wordPCA
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 66.43283582089553
    - type: ap
      value: 30.29663133704438
    - type: f1
      value: 60.96548204994961
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.5157
    - type: ap
      value: 60.635968290391354
    - type: f1
      value: 65.22797046096731
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.018
    - type: f1
      value: 32.56614947751552
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.768
    - type: map_at_10
      value: 33.792
    - type: map_at_100
      value: 34.961
    - type: map_at_1000
      value: 35.001
    - type: map_at_3
      value: 29.942999999999998
    - type: map_at_5
      value: 31.941999999999997
    - type: mrr_at_1
      value: 21.124000000000002
    - type: mrr_at_10
      value: 33.954
    - type: mrr_at_100
      value: 35.124
    - type: mrr_at_1000
      value: 35.164
    - type: mrr_at_3
      value: 30.133
    - type: mrr_at_5
      value: 32.082
    - type: ndcg_at_1
      value: 20.768
    - type: ndcg_at_10
      value: 41.001
    - type: ndcg_at_100
      value: 46.556
    - type: ndcg_at_1000
      value: 47.671
    - type: ndcg_at_3
      value: 32.938
    - type: ndcg_at_5
      value: 36.571
    - type: precision_at_1
      value: 20.768
    - type: precision_at_10
      value: 6.4079999999999995
    - type: precision_at_100
      value: 0.897
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.869000000000002
    - type: precision_at_5
      value: 10.100000000000001
    - type: recall_at_1
      value: 20.768
    - type: recall_at_10
      value: 64.083
    - type: recall_at_100
      value: 89.687
    - type: recall_at_1000
      value: 98.578
    - type: recall_at_3
      value: 41.607
    - type: recall_at_5
      value: 50.498
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.53339688014046
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 26.894818446313483
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.07897208491808
    - type: mrr
      value: 68.92175614474783
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 72.13906525048021
    - type: cos_sim_spearman
      value: 71.55223277580176
    - type: euclidean_pearson
      value: 72.00248024168417
    - type: euclidean_spearman
      value: 71.55223277580176
    - type: manhattan_pearson
      value: 72.96802825988968
    - type: manhattan_spearman
      value: 72.66912569484411
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 70.05194805194805
    - type: f1
      value: 68.84496347971877
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.41380417466471
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 24.417788232051212
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.139000000000003
    - type: map_at_10
      value: 27.015
    - type: map_at_100
      value: 28.132
    - type: map_at_1000
      value: 28.301
    - type: map_at_3
      value: 24.740000000000002
    - type: map_at_5
      value: 25.672
    - type: mrr_at_1
      value: 25.607999999999997
    - type: mrr_at_10
      value: 32.143
    - type: mrr_at_100
      value: 32.979
    - type: mrr_at_1000
      value: 33.062999999999995
    - type: mrr_at_3
      value: 30.067
    - type: mrr_at_5
      value: 30.875000000000004
    - type: ndcg_at_1
      value: 25.607999999999997
    - type: ndcg_at_10
      value: 31.913999999999998
    - type: ndcg_at_100
      value: 36.853
    - type: ndcg_at_1000
      value: 40.189
    - type: ndcg_at_3
      value: 28.214
    - type: ndcg_at_5
      value: 29.185
    - type: precision_at_1
      value: 25.607999999999997
    - type: precision_at_10
      value: 6.252000000000001
    - type: precision_at_100
      value: 1.11
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 13.591000000000001
    - type: precision_at_5
      value: 9.585
    - type: recall_at_1
      value: 20.139000000000003
    - type: recall_at_10
      value: 41.065000000000005
    - type: recall_at_100
      value: 62.966
    - type: recall_at_1000
      value: 85.545
    - type: recall_at_3
      value: 29.331000000000003
    - type: recall_at_5
      value: 32.532
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 14.366000000000001
    - type: map_at_10
      value: 19.827
    - type: map_at_100
      value: 20.727999999999998
    - type: map_at_1000
      value: 20.854
    - type: map_at_3
      value: 17.957
    - type: map_at_5
      value: 18.961
    - type: mrr_at_1
      value: 18.471
    - type: mrr_at_10
      value: 23.778
    - type: mrr_at_100
      value: 24.58
    - type: mrr_at_1000
      value: 24.661
    - type: mrr_at_3
      value: 21.847
    - type: mrr_at_5
      value: 22.872999999999998
    - type: ndcg_at_1
      value: 18.471
    - type: ndcg_at_10
      value: 23.555
    - type: ndcg_at_100
      value: 27.755000000000003
    - type: ndcg_at_1000
      value: 30.739
    - type: ndcg_at_3
      value: 20.371
    - type: ndcg_at_5
      value: 21.739
    - type: precision_at_1
      value: 18.471
    - type: precision_at_10
      value: 4.516
    - type: precision_at_100
      value: 0.832
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 9.851
    - type: precision_at_5
      value: 7.172000000000001
    - type: recall_at_1
      value: 14.366000000000001
    - type: recall_at_10
      value: 30.819999999999997
    - type: recall_at_100
      value: 49.303999999999995
    - type: recall_at_1000
      value: 69.975
    - type: recall_at_3
      value: 21.397
    - type: recall_at_5
      value: 25.223000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 23.610999999999997
    - type: map_at_10
      value: 31.745
    - type: map_at_100
      value: 32.844
    - type: map_at_1000
      value: 32.940999999999995
    - type: map_at_3
      value: 29.110000000000003
    - type: map_at_5
      value: 30.695
    - type: mrr_at_1
      value: 27.586
    - type: mrr_at_10
      value: 34.809
    - type: mrr_at_100
      value: 35.745
    - type: mrr_at_1000
      value: 35.806
