mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_307_w30k_b10k
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.955223880597
    - type: ap
      value: 34.13197114646943
    - type: f1
      value: 65.68946854348061
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.32617499999999
    - type: ap
      value: 59.490845212236245
    - type: f1
      value: 64.1040492114687
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.838
    - type: f1
      value: 33.407172447103896
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.128
    - type: map_at_10
      value: 34.056
    - type: map_at_100
      value: 35.238
    - type: map_at_1000
      value: 35.266999999999996
    - type: map_at_3
      value: 29.457
    - type: map_at_5
      value: 32.11
    - type: mrr_at_1
      value: 20.483999999999998
    - type: mrr_at_10
      value: 34.186
    - type: mrr_at_100
      value: 35.388
    - type: mrr_at_1000
      value: 35.416
    - type: mrr_at_3
      value: 29.576
    - type: mrr_at_5
      value: 32.236
    - type: ndcg_at_1
      value: 20.128
    - type: ndcg_at_10
      value: 42.05
    - type: ndcg_at_100
      value: 47.661
    - type: ndcg_at_1000
      value: 48.339999999999996
    - type: ndcg_at_3
      value: 32.555
    - type: ndcg_at_5
      value: 37.348
    - type: precision_at_1
      value: 20.128
    - type: precision_at_10
      value: 6.771000000000001
    - type: precision_at_100
      value: 0.936
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.844999999999999
    - type: precision_at_5
      value: 10.639999999999999
    - type: recall_at_1
      value: 20.128
    - type: recall_at_10
      value: 67.71000000000001
    - type: recall_at_100
      value: 93.599
    - type: recall_at_1000
      value: 98.791
    - type: recall_at_3
      value: 41.536
    - type: recall_at_5
      value: 53.201
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 30.332603841310025
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 20.867624126885154
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.71119008857963
    - type: mrr
      value: 66.35789033988479
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 78.18517708213652
    - type: cos_sim_spearman
      value: 77.68068566977038
    - type: euclidean_pearson
      value: 77.54287673443481
    - type: euclidean_spearman
      value: 77.68068566977038
    - type: manhattan_pearson
      value: 77.11580342725216
    - type: manhattan_spearman
      value: 76.84632930899711
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 71.8603896103896
    - type: f1
      value: 71.02556795780878
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 28.30104672592466
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 18.177382002944345
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.352999999999998
    - type: map_at_10
      value: 27.258
    - type: map_at_100
      value: 28.396
    - type: map_at_1000
      value: 28.554000000000002
    - type: map_at_3
      value: 25.013999999999996
    - type: map_at_5
      value: 26.384999999999998
    - type: mrr_at_1
      value: 25.894000000000002
    - type: mrr_at_10
      value: 32.863
    - type: mrr_at_100
      value: 33.809
    - type: mrr_at_1000
      value: 33.886
    - type: mrr_at_3
      value: 31.020999999999997
    - type: mrr_at_5
      value: 32.129000000000005
    - type: ndcg_at_1
      value: 25.894000000000002
    - type: ndcg_at_10
      value: 31.830000000000002
    - type: ndcg_at_100
      value: 36.895
    - type: ndcg_at_1000
      value: 40.233000000000004
    - type: ndcg_at_3
      value: 28.764
    - type: ndcg_at_5
      value: 30.267
    - type: precision_at_1
      value: 25.894000000000002
    - type: precision_at_10
      value: 6.094
    - type: precision_at_100
      value: 1.072
    - type: precision_at_1000
      value: 0.167
    - type: precision_at_3
      value: 13.828999999999999
    - type: precision_at_5
      value: 10.157
    - type: recall_at_1
      value: 20.352999999999998
    - type: recall_at_10
      value: 39.318999999999996
    - type: recall_at_100
      value: 61.989000000000004
    - type: recall_at_1000
      value: 84.74199999999999
    - type: recall_at_3
      value: 29.673
    - type: recall_at_5
      value: 34.136
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.134
    - type: map_at_10
      value: 21.423000000000002
    - type: map_at_100
      value: 22.326999999999998
    - type: map_at_1000
      value: 22.451999999999998
    - type: map_at_3
      value: 19.602
    - type: map_at_5
      value: 20.77
    - type: mrr_at_1
      value: 20.446
    - type: mrr_at_10
      value: 25.496999999999996
    - type: mrr_at_100
      value: 26.264
    - type: mrr_at_1000
      value: 26.339000000000002
    - type: mrr_at_3
      value: 23.662
    - type: mrr_at_5
      value: 24.752
    - type: ndcg_at_1
      value: 20.446
    - type: ndcg_at_10
      value: 24.933
    - type: ndcg_at_100
      value: 29.268
    - type: ndcg_at_1000
      value: 32.24
    - type: ndcg_at_3
      value: 21.919
    - type: ndcg_at_5
      value: 23.54
    - type: precision_at_1
      value: 20.446
    - type: precision_at_10
      value: 4.5920000000000005
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.424999999999999
    - type: precision_at_5
      value: 7.605
    - type: recall_at_1
      value: 16.134
    - type: recall_at_10
      value: 31.369000000000003
    - type: recall_at_100
      value: 50.592999999999996
    - type: recall_at_1000
      value: 71.06
    - type: recall_at_3
      value: 22.888
    - type: recall_at_5
      value: 27.189000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.673000000000002
    - type: map_at_10
      value: 32.711
    - type: map_at_100
      value: 33.711
    - type: map_at_1000
      value: 33.802
    - type: map_at_3
      value: 30.301000000000002
    - type: map_at_5
      value: 31.499
    - type: mrr_at_1
      value: 28.589
    - type: mrr_at_10
