mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_noabtt
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.07462686567165
    - type: ap
      value: 33.50009567410962
    - type: f1
      value: 64.94019749592687
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 70.35742499999999
    - type: ap
      value: 64.96577354828929
    - type: f1
      value: 70.10173476777325
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 37.744
    - type: f1
      value: 37.1575589065482
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 18.563
    - type: map_at_10
      value: 31.251
    - type: map_at_100
      value: 32.478
    - type: map_at_1000
      value: 32.519999999999996
    - type: map_at_3
      value: 27.156999999999996
    - type: map_at_5
      value: 29.387
    - type: mrr_at_1
      value: 19.061
    - type: mrr_at_10
      value: 31.445
    - type: mrr_at_100
      value: 32.672000000000004
    - type: mrr_at_1000
      value: 32.714
    - type: mrr_at_3
      value: 27.418
    - type: mrr_at_5
      value: 29.662
    - type: ndcg_at_1
      value: 18.563
    - type: ndcg_at_10
      value: 38.474000000000004
    - type: ndcg_at_100
      value: 44.279
    - type: ndcg_at_1000
      value: 45.421
    - type: ndcg_at_3
      value: 29.971999999999998
    - type: ndcg_at_5
      value: 34.003
    - type: precision_at_1
      value: 18.563
    - type: precision_at_10
      value: 6.166
    - type: precision_at_100
      value: 0.8840000000000001
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 12.706999999999999
    - type: precision_at_5
      value: 9.587
    - type: recall_at_1
      value: 18.563
    - type: recall_at_10
      value: 61.663999999999994
    - type: recall_at_100
      value: 88.407
    - type: recall_at_1000
      value: 97.51100000000001
    - type: recall_at_3
      value: 38.122
    - type: recall_at_5
      value: 47.937000000000005
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 32.47300171789877
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.26487242213987
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.31718220593814
    - type: mrr
      value: 66.08055225783758
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 75.59586654520326
    - type: cos_sim_spearman
      value: 74.60772408399097
    - type: euclidean_pearson
      value: 75.11071678890949
    - type: euclidean_spearman
      value: 74.60772408399097
    - type: manhattan_pearson
      value: 77.16315565066256
    - type: manhattan_spearman
      value: 75.86377680038974
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.12012987012987
    - type: f1
      value: 71.41155762297112
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.344363341369984
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 22.546344510374116
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.249000000000002
    - type: map_at_10
      value: 27.677000000000003
    - type: map_at_100
      value: 28.7
    - type: map_at_1000
      value: 28.837000000000003
    - type: map_at_3
      value: 25.672
    - type: map_at_5
      value: 26.679000000000002
    - type: mrr_at_1
      value: 26.753
    - type: mrr_at_10
      value: 33.056000000000004
    - type: mrr_at_100
      value: 33.859
    - type: mrr_at_1000
      value: 33.933
    - type: mrr_at_3
      value: 31.378
    - type: mrr_at_5
      value: 32.144
    - type: ndcg_at_1
      value: 26.753
    - type: ndcg_at_10
      value: 32.106
    - type: ndcg_at_100
      value: 36.842999999999996
    - type: ndcg_at_1000
      value: 39.814
    - type: ndcg_at_3
      value: 29.264000000000003
    - type: ndcg_at_5
      value: 30.220000000000002
    - type: precision_at_1
      value: 26.753
    - type: precision_at_10
      value: 5.9799999999999995
    - type: precision_at_100
      value: 1.04
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 14.163
    - type: precision_at_5
      value: 9.757
    - type: recall_at_1
      value: 21.249000000000002
    - type: recall_at_10
      value: 39.639
    - type: recall_at_100
      value: 60.946
    - type: recall_at_1000
      value: 81.388
    - type: recall_at_3
      value: 30.145
    - type: recall_at_5
      value: 33.735
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.333000000000002
    - type: map_at_10
      value: 21.517
    - type: map_at_100
      value: 22.470000000000002
    - type: map_at_1000
      value: 22.585
    - type: map_at_3
      value: 19.736
    - type: map_at_5
      value: 20.768
    - type: mrr_at_1
      value: 20.701
    - type: mrr_at_10
      value: 25.674000000000003
    - type: mrr_at_100
      value: 26.529999999999998
    - type: mrr_at_1000
      value: 26.604
    - type: mrr_at_3
      value: 23.938000000000002
    - type: mrr_at_5
      value: 24.91
    - type: ndcg_at_1
      value: 20.701
    - type: ndcg_at_10
      value: 25.127
    - type: ndcg_at_100
      value: 29.507
    - type: ndcg_at_1000
      value: 32.299
    - type: ndcg_at_3
      value: 22.142999999999997
    - type: ndcg_at_5
      value: 23.538
    - type: precision_at_1
      value: 20.701
    - type: precision_at_10
      value: 4.675
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 10.594000000000001
    - type: precision_at_5
      value: 7.631
    - type: recall_at_1
      value: 16.333000000000002
    - type: recall_at_10
      value: 31.759999999999998
    - type: recall_at_100
      value: 51.007000000000005
    - type: recall_at_1000
      value: 70.146
    - type: recall_at_3
      value: 22.936
    - type: recall_at_5
      value: 26.723999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.117
    - type: map_at_10
      value: 31.990000000000002
    - type: map_at_100
      value: 32.944
    - type: map_at_1000
      value: 33.036
    - type: map_at_3
      value: 29.720000000000002
    - type: map_at_5
      value: 30.958999999999996
    - type: mrr_at_1
      value: 28.088
    - type: mrr_at_10
      value: 35.333
    - type: mrr_at_100
      value: 36.169000000000004