    - type: mrr_at_3
      value: 32.414
    - type: mrr_at_5
      value: 33.839999999999996
    - type: ndcg_at_1
      value: 27.586
    - type: ndcg_at_10
      value: 36.369
    - type: ndcg_at_100
      value: 41.743
    - type: ndcg_at_1000
      value: 44.01
    - type: ndcg_at_3
      value: 31.551000000000002
    - type: ndcg_at_5
      value: 34.048
    - type: precision_at_1
      value: 27.586
    - type: precision_at_10
      value: 5.994
    - type: precision_at_100
      value: 0.958
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 14.023
    - type: precision_at_5
      value: 10.006
    - type: recall_at_1
      value: 23.610999999999997
    - type: recall_at_10
      value: 47.532999999999994
    - type: recall_at_100
      value: 71.89
    - type: recall_at_1000
      value: 88.469
    - type: recall_at_3
      value: 34.624
    - type: recall_at_5
      value: 40.760000000000005
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.452
    - type: map_at_10
      value: 14.865
    - type: map_at_100
      value: 15.709000000000001
    - type: map_at_1000
      value: 15.818999999999999
    - type: map_at_3
      value: 13.131
    - type: map_at_5
      value: 13.935
    - type: mrr_at_1
      value: 11.299
    - type: mrr_at_10
      value: 15.856
    - type: mrr_at_100
      value: 16.727
    - type: mrr_at_1000
      value: 16.817999999999998
    - type: mrr_at_3
      value: 14.143
    - type: mrr_at_5
      value: 14.962
    - type: ndcg_at_1
      value: 11.299
    - type: ndcg_at_10
      value: 17.807000000000002
    - type: ndcg_at_100
      value: 22.542
    - type: ndcg_at_1000
      value: 25.871
    - type: ndcg_at_3
      value: 14.277999999999999
    - type: ndcg_at_5
      value: 15.689
    - type: precision_at_1
      value: 11.299
    - type: precision_at_10
      value: 2.994
    - type: precision_at_100
      value: 0.571
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.177
    - type: precision_at_5
      value: 4.542
    - type: recall_at_1
      value: 10.452
    - type: recall_at_10
      value: 26.043
    - type: recall_at_100
      value: 48.955
    - type: recall_at_1000
      value: 75.03999999999999
    - type: recall_at_3
      value: 16.384
    - type: recall_at_5
      value: 19.819
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.7700000000000005
    - type: map_at_10
      value: 9.113
    - type: map_at_100
      value: 9.969999999999999
    - type: map_at_1000
      value: 10.086
    - type: map_at_3
      value: 7.797
    - type: map_at_5
      value: 8.512
    - type: mrr_at_1
      value: 7.463
    - type: mrr_at_10
      value: 11.491
    - type: mrr_at_100
      value: 12.354
    - type: mrr_at_1000
      value: 12.443999999999999
    - type: mrr_at_3
      value: 9.866999999999999
    - type: mrr_at_5
      value: 10.738
    - type: ndcg_at_1
      value: 7.463
    - type: ndcg_at_10
      value: 11.759
    - type: ndcg_at_100
      value: 16.364
    - type: ndcg_at_1000
      value: 19.614
    - type: ndcg_at_3
      value: 9.043
    - type: ndcg_at_5
      value: 10.25
    - type: precision_at_1
      value: 7.463
    - type: precision_at_10
      value: 2.363
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 4.436
    - type: precision_at_5
      value: 3.458
    - type: recall_at_1
      value: 5.7700000000000005
    - type: recall_at_10
      value: 17.69
    - type: recall_at_100
      value: 38.624
    - type: recall_at_1000
      value: 62.425
    - type: recall_at_3
      value: 10.281
    - type: recall_at_5
      value: 13.221
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.049999999999999
    - type: map_at_10
      value: 20.639
    - type: map_at_100
      value: 21.806
    - type: map_at_1000
      value: 21.953
    - type: map_at_3
      value: 18.549
    - type: map_at_5
      value: 19.686
    - type: mrr_at_1
      value: 18.864
    - type: mrr_at_10
      value: 24.948999999999998
    - type: mrr_at_100
      value: 25.933
    - type: mrr_at_1000
      value: 26.023000000000003
    - type: mrr_at_3
      value: 22.794
    - type: mrr_at_5
      value: 24.07
    - type: ndcg_at_1
      value: 18.864
    - type: ndcg_at_10
      value: 24.877
    - type: ndcg_at_100
      value: 30.705
    - type: ndcg_at_1000
      value: 34.195
    - type: ndcg_at_3
      value: 21.112000000000002
    - type: ndcg_at_5
      value: 22.895
    - type: precision_at_1
      value: 18.864
    - type: precision_at_10
      value: 4.793
    - type: precision_at_100
      value: 0.9390000000000001
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_3
      value: 10.106
    - type: precision_at_5
      value: 7.603
    - type: recall_at_1
      value: 15.049999999999999
    - type: recall_at_10
      value: 33.466
    - type: recall_at_100
      value: 59.496
    - type: recall_at_1000
      value: 84.101
    - type: recall_at_3
      value: 22.948
    - type: recall_at_5
      value: 27.389999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.477
    - type: map_at_10
      value: 15.299
    - type: map_at_100
      value: 16.372
    - type: map_at_1000
      value: 16.521
    - type: map_at_3
      value: 13.3
    - type: map_at_5
      value: 14.306
    - type: mrr_at_1
      value: 13.242
    - type: mrr_at_10
      value: 18.465
    - type: mrr_at_100
      value: 19.387
    - type: mrr_at_1000
      value: 19.483
    - type: mrr_at_3
      value: 16.362
    - type: mrr_at_5
      value: 17.452
    - type: ndcg_at_1
      value: 13.242
    - type: ndcg_at_10
      value: 19.016
    - type: ndcg_at_100
      value: 24.556
    - type: ndcg_at_1000
      value: 28.205999999999996
    - type: ndcg_at_3
      value: 15.242
    - type: ndcg_at_5
      value: 16.802
    - type: precision_at_1
      value: 13.242
    - type: precision_at_10
      value: 3.8129999999999997
    - type: precision_at_100
      value: 0.796
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 7.42
    - type: precision_at_5
      value: 5.639
    - type: recall_at_1