      value: 35.812
    - type: mrr_at_100
      value: 36.63
    - type: mrr_at_1000
      value: 36.687999999999995
    - type: mrr_at_3
      value: 33.532000000000004
    - type: mrr_at_5
      value: 34.682
    - type: ndcg_at_1
      value: 28.589
    - type: ndcg_at_10
      value: 37.4
    - type: ndcg_at_100
      value: 42.363
    - type: ndcg_at_1000
      value: 44.525999999999996
    - type: ndcg_at_3
      value: 32.768
    - type: ndcg_at_5
      value: 34.683
    - type: precision_at_1
      value: 28.589
    - type: precision_at_10
      value: 6.144
    - type: precision_at_100
      value: 0.9530000000000001
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 14.524999999999999
    - type: precision_at_5
      value: 10.006
    - type: recall_at_1
      value: 24.673000000000002
    - type: recall_at_10
      value: 48.711
    - type: recall_at_100
      value: 71.481
    - type: recall_at_1000
      value: 87.307
    - type: recall_at_3
      value: 36.04
    - type: recall_at_5
      value: 40.851
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.245
    - type: map_at_10
      value: 14.524000000000001
    - type: map_at_100
      value: 15.315000000000001
    - type: map_at_1000
      value: 15.418999999999999
    - type: map_at_3
      value: 13.255
    - type: map_at_5
      value: 13.898
    - type: mrr_at_1
      value: 11.411999999999999
    - type: mrr_at_10
      value: 15.681999999999999
    - type: mrr_at_100
      value: 16.497999999999998
    - type: mrr_at_1000
      value: 16.597
    - type: mrr_at_3
      value: 14.388000000000002
    - type: mrr_at_5
      value: 15.026
    - type: ndcg_at_1
      value: 11.411999999999999
    - type: ndcg_at_10
      value: 17.11
    - type: ndcg_at_100
      value: 21.426000000000002
    - type: ndcg_at_1000
      value: 24.747
    - type: ndcg_at_3
      value: 14.527999999999999
    - type: ndcg_at_5
      value: 15.626999999999999
    - type: precision_at_1
      value: 11.411999999999999
    - type: precision_at_10
      value: 2.723
    - type: precision_at_100
      value: 0.518
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.328
    - type: precision_at_5
      value: 4.3839999999999995
    - type: recall_at_1
      value: 10.245
    - type: recall_at_10
      value: 24.065
    - type: recall_at_100
      value: 44.627
    - type: recall_at_1000
      value: 70.844
    - type: recall_at_3
      value: 17.006
    - type: recall_at_5
      value: 19.661
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.197
    - type: map_at_10
      value: 9.278
    - type: map_at_100
      value: 9.916
    - type: map_at_1000
      value: 10.038
    - type: map_at_3
      value: 8.218
    - type: map_at_5
      value: 8.752
    - type: mrr_at_1
      value: 8.085
    - type: mrr_at_10
      value: 11.359
    - type: mrr_at_100
      value: 12.071
    - type: mrr_at_1000
      value: 12.174999999999999
    - type: mrr_at_3
      value: 10.158000000000001
    - type: mrr_at_5
      value: 10.73
    - type: ndcg_at_1
      value: 8.085
    - type: ndcg_at_10
      value: 11.545
    - type: ndcg_at_100
      value: 15.126999999999999
    - type: ndcg_at_1000
      value: 18.792
    - type: ndcg_at_3
      value: 9.462
    - type: ndcg_at_5
      value: 10.289
    - type: precision_at_1
      value: 8.085
    - type: precision_at_10
      value: 2.226
    - type: precision_at_100
      value: 0.47400000000000003
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 4.643
    - type: precision_at_5
      value: 3.3329999999999997
    - type: recall_at_1
      value: 6.197
    - type: recall_at_10
      value: 16.597
    - type: recall_at_100
      value: 32.922000000000004
    - type: recall_at_1000
      value: 60.171
    - type: recall_at_3
      value: 10.644
    - type: recall_at_5
      value: 12.867
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 16.543
    - type: map_at_10
      value: 22.024
    - type: map_at_100
      value: 23.169999999999998
    - type: map_at_1000
      value: 23.304
    - type: map_at_3
      value: 20.215
    - type: map_at_5
      value: 21.208
    - type: mrr_at_1
      value: 20.885
    - type: mrr_at_10
      value: 26.616
    - type: mrr_at_100
      value: 27.508
    - type: mrr_at_1000
      value: 27.589000000000002
    - type: mrr_at_3
      value: 24.607
    - type: mrr_at_5
      value: 25.81
    - type: ndcg_at_1
      value: 20.885
    - type: ndcg_at_10
      value: 25.921
    - type: ndcg_at_100
      value: 31.351000000000003
    - type: ndcg_at_1000
      value: 34.434
    - type: ndcg_at_3
      value: 22.686
    - type: ndcg_at_5
      value: 24.21
    - type: precision_at_1
      value: 20.885
    - type: precision_at_10
      value: 4.735
    - type: precision_at_100
      value: 0.906
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.555
    - type: precision_at_5
      value: 7.642
    - type: recall_at_1
      value: 16.543
    - type: recall_at_10
      value: 33.377
    - type: recall_at_100
      value: 57.043
    - type: recall_at_1000
      value: 78.497
    - type: recall_at_3
      value: 24.076
    - type: recall_at_5
      value: 28.101
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.985
    - type: map_at_10
      value: 16.586000000000002
    - type: map_at_100
      value: 17.616
    - type: map_at_1000
      value: 17.748
    - type: map_at_3
      value: 14.933
    - type: map_at_5
      value: 15.826
    - type: mrr_at_1
      value: 13.699
    - type: mrr_at_10
      value: 19.683999999999997
    - type: mrr_at_100
      value: 20.636
    - type: mrr_at_1000
      value: 20.719
    - type: mrr_at_3
      value: 17.941
    - type: mrr_at_5
      value: 18.866
    - type: ndcg_at_1
      value: 13.699
    - type: ndcg_at_10
      value: 20.057
    - type: ndcg_at_100
      value: 25.215
    - type: ndcg_at_1000
      value: 28.584
    - type: ndcg_at_3
      value: 16.989
    - type: ndcg_at_5
      value: 18.321
    - type: precision_at_1
      value: 13.699