    - type: mrr_at_1000
      value: 36.231
    - type: mrr_at_3
      value: 33.25
    - type: mrr_at_5
      value: 34.482
    - type: ndcg_at_1
      value: 28.088
    - type: ndcg_at_10
      value: 36.473
    - type: ndcg_at_100
      value: 41.129
    - type: ndcg_at_1000
      value: 43.502
    - type: ndcg_at_3
      value: 32.29
    - type: ndcg_at_5
      value: 34.266000000000005
    - type: precision_at_1
      value: 28.088
    - type: precision_at_10
      value: 5.918
    - type: precision_at_100
      value: 0.8920000000000001
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 14.441
    - type: precision_at_5
      value: 9.981
    - type: recall_at_1
      value: 24.117
    - type: recall_at_10
      value: 46.871
    - type: recall_at_100
      value: 68.003
    - type: recall_at_1000
      value: 85.489
    - type: recall_at_3
      value: 35.5
    - type: recall_at_5
      value: 40.469
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 11.111
    - type: map_at_10
      value: 14.554
    - type: map_at_100
      value: 15.276
    - type: map_at_1000
      value: 15.362
    - type: map_at_3
      value: 13.483999999999998
    - type: map_at_5
      value: 13.894
    - type: mrr_at_1
      value: 12.09
    - type: mrr_at_10
      value: 15.584999999999999
    - type: mrr_at_100
      value: 16.347
    - type: mrr_at_1000
      value: 16.428
    - type: mrr_at_3
      value: 14.539
    - type: mrr_at_5
      value: 14.945
    - type: ndcg_at_1
      value: 12.09
    - type: ndcg_at_10
      value: 16.766000000000002
    - type: ndcg_at_100
      value: 20.8
    - type: ndcg_at_1000
      value: 23.566000000000003
    - type: ndcg_at_3
      value: 14.519000000000002
    - type: ndcg_at_5
      value: 15.228
    - type: precision_at_1
      value: 12.09
    - type: precision_at_10
      value: 2.588
    - type: precision_at_100
      value: 0.485
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_3
      value: 6.101999999999999
    - type: precision_at_5
      value: 4.09
    - type: recall_at_1
      value: 11.111
    - type: recall_at_10
      value: 22.674
    - type: recall_at_100
      value: 42.146
    - type: recall_at_1000
      value: 64.144
    - type: recall_at_3
      value: 16.403000000000002
    - type: recall_at_5
      value: 18.098
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.268
    - type: map_at_10
      value: 9.113
    - type: map_at_100
      value: 9.774
    - type: map_at_1000
      value: 9.882
    - type: map_at_3
      value: 7.9670000000000005
    - type: map_at_5
      value: 8.568000000000001
    - type: mrr_at_1
      value: 8.333
    - type: mrr_at_10
      value: 11.584999999999999
    - type: mrr_at_100
      value: 12.237
    - type: mrr_at_1000
      value: 12.328
    - type: mrr_at_3
      value: 10.22
    - type: mrr_at_5
      value: 10.879
    - type: ndcg_at_1
      value: 8.333
    - type: ndcg_at_10
      value: 11.459
    - type: ndcg_at_100
      value: 15.187999999999999
    - type: ndcg_at_1000
      value: 18.437
    - type: ndcg_at_3
      value: 9.044
    - type: ndcg_at_5
      value: 10.099
    - type: precision_at_1
      value: 8.333
    - type: precision_at_10
      value: 2.189
    - type: precision_at_100
      value: 0.475
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 4.312
    - type: precision_at_5
      value: 3.259
    - type: recall_at_1
      value: 6.268
    - type: recall_at_10
      value: 16.496
    - type: recall_at_100
      value: 33.902
    - type: recall_at_1000
      value: 57.931
    - type: recall_at_3
      value: 9.711
    - type: recall_at_5
      value: 12.434000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.940999999999999
    - type: map_at_10
      value: 21.064
    - type: map_at_100
      value: 22.09
    - type: map_at_1000
      value: 22.226000000000003
    - type: map_at_3
      value: 19.222
    - type: map_at_5
      value: 20.219
    - type: mrr_at_1
      value: 19.923
    - type: mrr_at_10
      value: 25.557000000000002
    - type: mrr_at_100
      value: 26.407999999999998
    - type: mrr_at_1000
      value: 26.496
    - type: mrr_at_3
      value: 23.596
    - type: mrr_at_5
      value: 24.698
    - type: ndcg_at_1
      value: 19.923
    - type: ndcg_at_10
      value: 24.992
    - type: ndcg_at_100
      value: 30.133
    - type: ndcg_at_1000
      value: 33.391
    - type: ndcg_at_3
      value: 21.651
    - type: ndcg_at_5
      value: 23.164
    - type: precision_at_1
      value: 19.923
    - type: precision_at_10
      value: 4.62
    - type: precision_at_100
      value: 0.8699999999999999
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 10.17
    - type: precision_at_5
      value: 7.353
    - type: recall_at_1
      value: 15.940999999999999
    - type: recall_at_10
      value: 32.656
    - type: recall_at_100
      value: 55.566
    - type: recall_at_1000
      value: 78.594
    - type: recall_at_3
      value: 23.055
    - type: recall_at_5
      value: 27.107
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.347
    - type: map_at_10
      value: 15.798000000000002
    - type: map_at_100
      value: 16.59
    - type: map_at_1000
      value: 16.723
    - type: map_at_3
      value: 14.139
    - type: map_at_5
      value: 15.082999999999998
    - type: mrr_at_1
      value: 14.041
    - type: mrr_at_10
      value: 19.03
    - type: mrr_at_100
      value: 19.766000000000002
    - type: mrr_at_1000
      value: 19.858
    - type: mrr_at_3
      value: 17.39
    - type: mrr_at_5
      value: 18.291
    - type: ndcg_at_1
      value: 14.041
    - type: ndcg_at_10
      value: 19.073
    - type: ndcg_at_100
      value: 23.288
    - type: ndcg_at_1000
      value: 26.739
    - type: ndcg_at_3
      value: 16.072
    - type: ndcg_at_5
      value: 17.5
    - type: precision_at_1
      value: 14.041
    - type: precision_at_10
      value: 3.6069999999999998
    - type: precision_at_100
      value: 0.6839999999999999
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 7.763000000000001