      value: 10.477
    - type: recall_at_10
      value: 27.250000000000004
    - type: recall_at_100
      value: 52.459
    - type: recall_at_1000
      value: 78.224
    - type: recall_at_3
      value: 16.663
    - type: recall_at_5
      value: 20.759
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.268416666666667
    - type: map_at_10
      value: 17.1725
    - type: map_at_100
      value: 18.108
    - type: map_at_1000
      value: 18.239833333333337
    - type: map_at_3
      value: 15.385916666666667
    - type: map_at_5
      value: 16.33808333333333
    - type: mrr_at_1
      value: 15.043583333333332
    - type: mrr_at_10
      value: 20.076749999999997
    - type: mrr_at_100
      value: 20.9225
    - type: mrr_at_1000
      value: 21.012833333333333
    - type: mrr_at_3
      value: 18.25883333333333
    - type: mrr_at_5
      value: 19.230083333333333
    - type: ndcg_at_1
      value: 15.043583333333332
    - type: ndcg_at_10
      value: 20.6305
    - type: ndcg_at_100
      value: 25.39741666666667
    - type: ndcg_at_1000
      value: 28.71625
    - type: ndcg_at_3
      value: 17.321416666666668
    - type: ndcg_at_5
      value: 18.781666666666666
    - type: precision_at_1
      value: 15.043583333333332
    - type: precision_at_10
      value: 3.8265000000000007
    - type: precision_at_100
      value: 0.7464166666666667
    - type: precision_at_1000
      value: 0.12216666666666667
    - type: precision_at_3
      value: 8.127416666666665
    - type: precision_at_5
      value: 5.986083333333333
    - type: recall_at_1
      value: 12.268416666666667
    - type: recall_at_10
      value: 28.25583333333333
    - type: recall_at_100
      value: 50.277833333333334
    - type: recall_at_1000
      value: 74.42433333333332
    - type: recall_at_3
      value: 18.861
    - type: recall_at_5
      value: 22.663416666666674
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.209
    - type: map_at_10
      value: 13.633999999999999
    - type: map_at_100
      value: 14.328
    - type: map_at_1000
      value: 14.418000000000001
    - type: map_at_3
      value: 11.828
    - type: map_at_5
      value: 12.812000000000001
    - type: mrr_at_1
      value: 11.043
    - type: mrr_at_10
      value: 15.639
    - type: mrr_at_100
      value: 16.349
    - type: mrr_at_1000
      value: 16.426
    - type: mrr_at_3
      value: 13.88
    - type: mrr_at_5
      value: 14.838999999999999
    - type: ndcg_at_1
      value: 11.043
    - type: ndcg_at_10
      value: 16.738
    - type: ndcg_at_100
      value: 20.541
    - type: ndcg_at_1000
      value: 23.237
    - type: ndcg_at_3
      value: 13.261999999999999
    - type: ndcg_at_5
      value: 14.89
    - type: precision_at_1
      value: 11.043
    - type: precision_at_10
      value: 3.052
    - type: precision_at_100
      value: 0.549
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.135
    - type: precision_at_5
      value: 4.693
    - type: recall_at_1
      value: 9.209
    - type: recall_at_10
      value: 24.581
    - type: recall_at_100
      value: 42.473
    - type: recall_at_1000
      value: 63.19200000000001
    - type: recall_at_3
      value: 14.901
    - type: recall_at_5
      value: 19.067
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.831
    - type: map_at_10
      value: 9.002
    - type: map_at_100
      value: 9.646
    - type: map_at_1000
      value: 9.769
    - type: map_at_3
      value: 7.949000000000001
    - type: map_at_5
      value: 8.484
    - type: mrr_at_1
      value: 7.811
    - type: mrr_at_10
      value: 11.218
    - type: mrr_at_100
      value: 11.902
    - type: mrr_at_1000
      value: 12.005
    - type: mrr_at_3
      value: 10.077
    - type: mrr_at_5
      value: 10.652000000000001
    - type: ndcg_at_1
      value: 7.811
    - type: ndcg_at_10
      value: 11.342
    - type: ndcg_at_100
      value: 15.045
    - type: ndcg_at_1000
      value: 18.703
    - type: ndcg_at_3
      value: 9.293
    - type: ndcg_at_5
      value: 10.126
    - type: precision_at_1
      value: 7.811
    - type: precision_at_10
      value: 2.213
    - type: precision_at_100
      value: 0.501
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 4.565
    - type: precision_at_5
      value: 3.4070000000000005
    - type: recall_at_1
      value: 5.831
    - type: recall_at_10
      value: 16.456
    - type: recall_at_100
      value: 33.985
    - type: recall_at_1000
      value: 61.44500000000001
    - type: recall_at_3
      value: 10.578
    - type: recall_at_5
      value: 12.720999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.285
    - type: map_at_10
      value: 15.156
    - type: map_at_100
      value: 16.067999999999998
    - type: map_at_1000
      value: 16.189999999999998
    - type: map_at_3
      value: 13.806
    - type: map_at_5
      value: 14.471
    - type: mrr_at_1
      value: 13.899000000000001
    - type: mrr_at_10
      value: 18.291
    - type: mrr_at_100
      value: 19.141
    - type: mrr_at_1000
      value: 19.239
    - type: mrr_at_3
      value: 16.822
    - type: mrr_at_5
      value: 17.488999999999997
    - type: ndcg_at_1
      value: 13.899000000000001
    - type: ndcg_at_10
      value: 18.142
    - type: ndcg_at_100
      value: 23.116
    - type: ndcg_at_1000
      value: 26.406000000000002
    - type: ndcg_at_3
      value: 15.519
    - type: ndcg_at_5
      value: 16.502
    - type: precision_at_1
      value: 13.899000000000001
    - type: precision_at_10
      value: 3.125
    - type: precision_at_100
      value: 0.633
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 7.152
    - type: precision_at_5
      value: 4.981
    - type: recall_at_1
      value: 11.285
    - type: recall_at_10
      value: 24.481
    - type: recall_at_100
      value: 47.82
    - type: recall_at_1000
      value: 71.873
    - type: recall_at_3
      value: 16.954
    - type: recall_at_5
      value: 19.625999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.497