    - type: precision_at_10
      value: 3.8580000000000005
    - type: precision_at_100
      value: 0.76
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 8.219
    - type: precision_at_5
      value: 6.027
    - type: recall_at_1
      value: 10.985
    - type: recall_at_10
      value: 27.351
    - type: recall_at_100
      value: 50.221000000000004
    - type: recall_at_1000
      value: 74.368
    - type: recall_at_3
      value: 19.177
    - type: recall_at_5
      value: 22.42
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.05425
    - type: map_at_10
      value: 18.011166666666668
    - type: map_at_100
      value: 18.863249999999997
    - type: map_at_1000
      value: 18.986499999999996
    - type: map_at_3
      value: 16.473000000000003
    - type: map_at_5
      value: 17.302666666666667
    - type: mrr_at_1
      value: 15.915333333333335
    - type: mrr_at_10
      value: 20.951083333333333
    - type: mrr_at_100
      value: 21.731333333333332
    - type: mrr_at_1000
      value: 21.818749999999998
    - type: mrr_at_3
      value: 19.372833333333332
    - type: mrr_at_5
      value: 20.232750000000003
    - type: ndcg_at_1
      value: 15.915333333333335
    - type: ndcg_at_10
      value: 21.271500000000003
    - type: ndcg_at_100
      value: 25.59883333333333
    - type: ndcg_at_1000
      value: 28.81025
    - type: ndcg_at_3
      value: 18.473500000000005
    - type: ndcg_at_5
      value: 19.711666666666666
    - type: precision_at_1
      value: 15.915333333333335
    - type: precision_at_10
      value: 3.8305
    - type: precision_at_100
      value: 0.7128333333333334
    - type: precision_at_1000
      value: 0.11674999999999999
    - type: precision_at_3
      value: 8.618166666666667
    - type: precision_at_5
      value: 6.160166666666667
    - type: recall_at_1
      value: 13.05425
    - type: recall_at_10
      value: 28.18425
    - type: recall_at_100
      value: 48.085249999999995
    - type: recall_at_1000
      value: 71.58041666666665
    - type: recall_at_3
      value: 20.2705
    - type: recall_at_5
      value: 23.499916666666664
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.724
    - type: map_at_10
      value: 13.367
    - type: map_at_100
      value: 13.987
    - type: map_at_1000
      value: 14.075
    - type: map_at_3
      value: 12.4
    - type: map_at_5
      value: 12.838
    - type: mrr_at_1
      value: 11.35
    - type: mrr_at_10
      value: 15.268
    - type: mrr_at_100
      value: 15.885
    - type: mrr_at_1000
      value: 15.969
    - type: mrr_at_3
      value: 14.238000000000001
    - type: mrr_at_5
      value: 14.691
    - type: ndcg_at_1
      value: 11.35
    - type: ndcg_at_10
      value: 15.779000000000002
    - type: ndcg_at_100
      value: 19.204
    - type: ndcg_at_1000
      value: 21.964
    - type: ndcg_at_3
      value: 13.896
    - type: ndcg_at_5
      value: 14.538
    - type: precision_at_1
      value: 11.35
    - type: precision_at_10
      value: 2.699
    - type: precision_at_100
      value: 0.486
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 6.442
    - type: precision_at_5
      value: 4.387
    - type: recall_at_1
      value: 9.724
    - type: recall_at_10
      value: 21.393
    - type: recall_at_100
      value: 37.618
    - type: recall_at_1000
      value: 59.035000000000004
    - type: recall_at_3
      value: 15.751000000000001
    - type: recall_at_5
      value: 17.544999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.026000000000001
    - type: map_at_10
      value: 10.151
    - type: map_at_100
      value: 10.699
    - type: map_at_1000
      value: 10.816
    - type: map_at_3
      value: 9.118
    - type: map_at_5
      value: 9.684
    - type: mrr_at_1
      value: 8.706
    - type: mrr_at_10
      value: 12.289
    - type: mrr_at_100
      value: 12.857
    - type: mrr_at_1000
      value: 12.956999999999999
    - type: mrr_at_3
      value: 11.126
    - type: mrr_at_5
      value: 11.808
    - type: ndcg_at_1
      value: 8.706
    - type: ndcg_at_10
      value: 12.386
    - type: ndcg_at_100
      value: 15.562000000000001
    - type: ndcg_at_1000
      value: 19.038
    - type: ndcg_at_3
      value: 10.392
    - type: ndcg_at_5
      value: 11.33
    - type: precision_at_1
      value: 8.706
    - type: precision_at_10
      value: 2.3539999999999996
    - type: precision_at_100
      value: 0.47400000000000003
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 4.967
    - type: precision_at_5
      value: 3.7159999999999997
    - type: recall_at_1
      value: 7.026000000000001
    - type: recall_at_10
      value: 17.05
    - type: recall_at_100
      value: 32.12
    - type: recall_at_1000
      value: 58.179
    - type: recall_at_3
      value: 11.62
    - type: recall_at_5
      value: 13.91
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.023
    - type: map_at_10
      value: 15.139
    - type: map_at_100
      value: 15.919
    - type: map_at_1000
      value: 16.038
    - type: map_at_3
      value: 13.794
    - type: map_at_5
      value: 14.555000000000001
    - type: mrr_at_1
      value: 13.526
    - type: mrr_at_10
      value: 17.906
    - type: mrr_at_100
      value: 18.731
    - type: mrr_at_1000
      value: 18.831
    - type: mrr_at_3
      value: 16.496
    - type: mrr_at_5
      value: 17.317
    - type: ndcg_at_1
      value: 13.526
    - type: ndcg_at_10
      value: 17.999000000000002
    - type: ndcg_at_100
      value: 22.227
    - type: ndcg_at_1000
      value: 25.708
    - type: ndcg_at_3
      value: 15.421999999999999
    - type: ndcg_at_5
      value: 16.646
    - type: precision_at_1
      value: 13.526
    - type: precision_at_10
      value: 3.106
    - type: precision_at_100
      value: 0.5720000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 7.1209999999999996
    - type: precision_at_5
      value: 5.075
    - type: recall_at_1
      value: 11.023
    - type: recall_at_10
      value: 24.174