    - type: precision_at_5
      value: 5.799
    - type: recall_at_1
      value: 11.347
    - type: recall_at_10
      value: 25.833000000000002
    - type: recall_at_100
      value: 44.791
    - type: recall_at_1000
      value: 69.852
    - type: recall_at_3
      value: 17.605999999999998
    - type: recall_at_5
      value: 21.199
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.168666666666665
    - type: map_at_10
      value: 17.695583333333335
    - type: map_at_100
      value: 18.485000000000003
    - type: map_at_1000
      value: 18.60066666666667
    - type: map_at_3
      value: 16.195749999999997
    - type: map_at_5
      value: 16.985500000000002
    - type: mrr_at_1
      value: 16.058166666666665
    - type: mrr_at_10
      value: 20.69125
    - type: mrr_at_100
      value: 21.420333333333332
    - type: mrr_at_1000
      value: 21.50666666666667
    - type: mrr_at_3
      value: 19.175083333333337
    - type: mrr_at_5
      value: 19.96875
    - type: ndcg_at_1
      value: 16.058166666666665
    - type: ndcg_at_10
      value: 20.829833333333337
    - type: ndcg_at_100
      value: 24.898249999999997
    - type: ndcg_at_1000
      value: 27.985333333333333
    - type: ndcg_at_3
      value: 18.090000000000003
    - type: ndcg_at_5
      value: 19.25925
    - type: precision_at_1
      value: 16.058166666666665
    - type: precision_at_10
      value: 3.709916666666667
    - type: precision_at_100
      value: 0.6790833333333334
    - type: precision_at_1000
      value: 0.11083333333333331
    - type: precision_at_3
      value: 8.4085
    - type: precision_at_5
      value: 5.968416666666667
    - type: recall_at_1
      value: 13.168666666666665
    - type: recall_at_10
      value: 27.38641666666667
    - type: recall_at_100
      value: 46.209083333333325
    - type: recall_at_1000
      value: 68.84049999999999
    - type: recall_at_3
      value: 19.484750000000002
    - type: recall_at_5
      value: 22.63116666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.399000000000001
    - type: map_at_10
      value: 12.901000000000002
    - type: map_at_100
      value: 13.486
    - type: map_at_1000
      value: 13.575000000000001
    - type: map_at_3
      value: 11.732
    - type: map_at_5
      value: 12.256
    - type: mrr_at_1
      value: 11.503
    - type: mrr_at_10
      value: 15.065000000000001
    - type: mrr_at_100
      value: 15.639
    - type: mrr_at_1000
      value: 15.720999999999998
    - type: mrr_at_3
      value: 13.855
    - type: mrr_at_5
      value: 14.430000000000001
    - type: ndcg_at_1
      value: 11.503
    - type: ndcg_at_10
      value: 15.338
    - type: ndcg_at_100
      value: 18.511
    - type: ndcg_at_1000
      value: 21.002000000000002
    - type: ndcg_at_3
      value: 13.094
    - type: ndcg_at_5
      value: 13.883000000000001
    - type: precision_at_1
      value: 11.503
    - type: precision_at_10
      value: 2.638
    - type: precision_at_100
      value: 0.468
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 6.033
    - type: precision_at_5
      value: 4.172
    - type: recall_at_1
      value: 9.399000000000001
    - type: recall_at_10
      value: 20.947
    - type: recall_at_100
      value: 35.878
    - type: recall_at_1000
      value: 54.86299999999999
    - type: recall_at_3
      value: 14.333000000000002
    - type: recall_at_5
      value: 16.475
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.571000000000001
    - type: map_at_10
      value: 9.708
    - type: map_at_100
      value: 10.267999999999999
    - type: map_at_1000
      value: 10.376000000000001
    - type: map_at_3
      value: 8.844000000000001
    - type: map_at_5
      value: 9.253
    - type: mrr_at_1
      value: 8.362
    - type: mrr_at_10
      value: 11.974
    - type: mrr_at_100
      value: 12.547
    - type: mrr_at_1000
      value: 12.64
    - type: mrr_at_3
      value: 11.0
    - type: mrr_at_5
      value: 11.446000000000002
    - type: ndcg_at_1
      value: 8.362
    - type: ndcg_at_10
      value: 11.908000000000001
    - type: ndcg_at_100
      value: 15.151
    - type: ndcg_at_1000
      value: 18.336
    - type: ndcg_at_3
      value: 10.224
    - type: ndcg_at_5
      value: 10.815
    - type: precision_at_1
      value: 8.362
    - type: precision_at_10
      value: 2.278
    - type: precision_at_100
      value: 0.466
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 5.047
    - type: precision_at_5
      value: 3.544
    - type: recall_at_1
      value: 6.571000000000001
    - type: recall_at_10
      value: 16.402
    - type: recall_at_100
      value: 31.904
    - type: recall_at_1000
      value: 55.694
    - type: recall_at_3
      value: 11.476
    - type: recall_at_5
      value: 13.094
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.536
    - type: map_at_10
      value: 16.276
    - type: map_at_100
      value: 16.936
    - type: map_at_1000
      value: 17.047
    - type: map_at_3
      value: 15.018999999999998
    - type: map_at_5
      value: 15.659
    - type: mrr_at_1
      value: 14.924999999999999
    - type: mrr_at_10
      value: 18.979
    - type: mrr_at_100
      value: 19.654
    - type: mrr_at_1000
      value: 19.753
    - type: mrr_at_3
      value: 17.537
    - type: mrr_at_5
      value: 18.274
    - type: ndcg_at_1
      value: 14.924999999999999
    - type: ndcg_at_10
      value: 19.0
    - type: ndcg_at_100
      value: 22.648
    - type: ndcg_at_1000
      value: 26.014
    - type: ndcg_at_3
      value: 16.5
    - type: ndcg_at_5
      value: 17.512
    - type: precision_at_1
      value: 14.924999999999999
    - type: precision_at_10
      value: 3.144
    - type: precision_at_100
      value: 0.5559999999999999
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.369000000000001
    - type: precision_at_5
      value: 5.093
    - type: recall_at_1
      value: 12.536
    - type: recall_at_10
      value: 24.886
    - type: recall_at_100
      value: 41.769
