mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_noPCA
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 69.5223880597015
    - type: ap
      value: 32.188029961997856
    - type: f1
      value: 63.507035721662255
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 69.82842500000001
    - type: ap
      value: 65.05751252754372
    - type: f1
      value: 69.20990625365141
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 36.588
    - type: f1
      value: 35.418251249983605
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 14.793999999999999
    - type: map_at_10
      value: 25.576999999999998
    - type: map_at_100
      value: 26.693
    - type: map_at_1000
      value: 26.756
    - type: map_at_3
      value: 22.451
    - type: map_at_5
      value: 24.093999999999998
    - type: mrr_at_1
      value: 15.22
    - type: mrr_at_10
      value: 25.743
    - type: mrr_at_100
      value: 26.86
    - type: mrr_at_1000
      value: 26.922
    - type: mrr_at_3
      value: 22.582
    - type: mrr_at_5
      value: 24.275
    - type: ndcg_at_1
      value: 14.793999999999999
    - type: ndcg_at_10
      value: 31.554
    - type: ndcg_at_100
      value: 37.367
    - type: ndcg_at_1000
      value: 39.156
    - type: ndcg_at_3
      value: 25.044
    - type: ndcg_at_5
      value: 28.019
    - type: precision_at_1
      value: 14.793999999999999
    - type: precision_at_10
      value: 5.064
    - type: precision_at_100
      value: 0.787
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 10.857999999999999
    - type: precision_at_5
      value: 7.965999999999999
    - type: recall_at_1
      value: 14.793999999999999
    - type: recall_at_10
      value: 50.63999999999999
    - type: recall_at_100
      value: 78.73400000000001
    - type: recall_at_1000
      value: 93.172
    - type: recall_at_3
      value: 32.574999999999996
    - type: recall_at_5
      value: 39.829
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 30.971489779907653
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 21.568018798597137
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 49.98416553839047
    - type: mrr
      value: 64.6418678274634
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 49.466850107369204
    - type: cos_sim_spearman
      value: 57.07419204044854
    - type: euclidean_pearson
      value: 52.9281249064291
    - type: euclidean_spearman
      value: 57.07419204044854
    - type: manhattan_pearson
      value: 53.02817511738712
    - type: manhattan_spearman
      value: 57.26395540047999
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 62.948051948051955
    - type: f1
      value: 61.58649884446328
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 29.961219232394214
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 20.82397852889056
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 19.189999999999998
    - type: map_at_10
      value: 25.446999999999996
    - type: map_at_100
      value: 26.392
    - type: map_at_1000
      value: 26.548
    - type: map_at_3
      value: 23.368
    - type: map_at_5
      value: 24.65
    - type: mrr_at_1
      value: 24.464
    - type: mrr_at_10
      value: 30.43
    - type: mrr_at_100
      value: 31.217
    - type: mrr_at_1000
      value: 31.313999999999997
    - type: mrr_at_3
      value: 28.732000000000003
    - type: mrr_at_5
      value: 29.797
    - type: ndcg_at_1
      value: 24.464
    - type: ndcg_at_10
      value: 29.677
    - type: ndcg_at_100
      value: 34.116
    - type: ndcg_at_1000
      value: 37.489
    - type: ndcg_at_3
      value: 26.755000000000003
    - type: ndcg_at_5
      value: 28.249999999999996
    - type: precision_at_1
      value: 24.464
    - type: precision_at_10
      value: 5.5649999999999995
    - type: precision_at_100
      value: 0.979
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 12.876000000000001
    - type: precision_at_5
      value: 9.442
    - type: recall_at_1
      value: 19.189999999999998
    - type: recall_at_10
      value: 37.124
    - type: recall_at_100
      value: 56.796
    - type: recall_at_1000
      value: 79.963
    - type: recall_at_3
      value: 27.982000000000003
    - type: recall_at_5
      value: 32.289
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 14.969
    - type: map_at_10
      value: 20.576
    - type: map_at_100
      value: 21.414
    - type: map_at_1000
      value: 21.523999999999997
    - type: map_at_3
      value: 18.709
    - type: map_at_5
      value: 19.723
    - type: mrr_at_1
      value: 19.363
    - type: mrr_at_10
      value: 24.97
    - type: mrr_at_100
      value: 25.688
    - type: mrr_at_1000
      value: 25.759
    - type: mrr_at_3
      value: 23.067999999999998
    - type: mrr_at_5
      value: 24.105999999999998
    - type: ndcg_at_1
      value: 19.363
    - type: ndcg_at_10
      value: 24.465999999999998
    - type: ndcg_at_100
      value: 28.308
    - type: ndcg_at_1000
      value: 30.989
    - type: ndcg_at_3
      value: 21.285999999999998
    - type: ndcg_at_5
      value: 22.668
    - type: precision_at_1
      value: 19.363
    - type: precision_at_10
      value: 4.713
    - type: precision_at_100
      value: 0.8170000000000001
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 10.34
    - type: precision_at_5
      value: 7.478
    - type: recall_at_1
      value: 14.969
    - type: recall_at_10
      value: 31.616
    - type: recall_at_100
