mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_nobivec
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.4179104477612
    - type: ap
      value: 34.63780365598458
    - type: f1
      value: 66.15457281659042
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 64.979125
    - type: ap
      value: 60.068877740256944
    - type: f1
      value: 64.73214550243449
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.13
    - type: f1
      value: 33.6415337800296
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.55
    - type: map_at_10
      value: 35.672
    - type: map_at_100
      value: 36.855
    - type: map_at_1000
      value: 36.879
    - type: map_at_3
      value: 31.163999999999998
    - type: map_at_5
      value: 33.639
    - type: mrr_at_1
      value: 22.191
    - type: mrr_at_10
      value: 35.916
    - type: mrr_at_100
      value: 37.106
    - type: mrr_at_1000
      value: 37.13
    - type: mrr_at_3
      value: 31.424999999999997
    - type: mrr_at_5
      value: 33.854
    - type: ndcg_at_1
      value: 21.55
    - type: ndcg_at_10
      value: 43.796
    - type: ndcg_at_100
      value: 49.260999999999996
    - type: ndcg_at_1000
      value: 49.823
    - type: ndcg_at_3
      value: 34.455000000000005
    - type: ndcg_at_5
      value: 38.926
    - type: precision_at_1
      value: 21.55
    - type: precision_at_10
      value: 6.984
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.674999999999999
    - type: precision_at_5
      value: 10.982
    - type: recall_at_1
      value: 21.55
    - type: recall_at_10
      value: 69.844
    - type: recall_at_100
      value: 94.666
    - type: recall_at_1000
      value: 98.933
    - type: recall_at_3
      value: 44.025999999999996
    - type: recall_at_5
      value: 54.908
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 33.85061123853429
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.43376523076998
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.394179738377154
    - type: mrr
      value: 66.89860616453414
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.85377718907006
    - type: cos_sim_spearman
      value: 80.32893878309842
    - type: euclidean_pearson
      value: 80.64645390094664
    - type: euclidean_spearman
      value: 80.32893878309842
    - type: manhattan_pearson
      value: 80.0646777271307
    - type: manhattan_spearman
      value: 79.71627422071113
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.52597402597404
    - type: f1
      value: 72.74726159139323
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.153351191346665
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.419276973031316
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.231
    - type: map_at_10
      value: 28.671999999999997
    - type: map_at_100
      value: 29.804000000000002
    - type: map_at_1000
      value: 29.963
    - type: map_at_3
      value: 26.308
    - type: map_at_5
      value: 27.633000000000003
    - type: mrr_at_1
      value: 27.325
    - type: mrr_at_10
      value: 34.69
    - type: mrr_at_100
      value: 35.56
    - type: mrr_at_1000
      value: 35.636
    - type: mrr_at_3
      value: 32.879999999999995
    - type: mrr_at_5
      value: 33.796
    - type: ndcg_at_1
      value: 27.325
    - type: ndcg_at_10
      value: 33.606
    - type: ndcg_at_100
      value: 38.623000000000005
    - type: ndcg_at_1000
      value: 41.93
    - type: ndcg_at_3
      value: 30.296
    - type: ndcg_at_5
      value: 31.629
    - type: precision_at_1
      value: 27.325
    - type: precision_at_10
      value: 6.481000000000001
    - type: precision_at_100
      value: 1.11
    - type: precision_at_1000
      value: 0.169
    - type: precision_at_3
      value: 14.735000000000001
    - type: precision_at_5
      value: 10.615
    - type: recall_at_1
      value: 21.231
    - type: recall_at_10
      value: 42.033
    - type: recall_at_100
      value: 64.452
    - type: recall_at_1000
      value: 87.047
    - type: recall_at_3
      value: 31.433
    - type: recall_at_5
      value: 35.69
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.583
    - type: map_at_10
      value: 23.139000000000003
    - type: map_at_100
      value: 24.071
    - type: map_at_1000
      value: 24.194
    - type: map_at_3
      value: 21.171
    - type: map_at_5
      value: 22.309
    - type: mrr_at_1
      value: 22.102
    - type: mrr_at_10
      value: 27.442
    - type: mrr_at_100
      value: 28.199999999999996
    - type: mrr_at_1000
      value: 28.269
    - type: mrr_at_3
      value: 25.34
    - type: mrr_at_5
      value: 26.521
    - type: ndcg_at_1
      value: 22.102
    - type: ndcg_at_10
      value: 27.039
    - type: ndcg_at_100
      value: 31.389
    - type: ndcg_at_1000
      value: 34.247
    - type: ndcg_at_3
      value: 23.573
    - type: ndcg_at_5
      value: 25.185000000000002
    - type: precision_at_1
      value: 22.102
    - type: precision_at_10
      value: 5.019
    - type: precision_at_100
      value: 0.902
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 11.168
    - type: precision_at_5
      value: 8.102
    - type: recall_at_1
      value: 17.583
    - type: recall_at_10
      value: 34.479
    - type: recall_at_100
      value: 53.76499999999999
    - type: recall_at_1000
      value: 73.169
    - type: recall_at_3
      value: 24.532
    - type: recall_at_5
      value: 28.810000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 26.637
    - type: map_at_10
      value: 35.083999999999996
    - type: map_at_100
      value: 36.248999999999995
    - type: map_at_1000
      value: 36.346000000000004
    - type: map_at_3
      value: 32.623000000000005
    - type: map_at_5
      value: 33.969
    - type: mrr_at_1
      value: 31.034
    - type: mrr_at_10
      value: 38.440000000000005
    - type: mrr_at_100
      value: 39.363
    - type: mrr_at_1000
      value: 39.425
    - type: mrr_at_3