    - type: recall_at_1000
      value: 67.163
    - type: recall_at_3
      value: 17.801000000000002
    - type: recall_at_5
      value: 20.464
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.488999999999999
    - type: map_at_10
      value: 19.076999999999998
    - type: map_at_100
      value: 19.907
    - type: map_at_1000
      value: 20.073
    - type: map_at_3
      value: 17.499000000000002
    - type: map_at_5
      value: 18.321
    - type: mrr_at_1
      value: 18.182000000000002
    - type: mrr_at_10
      value: 22.594
    - type: mrr_at_100
      value: 23.285
    - type: mrr_at_1000
      value: 23.388
    - type: mrr_at_3
      value: 21.014
    - type: mrr_at_5
      value: 21.845
    - type: ndcg_at_1
      value: 18.182000000000002
    - type: ndcg_at_10
      value: 22.589000000000002
    - type: ndcg_at_100
      value: 26.525
    - type: ndcg_at_1000
      value: 30.294999999999998
    - type: ndcg_at_3
      value: 19.911
    - type: ndcg_at_5
      value: 21.002000000000002
    - type: precision_at_1
      value: 18.182000000000002
    - type: precision_at_10
      value: 4.387
    - type: precision_at_100
      value: 0.8789999999999999
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 9.486
    - type: precision_at_5
      value: 6.837999999999999
    - type: recall_at_1
      value: 14.488999999999999
    - type: recall_at_10
      value: 28.797
    - type: recall_at_100
      value: 48.058
    - type: recall_at_1000
      value: 74.207
    - type: recall_at_3
      value: 20.575
    - type: recall_at_5
      value: 23.771
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.663
    - type: map_at_10
      value: 12.672
    - type: map_at_100
      value: 13.379
    - type: map_at_1000
      value: 13.486
    - type: map_at_3
      value: 11.315
    - type: map_at_5
      value: 12.167
    - type: mrr_at_1
      value: 9.797
    - type: mrr_at_10
      value: 13.863
    - type: mrr_at_100
      value: 14.603
    - type: mrr_at_1000
      value: 14.7
    - type: mrr_at_3
      value: 12.384
    - type: mrr_at_5
      value: 13.281
    - type: ndcg_at_1
      value: 9.797
    - type: ndcg_at_10
      value: 15.126999999999999
    - type: ndcg_at_100
      value: 19.056
    - type: ndcg_at_1000
      value: 22.429
    - type: ndcg_at_3
      value: 12.368
    - type: ndcg_at_5
      value: 13.883999999999999
    - type: precision_at_1
      value: 9.797
    - type: precision_at_10
      value: 2.495
    - type: precision_at_100
      value: 0.481
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 5.422
    - type: precision_at_5
      value: 4.104
    - type: recall_at_1
      value: 8.663
    - type: recall_at_10
      value: 21.676000000000002
    - type: recall_at_100
      value: 40.538999999999994
    - type: recall_at_1000
      value: 66.61500000000001
    - type: recall_at_3
      value: 14.276
    - type: recall_at_5
      value: 18.004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.491
    - type: map_at_10
      value: 9.945
    - type: map_at_100
      value: 11.288
    - type: map_at_1000
      value: 11.471
    - type: map_at_3
      value: 8.029
    - type: map_at_5
      value: 8.965
    - type: mrr_at_1
      value: 11.922
    - type: mrr_at_10
      value: 19.881999999999998
    - type: mrr_at_100
      value: 21.061
    - type: mrr_at_1000
      value: 21.134
    - type: mrr_at_3
      value: 17.188
    - type: mrr_at_5
      value: 18.641
    - type: ndcg_at_1
      value: 11.922
    - type: ndcg_at_10
      value: 15.045
    - type: ndcg_at_100
      value: 21.368000000000002
    - type: ndcg_at_1000
      value: 25.262
    - type: ndcg_at_3
      value: 11.386000000000001
    - type: ndcg_at_5
      value: 12.662999999999998
    - type: precision_at_1
      value: 11.922
    - type: precision_at_10
      value: 5.114
    - type: precision_at_100
      value: 1.1860000000000002
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 8.817
    - type: precision_at_5
      value: 7.114
    - type: recall_at_1
      value: 5.491
    - type: recall_at_10
      value: 19.466
    - type: recall_at_100
      value: 41.939
    - type: recall_at_1000
      value: 64.396
    - type: recall_at_3
      value: 10.835
    - type: recall_at_5
      value: 14.047
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.594
    - type: map_at_10
      value: 8.442
    - type: map_at_100
      value: 11.575000000000001
    - type: map_at_1000
      value: 12.428
    - type: map_at_3
      value: 5.989
    - type: map_at_5
      value: 7.013999999999999
    - type: mrr_at_1
      value: 35.5
    - type: mrr_at_10
      value: 45.985
    - type: mrr_at_100
      value: 46.79
    - type: mrr_at_1000
      value: 46.821
    - type: mrr_at_3
      value: 43.333
    - type: mrr_at_5
      value: 45.021
    - type: ndcg_at_1
      value: 25.874999999999996
    - type: ndcg_at_10
      value: 21.535
    - type: ndcg_at_100
      value: 24.172
    - type: ndcg_at_1000
      value: 30.525999999999996
    - type: ndcg_at_3
      value: 24.108
    - type: ndcg_at_5
      value: 22.861
    - type: precision_at_1
      value: 35.5
    - type: precision_at_10
      value: 18.975
    - type: precision_at_100
      value: 6.075
    - type: precision_at_1000
      value: 1.323
    - type: precision_at_3
      value: 28.416999999999998
    - type: precision_at_5
      value: 24.7
    - type: recall_at_1
      value: 3.594
    - type: recall_at_10
      value: 13.058
    - type: recall_at_100
      value: 29.7
    - type: recall_at_1000
      value: 50.951
    - type: recall_at_3
      value: 7.485
    - type: recall_at_5
      value: 9.471
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.935
    - type: f1
      value: 39.75131133061496
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.338000000000001
    - type: map_at_10
      value: 21.424000000000003
    - type: map_at_100
      value: 22.314999999999998
    - type: map_at_1000
      value: 22.395
    - type: map_at_3