    - type: map_at_10
      value: 17.415
    - type: map_at_100
      value: 18.551000000000002
    - type: map_at_1000
      value: 18.759
    - type: map_at_3
      value: 15.648000000000001
    - type: map_at_5
      value: 16.685
    - type: mrr_at_1
      value: 15.809999999999999
    - type: mrr_at_10
      value: 20.74
    - type: mrr_at_100
      value: 21.657
    - type: mrr_at_1000
      value: 21.764
    - type: mrr_at_3
      value: 18.972
    - type: mrr_at_5
      value: 20.01
    - type: ndcg_at_1
      value: 15.809999999999999
    - type: ndcg_at_10
      value: 21.061
    - type: ndcg_at_100
      value: 26.150000000000002
    - type: ndcg_at_1000
      value: 30.381000000000004
    - type: ndcg_at_3
      value: 18.167
    - type: ndcg_at_5
      value: 19.599
    - type: precision_at_1
      value: 15.809999999999999
    - type: precision_at_10
      value: 4.289
    - type: precision_at_100
      value: 0.996
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 8.959
    - type: precision_at_5
      value: 6.68
    - type: recall_at_1
      value: 12.497
    - type: recall_at_10
      value: 27.615000000000002
    - type: recall_at_100
      value: 52.063
    - type: recall_at_1000
      value: 81.321
    - type: recall_at_3
      value: 18.648
    - type: recall_at_5
      value: 22.808
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.534
    - type: map_at_10
      value: 12.36
    - type: map_at_100
      value: 13.142000000000001
    - type: map_at_1000
      value: 13.267000000000001
    - type: map_at_3
      value: 10.816
    - type: map_at_5
      value: 11.838
    - type: mrr_at_1
      value: 9.427000000000001
    - type: mrr_at_10
      value: 13.542000000000002
    - type: mrr_at_100
      value: 14.316
    - type: mrr_at_1000
      value: 14.421999999999999
    - type: mrr_at_3
      value: 11.860999999999999
    - type: mrr_at_5
      value: 12.961
    - type: ndcg_at_1
      value: 9.427000000000001
    - type: ndcg_at_10
      value: 14.985999999999999
    - type: ndcg_at_100
      value: 19.399
    - type: ndcg_at_1000
      value: 23.044
    - type: ndcg_at_3
      value: 11.805
    - type: ndcg_at_5
      value: 13.655000000000001
    - type: precision_at_1
      value: 9.427000000000001
    - type: precision_at_10
      value: 2.514
    - type: precision_at_100
      value: 0.519
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 5.114
    - type: precision_at_5
      value: 4.067
    - type: recall_at_1
      value: 8.534
    - type: recall_at_10
      value: 22.07
    - type: recall_at_100
      value: 43.299
    - type: recall_at_1000
      value: 71.482
    - type: recall_at_3
      value: 13.623
    - type: recall_at_5
      value: 18.035
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.146999999999999
    - type: map_at_10
      value: 11.126
    - type: map_at_100
      value: 12.579
    - type: map_at_1000
      value: 12.791
    - type: map_at_3
      value: 9.035
    - type: map_at_5
      value: 10.111
    - type: mrr_at_1
      value: 13.941
    - type: mrr_at_10
      value: 22.84
    - type: mrr_at_100
      value: 24.03
    - type: mrr_at_1000
      value: 24.093999999999998
    - type: mrr_at_3
      value: 19.695999999999998
    - type: mrr_at_5
      value: 21.455
    - type: ndcg_at_1
      value: 13.941
    - type: ndcg_at_10
      value: 16.864
    - type: ndcg_at_100
      value: 23.701
    - type: ndcg_at_1000
      value: 27.817999999999998
    - type: ndcg_at_3
      value: 12.888
    - type: ndcg_at_5
      value: 14.359
    - type: precision_at_1
      value: 13.941
    - type: precision_at_10
      value: 5.6419999999999995
    - type: precision_at_100
      value: 1.298
    - type: precision_at_1000
      value: 0.20400000000000001
    - type: precision_at_3
      value: 10.011000000000001
    - type: precision_at_5
      value: 8.065
    - type: recall_at_1
      value: 6.146999999999999
    - type: recall_at_10
      value: 21.701
    - type: recall_at_100
      value: 46.117000000000004
    - type: recall_at_1000
      value: 69.64
    - type: recall_at_3
      value: 12.052999999999999
    - type: recall_at_5
      value: 15.956999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.2620000000000005
    - type: map_at_10
      value: 7.564
    - type: map_at_100
      value: 10.668999999999999
    - type: map_at_1000
      value: 11.533999999999999
    - type: map_at_3
      value: 5.322
    - type: map_at_5
      value: 6.135
    - type: mrr_at_1
      value: 36.5
    - type: mrr_at_10
      value: 45.622
    - type: mrr_at_100
      value: 46.312999999999995
    - type: mrr_at_1000
      value: 46.342
    - type: mrr_at_3
      value: 42.458
    - type: mrr_at_5
      value: 43.796
    - type: ndcg_at_1
      value: 26.125
    - type: ndcg_at_10
      value: 20.279
    - type: ndcg_at_100
      value: 23.253
    - type: ndcg_at_1000
      value: 29.804000000000002
    - type: ndcg_at_3
      value: 21.688
    - type: ndcg_at_5
      value: 20.203
    - type: precision_at_1
      value: 36.5
    - type: precision_at_10
      value: 18.45
    - type: precision_at_100
      value: 5.997
    - type: precision_at_1000
      value: 1.309
    - type: precision_at_3
      value: 26.25
    - type: precision_at_5
      value: 21.95
    - type: recall_at_1
      value: 3.2620000000000005
    - type: recall_at_10
      value: 12.374
    - type: recall_at_100
      value: 30.087000000000003
    - type: recall_at_1000
      value: 52.72599999999999
    - type: recall_at_3
      value: 6.393
    - type: recall_at_5
      value: 8.013
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.93000000000001
    - type: f1
      value: 40.84475902511729
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.41
    - type: map_at_10
      value: 18.831999999999997
    - type: map_at_100
      value: 19.747
    - type: map_at_1000
      value: 19.832
    - type: map_at_3
      value: 16.712
    - type: map_at_5
      value: 17.876
    - type: mrr_at_1