      value: 36.176
    - type: mrr_at_5
      value: 37.461
    - type: ndcg_at_1
      value: 31.034
    - type: ndcg_at_10
      value: 39.834
    - type: ndcg_at_100
      value: 45.091
    - type: ndcg_at_1000
      value: 47.321999999999996
    - type: ndcg_at_3
      value: 35.253
    - type: ndcg_at_5
      value: 37.403999999999996
    - type: precision_at_1
      value: 31.034
    - type: precision_at_10
      value: 6.47
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 15.674
    - type: precision_at_5
      value: 10.897
    - type: recall_at_1
      value: 26.637
    - type: recall_at_10
      value: 51.03
    - type: recall_at_100
      value: 74.30600000000001
    - type: recall_at_1000
      value: 90.51599999999999
    - type: recall_at_3
      value: 38.461
    - type: recall_at_5
      value: 43.823
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.674
    - type: map_at_10
      value: 16.922
    - type: map_at_100
      value: 17.741
    - type: map_at_1000
      value: 17.855999999999998
    - type: map_at_3
      value: 15.329999999999998
    - type: map_at_5
      value: 16.236
    - type: mrr_at_1
      value: 13.785
    - type: mrr_at_10
      value: 18.076
    - type: mrr_at_100
      value: 18.904
    - type: mrr_at_1000
      value: 19.008
    - type: mrr_at_3
      value: 16.46
    - type: mrr_at_5
      value: 17.375
    - type: ndcg_at_1
      value: 13.785
    - type: ndcg_at_10
      value: 19.759999999999998
    - type: ndcg_at_100
      value: 24.121000000000002
    - type: ndcg_at_1000
      value: 27.662
    - type: ndcg_at_3
      value: 16.477
    - type: ndcg_at_5
      value: 18.09
    - type: precision_at_1
      value: 13.785
    - type: precision_at_10
      value: 3.096
    - type: precision_at_100
      value: 0.5599999999999999
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.816999999999999
    - type: precision_at_5
      value: 4.994
    - type: recall_at_1
      value: 12.674
    - type: recall_at_10
      value: 27.589000000000002
    - type: recall_at_100
      value: 48.197
    - type: recall_at_1000
      value: 76.108
    - type: recall_at_3
      value: 18.644
    - type: recall_at_5
      value: 22.514
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.279999999999999
    - type: map_at_10
      value: 9.957
    - type: map_at_100
      value: 10.719
    - type: map_at_1000
      value: 10.854999999999999
    - type: map_at_3
      value: 8.73
    - type: map_at_5
      value: 9.293999999999999
    - type: mrr_at_1
      value: 8.333
    - type: mrr_at_10
      value: 12.375
    - type: mrr_at_100
      value: 13.191
    - type: mrr_at_1000
      value: 13.295000000000002
    - type: mrr_at_3
      value: 10.925
    - type: mrr_at_5
      value: 11.602
    - type: ndcg_at_1
      value: 8.333
    - type: ndcg_at_10
      value: 12.581999999999999
    - type: ndcg_at_100
      value: 16.589000000000002
    - type: ndcg_at_1000
      value: 20.339
    - type: ndcg_at_3
      value: 10.128
    - type: ndcg_at_5
      value: 11.046
    - type: precision_at_1
      value: 8.333
    - type: precision_at_10
      value: 2.463
    - type: precision_at_100
      value: 0.516
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 5.017
    - type: precision_at_5
      value: 3.682
    - type: recall_at_1
      value: 6.279999999999999
    - type: recall_at_10
      value: 18.367
    - type: recall_at_100
      value: 36.211
    - type: recall_at_1000
      value: 63.771
    - type: recall_at_3
      value: 11.556
    - type: recall_at_5
      value: 13.882
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.515
    - type: map_at_10
      value: 23.783
    - type: map_at_100
      value: 24.932000000000002
    - type: map_at_1000
      value: 25.063999999999997
    - type: map_at_3
      value: 21.579
    - type: map_at_5
      value: 22.732
    - type: mrr_at_1
      value: 21.752
    - type: mrr_at_10
      value: 28.335
    - type: mrr_at_100
      value: 29.264000000000003
    - type: mrr_at_1000
      value: 29.34
    - type: mrr_at_3
      value: 26.051000000000002
    - type: mrr_at_5
      value: 27.339999999999996
    - type: ndcg_at_1
      value: 21.752
    - type: ndcg_at_10
      value: 28.232000000000003
    - type: ndcg_at_100
      value: 33.822
    - type: ndcg_at_1000
      value: 36.802
    - type: ndcg_at_3
      value: 24.311
    - type: ndcg_at_5
      value: 26.019
    - type: precision_at_1
      value: 21.752
    - type: precision_at_10
      value: 5.265000000000001
    - type: precision_at_100
      value: 0.9730000000000001
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 11.421000000000001
    - type: precision_at_5
      value: 8.354000000000001
    - type: recall_at_1
      value: 17.515
    - type: recall_at_10
      value: 37.284
    - type: recall_at_100
      value: 61.987
    - type: recall_at_1000
      value: 82.52199999999999
    - type: recall_at_3
      value: 25.964
    - type: recall_at_5
      value: 30.523
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.753999999999998
    - type: map_at_10
      value: 18.490000000000002
    - type: map_at_100
      value: 19.615
    - type: map_at_1000
      value: 19.750999999999998
    - type: map_at_3
      value: 16.762
    - type: map_at_5
      value: 17.69
    - type: mrr_at_1
      value: 16.096
    - type: mrr_at_10
      value: 21.971
    - type: mrr_at_100
      value: 22.976
    - type: mrr_at_1000
      value: 23.058999999999997
    - type: mrr_at_3
      value: 20.186
    - type: mrr_at_5
      value: 21.077
    - type: ndcg_at_1
      value: 16.096
    - type: ndcg_at_10
      value: 22.201
    - type: ndcg_at_100
      value: 27.668
    - type: ndcg_at_1000
      value: 31.123
    - type: ndcg_at_3
      value: 18.983
    - type: ndcg_at_5
      value: 20.314
    - type: precision_at_1
      value: 16.096
    - type: precision_at_10
      value: 4.189
    - type: precision_at_100
      value: 0.828