      value: 19.17
    - type: map_at_5
      value: 20.412
    - type: mrr_at_1
      value: 15.302
    - type: mrr_at_10
      value: 22.759999999999998
    - type: mrr_at_100
      value: 23.647000000000002
    - type: mrr_at_1000
      value: 23.72
    - type: mrr_at_3
      value: 20.395
    - type: mrr_at_5
      value: 21.705
    - type: ndcg_at_1
      value: 15.302
    - type: ndcg_at_10
      value: 25.771
    - type: ndcg_at_100
      value: 30.489
    - type: ndcg_at_1000
      value: 32.722
    - type: ndcg_at_3
      value: 21.077
    - type: ndcg_at_5
      value: 23.326
    - type: precision_at_1
      value: 15.302
    - type: precision_at_10
      value: 4.146
    - type: precision_at_100
      value: 0.6709999999999999
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 9.096
    - type: precision_at_5
      value: 6.6339999999999995
    - type: recall_at_1
      value: 14.338000000000001
    - type: recall_at_10
      value: 38.171
    - type: recall_at_100
      value: 60.540000000000006
    - type: recall_at_1000
      value: 77.86999999999999
    - type: recall_at_3
      value: 25.369999999999997
    - type: recall_at_5
      value: 30.795
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.959
    - type: map_at_10
      value: 9.366
    - type: map_at_100
      value: 10.231
    - type: map_at_1000
      value: 10.41
    - type: map_at_3
      value: 8.049000000000001
    - type: map_at_5
      value: 8.687000000000001
    - type: mrr_at_1
      value: 11.883000000000001
    - type: mrr_at_10
      value: 16.502
    - type: mrr_at_100
      value: 17.419
    - type: mrr_at_1000
      value: 17.528
    - type: mrr_at_3
      value: 14.943000000000001
    - type: mrr_at_5
      value: 15.754000000000001
    - type: ndcg_at_1
      value: 11.883000000000001
    - type: ndcg_at_10
      value: 12.85
    - type: ndcg_at_100
      value: 17.351
    - type: ndcg_at_1000
      value: 21.794
    - type: ndcg_at_3
      value: 10.898
    - type: ndcg_at_5
      value: 11.489
    - type: precision_at_1
      value: 11.883000000000001
    - type: precision_at_10
      value: 3.565
    - type: precision_at_100
      value: 0.818
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 7.1499999999999995
    - type: precision_at_5
      value: 5.247
    - type: recall_at_1
      value: 5.959
    - type: recall_at_10
      value: 16.46
    - type: recall_at_100
      value: 33.967999999999996
    - type: recall_at_1000
      value: 62.300999999999995
    - type: recall_at_3
      value: 10.09
    - type: recall_at_5
      value: 12.520999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 16.509
    - type: map_at_10
      value: 23.330000000000002
    - type: map_at_100
      value: 24.178
    - type: map_at_1000
      value: 24.288
    - type: map_at_3
      value: 21.436
    - type: map_at_5
      value: 22.534000000000002
    - type: mrr_at_1
      value: 33.018
    - type: mrr_at_10
      value: 40.089999999999996
    - type: mrr_at_100
      value: 40.82
    - type: mrr_at_1000
      value: 40.879
    - type: mrr_at_3
      value: 38.285000000000004
    - type: mrr_at_5
      value: 39.315
    - type: ndcg_at_1
      value: 33.018
    - type: ndcg_at_10
      value: 29.936
    - type: ndcg_at_100
      value: 34.015
    - type: ndcg_at_1000
      value: 36.714999999999996
    - type: ndcg_at_3
      value: 26.387
    - type: ndcg_at_5
      value: 28.168
    - type: precision_at_1
      value: 33.018
    - type: precision_at_10
      value: 6.614000000000001
    - type: precision_at_100
      value: 0.9900000000000001
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 16.714000000000002
    - type: precision_at_5
      value: 11.437999999999999
    - type: recall_at_1
      value: 16.509
    - type: recall_at_10
      value: 33.072
    - type: recall_at_100
      value: 49.507
    - type: recall_at_1000
      value: 67.61
    - type: recall_at_3
      value: 25.070999999999998
    - type: recall_at_5
      value: 28.596
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 68.22359999999999
    - type: ap
      value: 62.61788088243551
    - type: f1
      value: 68.12275573843208
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.094
    - type: map_at_10
      value: 10.42
    - type: map_at_100
      value: 11.294
    - type: map_at_1000
      value: 11.391
    - type: map_at_3
      value: 8.767
    - type: map_at_5
      value: 9.611
    - type: mrr_at_1
      value: 6.318
    - type: mrr_at_10
      value: 10.729
    - type: mrr_at_100
      value: 11.612
    - type: mrr_at_1000
      value: 11.706
    - type: mrr_at_3
      value: 9.049999999999999
    - type: mrr_at_5
      value: 9.919
    - type: ndcg_at_1
      value: 6.304
    - type: ndcg_at_10
      value: 13.241
    - type: ndcg_at_100
      value: 17.977
    - type: ndcg_at_1000
      value: 20.965
    - type: ndcg_at_3
      value: 9.743
    - type: ndcg_at_5
      value: 11.275
    - type: precision_at_1
      value: 6.304
    - type: precision_at_10
      value: 2.2950000000000004
    - type: precision_at_100
      value: 0.47400000000000003
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 4.26
    - type: precision_at_5
      value: 3.3300000000000005
    - type: recall_at_1
      value: 6.094
    - type: recall_at_10
      value: 22.056
    - type: recall_at_100
      value: 45.092
    - type: recall_at_1000
      value: 69.169
    - type: recall_at_3
      value: 12.309000000000001
    - type: recall_at_5
      value: 16.003
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.83948928408574
    - type: f1
      value: 88.17547793768752
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 61.181030551755576
    - type: f1
      value: 42.11062876335908
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 64.18964357767318
    - type: f1
      value: 62.0477878647256
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.7901815736382
    - type: f1
      value: 69.20926608450402
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.957591249143125