    - type: recall_at_100
      value: 43.861
    - type: recall_at_1000
      value: 69.729
    - type: recall_at_3
      value: 17.019000000000002
    - type: recall_at_5
      value: 20.189
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.83
    - type: map_at_10
      value: 18.9
    - type: map_at_100
      value: 19.874
    - type: map_at_1000
      value: 20.047
    - type: map_at_3
      value: 17.413
    - type: map_at_5
      value: 18.127
    - type: mrr_at_1
      value: 16.008
    - type: mrr_at_10
      value: 22.157
    - type: mrr_at_100
      value: 22.952
    - type: mrr_at_1000
      value: 23.035
    - type: mrr_at_3
      value: 20.487
    - type: mrr_at_5
      value: 21.397
    - type: ndcg_at_1
      value: 16.008
    - type: ndcg_at_10
      value: 22.898
    - type: ndcg_at_100
      value: 27.345999999999997
    - type: ndcg_at_1000
      value: 30.818
    - type: ndcg_at_3
      value: 20.294
    - type: ndcg_at_5
      value: 21.328
    - type: precision_at_1
      value: 16.008
    - type: precision_at_10
      value: 4.625
    - type: precision_at_100
      value: 0.972
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 10.079
    - type: precision_at_5
      value: 7.154000000000001
    - type: recall_at_1
      value: 12.83
    - type: recall_at_10
      value: 30.509999999999998
    - type: recall_at_100
      value: 51.671
    - type: recall_at_1000
      value: 75.529
    - type: recall_at_3
      value: 22.889
    - type: recall_at_5
      value: 25.740000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.918
    - type: map_at_10
      value: 14.773
    - type: map_at_100
      value: 15.429
    - type: map_at_1000
      value: 15.545
    - type: map_at_3
      value: 13.413
    - type: map_at_5
      value: 14.09
    - type: mrr_at_1
      value: 12.384
    - type: mrr_at_10
      value: 16.28
    - type: mrr_at_100
      value: 16.935
    - type: mrr_at_1000
      value: 17.04
    - type: mrr_at_3
      value: 14.818000000000001
    - type: mrr_at_5
      value: 15.584999999999999
    - type: ndcg_at_1
      value: 12.384
    - type: ndcg_at_10
      value: 17.4
    - type: ndcg_at_100
      value: 21.201999999999998
    - type: ndcg_at_1000
      value: 24.639
    - type: ndcg_at_3
      value: 14.562
    - type: ndcg_at_5
      value: 15.761
    - type: precision_at_1
      value: 12.384
    - type: precision_at_10
      value: 2.81
    - type: precision_at_100
      value: 0.514
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.285
    - type: precision_at_5
      value: 4.436
    - type: recall_at_1
      value: 10.918
    - type: recall_at_10
      value: 24.295
    - type: recall_at_100
      value: 42.876999999999995
    - type: recall_at_1000
      value: 69.504
    - type: recall_at_3
      value: 16.463
    - type: recall_at_5
      value: 19.39
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.498
    - type: map_at_10
      value: 9.462
    - type: map_at_100
      value: 10.659
    - type: map_at_1000
      value: 10.837
    - type: map_at_3
      value: 7.701
    - type: map_at_5
      value: 8.524
    - type: mrr_at_1
      value: 12.182
    - type: mrr_at_10
      value: 19.561999999999998
    - type: mrr_at_100
      value: 20.665
    - type: mrr_at_1000
      value: 20.747
    - type: mrr_at_3
      value: 16.84
    - type: mrr_at_5
      value: 18.287
    - type: ndcg_at_1
      value: 12.182
    - type: ndcg_at_10
      value: 14.382
    - type: ndcg_at_100
      value: 20.244
    - type: ndcg_at_1000
      value: 24.247
    - type: ndcg_at_3
      value: 10.876
    - type: ndcg_at_5
      value: 12.064
    - type: precision_at_1
      value: 12.182
    - type: precision_at_10
      value: 4.853
    - type: precision_at_100
      value: 1.115
    - type: precision_at_1000
      value: 0.184
    - type: precision_at_3
      value: 8.208
    - type: precision_at_5
      value: 6.632000000000001
    - type: recall_at_1
      value: 5.498
    - type: recall_at_10
      value: 18.336
    - type: recall_at_100
      value: 39.318999999999996
    - type: recall_at_1000
      value: 62.760000000000005
    - type: recall_at_3
      value: 10.16
    - type: recall_at_5
      value: 13.149
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.928
    - type: map_at_10
      value: 6.816
    - type: map_at_100
      value: 9.347999999999999
    - type: map_at_1000
      value: 10.051
    - type: map_at_3
      value: 4.7669999999999995
    - type: map_at_5
      value: 5.6419999999999995
    - type: mrr_at_1
      value: 33.75
    - type: mrr_at_10
      value: 41.662
    - type: mrr_at_100
      value: 42.483
    - type: mrr_at_1000
      value: 42.536
    - type: mrr_at_3
      value: 39.125
    - type: mrr_at_5
      value: 40.363
    - type: ndcg_at_1
      value: 24.5
    - type: ndcg_at_10
      value: 18.73
    - type: ndcg_at_100
      value: 20.355
    - type: ndcg_at_1000
      value: 26.606
    - type: ndcg_at_3
      value: 21.169
    - type: ndcg_at_5
      value: 19.776
    - type: precision_at_1
      value: 33.75
    - type: precision_at_10
      value: 16.85
    - type: precision_at_100
      value: 5.095000000000001
    - type: precision_at_1000
      value: 1.107
    - type: precision_at_3
      value: 24.667
    - type: precision_at_5
      value: 21.3
    - type: recall_at_1
      value: 2.928
    - type: recall_at_10
      value: 10.637
    - type: recall_at_100
      value: 24.968
    - type: recall_at_1000
      value: 46.566
    - type: recall_at_3
      value: 5.619
    - type: recall_at_5
      value: 7.344
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.254999999999995
    - type: f1
      value: 39.47105271415231
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 9.212
    - type: map_at_10
      value: 13.952
    - type: map_at_100
      value: 14.680000000000001
    - type: map_at_1000
      value: 14.766000000000002
    - type: map_at_3
      value: 12.292
    - type: map_at_5
      value: 13.192