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 9.285
    - type: precision_at_5
      value: 6.621
    - type: recall_at_1
      value: 12.753999999999998
    - type: recall_at_10
      value: 30.062
    - type: recall_at_100
      value: 53.913
    - type: recall_at_1000
      value: 78.846
    - type: recall_at_3
      value: 21.024
    - type: recall_at_5
      value: 24.524
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.441
    - type: map_at_10
      value: 19.80083333333333
    - type: map_at_100
      value: 20.72533333333334
    - type: map_at_1000
      value: 20.851166666666664
    - type: map_at_3
      value: 18.076749999999997
    - type: map_at_5
      value: 19.03183333333333
    - type: mrr_at_1
      value: 17.60725
    - type: mrr_at_10
      value: 22.957833333333333
    - type: mrr_at_100
      value: 23.786583333333333
    - type: mrr_at_1000
      value: 23.871666666666666
    - type: mrr_at_3
      value: 21.23666666666667
    - type: mrr_at_5
      value: 22.187416666666667
    - type: ndcg_at_1
      value: 17.60725
    - type: ndcg_at_10
      value: 23.32825
    - type: ndcg_at_100
      value: 27.8915
    - type: ndcg_at_1000
      value: 31.089166666666667
    - type: ndcg_at_3
      value: 20.2065
    - type: ndcg_at_5
      value: 21.6315
    - type: precision_at_1
      value: 17.60725
    - type: precision_at_10
      value: 4.173833333333333
    - type: precision_at_100
      value: 0.7679166666666666
    - type: precision_at_1000
      value: 0.12241666666666666
    - type: precision_at_3
      value: 9.375000000000002
    - type: precision_at_5
      value: 6.76125
    - type: recall_at_1
      value: 14.441
    - type: recall_at_10
      value: 30.861833333333333
    - type: recall_at_100
      value: 51.641583333333344
    - type: recall_at_1000
      value: 74.93816666666666
    - type: recall_at_3
      value: 22.006
    - type: recall_at_5
      value: 25.715833333333336
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.766
    - type: map_at_10
      value: 14.588999999999999
    - type: map_at_100
      value: 15.314
    - type: map_at_1000
      value: 15.396
    - type: map_at_3
      value: 13.164000000000001
    - type: map_at_5
      value: 13.880999999999998
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 16.607
    - type: mrr_at_100
      value: 17.365
    - type: mrr_at_1000
      value: 17.435000000000002
    - type: mrr_at_3
      value: 15.133
    - type: mrr_at_5
      value: 15.946
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 17.252000000000002
    - type: ndcg_at_100
      value: 21.156
    - type: ndcg_at_1000
      value: 23.696
    - type: ndcg_at_3
      value: 14.48
    - type: ndcg_at_5
      value: 15.684000000000001
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 2.945
    - type: precision_at_100
      value: 0.5369999999999999
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 6.390999999999999
    - type: precision_at_5
      value: 4.693
    - type: recall_at_1
      value: 10.766
    - type: recall_at_10
      value: 23.576
    - type: recall_at_100
      value: 41.887
    - type: recall_at_1000
      value: 61.41
    - type: recall_at_3
      value: 15.974
    - type: recall_at_5
      value: 18.879
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.003
    - type: map_at_10
      value: 11.571
    - type: map_at_100
      value: 12.196
    - type: map_at_1000
      value: 12.318
    - type: map_at_3
      value: 10.5
    - type: map_at_5
      value: 11.125
    - type: mrr_at_1
      value: 9.841999999999999
    - type: mrr_at_10
      value: 13.86
    - type: mrr_at_100
      value: 14.493
    - type: mrr_at_1000
      value: 14.593
    - type: mrr_at_3
      value: 12.681000000000001
    - type: mrr_at_5
      value: 13.345
    - type: ndcg_at_1
      value: 9.841999999999999
    - type: ndcg_at_10
      value: 13.975999999999999
    - type: ndcg_at_100
      value: 17.524
    - type: ndcg_at_1000
      value: 21.053
    - type: ndcg_at_3
      value: 11.974
    - type: ndcg_at_5
      value: 12.934999999999999
    - type: precision_at_1
      value: 9.841999999999999
    - type: precision_at_10
      value: 2.588
    - type: precision_at_100
      value: 0.526
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 5.804
    - type: precision_at_5
      value: 4.218999999999999
    - type: recall_at_1
      value: 8.003
    - type: recall_at_10
      value: 18.995
    - type: recall_at_100
      value: 35.741
    - type: recall_at_1000
      value: 61.997
    - type: recall_at_3
      value: 13.367999999999999
    - type: recall_at_5
      value: 15.83
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.591
    - type: map_at_10
      value: 17.537
    - type: map_at_100
      value: 18.345
    - type: map_at_1000
      value: 18.471
    - type: map_at_3
      value: 16.066
    - type: map_at_5
      value: 16.858
    - type: mrr_at_1
      value: 15.485
    - type: mrr_at_10
      value: 20.683
    - type: mrr_at_100
      value: 21.498
    - type: mrr_at_1000
      value: 21.598
    - type: mrr_at_3
      value: 19.092000000000002
    - type: mrr_at_5
      value: 19.964000000000002
    - type: ndcg_at_1
      value: 15.485
    - type: ndcg_at_10
      value: 20.888
    - type: ndcg_at_100
      value: 25.096
    - type: ndcg_at_1000
      value: 28.579
    - type: ndcg_at_3
      value: 18.014
    - type: ndcg_at_5
      value: 19.31
    - type: precision_at_1
      value: 15.485
    - type: precision_at_10
      value: 3.601
    - type: precision_at_100
      value: 0.623
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 8.364
    - type: precision_at_5
      value: 5.877000000000001
    - type: recall_at_1
      value: 12.591
    - type: recall_at_10
      value: 28.189999999999998
    - type: recall_at_100
      value: 47.453
    - type: recall_at_1000
      value: 72.968
    - type: recall_at_3
      value: 20.194000000000003