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.7836417376295
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.26767729140636
    - type: mrr
      value: 29.156549403525638
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.184
    - type: map_at_10
      value: 7.244000000000001
    - type: map_at_100
      value: 8.914
    - type: map_at_1000
      value: 10.051
    - type: map_at_3
      value: 5.843
    - type: map_at_5
      value: 6.474
    - type: mrr_at_1
      value: 31.889
    - type: mrr_at_10
      value: 41.205999999999996
    - type: mrr_at_100
      value: 41.964
    - type: mrr_at_1000
      value: 42.038
    - type: mrr_at_3
      value: 38.7
    - type: mrr_at_5
      value: 40.325
    - type: ndcg_at_1
      value: 29.876
    - type: ndcg_at_10
      value: 22.332
    - type: ndcg_at_100
      value: 21.098
    - type: ndcg_at_1000
      value: 30.534
    - type: ndcg_at_3
      value: 25.811
    - type: ndcg_at_5
      value: 24.169999999999998
    - type: precision_at_1
      value: 31.889
    - type: precision_at_10
      value: 15.851
    - type: precision_at_100
      value: 5.628
    - type: precision_at_1000
      value: 1.8419999999999999
    - type: precision_at_3
      value: 23.942
    - type: precision_at_5
      value: 20.061999999999998
    - type: recall_at_1
      value: 4.184
    - type: recall_at_10
      value: 10.85
    - type: recall_at_100
      value: 22.869999999999997
    - type: recall_at_1000
      value: 56.22200000000001
    - type: recall_at_3
      value: 6.65
    - type: recall_at_5
      value: 8.237
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.133
    - type: map_at_10
      value: 14.099999999999998
    - type: map_at_100
      value: 15.186
    - type: map_at_1000
      value: 15.289
    - type: map_at_3
      value: 11.755
    - type: map_at_5
      value: 12.967
    - type: mrr_at_1
      value: 9.154
    - type: mrr_at_10
      value: 15.473999999999998
    - type: mrr_at_100
      value: 16.503
    - type: mrr_at_1000
      value: 16.59
    - type: mrr_at_3
      value: 13.001999999999999
    - type: mrr_at_5
      value: 14.341999999999999
    - type: ndcg_at_1
      value: 9.154
    - type: ndcg_at_10
      value: 18.119
    - type: ndcg_at_100
      value: 23.821
    - type: ndcg_at_1000
      value: 26.726
    - type: ndcg_at_3
      value: 13.222000000000001
    - type: ndcg_at_5
      value: 15.431000000000001
    - type: precision_at_1
      value: 9.154
    - type: precision_at_10
      value: 3.4389999999999996
    - type: precision_at_100
      value: 0.6709999999999999
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.199000000000001
    - type: precision_at_5
      value: 4.942
    - type: recall_at_1
      value: 8.133
    - type: recall_at_10
      value: 29.331000000000003
    - type: recall_at_100
      value: 56.175
    - type: recall_at_1000
      value: 78.621
    - type: recall_at_3
      value: 16.250999999999998
    - type: recall_at_5
      value: 21.389
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.604000000000006
    - type: map_at_10
      value: 73.765
    - type: map_at_100
      value: 74.556
    - type: map_at_1000
      value: 74.595
    - type: map_at_3
      value: 70.962
    - type: map_at_5
      value: 72.63300000000001
    - type: mrr_at_1
      value: 71.0
    - type: mrr_at_10
      value: 78.304
    - type: mrr_at_100
      value: 78.586
    - type: mrr_at_1000
      value: 78.594
    - type: mrr_at_3
      value: 76.80799999999999
    - type: mrr_at_5
      value: 77.779
    - type: ndcg_at_1
      value: 71.1
    - type: ndcg_at_10
      value: 78.48
    - type: ndcg_at_100
      value: 80.792
    - type: ndcg_at_1000
      value: 81.294
    - type: ndcg_at_3
      value: 74.956
    - type: ndcg_at_5
      value: 76.742
    - type: precision_at_1
      value: 71.1
    - type: precision_at_10
      value: 11.819
    - type: precision_at_100
      value: 1.428
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 32.45
    - type: precision_at_5
      value: 21.398
    - type: recall_at_1
      value: 61.604000000000006
    - type: recall_at_10
      value: 87.394
    - type: recall_at_100
      value: 96.301
    - type: recall_at_1000
      value: 99.262
    - type: recall_at_3
      value: 77.168
    - type: recall_at_5
      value: 82.24000000000001
    - type: map_at_1
      value: 2.54
    - type: map_at_10
      value: 5.949999999999999
    - type: map_at_100
      value: 7.1129999999999995
    - type: map_at_1000
      value: 7.324999999999999
    - type: map_at_3
      value: 4.373
    - type: map_at_5
      value: 5.176
    - type: mrr_at_1
      value: 12.5
    - type: mrr_at_10
      value: 19.913
    - type: mrr_at_100
      value: 21.109
    - type: mrr_at_1000
      value: 21.203
    - type: mrr_at_3
      value: 17.1
    - type: mrr_at_5
      value: 18.815
    - type: ndcg_at_1
      value: 12.5
    - type: ndcg_at_10
      value: 10.861
    - type: ndcg_at_100
      value: 16.451999999999998
    - type: ndcg_at_1000
      value: 21.203
    - type: ndcg_at_3
      value: 10.062999999999999
    - type: ndcg_at_5
      value: 8.993
    - type: precision_at_1
      value: 12.5
    - type: precision_at_10
      value: 5.67
    - type: precision_at_100
      value: 1.38
    - type: precision_at_1000
      value: 0.254
    - type: precision_at_3
      value: 9.3
    - type: precision_at_5
      value: 7.960000000000001
    - type: recall_at_1
      value: 2.54
    - type: recall_at_10
      value: 11.498
    - type: recall_at_100
      value: 28.027
    - type: recall_at_1000
      value: 51.538
    - type: recall_at_3
      value: 5.66
    - type: recall_at_5
      value: 8.05
    - type: map_at_1
      value: 0.11399999999999999
    - type: map_at_10
      value: 0.712
    - type: map_at_100
      value: 3.5450000000000004
    - type: map_at_1000
      value: 8.892
    - type: map_at_3
      value: 0.265
    - type: map_at_5
      value: 0.41200000000000003