    - type: mrr_at_1
      value: 9.796000000000001
    - type: mrr_at_10
      value: 14.825
    - type: mrr_at_100
      value: 15.573999999999998
    - type: mrr_at_1000
      value: 15.656
    - type: mrr_at_3
      value: 13.064
    - type: mrr_at_5
      value: 14.025000000000002
    - type: ndcg_at_1
      value: 9.796000000000001
    - type: ndcg_at_10
      value: 16.985
    - type: ndcg_at_100
      value: 21.015
    - type: ndcg_at_1000
      value: 23.507
    - type: ndcg_at_3
      value: 13.505
    - type: ndcg_at_5
      value: 15.132000000000001
    - type: precision_at_1
      value: 9.796000000000001
    - type: precision_at_10
      value: 2.789
    - type: precision_at_100
      value: 0.49899999999999994
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 5.816000000000001
    - type: precision_at_5
      value: 4.340999999999999
    - type: recall_at_1
      value: 9.212
    - type: recall_at_10
      value: 25.756
    - type: recall_at_100
      value: 45.279
    - type: recall_at_1000
      value: 64.806
    - type: recall_at_3
      value: 16.235
    - type: recall_at_5
      value: 20.125999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.604
    - type: map_at_10
      value: 9.46
    - type: map_at_100
      value: 10.417
    - type: map_at_1000
      value: 10.604
    - type: map_at_3
      value: 7.776
    - type: map_at_5
      value: 8.601
    - type: mrr_at_1
      value: 11.265
    - type: mrr_at_10
      value: 16.661
    - type: mrr_at_100
      value: 17.575
    - type: mrr_at_1000
      value: 17.684
    - type: mrr_at_3
      value: 14.582999999999998
    - type: mrr_at_5
      value: 15.717999999999998
    - type: ndcg_at_1
      value: 11.265
    - type: ndcg_at_10
      value: 13.36
    - type: ndcg_at_100
      value: 18.199
    - type: ndcg_at_1000
      value: 22.682
    - type: ndcg_at_3
      value: 10.677
    - type: ndcg_at_5
      value: 11.64
    - type: precision_at_1
      value: 11.265
    - type: precision_at_10
      value: 4.043
    - type: precision_at_100
      value: 0.8920000000000001
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 7.305000000000001
    - type: precision_at_5
      value: 5.772
    - type: recall_at_1
      value: 5.604
    - type: recall_at_10
      value: 17.756
    - type: recall_at_100
      value: 36.913000000000004
    - type: recall_at_1000
      value: 65.438
    - type: recall_at_3
      value: 9.626999999999999
    - type: recall_at_5
      value: 12.665000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 12.026
    - type: map_at_10
      value: 16.878999999999998
    - type: map_at_100
      value: 17.607999999999997
    - type: map_at_1000
      value: 17.716
    - type: map_at_3
      value: 15.514
    - type: map_at_5
      value: 16.236
    - type: mrr_at_1
      value: 24.038
    - type: mrr_at_10
      value: 29.831999999999997
    - type: mrr_at_100
      value: 30.578
    - type: mrr_at_1000
      value: 30.656
    - type: mrr_at_3
      value: 28.298000000000002
    - type: mrr_at_5
      value: 29.116999999999997
    - type: ndcg_at_1
      value: 24.051000000000002
    - type: ndcg_at_10
      value: 22.042
    - type: ndcg_at_100
      value: 25.756
    - type: ndcg_at_1000
      value: 28.579
    - type: ndcg_at_3
      value: 19.296
    - type: ndcg_at_5
      value: 20.549999999999997
    - type: precision_at_1
      value: 24.051000000000002
    - type: precision_at_10
      value: 4.920999999999999
    - type: precision_at_100
      value: 0.792
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 12.225999999999999
    - type: precision_at_5
      value: 8.332
    - type: recall_at_1
      value: 12.026
    - type: recall_at_10
      value: 24.605
    - type: recall_at_100
      value: 39.595
    - type: recall_at_1000
      value: 58.494
    - type: recall_at_3
      value: 18.339
    - type: recall_at_5
      value: 20.831
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.706399999999995
    - type: ap
      value: 58.9524031201249
    - type: f1
      value: 63.556083975109466
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 4.845
    - type: map_at_10
      value: 8.402999999999999
    - type: map_at_100
      value: 9.106
    - type: map_at_1000
      value: 9.199
    - type: map_at_3
      value: 7.074999999999999
    - type: map_at_5
      value: 7.757
    - type: mrr_at_1
      value: 5.0
    - type: mrr_at_10
      value: 8.625
    - type: mrr_at_100
      value: 9.337
    - type: mrr_at_1000
      value: 9.428
    - type: mrr_at_3
      value: 7.266
    - type: mrr_at_5
      value: 7.965999999999999
    - type: ndcg_at_1
      value: 4.971
    - type: ndcg_at_10
      value: 10.696
    - type: ndcg_at_100
      value: 14.716000000000001
    - type: ndcg_at_1000
      value: 17.663999999999998
    - type: ndcg_at_3
      value: 7.881
    - type: ndcg_at_5
      value: 9.118
    - type: precision_at_1
      value: 4.971
    - type: precision_at_10
      value: 1.855
    - type: precision_at_100
      value: 0.398
    - type: precision_at_1000
      value: 0.066
    - type: precision_at_3
      value: 3.453
    - type: precision_at_5
      value: 2.693
    - type: recall_at_1
      value: 4.845
    - type: recall_at_10
      value: 17.88
    - type: recall_at_100
      value: 37.816
    - type: recall_at_1000
      value: 61.726000000000006
    - type: recall_at_3
      value: 10.045
    - type: recall_at_5
      value: 13.032
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.28408572731419
    - type: f1
      value: 88.36057445001192
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.366165070679436
    - type: f1
      value: 40.06121455563378
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.80228648285138
    - type: f1
      value: 59.56813863530079
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.55413584398117
    - type: f1
      value: 67.09171141857304
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.373735594129403