    - type: recall_at_5
      value: 23.592
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.137999999999998
    - type: map_at_10
      value: 21.215
    - type: map_at_100
      value: 22.355
    - type: map_at_1000
      value: 22.527
    - type: map_at_3
      value: 19.527
    - type: map_at_5
      value: 20.538999999999998
    - type: mrr_at_1
      value: 18.972
    - type: mrr_at_10
      value: 24.792
    - type: mrr_at_100
      value: 25.697
    - type: mrr_at_1000
      value: 25.772000000000002
    - type: mrr_at_3
      value: 23.188
    - type: mrr_at_5
      value: 24.206
    - type: ndcg_at_1
      value: 18.972
    - type: ndcg_at_10
      value: 25.144
    - type: ndcg_at_100
      value: 30.163
    - type: ndcg_at_1000
      value: 33.575
    - type: ndcg_at_3
      value: 22.462
    - type: ndcg_at_5
      value: 23.885
    - type: precision_at_1
      value: 18.972
    - type: precision_at_10
      value: 4.901
    - type: precision_at_100
      value: 1.093
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 10.738
    - type: precision_at_5
      value: 7.904999999999999
    - type: recall_at_1
      value: 15.137999999999998
    - type: recall_at_10
      value: 32.132
    - type: recall_at_100
      value: 55.574
    - type: recall_at_1000
      value: 79.377
    - type: recall_at_3
      value: 24.08
    - type: recall_at_5
      value: 27.983999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.120000000000001
    - type: map_at_10
      value: 16.651
    - type: map_at_100
      value: 17.363
    - type: map_at_1000
      value: 17.473
    - type: map_at_3
      value: 15.161
    - type: map_at_5
      value: 16.116
    - type: mrr_at_1
      value: 13.678
    - type: mrr_at_10
      value: 18.223
    - type: mrr_at_100
      value: 18.928
    - type: mrr_at_1000
      value: 19.03
    - type: mrr_at_3
      value: 16.728
    - type: mrr_at_5
      value: 17.616
    - type: ndcg_at_1
      value: 13.678
    - type: ndcg_at_10
      value: 19.425
    - type: ndcg_at_100
      value: 23.456
    - type: ndcg_at_1000
      value: 26.741999999999997
    - type: ndcg_at_3
      value: 16.527
    - type: ndcg_at_5
      value: 18.076999999999998
    - type: precision_at_1
      value: 13.678
    - type: precision_at_10
      value: 3.068
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 7.086
    - type: precision_at_5
      value: 5.176
    - type: recall_at_1
      value: 12.120000000000001
    - type: recall_at_10
      value: 26.605
    - type: recall_at_100
      value: 46.213
    - type: recall_at_1000
      value: 71.527
    - type: recall_at_3
      value: 18.842
    - type: recall_at_5
      value: 22.539
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.872
    - type: map_at_10
      value: 10.459
    - type: map_at_100
      value: 11.911
    - type: map_at_1000
      value: 12.113999999999999
    - type: map_at_3
      value: 8.425
    - type: map_at_5
      value: 9.459
    - type: mrr_at_1
      value: 13.29
    - type: mrr_at_10
      value: 21.566
    - type: mrr_at_100
      value: 22.814
    - type: mrr_at_1000
      value: 22.883
    - type: mrr_at_3
      value: 18.491
    - type: mrr_at_5
      value: 20.175
    - type: ndcg_at_1
      value: 13.29
    - type: ndcg_at_10
      value: 15.93
    - type: ndcg_at_100
      value: 22.666
    - type: ndcg_at_1000
      value: 26.784000000000002
    - type: ndcg_at_3
      value: 11.991999999999999
    - type: ndcg_at_5
      value: 13.453000000000001
    - type: precision_at_1
      value: 13.29
    - type: precision_at_10
      value: 5.349
    - type: precision_at_100
      value: 1.247
    - type: precision_at_1000
      value: 0.199
    - type: precision_at_3
      value: 9.121
    - type: precision_at_5
      value: 7.5569999999999995
    - type: recall_at_1
      value: 5.872
    - type: recall_at_10
      value: 20.546
    - type: recall_at_100
      value: 44.262
    - type: recall_at_1000
      value: 68.027
    - type: recall_at_3
      value: 11.219999999999999
    - type: recall_at_5
      value: 14.846
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.481
    - type: map_at_10
      value: 9.783999999999999
    - type: map_at_100
      value: 13.401
    - type: map_at_1000
      value: 14.316
    - type: map_at_3
      value: 6.957000000000001
    - type: map_at_5
      value: 8.315999999999999
    - type: mrr_at_1
      value: 41.5
    - type: mrr_at_10
      value: 50.479
    - type: mrr_at_100
      value: 51.309000000000005
    - type: mrr_at_1000
      value: 51.346000000000004
    - type: mrr_at_3
      value: 48.167
    - type: mrr_at_5
      value: 49.429
    - type: ndcg_at_1
      value: 30.625000000000004
    - type: ndcg_at_10
      value: 23.841
    - type: ndcg_at_100
      value: 26.651000000000003
    - type: ndcg_at_1000
      value: 33.273
    - type: ndcg_at_3
      value: 26.772000000000002
    - type: ndcg_at_5
      value: 25.564999999999998
    - type: precision_at_1
      value: 41.5
    - type: precision_at_10
      value: 20.8
    - type: precision_at_100
      value: 6.47
    - type: precision_at_1000
      value: 1.3639999999999999
    - type: precision_at_3
      value: 31.917
    - type: precision_at_5
      value: 27.35
    - type: recall_at_1
      value: 4.481
    - type: recall_at_10
      value: 14.294
    - type: recall_at_100
      value: 32.693
    - type: recall_at_1000
      value: 54.698
    - type: recall_at_3
      value: 7.994999999999999
    - type: recall_at_5
      value: 10.823
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.86
    - type: f1
      value: 40.914967776838886
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 13.886000000000001
    - type: map_at_10
      value: 21.253
    - type: map_at_100
      value: 22.154
    - type: map_at_1000
      value: 22.234
    - type: map_at_3
      value: 18.92
    - type: map_at_5
      value: 20.24
    - type: mrr_at_1
      value: 14.731