    - type: mrr_at_1
      value: 50.0
    - type: mrr_at_10
      value: 60.705
    - type: mrr_at_100
      value: 61.346000000000004
    - type: mrr_at_1000
      value: 61.346000000000004
    - type: mrr_at_3
      value: 56.667
    - type: mrr_at_5
      value: 59.267
    - type: ndcg_at_1
      value: 42.0
    - type: ndcg_at_10
      value: 39.35
    - type: ndcg_at_100
      value: 29.799999999999997
    - type: ndcg_at_1000
      value: 26.971
    - type: ndcg_at_3
      value: 40.888000000000005
    - type: ndcg_at_5
      value: 41.197
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 43.4
    - type: precision_at_100
      value: 31.22
    - type: precision_at_1000
      value: 13.206000000000001
    - type: precision_at_3
      value: 45.333
    - type: precision_at_5
      value: 46.0
    - type: recall_at_1
      value: 0.11399999999999999
    - type: recall_at_10
      value: 0.988
    - type: recall_at_100
      value: 6.576
    - type: recall_at_1000
      value: 26.212000000000003
    - type: recall_at_3
      value: 0.294
    - type: recall_at_5
      value: 0.514
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 31.338220199578554
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 40.325683029312046
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.20682984602023
    - type: cos_sim_spearman
      value: 67.35097584082362
    - type: euclidean_pearson
      value: 72.52260527885531
    - type: euclidean_spearman
      value: 67.35114336163551
    - type: manhattan_pearson
      value: 69.63863975989145
    - type: manhattan_spearman
      value: 65.02547526652067
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 71.05647805173803
    - type: cos_sim_spearman
      value: 63.18217786548185
    - type: euclidean_pearson
      value: 67.74142832925921
    - type: euclidean_spearman
      value: 63.183417576357705
    - type: manhattan_pearson
      value: 68.84684674085601
    - type: manhattan_spearman
      value: 64.90346494119913
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.13286673739663
    - type: cos_sim_spearman
      value: 77.7543440807716
    - type: euclidean_pearson
      value: 77.45575885153325
    - type: euclidean_spearman
      value: 77.7543818952591
    - type: manhattan_pearson
      value: 78.53266387038217
    - type: manhattan_spearman
      value: 79.06679464386961
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.06132087749309
    - type: cos_sim_spearman
      value: 73.08921942367398
    - type: euclidean_pearson
      value: 75.79922605048824
    - type: euclidean_spearman
      value: 73.08920973438467
    - type: manhattan_pearson
      value: 75.87870447341405
    - type: manhattan_spearman
      value: 73.58401651924679
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 77.29002016771014
    - type: cos_sim_spearman
      value: 79.07933600906055
    - type: euclidean_pearson
      value: 79.27807382103967
    - type: euclidean_spearman
      value: 79.07934229566574
    - type: manhattan_pearson
      value: 80.69826282605507
    - type: manhattan_spearman
      value: 80.81969995289413
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.2513693479355
    - type: cos_sim_spearman
      value: 76.66745115845943
    - type: euclidean_pearson
      value: 76.48085821615652
    - type: euclidean_spearman
      value: 76.66800146535034
    - type: manhattan_pearson
      value: 76.22156101328721
    - type: manhattan_spearman
      value: 76.05717748281052
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.06139749059489
    - type: cos_sim_spearman
      value: 85.44961226631894
    - type: euclidean_pearson
      value: 85.09865397731325
    - type: euclidean_spearman
      value: 85.45048559842137
    - type: manhattan_pearson
      value: 85.34668730968951
    - type: manhattan_spearman
      value: 86.0991933425676
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 53.70397809745454
    - type: cos_sim_spearman
      value: 57.49164639993963
    - type: euclidean_pearson
      value: 57.10081764140929
    - type: euclidean_spearman
      value: 57.49164639993963
    - type: manhattan_pearson
      value: 60.1223075719587
    - type: manhattan_spearman
      value: 58.999981844055924
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 76.20429284013153
    - type: cos_sim_spearman
      value: 75.46585580444099
    - type: euclidean_pearson
      value: 76.96878126891205
    - type: euclidean_spearman
      value: 75.4658742729028
    - type: manhattan_pearson
      value: 76.09950215912873
    - type: manhattan_spearman
      value: 74.29351006444855
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.8984364780628
    - type: mrr
      value: 90.59005083514887
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.139
    - type: map_at_10
      value: 40.749
    - type: map_at_100
      value: 41.778999999999996
    - type: map_at_1000
      value: 41.849
    - type: map_at_3
      value: 38.444
    - type: map_at_5
      value: 39.694
    - type: mrr_at_1
      value: 35.0
    - type: mrr_at_10
      value: 42.501
    - type: mrr_at_100
      value: 43.375
    - type: mrr_at_1000
      value: 43.434
    - type: mrr_at_3
      value: 40.444
    - type: mrr_at_5
      value: 41.577999999999996
    - type: ndcg_at_1
      value: 35.0
    - type: ndcg_at_10
      value: 45.153
    - type: ndcg_at_100
      value: 50.114999999999995
    - type: ndcg_at_1000
      value: 52.074
    - type: ndcg_at_3
      value: 40.662
    - type: ndcg_at_5
      value: 42.739
    - type: precision_at_1
      value: 35.0
    - type: precision_at_10
      value: 6.267
    - type: precision_at_100
      value: 0.907
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 16.222
    - type: precision_at_5
      value: 10.867
    - type: recall_at_1
      value: 33.139
    - type: recall_at_10
      value: 57.260999999999996
    - type: recall_at_100
      value: 80.239
    - type: recall_at_1000
      value: 95.733
    - type: recall_at_3
      value: 44.833