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 22.97944248268257
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.174012229019485
    - type: mrr
      value: 28.972842705926528
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.814
    - type: map_at_10
      value: 5.412999999999999
    - type: map_at_100
      value: 7.0120000000000005
    - type: map_at_1000
      value: 8.187
    - type: map_at_3
      value: 4.289
    - type: map_at_5
      value: 4.825
    - type: mrr_at_1
      value: 29.102
    - type: mrr_at_10
      value: 36.876999999999995
    - type: mrr_at_100
      value: 37.506
    - type: mrr_at_1000
      value: 37.592
    - type: mrr_at_3
      value: 34.262
    - type: mrr_at_5
      value: 35.888
    - type: ndcg_at_1
      value: 27.089999999999996
    - type: ndcg_at_10
      value: 19.134999999999998
    - type: ndcg_at_100
      value: 18.29
    - type: ndcg_at_1000
      value: 27.842
    - type: ndcg_at_3
      value: 22.417
    - type: ndcg_at_5
      value: 21.081
    - type: precision_at_1
      value: 29.102
    - type: precision_at_10
      value: 14.302999999999999
    - type: precision_at_100
      value: 5.632000000000001
    - type: precision_at_1000
      value: 1.856
    - type: precision_at_3
      value: 21.156
    - type: precision_at_5
      value: 18.39
    - type: recall_at_1
      value: 2.814
    - type: recall_at_10
      value: 8.431
    - type: recall_at_100
      value: 19.332
    - type: recall_at_1000
      value: 53.879999999999995
    - type: recall_at_3
      value: 5.212
    - type: recall_at_5
      value: 6.364
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 7.423
    - type: map_at_10
      value: 12.638
    - type: map_at_100
      value: 13.672
    - type: map_at_1000
      value: 13.776
    - type: map_at_3
      value: 10.727
    - type: map_at_5
      value: 11.745
    - type: mrr_at_1
      value: 8.459
    - type: mrr_at_10
      value: 14.068
    - type: mrr_at_100
      value: 15.067
    - type: mrr_at_1000
      value: 15.155
    - type: mrr_at_3
      value: 12.065
    - type: mrr_at_5
      value: 13.142999999999999
    - type: ndcg_at_1
      value: 8.459
    - type: ndcg_at_10
      value: 16.152
    - type: ndcg_at_100
      value: 21.636
    - type: ndcg_at_1000
      value: 24.593
    - type: ndcg_at_3
      value: 12.16
    - type: ndcg_at_5
      value: 14.011000000000001
    - type: precision_at_1
      value: 8.459
    - type: precision_at_10
      value: 3.004
    - type: precision_at_100
      value: 0.615
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 5.755
    - type: precision_at_5
      value: 4.460999999999999
    - type: recall_at_1
      value: 7.423
    - type: recall_at_10
      value: 25.698
    - type: recall_at_100
      value: 51.556999999999995
    - type: recall_at_1000
      value: 74.435
    - type: recall_at_3
      value: 15.015
    - type: recall_at_5
      value: 19.397000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.516999999999996
    - type: map_at_10
      value: 72.943
    - type: map_at_100
      value: 73.741
    - type: map_at_1000
      value: 73.78
    - type: map_at_3
      value: 70.025
    - type: map_at_5
      value: 71.786
    - type: mrr_at_1
      value: 69.82000000000001
    - type: mrr_at_10
      value: 77.402
    - type: mrr_at_100
      value: 77.694
    - type: mrr_at_1000
      value: 77.702
    - type: mrr_at_3
      value: 75.852
    - type: mrr_at_5
      value: 76.839
    - type: ndcg_at_1
      value: 69.78
    - type: ndcg_at_10
      value: 77.777
    - type: ndcg_at_100
      value: 80.148
    - type: ndcg_at_1000
      value: 80.64
    - type: ndcg_at_3
      value: 74.071
    - type: ndcg_at_5
      value: 75.974
    - type: precision_at_1
      value: 69.78
    - type: precision_at_10
      value: 11.776
    - type: precision_at_100
      value: 1.431
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 32.11
    - type: precision_at_5
      value: 21.284
    - type: recall_at_1
      value: 60.516999999999996
    - type: recall_at_10
      value: 87.149
    - type: recall_at_100
      value: 96.33
    - type: recall_at_1000
      value: 99.236
    - type: recall_at_3
      value: 76.592
    - type: recall_at_5
      value: 81.828
    - type: map_at_1
      value: 2.545
    - type: map_at_10
      value: 5.84
    - type: map_at_100
      value: 6.984999999999999
    - type: map_at_1000
      value: 7.216
    - type: map_at_3
      value: 4.348
    - type: map_at_5
      value: 5.064
    - type: mrr_at_1
      value: 12.6
    - type: mrr_at_10
      value: 19.799
    - type: mrr_at_100
      value: 20.964
    - type: mrr_at_1000
      value: 21.067
    - type: mrr_at_3
      value: 17.349999999999998
    - type: mrr_at_5
      value: 18.77
    - type: ndcg_at_1
      value: 12.6
    - type: ndcg_at_10
      value: 10.683
    - type: ndcg_at_100
      value: 16.256
    - type: ndcg_at_1000
      value: 21.304000000000002
    - type: ndcg_at_3
      value: 10.167
    - type: ndcg_at_5
      value: 8.853
    - type: precision_at_1
      value: 12.6
    - type: precision_at_10
      value: 5.54
    - type: precision_at_100
      value: 1.3679999999999999
    - type: precision_at_1000
      value: 0.259
    - type: precision_at_3
      value: 9.467
    - type: precision_at_5
      value: 7.739999999999999
    - type: recall_at_1
      value: 2.545
    - type: recall_at_10
      value: 11.212
    - type: recall_at_100
      value: 27.785
    - type: recall_at_1000
      value: 52.588
    - type: recall_at_3
      value: 5.768
    - type: recall_at_5
      value: 7.843
    - type: map_at_1
      value: 0.13
    - type: map_at_10
      value: 0.653
    - type: map_at_100
      value: 3.5479999999999996
    - type: map_at_1000
      value: 8.239
    - type: map_at_3
      value: 0.27
    - type: map_at_5
      value: 0.387
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 58.477999999999994
    - type: mrr_at_100
      value: 59.079
    - type: mrr_at_1000