    - type: mrr_at_10
      value: 22.512999999999998
    - type: mrr_at_100
      value: 23.429
    - type: mrr_at_1000
      value: 23.5
    - type: mrr_at_3
      value: 20.064999999999998
    - type: mrr_at_5
      value: 21.451999999999998
    - type: ndcg_at_1
      value: 14.731
    - type: ndcg_at_10
      value: 25.730999999999998
    - type: ndcg_at_100
      value: 30.493
    - type: ndcg_at_1000
      value: 32.713
    - type: ndcg_at_3
      value: 20.893
    - type: ndcg_at_5
      value: 23.278
    - type: precision_at_1
      value: 14.731
    - type: precision_at_10
      value: 4.188
    - type: precision_at_100
      value: 0.677
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 9.096
    - type: precision_at_5
      value: 6.709
    - type: recall_at_1
      value: 13.886000000000001
    - type: recall_at_10
      value: 38.576
    - type: recall_at_100
      value: 61.08
    - type: recall_at_1000
      value: 78.25800000000001
    - type: recall_at_3
      value: 25.435000000000002
    - type: recall_at_5
      value: 31.176
  - 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: 10.035
    - type: map_at_100
      value: 11.094999999999999
    - type: map_at_1000
      value: 11.275
    - type: map_at_3
      value: 8.205
    - type: map_at_5
      value: 9.207
    - type: mrr_at_1
      value: 11.42
    - type: mrr_at_10
      value: 17.53
    - type: mrr_at_100
      value: 18.447
    - type: mrr_at_1000
      value: 18.545
    - type: mrr_at_3
      value: 15.201
    - type: mrr_at_5
      value: 16.497
    - type: ndcg_at_1
      value: 11.42
    - type: ndcg_at_10
      value: 14.27
    - type: ndcg_at_100
      value: 19.518
    - type: ndcg_at_1000
      value: 23.851
    - type: ndcg_at_3
      value: 11.315999999999999
    - type: ndcg_at_5
      value: 12.526000000000002
    - type: precision_at_1
      value: 11.42
    - type: precision_at_10
      value: 4.367
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 7.767
    - type: precision_at_5
      value: 6.235
    - type: recall_at_1
      value: 5.604
    - type: recall_at_10
      value: 19.182
    - type: recall_at_100
      value: 40.053
    - type: recall_at_1000
      value: 67.367
    - type: recall_at_3
      value: 10.530000000000001
    - type: recall_at_5
      value: 14.11
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 15.847
    - type: map_at_10
      value: 22.32
    - type: map_at_100
      value: 23.211000000000002
    - type: map_at_1000
      value: 23.322000000000003
    - type: map_at_3
      value: 20.47
    - type: map_at_5
      value: 21.497
    - type: mrr_at_1
      value: 31.695
    - type: mrr_at_10
      value: 38.491
    - type: mrr_at_100
      value: 39.231
    - type: mrr_at_1000
      value: 39.294000000000004
    - type: mrr_at_3
      value: 36.516
    - type: mrr_at_5
      value: 37.647999999999996
    - type: ndcg_at_1
      value: 31.695
    - type: ndcg_at_10
      value: 28.759
    - type: ndcg_at_100
      value: 32.957
    - type: ndcg_at_1000
      value: 35.686
    - type: ndcg_at_3
      value: 25.144
    - type: ndcg_at_5
      value: 26.909
    - type: precision_at_1
      value: 31.695
    - type: precision_at_10
      value: 6.394
    - type: precision_at_100
      value: 0.9769999999999999
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 15.867999999999999
    - type: precision_at_5
      value: 10.922
    - type: recall_at_1
      value: 15.847
    - type: recall_at_10
      value: 31.972
    - type: recall_at_100
      value: 48.825
    - type: recall_at_1000
      value: 67.07
    - type: recall_at_3
      value: 23.801
    - type: recall_at_5
      value: 27.306
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.0996
    - type: ap
      value: 59.24690414462077
    - type: f1
      value: 63.901632743552675
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.032
    - type: map_at_10
      value: 10.571
    - type: map_at_100
      value: 11.434
    - type: map_at_1000
      value: 11.536
    - type: map_at_3
      value: 8.927
    - type: map_at_5
      value: 9.745
    - type: mrr_at_1
      value: 6.218
    - type: mrr_at_10
      value: 10.857999999999999
    - type: mrr_at_100
      value: 11.728
    - type: mrr_at_1000
      value: 11.826
    - type: mrr_at_3
      value: 9.181000000000001
    - type: mrr_at_5
      value: 10.014000000000001
    - type: ndcg_at_1
      value: 6.203
    - type: ndcg_at_10
      value: 13.471
    - type: ndcg_at_100
      value: 18.267
    - type: ndcg_at_1000
      value: 21.367
    - type: ndcg_at_3
      value: 9.993
    - type: ndcg_at_5
      value: 11.472
    - type: precision_at_1
      value: 6.203
    - type: precision_at_10
      value: 2.341
    - type: precision_at_100
      value: 0.484
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.436
    - type: precision_at_5
      value: 3.4070000000000005
    - type: recall_at_1
      value: 6.032
    - type: recall_at_10
      value: 22.514
    - type: recall_at_100
      value: 46.061
    - type: recall_at_1000
      value: 71.002
    - type: recall_at_3
      value: 12.845999999999998
    - type: recall_at_5
      value: 16.411
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.89056087551299
    - type: f1
      value: 88.92611201654476
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 59.46648426812586
    - type: f1
      value: 40.09031702149602
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.882985877605925
    - type: f1
      value: 59.62547960951362
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.67854741089442
    - type: f1
      value: 67.30454712745052
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.12525413973902
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.349303249863205
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.51131395873944
    - type: mrr
      value: 30.491052548905884
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.676