      value: 13.141
    - type: mrr_at_10
      value: 19.917
    - type: mrr_at_100
      value: 20.846999999999998
    - type: mrr_at_1000
      value: 20.924
    - type: mrr_at_3
      value: 17.737
    - type: mrr_at_5
      value: 18.948
    - type: ndcg_at_1
      value: 13.141
    - type: ndcg_at_10
      value: 22.787
    - type: ndcg_at_100
      value: 27.505000000000003
    - type: ndcg_at_1000
      value: 29.904999999999998
    - type: ndcg_at_3
      value: 18.41
    - type: ndcg_at_5
      value: 20.508000000000003
    - type: precision_at_1
      value: 13.141
    - type: precision_at_10
      value: 3.6929999999999996
    - type: precision_at_100
      value: 0.624
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 7.991
    - type: precision_at_5
      value: 5.869
    - type: recall_at_1
      value: 12.41
    - type: recall_at_10
      value: 34.211999999999996
    - type: recall_at_100
      value: 56.301
    - type: recall_at_1000
      value: 74.936
    - type: recall_at_3
      value: 22.283
    - type: recall_at_5
      value: 27.342
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.861000000000001
    - type: map_at_10
      value: 9.26
    - type: map_at_100
      value: 10.441
    - type: map_at_1000
      value: 10.642
    - type: map_at_3
      value: 8.008
    - type: map_at_5
      value: 8.674999999999999
    - type: mrr_at_1
      value: 11.574
    - type: mrr_at_10
      value: 16.729
    - type: mrr_at_100
      value: 17.842
    - type: mrr_at_1000
      value: 17.949
    - type: mrr_at_3
      value: 15.072
    - type: mrr_at_5
      value: 16.106
    - type: ndcg_at_1
      value: 11.574
    - type: ndcg_at_10
      value: 12.805
    - type: ndcg_at_100
      value: 18.877
    - type: ndcg_at_1000
      value: 23.662
    - type: ndcg_at_3
      value: 10.992
    - type: ndcg_at_5
      value: 11.677
    - type: precision_at_1
      value: 11.574
    - type: precision_at_10
      value: 3.673
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 7.407
    - type: precision_at_5
      value: 5.679
    - type: recall_at_1
      value: 5.861000000000001
    - type: recall_at_10
      value: 15.911
    - type: recall_at_100
      value: 40.158
    - type: recall_at_1000
      value: 70.295
    - type: recall_at_3
      value: 10.142
    - type: recall_at_5
      value: 12.509999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.794999999999998
    - type: map_at_10
      value: 19.573999999999998
    - type: map_at_100
      value: 20.363
    - type: map_at_1000
      value: 20.469
    - type: map_at_3
      value: 17.862000000000002
    - type: map_at_5
      value: 18.849
    - type: mrr_at_1
      value: 27.589000000000002
    - type: mrr_at_10
      value: 33.997
    - type: mrr_at_100
      value: 34.747
    - type: mrr_at_1000
      value: 34.812
    - type: mrr_at_3
      value: 32.163000000000004
    - type: mrr_at_5
      value: 33.265
    - type: ndcg_at_1
      value: 27.589000000000002
    - type: ndcg_at_10
      value: 25.413999999999998
    - type: ndcg_at_100
      value: 29.336000000000002
    - type: ndcg_at_1000
      value: 32.012
    - type: ndcg_at_3
      value: 22.093
    - type: ndcg_at_5
      value: 23.794999999999998
    - type: precision_at_1
      value: 27.589000000000002
    - type: precision_at_10
      value: 5.699
    - type: precision_at_100
      value: 0.886
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 14.027000000000001
    - type: precision_at_5
      value: 9.766
    - type: recall_at_1
      value: 13.794999999999998
    - type: recall_at_10
      value: 28.494000000000003
    - type: recall_at_100
      value: 44.308
    - type: recall_at_1000
      value: 62.22800000000001
    - type: recall_at_3
      value: 21.04
    - type: recall_at_5
      value: 24.416
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.60480000000001
    - type: ap
      value: 59.727131414185166
    - type: f1
      value: 64.1072904179992
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.826
    - type: map_at_10
      value: 9.851
    - type: map_at_100
      value: 10.697
    - type: map_at_1000
      value: 10.803
    - type: map_at_3
      value: 8.238
    - type: map_at_5
      value: 9.104
    - type: mrr_at_1
      value: 6.046
    - type: mrr_at_10
      value: 10.134
    - type: mrr_at_100
      value: 10.987
    - type: mrr_at_1000
      value: 11.091
    - type: mrr_at_3
      value: 8.508000000000001
    - type: mrr_at_5
      value: 9.371
    - type: ndcg_at_1
      value: 6.046
    - type: ndcg_at_10
      value: 12.536
    - type: ndcg_at_100
      value: 17.187
    - type: ndcg_at_1000
      value: 20.371
    - type: ndcg_at_3
      value: 9.164
    - type: ndcg_at_5
      value: 10.725999999999999
    - type: precision_at_1
      value: 6.046
    - type: precision_at_10
      value: 2.175
    - type: precision_at_100
      value: 0.45799999999999996
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 4.016
    - type: precision_at_5
      value: 3.206
    - type: recall_at_1
      value: 5.826
    - type: recall_at_10
      value: 20.926000000000002
    - type: recall_at_100
      value: 43.669000000000004
    - type: recall_at_1000
      value: 69.247
    - type: recall_at_3
      value: 11.609
    - type: recall_at_5
      value: 15.376999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.16689466484269
    - type: f1
      value: 87.5981029414324
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 55.33515731874146
    - type: f1
      value: 37.77464057733795
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.044384667115004
    - type: f1
      value: 60.29405543040358
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.21721587088096
    - type: f1
      value: 69.8224169927227
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.09923884257758
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.58464252003336
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.685278831397703
    - type: mrr