      value: 59.099000000000004
    - type: mrr_at_3
      value: 56.00000000000001
    - type: mrr_at_5
      value: 57.3
    - type: ndcg_at_1
      value: 42.0
    - type: ndcg_at_10
      value: 34.636
    - type: ndcg_at_100
      value: 26.856
    - type: ndcg_at_1000
      value: 24.409
    - type: ndcg_at_3
      value: 39.050000000000004
    - type: ndcg_at_5
      value: 36.541000000000004
    - type: precision_at_1
      value: 50.0
    - type: precision_at_10
      value: 37.2
    - type: precision_at_100
      value: 28.28
    - type: precision_at_1000
      value: 11.996
    - type: precision_at_3
      value: 44.0
    - type: precision_at_5
      value: 40.0
    - type: recall_at_1
      value: 0.13
    - type: recall_at_10
      value: 0.822
    - type: recall_at_100
      value: 6.015000000000001
    - type: recall_at_1000
      value: 23.772
    - type: recall_at_3
      value: 0.307
    - type: recall_at_5
      value: 0.453
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 24.96238867406633
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 42.15456565539958
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.14154775161344
    - type: cos_sim_spearman
      value: 67.34346119954171
    - type: euclidean_pearson
      value: 72.35899953785258
    - type: euclidean_spearman
      value: 67.3437533363199
    - type: manhattan_pearson
      value: 70.9274622484765
    - type: manhattan_spearman
      value: 66.00500346801255
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 73.45319575935073
    - type: cos_sim_spearman
      value: 66.85451568709998
    - type: euclidean_pearson
      value: 69.91095676583507
    - type: euclidean_spearman
      value: 66.8557417173495
    - type: manhattan_pearson
      value: 70.79095833168148
    - type: manhattan_spearman
      value: 68.07407266249538
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.69086874055675
    - type: cos_sim_spearman
      value: 78.04733839857
    - type: euclidean_pearson
      value: 77.63075897573337
    - type: euclidean_spearman
      value: 78.04737621071355
    - type: manhattan_pearson
      value: 77.94694857794688
    - type: manhattan_spearman
      value: 78.45352622493287
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.79462726940899
    - type: cos_sim_spearman
      value: 73.75004555900799
    - type: euclidean_pearson
      value: 75.98934348748296
    - type: euclidean_spearman
      value: 73.7500358689292
    - type: manhattan_pearson
      value: 76.00086800123202
    - type: manhattan_spearman
      value: 74.06711780537452
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.78001899088082
    - type: cos_sim_spearman
      value: 80.8098659330615
    - type: euclidean_pearson
      value: 80.81455975868363
    - type: euclidean_spearman
      value: 80.80987420717732
    - type: manhattan_pearson
      value: 81.43248963554757
    - type: manhattan_spearman
      value: 81.56756512374152
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.09273075600336
    - type: cos_sim_spearman
      value: 76.44072137673248
    - type: euclidean_pearson
      value: 76.07667290013225
    - type: euclidean_spearman
      value: 76.44127170482552
    - type: manhattan_pearson
      value: 76.6332220160955
    - type: manhattan_spearman
      value: 77.11730946641201
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.86191718272701
    - type: cos_sim_spearman
      value: 84.05759596682893
    - type: euclidean_pearson
      value: 84.05247433515731
    - type: euclidean_spearman
      value: 84.05847010074612
    - type: manhattan_pearson
      value: 84.20796352611727
    - type: manhattan_spearman
      value: 84.20823102579908
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.405232991348434
    - type: cos_sim_spearman
      value: 61.017715202418366
    - type: euclidean_pearson
      value: 63.436431062341434
    - type: euclidean_spearman
      value: 61.017715202418366
    - type: manhattan_pearson
      value: 63.6521277557926
    - type: manhattan_spearman
      value: 61.73049790460205
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.80795371667985
    - type: cos_sim_spearman
      value: 75.43643133516306
    - type: euclidean_pearson
      value: 76.87791904895818
    - type: euclidean_spearman
      value: 75.4364797257313
    - type: manhattan_pearson
      value: 76.89603534893224
    - type: manhattan_spearman
      value: 75.44538808910046
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 69.67746354273282
    - type: mrr
      value: 89.80577701165936
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 31.333
    - type: map_at_10
      value: 37.378
    - type: map_at_100
      value: 38.641999999999996
    - type: map_at_1000
      value: 38.719
    - type: map_at_3
      value: 35.06
    - type: map_at_5
      value: 36.64
    - type: mrr_at_1
      value: 33.667
    - type: mrr_at_10
      value: 39.324
    - type: mrr_at_100
      value: 40.449
    - type: mrr_at_1000
      value: 40.512
    - type: mrr_at_3
      value: 37.278
    - type: mrr_at_5
      value: 38.744
    - type: ndcg_at_1
      value: 33.667
    - type: ndcg_at_10
      value: 40.92
    - type: ndcg_at_100
      value: 46.938
    - type: ndcg_at_1000
      value: 48.811
    - type: ndcg_at_3
      value: 36.675999999999995
    - type: ndcg_at_5
      value: 39.31
    - type: precision_at_1
      value: 33.667
    - type: precision_at_10
      value: 5.633
    - type: precision_at_100
      value: 0.88
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.222000000000001
    - type: precision_at_5
      value: 10.0
    - type: recall_at_1
      value: 31.333
    - type: recall_at_10
      value: 49.956
    - type: recall_at_100
      value: 77.683
    - type: recall_at_1000
      value: 92.133
    - type: recall_at_3
      value: 39.0
    - type: recall_at_5
      value: 45.317
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.63663366336634
    - type: cos_sim_ap