    - type: map_at_10
      value: 7.663
    - type: map_at_100
      value: 9.617
    - type: map_at_1000
      value: 10.937
    - type: map_at_3
      value: 5.795
    - type: map_at_5
      value: 6.7940000000000005
    - type: mrr_at_1
      value: 33.437
    - type: mrr_at_10
      value: 42.714
    - type: mrr_at_100
      value: 43.322
    - type: mrr_at_1000
      value: 43.387
    - type: mrr_at_3
      value: 39.732
    - type: mrr_at_5
      value: 41.914
    - type: ndcg_at_1
      value: 31.424000000000003
    - type: ndcg_at_10
      value: 24.458
    - type: ndcg_at_100
      value: 22.656000000000002
    - type: ndcg_at_1000
      value: 32.381
    - type: ndcg_at_3
      value: 27.326
    - type: ndcg_at_5
      value: 26.680999999999997
    - type: precision_at_1
      value: 33.437
    - type: precision_at_10
      value: 18.39
    - type: precision_at_100
      value: 6.328
    - type: precision_at_1000
      value: 1.984
    - type: precision_at_3
      value: 26.006
    - type: precision_at_5
      value: 23.406
    - type: recall_at_1
      value: 3.676
    - type: recall_at_10
      value: 11.702
    - type: recall_at_100
      value: 24.608
    - type: recall_at_1000
      value: 59.004
    - type: recall_at_3
      value: 7.112
    - type: recall_at_5
      value: 9.462
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.774999999999999
    - type: map_at_10
      value: 14.562
    - type: map_at_100
      value: 15.767000000000001
    - type: map_at_1000
      value: 15.870000000000001
    - type: map_at_3
      value: 12.216000000000001
    - type: map_at_5
      value: 13.455
    - type: mrr_at_1
      value: 9.936
    - type: mrr_at_10
      value: 16.105
    - type: mrr_at_100
      value: 17.255000000000003
    - type: mrr_at_1000
      value: 17.339
    - type: mrr_at_3
      value: 13.654
    - type: mrr_at_5
      value: 14.968
    - type: ndcg_at_1
      value: 9.936
    - type: ndcg_at_10
      value: 18.602
    - type: ndcg_at_100
      value: 24.797
    - type: ndcg_at_1000
      value: 27.609
    - type: ndcg_at_3
      value: 13.700999999999999
    - type: ndcg_at_5
      value: 15.93
    - type: precision_at_1
      value: 9.936
    - type: precision_at_10
      value: 3.4939999999999998
    - type: precision_at_100
      value: 0.7000000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 6.383
    - type: precision_at_5
      value: 5.075
    - type: recall_at_1
      value: 8.774999999999999
    - type: recall_at_10
      value: 29.751
    - type: recall_at_100
      value: 58.623000000000005
    - type: recall_at_1000
      value: 80.239
    - type: recall_at_3
      value: 16.604
    - type: recall_at_5
      value: 21.799
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.849000000000004
    - type: map_at_10
      value: 76.554
    - type: map_at_100
      value: 77.318
    - type: map_at_1000
      value: 77.35
    - type: map_at_3
      value: 73.658
    - type: map_at_5
      value: 75.402
    - type: mrr_at_1
      value: 73.42
    - type: mrr_at_10
      value: 80.78
    - type: mrr_at_100
      value: 81.004
    - type: mrr_at_1000
      value: 81.009
    - type: mrr_at_3
      value: 79.39699999999999
    - type: mrr_at_5
      value: 80.274
    - type: ndcg_at_1
      value: 73.55000000000001
    - type: ndcg_at_10
      value: 81.15599999999999
    - type: ndcg_at_100
      value: 83.231
    - type: ndcg_at_1000
      value: 83.581
    - type: ndcg_at_3
      value: 77.705
    - type: ndcg_at_5
      value: 79.461
    - type: precision_at_1
      value: 73.55000000000001
    - type: precision_at_10
      value: 12.225
    - type: precision_at_100
      value: 1.462
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.7
    - type: precision_at_5
      value: 22.189999999999998
    - type: recall_at_1
      value: 63.849000000000004
    - type: recall_at_10
      value: 89.888
    - type: recall_at_100
      value: 97.674
    - type: recall_at_1000
      value: 99.636
    - type: recall_at_3
      value: 79.95
    - type: recall_at_5
      value: 84.911
    - type: map_at_1
      value: 2.835
    - type: map_at_10
      value: 6.683999999999999
    - type: map_at_100
      value: 7.9719999999999995
    - type: map_at_1000
      value: 8.216
    - type: map_at_3
      value: 4.856
    - type: map_at_5
      value: 5.702
    - type: mrr_at_1
      value: 14.000000000000002
    - type: mrr_at_10
      value: 21.475
    - type: mrr_at_100
      value: 22.74
    - type: mrr_at_1000
      value: 22.834
    - type: mrr_at_3
      value: 18.917
    - type: mrr_at_5
      value: 20.137
    - type: ndcg_at_1
      value: 14.000000000000002
    - type: ndcg_at_10
      value: 11.935
    - type: ndcg_at_100
      value: 18.062
    - type: ndcg_at_1000
      value: 23.083000000000002
    - type: ndcg_at_3
      value: 11.236
    - type: ndcg_at_5
      value: 9.711
    - type: precision_at_1
      value: 14.000000000000002
    - type: precision_at_10
      value: 6.23
    - type: precision_at_100
      value: 1.518
    - type: precision_at_1000
      value: 0.27299999999999996
    - type: precision_at_3
      value: 10.467
    - type: precision_at_5
      value: 8.459999999999999
    - type: recall_at_1
      value: 2.835
    - type: recall_at_10
      value: 12.620000000000001
    - type: recall_at_100
      value: 30.830000000000002
    - type: recall_at_1000
      value: 55.401999999999994
    - type: recall_at_3
      value: 6.3549999999999995
    - type: recall_at_5
      value: 8.558
    - type: map_at_1
      value: 0.11399999999999999
    - type: map_at_10
      value: 0.749
    - type: map_at_100
      value: 4.265
    - type: map_at_1000
      value: 10.392
    - type: map_at_3
      value: 0.303
    - type: map_at_5
      value: 0.45199999999999996
    - type: mrr_at_1
      value: 46.0
    - type: mrr_at_10
      value: 60.651999999999994
    - type: mrr_at_100
      value: 61.18599999999999