    - type: recall_at_5
      value: 50.0
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.64554455445544
    - type: cos_sim_ap
      value: 88.04680322752864
    - type: cos_sim_f1
      value: 81.5005138746146
    - type: cos_sim_precision
      value: 83.82663847780127
    - type: cos_sim_recall
      value: 79.3
    - type: dot_accuracy
      value: 99.64554455445544
    - type: dot_ap
      value: 88.04680322752864
    - type: dot_f1
      value: 81.5005138746146
    - type: dot_precision
      value: 83.82663847780127
    - type: dot_recall
      value: 79.3
    - type: euclidean_accuracy
      value: 99.64554455445544
    - type: euclidean_ap
      value: 88.04680322752864
    - type: euclidean_f1
      value: 81.5005138746146
    - type: euclidean_precision
      value: 83.82663847780127
    - type: euclidean_recall
      value: 79.3
    - type: manhattan_accuracy
      value: 99.76237623762376
    - type: manhattan_ap
      value: 93.44688329620541
    - type: manhattan_f1
      value: 87.66700924974306
    - type: manhattan_precision
      value: 90.16913319238901
    - type: manhattan_recall
      value: 85.3
    - type: max_accuracy
      value: 99.76237623762376
    - type: max_ap
      value: 93.44688329620541
    - type: max_f1
      value: 87.66700924974306
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 40.325339645616445
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 28.341053317548482
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.183294423577806
    - type: mrr
      value: 43.73416412019353
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 32.08507062590542
    - type: cos_sim_spearman
      value: 30.726839502202168
    - type: dot_pearson
      value: 32.08507055463063
    - type: dot_spearman
      value: 30.606596489681966
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.218
    - type: map_at_10
      value: 7.431
    - type: map_at_100
      value: 11.933
    - type: map_at_1000
      value: 13.369
    - type: map_at_3
      value: 4.257
    - type: map_at_5
      value: 6.0089999999999995
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 41.459
    - type: mrr_at_100
      value: 42.421
    - type: mrr_at_1000
      value: 42.421
    - type: mrr_at_3
      value: 37.415
    - type: mrr_at_5
      value: 38.333
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 19.465
    - type: ndcg_at_100
      value: 31.013
    - type: ndcg_at_1000
      value: 42.147
    - type: ndcg_at_3
      value: 23.211000000000002
    - type: ndcg_at_5
      value: 22.148
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 17.143
    - type: precision_at_100
      value: 6.857
    - type: precision_at_1000
      value: 1.39
    - type: precision_at_3
      value: 24.490000000000002
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 2.218
    - type: recall_at_10
      value: 12.159
    - type: recall_at_100
      value: 41.073
    - type: recall_at_1000
      value: 74.899
    - type: recall_at_3
      value: 5.231
    - type: recall_at_5
      value: 8.047
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.7934
    - type: ap
      value: 14.426855843022313
    - type: f1
      value: 54.634287130783854
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 58.684210526315795
    - type: f1
      value: 58.943454482611344
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 31.997934167624948
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.3953030935209
    - type: cos_sim_ap
      value: 67.5453547831567
    - type: cos_sim_f1
      value: 64.68827930174564
    - type: cos_sim_precision
      value: 61.32387706855792
    - type: cos_sim_recall
      value: 68.44327176781002
    - type: dot_accuracy
      value: 84.3953030935209
    - type: dot_ap
      value: 67.5453547831567
    - type: dot_f1
      value: 64.68827930174564
    - type: dot_precision
      value: 61.32387706855792
    - type: dot_recall
      value: 68.44327176781002
    - type: euclidean_accuracy
      value: 84.3953030935209
    - type: euclidean_ap
      value: 67.5453547831567
    - type: euclidean_f1
      value: 64.68827930174564
    - type: euclidean_precision
      value: 61.32387706855792
    - type: euclidean_recall
      value: 68.44327176781002
    - type: manhattan_accuracy
      value: 83.33432675686953
    - type: manhattan_ap
      value: 64.94303732873902
    - type: manhattan_f1
      value: 62.113102164300656
    - type: manhattan_precision
      value: 55.5578684429642
    - type: manhattan_recall
      value: 70.42216358839049
    - type: max_accuracy
      value: 84.3953030935209
    - type: max_ap
      value: 67.5453547831567
    - type: max_f1
      value: 64.68827930174564
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.63728800403618
    - type: cos_sim_ap
      value: 82.87900370539121
    - type: cos_sim_f1
      value: 75.31482436114588
    - type: cos_sim_precision
      value: 72.17360621030345
    - type: cos_sim_recall
      value: 78.7419156144133
    - type: dot_accuracy
      value: 87.63728800403618
    - type: dot_ap
      value: 82.87900355677051
    - type: dot_f1
      value: 75.31482436114588
    - type: dot_precision
      value: 72.17360621030345
    - type: dot_recall
      value: 78.7419156144133
    - type: euclidean_accuracy
      value: 87.63728800403618
    - type: euclidean_ap
      value: 82.87900370539121
    - type: euclidean_f1
      value: 75.31482436114588
    - type: euclidean_precision
      value: 72.17360621030345
    - type: euclidean_recall
      value: 78.7419156144133
    - type: manhattan_accuracy
      value: 87.78282299064695
    - type: manhattan_ap
      value: 83.28196017917277
    - type: manhattan_f1
      value: 75.69079315359659
    - type: manhattan_precision
      value: 73.38925446525417
    - type: manhattan_recall
      value: 78.1413612565445
    - type: max_accuracy
      value: 87.78282299064695
    - type: max_ap
      value: 83.28196017917277
    - type: max_f1
      value: 75.69079315359659
---