      value: 30.52917269137772
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.274
    - type: map_at_10
      value: 7.764
    - type: map_at_100
      value: 10.043000000000001
    - type: map_at_1000
      value: 11.394
    - type: map_at_3
      value: 5.887
    - type: map_at_5
      value: 6.761
    - type: mrr_at_1
      value: 33.745999999999995
    - type: mrr_at_10
      value: 42.836
    - type: mrr_at_100
      value: 43.701
    - type: mrr_at_1000
      value: 43.749
    - type: mrr_at_3
      value: 40.248
    - type: mrr_at_5
      value: 41.78
    - type: ndcg_at_1
      value: 31.734
    - type: ndcg_at_10
      value: 24.268
    - type: ndcg_at_100
      value: 23.801
    - type: ndcg_at_1000
      value: 33.347
    - type: ndcg_at_3
      value: 27.394000000000002
    - type: ndcg_at_5
      value: 26.312
    - type: precision_at_1
      value: 33.745999999999995
    - type: precision_at_10
      value: 17.802
    - type: precision_at_100
      value: 6.616
    - type: precision_at_1000
      value: 2.008
    - type: precision_at_3
      value: 25.8
    - type: precision_at_5
      value: 22.972
    - type: recall_at_1
      value: 4.274
    - type: recall_at_10
      value: 12.012
    - type: recall_at_100
      value: 26.706999999999997
    - type: recall_at_1000
      value: 60.634
    - type: recall_at_3
      value: 6.61
    - type: recall_at_5
      value: 8.545
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.519
    - type: map_at_10
      value: 14.407
    - type: map_at_100
      value: 15.607
    - type: map_at_1000
      value: 15.705
    - type: map_at_3
      value: 12.241
    - type: map_at_5
      value: 13.291
    - type: mrr_at_1
      value: 9.676
    - type: mrr_at_10
      value: 16.025
    - type: mrr_at_100
      value: 17.151
    - type: mrr_at_1000
      value: 17.233
    - type: mrr_at_3
      value: 13.783999999999999
    - type: mrr_at_5
      value: 14.875
    - type: ndcg_at_1
      value: 9.676
    - type: ndcg_at_10
      value: 18.439
    - type: ndcg_at_100
      value: 24.375
    - type: ndcg_at_1000
      value: 27.111
    - type: ndcg_at_3
      value: 13.862
    - type: ndcg_at_5
      value: 15.747
    - type: precision_at_1
      value: 9.676
    - type: precision_at_10
      value: 3.473
    - type: precision_at_100
      value: 0.681
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 6.615
    - type: precision_at_5
      value: 5.017
    - type: recall_at_1
      value: 8.519
    - type: recall_at_10
      value: 29.442
    - type: recall_at_100
      value: 56.704
    - type: recall_at_1000
      value: 77.827
    - type: recall_at_3
      value: 17.055
    - type: recall_at_5
      value: 21.454
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.114000000000004
    - type: map_at_10
      value: 75.723
    - type: map_at_100
      value: 76.50099999999999
    - type: map_at_1000
      value: 76.536
    - type: map_at_3
      value: 72.80499999999999
    - type: map_at_5
      value: 74.512
    - type: mrr_at_1
      value: 72.59
    - type: mrr_at_10
      value: 79.794
    - type: mrr_at_100
      value: 80.05499999999999
    - type: mrr_at_1000
      value: 80.061
    - type: mrr_at_3
      value: 78.333
    - type: mrr_at_5
      value: 79.244
    - type: ndcg_at_1
      value: 72.66
    - type: ndcg_at_10
      value: 80.306
    - type: ndcg_at_100
      value: 82.439
    - type: ndcg_at_1000
      value: 82.826
    - type: ndcg_at_3
      value: 76.72099999999999
    - type: ndcg_at_5
      value: 78.482
    - type: precision_at_1
      value: 72.66
    - type: precision_at_10
      value: 12.169
    - type: precision_at_100
      value: 1.4529999999999998
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 33.267
    - type: precision_at_5
      value: 21.954
    - type: recall_at_1
      value: 63.114000000000004
    - type: recall_at_10
      value: 89.17699999999999
    - type: recall_at_100
      value: 97.208
    - type: recall_at_1000
      value: 99.39
    - type: recall_at_3
      value: 78.949
    - type: recall_at_5
      value: 83.848
    - type: map_at_1
      value: 2.6229999999999998
    - type: map_at_10
      value: 6.6290000000000004
    - type: map_at_100
      value: 8.052
    - type: map_at_1000
      value: 8.322000000000001
    - type: map_at_3
      value: 4.749
    - type: map_at_5
      value: 5.649
    - type: mrr_at_1
      value: 12.9
    - type: mrr_at_10
      value: 21.098
    - type: mrr_at_100
      value: 22.301000000000002
    - type: mrr_at_1000
      value: 22.391
    - type: mrr_at_3
      value: 18.099999999999998
    - type: mrr_at_5
      value: 19.615
    - type: ndcg_at_1
      value: 12.9
    - type: ndcg_at_10
      value: 12.031
    - type: ndcg_at_100
      value: 18.526
    - type: ndcg_at_1000
      value: 23.993000000000002
    - type: ndcg_at_3
      value: 10.894
    - type: ndcg_at_5
      value: 9.638
    - type: precision_at_1
      value: 12.9
    - type: precision_at_10
      value: 6.460000000000001
    - type: precision_at_100
      value: 1.598
    - type: precision_at_1000
      value: 0.292
    - type: precision_at_3
      value: 10.233
    - type: precision_at_5
      value: 8.559999999999999
    - type: recall_at_1
      value: 2.6229999999999998
    - type: recall_at_10
      value: 13.111999999999998
    - type: recall_at_100
      value: 32.418
    - type: recall_at_1000
      value: 59.24700000000001
    - type: recall_at_3
      value: 6.2330000000000005
    - type: recall_at_5
      value: 8.673
    - type: map_at_1
      value: 0.152
    - type: map_at_10
      value: 1.0370000000000001
    - type: map_at_100
      value: 5.169
    - type: map_at_1000
      value: 11.804
    - type: map_at_3
      value: 0.367
    - type: map_at_5
      value: 0.557
    - type: mrr_at_1
      value: 62.0
    - type: mrr_at_10
      value: 72.786
    - type: mrr_at_100
      value: 73.009
    - type: mrr_at_1000
      value: 73.009
    - type: mrr_at_3
      value: 69.0