    - type: mrr_at_1000
      value: 61.18599999999999
    - type: mrr_at_3
      value: 56.667
    - type: mrr_at_5
      value: 59.367000000000004
    - type: ndcg_at_1
      value: 43.0
    - type: ndcg_at_10
      value: 40.046
    - type: ndcg_at_100
      value: 31.291000000000004
    - type: ndcg_at_1000
      value: 28.277
    - type: ndcg_at_3
      value: 44.48
    - type: ndcg_at_5
      value: 42.684
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 42.8
    - type: precision_at_100
      value: 33.019999999999996
    - type: precision_at_1000
      value: 13.984
    - type: precision_at_3
      value: 48.667
    - type: precision_at_5
      value: 46.800000000000004
    - type: recall_at_1
      value: 0.11399999999999999
    - type: recall_at_10
      value: 0.9780000000000001
    - type: recall_at_100
      value: 7.105
    - type: recall_at_1000
      value: 27.417
    - type: recall_at_3
      value: 0.346
    - type: recall_at_5
      value: 0.5479999999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.62306630082035
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 45.094055344099466
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.60485813657951
    - type: cos_sim_spearman
      value: 67.55018251099548
    - type: euclidean_pearson
      value: 72.54046568178227
    - type: euclidean_spearman
      value: 67.55019006488925
    - type: manhattan_pearson
      value: 69.6762686221389
    - type: manhattan_spearman
      value: 65.26267981325925
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.82523314263273
    - type: cos_sim_spearman
      value: 67.79344024125452
    - type: euclidean_pearson
      value: 70.9783299378683
    - type: euclidean_spearman
      value: 67.79459969769313
    - type: manhattan_pearson
      value: 70.12828880808506
    - type: manhattan_spearman
      value: 67.73698113382844
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.43471334909646
    - type: cos_sim_spearman
      value: 78.87612165161259
    - type: euclidean_pearson
      value: 78.51433127433613
    - type: euclidean_spearman
      value: 78.87613383277751
    - type: manhattan_pearson
      value: 78.60881303718293
    - type: manhattan_spearman
      value: 79.09512930090479
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.97539508509726
    - type: cos_sim_spearman
      value: 74.75819046899458
    - type: euclidean_pearson
      value: 77.12281177184511
    - type: euclidean_spearman
      value: 74.7581807777114
    - type: manhattan_pearson
      value: 76.26704335508094
    - type: manhattan_spearman
      value: 74.34393206667237
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.85922976490097
    - type: cos_sim_spearman
      value: 81.84645055567681
    - type: euclidean_pearson
      value: 81.81830833050186
    - type: euclidean_spearman
      value: 81.8464588106734
    - type: manhattan_pearson
      value: 81.84644569552097
    - type: manhattan_spearman
      value: 82.07418063887212
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.29500455505787
    - type: cos_sim_spearman
      value: 77.62306117264794
    - type: euclidean_pearson
      value: 77.17400157807901
    - type: euclidean_spearman
      value: 77.62361139017713
    - type: manhattan_pearson
      value: 77.47217811108837
    - type: manhattan_spearman
      value: 77.97210958449658
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.05858425825969
    - type: cos_sim_spearman
      value: 85.20355984500516
    - type: euclidean_pearson
      value: 85.13424143442064
    - type: euclidean_spearman
      value: 85.20443331883615
    - type: manhattan_pearson
      value: 85.38984808229498
    - type: manhattan_spearman
      value: 86.08189549444803
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.81457561891979
    - type: cos_sim_spearman
      value: 59.85388868480853
    - type: euclidean_pearson
      value: 62.69073748353527
    - type: euclidean_spearman
      value: 59.85388868480853
    - type: manhattan_pearson
      value: 62.22005303389897
    - type: manhattan_spearman
      value: 60.41700166909821
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.86417632861593
    - type: cos_sim_spearman
      value: 76.40396426411002
    - type: euclidean_pearson
      value: 77.91668686082956
    - type: euclidean_spearman
      value: 76.40398273149863
    - type: manhattan_pearson
      value: 77.23413224696387
    - type: manhattan_spearman
      value: 75.8417428842207
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.11890674541019
    - type: mrr
      value: 90.97487570526785
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 36.306
    - type: map_at_10
      value: 43.081
    - type: map_at_100
      value: 44.352999999999994
    - type: map_at_1000
      value: 44.409
    - type: map_at_3
      value: 40.713
    - type: map_at_5
      value: 42.019
    - type: mrr_at_1
      value: 38.333
    - type: mrr_at_10
      value: 44.721
    - type: mrr_at_100
      value: 45.83
    - type: mrr_at_1000
      value: 45.879
    - type: mrr_at_3
      value: 42.722
    - type: mrr_at_5
      value: 43.739
    - type: ndcg_at_1
      value: 38.333
    - type: ndcg_at_10
      value: 47.152
    - type: ndcg_at_100
      value: 53.137
    - type: ndcg_at_1000
      value: 54.642
    - type: ndcg_at_3
      value: 42.614000000000004
    - type: ndcg_at_5
      value: 44.649
    - type: precision_at_1
      value: 38.333
    - type: precision_at_10
      value: 6.433
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 16.556
    - type: precision_at_5
      value: 11.067
    - type: recall_at_1
      value: 36.306
    - type: recall_at_10
      value: 58.306000000000004
    - type: recall_at_100
      value: 85.68299999999999
    - type: recall_at_1000
      value: 97.467
    - type: recall_at_3
      value: 45.889
    - type: recall_at_5
      value: 50.833
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.67821782178218