      value: 87.01958641278611
    - type: cos_sim_f1
      value: 80.12684989429175
    - type: cos_sim_precision
      value: 84.97757847533633
    - type: cos_sim_recall
      value: 75.8
    - type: dot_accuracy
      value: 99.63663366336634
    - type: dot_ap
      value: 87.01958641278611
    - type: dot_f1
      value: 80.12684989429175
    - type: dot_precision
      value: 84.97757847533633
    - type: dot_recall
      value: 75.8
    - type: euclidean_accuracy
      value: 99.63663366336634
    - type: euclidean_ap
      value: 87.01958641278611
    - type: euclidean_f1
      value: 80.12684989429175
    - type: euclidean_precision
      value: 84.97757847533633
    - type: euclidean_recall
      value: 75.8
    - type: manhattan_accuracy
      value: 99.68613861386139
    - type: manhattan_ap
      value: 90.11510992894823
    - type: manhattan_f1
      value: 83.73035985808414
    - type: manhattan_precision
      value: 84.89208633093526
    - type: manhattan_recall
      value: 82.6
    - type: max_accuracy
      value: 99.68613861386139
    - type: max_ap
      value: 90.11510992894823
    - type: max_f1
      value: 83.73035985808414
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 31.564966710258002
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.902331000032934
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.84399261061117
    - type: mrr
      value: 43.29435372633902
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.95259336062129
    - type: cos_sim_spearman
      value: 29.305731756791836
    - type: dot_pearson
      value: 29.95259337454406
    - type: dot_spearman
      value: 29.33902263846769
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.537
    - type: map_at_10
      value: 8.591
    - type: map_at_100
      value: 14.328
    - type: map_at_1000
      value: 15.919
    - type: map_at_3
      value: 4.8500000000000005
    - type: map_at_5
      value: 6.389
    - type: mrr_at_1
      value: 34.694
    - type: mrr_at_10
      value: 46.553
    - type: mrr_at_100
      value: 47.515
    - type: mrr_at_1000
      value: 47.515
    - type: mrr_at_3
      value: 42.857
    - type: mrr_at_5
      value: 44.796
    - type: ndcg_at_1
      value: 33.672999999999995
    - type: ndcg_at_10
      value: 21.73
    - type: ndcg_at_100
      value: 34.699000000000005
    - type: ndcg_at_1000
      value: 46.143
    - type: ndcg_at_3
      value: 27.343
    - type: ndcg_at_5
      value: 24.11
    - type: precision_at_1
      value: 34.694
    - type: precision_at_10
      value: 18.776
    - type: precision_at_100
      value: 7.571
    - type: precision_at_1000
      value: 1.478
    - type: precision_at_3
      value: 27.211000000000002
    - type: precision_at_5
      value: 23.673
    - type: recall_at_1
      value: 2.537
    - type: recall_at_10
      value: 13.012
    - type: recall_at_100
      value: 45.891
    - type: recall_at_1000
      value: 80.739
    - type: recall_at_3
      value: 5.744
    - type: recall_at_5
      value: 8.278
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.004
    - type: ap
      value: 13.022449069209996
    - type: f1
      value: 52.831422157603235
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.55687606112054
    - type: f1
      value: 53.742471169925146
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 30.854612368831237
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.20915539130954
    - type: cos_sim_ap
      value: 64.64935846149021
    - type: cos_sim_f1
      value: 61.74544588641505
    - type: cos_sim_precision
      value: 56.25949229767846
    - type: cos_sim_recall
      value: 68.41688654353561
    - type: dot_accuracy
      value: 83.20915539130954
    - type: dot_ap
      value: 64.64935846149021
    - type: dot_f1
      value: 61.74544588641505
    - type: dot_precision
      value: 56.25949229767846
    - type: dot_recall
      value: 68.41688654353561
    - type: euclidean_accuracy
      value: 83.20915539130954
    - type: euclidean_ap
      value: 64.64935846149021
    - type: euclidean_f1
      value: 61.74544588641505
    - type: euclidean_precision
      value: 56.25949229767846
    - type: euclidean_recall
      value: 68.41688654353561
    - type: manhattan_accuracy
      value: 83.00649698992669
    - type: manhattan_ap
      value: 63.241363240922475
    - type: manhattan_f1
      value: 60.10508778674869
    - type: manhattan_precision
      value: 58.435085970595566
    - type: manhattan_recall
      value: 61.87335092348285
    - type: max_accuracy
      value: 83.20915539130954
    - type: max_ap
      value: 64.64935846149021
    - type: max_f1
      value: 61.74544588641505
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.33457523188575
    - type: cos_sim_ap
      value: 82.48667288124405
    - type: cos_sim_f1
      value: 74.60564319040213
    - type: cos_sim_precision
      value: 71.86474532743615
    - type: cos_sim_recall
      value: 77.56390514320911
    - type: dot_accuracy
      value: 87.33457523188575
    - type: dot_ap
      value: 82.48667984460607
    - type: dot_f1
      value: 74.60564319040213
    - type: dot_precision
      value: 71.86474532743615
    - type: dot_recall
      value: 77.56390514320911
    - type: euclidean_accuracy
      value: 87.33457523188575
    - type: euclidean_ap
      value: 82.48667328332766
    - type: euclidean_f1
      value: 74.60564319040213
    - type: euclidean_precision
      value: 71.86474532743615
    - type: euclidean_recall
      value: 77.56390514320911
    - type: manhattan_accuracy
      value: 87.28994450265843
    - type: manhattan_ap
      value: 82.53662260997004
    - type: manhattan_f1
      value: 74.64819224940463
    - type: manhattan_precision
      value: 70.24310742903708
    - type: manhattan_recall
      value: 79.64274715121651
    - type: max_accuracy
      value: 87.33457523188575
    - type: max_ap
      value: 82.53662260997004
    - type: max_f1
      value: 74.64819224940463
---