    - type: mrr_at_5
      value: 72.0
    - type: ndcg_at_1
      value: 56.99999999999999
    - type: ndcg_at_10
      value: 52.013
    - type: ndcg_at_100
      value: 36.669000000000004
    - type: ndcg_at_1000
      value: 31.721
    - type: ndcg_at_3
      value: 53.52
    - type: ndcg_at_5
      value: 52.54600000000001
    - type: precision_at_1
      value: 64.0
    - type: precision_at_10
      value: 57.4
    - type: precision_at_100
      value: 38.14
    - type: precision_at_1000
      value: 14.996
    - type: precision_at_3
      value: 58.667
    - type: precision_at_5
      value: 57.599999999999994
    - type: recall_at_1
      value: 0.152
    - type: recall_at_10
      value: 1.352
    - type: recall_at_100
      value: 8.392
    - type: recall_at_1000
      value: 30.470000000000002
    - type: recall_at_3
      value: 0.409
    - type: recall_at_5
      value: 0.661
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 36.72406468585852
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 43.472169436837376
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 77.29221538383013
    - type: cos_sim_spearman
      value: 65.00237260316423
    - type: euclidean_pearson
      value: 71.97594877548565
    - type: euclidean_spearman
      value: 65.00224511756271
    - type: manhattan_pearson
      value: 70.69044074330846
    - type: manhattan_spearman
      value: 64.56188226107231
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.15455031153215
    - type: cos_sim_spearman
      value: 68.87516936019733
    - type: euclidean_pearson
      value: 74.40173366578063
    - type: euclidean_spearman
      value: 68.87649875376111
    - type: manhattan_pearson
      value: 71.37948083917088
    - type: manhattan_spearman
      value: 66.87593196817534
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.85372381398427
    - type: cos_sim_spearman
      value: 78.70991572075931
    - type: euclidean_pearson
      value: 78.02059239423504
    - type: euclidean_spearman
      value: 78.70995352760224
    - type: manhattan_pearson
      value: 77.29573198105021
    - type: manhattan_spearman
      value: 77.83698304986561
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 75.62945293081356
    - type: cos_sim_spearman
      value: 72.21402271266491
    - type: euclidean_pearson
      value: 74.8632992511187
    - type: euclidean_spearman
      value: 72.21401302442116
    - type: manhattan_pearson
      value: 74.12692290251161
    - type: manhattan_spearman
      value: 71.68132558277071
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 78.39263075496403
    - type: cos_sim_spearman
      value: 80.29205232773359
    - type: euclidean_pearson
      value: 79.98077838577872
    - type: euclidean_spearman
      value: 80.29205083786974
    - type: manhattan_pearson
      value: 79.40585067880913
    - type: manhattan_spearman
      value: 79.76402780723464
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 67.87975357523919
    - type: cos_sim_spearman
      value: 71.32759045416529
    - type: euclidean_pearson
      value: 71.38828468907693
    - type: euclidean_spearman
      value: 71.32841999853918
    - type: manhattan_pearson
      value: 71.52115254680312
    - type: manhattan_spearman
      value: 71.36502371568079
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 79.73783641527713
    - type: cos_sim_spearman
      value: 80.83877209500405
    - type: euclidean_pearson
      value: 80.9815305740776
    - type: euclidean_spearman
      value: 80.8396480829947
    - type: manhattan_pearson
      value: 80.20252699531369
    - type: manhattan_spearman
      value: 80.06981696234901
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 47.00304169592553
    - type: cos_sim_spearman
      value: 56.38544150292195
    - type: euclidean_pearson
      value: 53.01919280358667
    - type: euclidean_spearman
      value: 56.38544150292195
    - type: manhattan_pearson
      value: 51.65539290367504
    - type: manhattan_spearman
      value: 55.124846472764
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 71.91396118730897
    - type: cos_sim_spearman
      value: 70.00936285125462
    - type: euclidean_pearson
      value: 72.92234042209962
    - type: euclidean_spearman
      value: 70.00938132595871
    - type: manhattan_pearson
      value: 72.83606277528781
    - type: manhattan_spearman
      value: 70.11738672765205
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 74.41530407041719
    - type: mrr
      value: 91.4664184762224
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 31.667
    - type: map_at_10
      value: 40.327
    - type: map_at_100
      value: 41.29
    - type: map_at_1000
      value: 41.374
    - type: map_at_3
      value: 37.824000000000005
    - type: map_at_5
      value: 39.455
    - type: mrr_at_1
      value: 33.333
    - type: mrr_at_10
      value: 41.650999999999996
    - type: mrr_at_100
      value: 42.516
    - type: mrr_at_1000
      value: 42.586
    - type: mrr_at_3
      value: 39.333
    - type: mrr_at_5
      value: 40.967
    - type: ndcg_at_1
      value: 33.333
    - type: ndcg_at_10
      value: 44.955
    - type: ndcg_at_100
      value: 50.176
    - type: ndcg_at_1000
      value: 52.18000000000001
    - type: ndcg_at_3
      value: 40.233999999999995
    - type: ndcg_at_5
      value: 43.04
    - type: precision_at_1
      value: 33.333
    - type: precision_at_10
      value: 6.367000000000001
    - type: precision_at_100
      value: 0.9369999999999999
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 16.111
    - type: precision_at_5
      value: 11.267000000000001
    - type: recall_at_1
      value: 31.667
    - type: recall_at_10
      value: 57.778
    - type: recall_at_100
      value: 82.989
    - type: recall_at_1000
      value: 98.26700000000001
    - type: recall_at_3
      value: 45.639
    - type: recall_at_5
      value: 52.278000000000006
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.67029702970297