    - type: cos_sim_ap
      value: 89.88249977581106
    - type: cos_sim_f1
      value: 83.24270884824519
    - type: cos_sim_precision
      value: 82.3069403714565
    - type: cos_sim_recall
      value: 84.2
    - type: dot_accuracy
      value: 99.67821782178218
    - type: dot_ap
      value: 89.88249977581106
    - type: dot_f1
      value: 83.24270884824519
    - type: dot_precision
      value: 82.3069403714565
    - type: dot_recall
      value: 84.2
    - type: euclidean_accuracy
      value: 99.67821782178218
    - type: euclidean_ap
      value: 89.88249977581106
    - type: euclidean_f1
      value: 83.24270884824519
    - type: euclidean_precision
      value: 82.3069403714565
    - type: euclidean_recall
      value: 84.2
    - type: manhattan_accuracy
      value: 99.74653465346535
    - type: manhattan_ap
      value: 92.47796158955659
    - type: manhattan_f1
      value: 86.55462184873949
    - type: manhattan_precision
      value: 91.1504424778761
    - type: manhattan_recall
      value: 82.39999999999999
    - type: max_accuracy
      value: 99.74653465346535
    - type: max_ap
      value: 92.47796158955659
    - type: max_f1
      value: 86.55462184873949
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 41.72268428949898
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.535996461064713
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.41913643582162
    - type: mrr
      value: 43.91500350140056
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.332915201869763
    - type: cos_sim_spearman
      value: 30.291662163948462
    - type: dot_pearson
      value: 30.332915151592584
    - type: dot_spearman
      value: 30.1834748432304
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.067
    - type: map_at_10
      value: 8.561
    - type: map_at_100
      value: 14.677999999999999
    - type: map_at_1000
      value: 16.313
    - type: map_at_3
      value: 4.481
    - type: map_at_5
      value: 6.081
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 44.07
    - type: mrr_at_100
      value: 45.153
    - type: mrr_at_1000
      value: 45.153
    - type: mrr_at_3
      value: 39.796
    - type: mrr_at_5
      value: 42.653
    - type: ndcg_at_1
      value: 26.531
    - type: ndcg_at_10
      value: 22.528000000000002
    - type: ndcg_at_100
      value: 35.595
    - type: ndcg_at_1000
      value: 46.97
    - type: ndcg_at_3
      value: 25.011
    - type: ndcg_at_5
      value: 23.759
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 20.816000000000003
    - type: precision_at_100
      value: 8.0
    - type: precision_at_1000
      value: 1.529
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 24.082
    - type: recall_at_1
      value: 2.067
    - type: recall_at_10
      value: 14.265
    - type: recall_at_100
      value: 48.504999999999995
    - type: recall_at_1000
      value: 83.176
    - type: recall_at_3
      value: 5.5489999999999995
    - type: recall_at_5
      value: 8.319
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.587
    - type: ap
      value: 13.787371974957502
    - type: f1
      value: 54.112483754025895
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.18788907753254
    - type: f1
      value: 54.373057834087724
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.37540475772647
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.54294569946951
    - type: cos_sim_ap
      value: 64.48967648355864
    - type: cos_sim_f1
      value: 61.59177820267685
    - type: cos_sim_precision
      value: 56.29095674967235
    - type: cos_sim_recall
      value: 67.99472295514512
    - type: dot_accuracy
      value: 83.54294569946951
    - type: dot_ap
      value: 64.48967648355864
    - type: dot_f1
      value: 61.59177820267685
    - type: dot_precision
      value: 56.29095674967235
    - type: dot_recall
      value: 67.99472295514512
    - type: euclidean_accuracy
      value: 83.54294569946951
    - type: euclidean_ap
      value: 64.48967648355864
    - type: euclidean_f1
      value: 61.59177820267685
    - type: euclidean_precision
      value: 56.29095674967235
    - type: euclidean_recall
      value: 67.99472295514512
    - type: manhattan_accuracy
      value: 82.55945639864099
    - type: manhattan_ap
      value: 61.57762963239964
    - type: manhattan_f1
      value: 59.04949519822704
    - type: manhattan_precision
      value: 55.355493998153285
    - type: manhattan_recall
      value: 63.27176781002638
    - type: max_accuracy
      value: 83.54294569946951
    - type: max_ap
      value: 64.48967648355864
    - type: max_f1
      value: 61.59177820267685
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.61012147320216
    - type: cos_sim_ap
      value: 83.07983490905391
    - type: cos_sim_f1
      value: 75.18353192902202
    - type: cos_sim_precision
      value: 72.17225015935973
    - type: cos_sim_recall
      value: 78.45703726516786
    - type: dot_accuracy
      value: 87.61012147320216
    - type: dot_ap
      value: 83.07984253532115
    - type: dot_f1
      value: 75.18353192902202
    - type: dot_precision
      value: 72.17225015935973
    - type: dot_recall
      value: 78.45703726516786
    - type: euclidean_accuracy
      value: 87.61012147320216
    - type: euclidean_ap
      value: 83.07983413095812
    - type: euclidean_f1
      value: 75.18353192902202
    - type: euclidean_precision
      value: 72.17225015935973
    - type: euclidean_recall
      value: 78.45703726516786
    - type: manhattan_accuracy
      value: 87.58489540885628
    - type: manhattan_ap
      value: 82.95071093691672
    - type: manhattan_f1
      value: 75.19792822789493
    - type: manhattan_precision
      value: 72.37572995299814
    - type: manhattan_recall
      value: 78.2491530643671
    - type: max_accuracy
      value: 87.61012147320216
    - type: max_ap
      value: 83.07984253532115
    - type: max_f1
      value: 75.19792822789493
---