    - type: cos_sim_ap
      value: 89.07129165961199
    - type: cos_sim_f1
      value: 82.57537046499746
    - type: cos_sim_precision
      value: 84.43051201671892
    - type: cos_sim_recall
      value: 80.80000000000001
    - type: dot_accuracy
      value: 99.67029702970297
    - type: dot_ap
      value: 89.07129165961199
    - type: dot_f1
      value: 82.57537046499746
    - type: dot_precision
      value: 84.43051201671892
    - type: dot_recall
      value: 80.80000000000001
    - type: euclidean_accuracy
      value: 99.67029702970297
    - type: euclidean_ap
      value: 89.07129165961199
    - type: euclidean_f1
      value: 82.57537046499746
    - type: euclidean_precision
      value: 84.43051201671892
    - type: euclidean_recall
      value: 80.80000000000001
    - type: manhattan_accuracy
      value: 99.65643564356435
    - type: manhattan_ap
      value: 88.41137288354716
    - type: manhattan_f1
      value: 81.70347003154575
    - type: manhattan_precision
      value: 86.14190687361419
    - type: manhattan_recall
      value: 77.7
    - type: max_accuracy
      value: 99.67029702970297
    - type: max_ap
      value: 89.07129165961199
    - type: max_f1
      value: 82.57537046499746
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 41.60638325431974
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.664294828405303
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.25132223734513
    - type: mrr
      value: 42.64716492657669
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.69873203329748
    - type: cos_sim_spearman
      value: 30.504626278665437
    - type: dot_pearson
      value: 30.69873212465138
    - type: dot_spearman
      value: 30.576343071933813
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.165
    - type: map_at_10
      value: 4.088
    - type: map_at_100
      value: 7.378
    - type: map_at_1000
      value: 8.958
    - type: map_at_3
      value: 2.254
    - type: map_at_5
      value: 3.524
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 30.646
    - type: mrr_at_100
      value: 32.625
    - type: mrr_at_1000
      value: 32.661
    - type: mrr_at_3
      value: 26.871000000000002
    - type: mrr_at_5
      value: 30.238
    - type: ndcg_at_1
      value: 18.367
    - type: ndcg_at_10
      value: 13.061
    - type: ndcg_at_100
      value: 23.47
    - type: ndcg_at_1000
      value: 37.61
    - type: ndcg_at_3
      value: 15.546
    - type: ndcg_at_5
      value: 16.355
    - type: precision_at_1
      value: 18.367
    - type: precision_at_10
      value: 11.429
    - type: precision_at_100
      value: 5.653
    - type: precision_at_1000
      value: 1.451
    - type: precision_at_3
      value: 15.645999999999999
    - type: precision_at_5
      value: 17.551
    - type: recall_at_1
      value: 1.165
    - type: recall_at_10
      value: 8.018
    - type: recall_at_100
      value: 35.23
    - type: recall_at_1000
      value: 79.57600000000001
    - type: recall_at_3
      value: 3.076
    - type: recall_at_5
      value: 6.242
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.9568
    - type: ap
      value: 13.253846581305634
    - type: f1
      value: 54.324508660685645
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.39049235993209
    - type: f1
      value: 55.53656453466803
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.252056863048416
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.41640340942958
    - type: cos_sim_ap
      value: 61.46818116365959
    - type: cos_sim_f1
      value: 59.05859279235107
    - type: cos_sim_precision
      value: 55.151098901098905
    - type: cos_sim_recall
      value: 63.562005277044854
    - type: dot_accuracy
      value: 82.41640340942958
    - type: dot_ap
      value: 61.46818116365959
    - type: dot_f1
      value: 59.05859279235107
    - type: dot_precision
      value: 55.151098901098905
    - type: dot_recall
      value: 63.562005277044854
    - type: euclidean_accuracy
      value: 82.41640340942958
    - type: euclidean_ap
      value: 61.46818116365959
    - type: euclidean_f1
      value: 59.05859279235107
    - type: euclidean_precision
      value: 55.151098901098905
    - type: euclidean_recall
      value: 63.562005277044854
    - type: manhattan_accuracy
      value: 82.80979912976099
    - type: manhattan_ap
      value: 62.57319706784323
    - type: manhattan_f1
      value: 59.7376886909181
    - type: manhattan_precision
      value: 56.24417520969245
    - type: manhattan_recall
      value: 63.69393139841689
    - type: max_accuracy
      value: 82.80979912976099
    - type: max_ap
      value: 62.57319706784323
    - type: max_f1
      value: 59.7376886909181
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.4012108510886
    - type: cos_sim_ap
      value: 80.82375141067818
    - type: cos_sim_f1
      value: 72.80055190443339
    - type: cos_sim_precision
      value: 68.88614031471174
    - type: cos_sim_recall
      value: 77.18663381582999
    - type: dot_accuracy
      value: 86.4012108510886
    - type: dot_ap
      value: 80.82375193841179
    - type: dot_f1
      value: 72.80055190443339
    - type: dot_precision
      value: 68.88614031471174
    - type: dot_recall
      value: 77.18663381582999
    - type: euclidean_accuracy
      value: 86.4012108510886
    - type: euclidean_ap
      value: 80.82375158687223
    - type: euclidean_f1
      value: 72.80055190443339
    - type: euclidean_precision
      value: 68.88614031471174
    - type: euclidean_recall
      value: 77.18663381582999
    - type: manhattan_accuracy
      value: 86.5700314355571
    - type: manhattan_ap
      value: 81.24256901305888
    - type: manhattan_f1
      value: 73.30839356408673
    - type: manhattan_precision
      value: 69.38466827088347
    - type: manhattan_recall
      value: 77.70249461040962
    - type: max_accuracy
      value: 86.5700314355571
    - type: max_ap
      value: 81.24256901305888
    - type: max_f1
      value: 73.30839356408673
---