      value: 48.775
    - type: recall_at_1000
      value: 67.186
    - type: recall_at_3
      value: 22.386
    - type: recall_at_5
      value: 26.141
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 23.652
    - type: map_at_10
      value: 31.282
    - type: map_at_100
      value: 32.265
    - type: map_at_1000
      value: 32.362
    - type: map_at_3
      value: 28.918
    - type: map_at_5
      value: 30.227999999999998
    - type: mrr_at_1
      value: 27.461000000000002
    - type: mrr_at_10
      value: 34.54
    - type: mrr_at_100
      value: 35.394999999999996
    - type: mrr_at_1000
      value: 35.458
    - type: mrr_at_3
      value: 32.340999999999994
    - type: mrr_at_5
      value: 33.642
    - type: ndcg_at_1
      value: 27.461000000000002
    - type: ndcg_at_10
      value: 35.715
    - type: ndcg_at_100
      value: 40.328
    - type: ndcg_at_1000
      value: 42.724000000000004
    - type: ndcg_at_3
      value: 31.329
    - type: ndcg_at_5
      value: 33.451
    - type: precision_at_1
      value: 27.461000000000002
    - type: precision_at_10
      value: 5.806
    - type: precision_at_100
      value: 0.8789999999999999
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 13.980999999999998
    - type: precision_at_5
      value: 9.793000000000001
    - type: recall_at_1
      value: 23.652
    - type: recall_at_10
      value: 46.078
    - type: recall_at_100
      value: 66.542
    - type: recall_at_1000
      value: 84.24199999999999
    - type: recall_at_3
      value: 34.237
    - type: recall_at_5
      value: 39.469
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 8.362
    - type: map_at_10
      value: 11.64
    - type: map_at_100
      value: 12.299
    - type: map_at_1000
      value: 12.388
    - type: map_at_3
      value: 10.452
    - type: map_at_5
      value: 11.04
    - type: mrr_at_1
      value: 9.04
    - type: mrr_at_10
      value: 12.45
    - type: mrr_at_100
      value: 13.129
    - type: mrr_at_1000
      value: 13.211999999999998
    - type: mrr_at_3
      value: 11.243
    - type: mrr_at_5
      value: 11.825
    - type: ndcg_at_1
      value: 9.04
    - type: ndcg_at_10
      value: 13.821
    - type: ndcg_at_100
      value: 17.593
    - type: ndcg_at_1000
      value: 20.468
    - type: ndcg_at_3
      value: 11.399
    - type: ndcg_at_5
      value: 12.392
    - type: precision_at_1
      value: 9.04
    - type: precision_at_10
      value: 2.282
    - type: precision_at_100
      value: 0.445
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 4.896
    - type: precision_at_5
      value: 3.5709999999999997
    - type: recall_at_1
      value: 8.362
    - type: recall_at_10
      value: 19.843
    - type: recall_at_100
      value: 38.153
    - type: recall_at_1000
      value: 61.06700000000001
    - type: recall_at_3
      value: 13.296
    - type: recall_at_5
      value: 15.565000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.335
    - type: map_at_10
      value: 8.286
    - type: map_at_100
      value: 8.969000000000001
    - type: map_at_1000
      value: 9.065
    - type: map_at_3
      value: 7.319000000000001
    - type: map_at_5
      value: 7.8020000000000005
    - type: mrr_at_1
      value: 6.965000000000001
    - type: mrr_at_10
      value: 10.523
    - type: mrr_at_100
      value: 11.244
    - type: mrr_at_1000
      value: 11.326
    - type: mrr_at_3
      value: 9.370000000000001
    - type: mrr_at_5
      value: 9.954
    - type: ndcg_at_1
      value: 6.965000000000001
    - type: ndcg_at_10
      value: 10.491
    - type: ndcg_at_100
      value: 14.155000000000001
    - type: ndcg_at_1000
      value: 16.853
    - type: ndcg_at_3
      value: 8.476
    - type: ndcg_at_5
      value: 9.31
    - type: precision_at_1
      value: 6.965000000000001
    - type: precision_at_10
      value: 2.027
    - type: precision_at_100
      value: 0.44999999999999996
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.146
    - type: precision_at_5
      value: 3.06
    - type: recall_at_1
      value: 5.335
    - type: recall_at_10
      value: 15.195
    - type: recall_at_100
      value: 31.796999999999997
    - type: recall_at_1000
      value: 51.55800000000001
    - type: recall_at_3
      value: 9.623
    - type: recall_at_5
      value: 11.667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 13.664000000000001
    - type: map_at_10
      value: 18.562
    - type: map_at_100
      value: 19.586000000000002
    - type: map_at_1000
      value: 19.716
    - type: map_at_3
      value: 16.705000000000002
    - type: map_at_5
      value: 17.733999999999998
    - type: mrr_at_1
      value: 17.421
    - type: mrr_at_10
      value: 22.729
    - type: mrr_at_100
      value: 23.626
    - type: mrr_at_1000
      value: 23.708000000000002
    - type: mrr_at_3
      value: 20.645
    - type: mrr_at_5
      value: 21.770999999999997
    - type: ndcg_at_1
      value: 17.421
    - type: ndcg_at_10
      value: 22.342000000000002
    - type: ndcg_at_100
      value: 27.556000000000004
    - type: ndcg_at_1000
      value: 30.805
    - type: ndcg_at_3
      value: 18.962
    - type: ndcg_at_5
      value: 20.469
    - type: precision_at_1
      value: 17.421
    - type: precision_at_10
      value: 4.2540000000000004
    - type: precision_at_100
      value: 0.831
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 9.014999999999999
    - type: precision_at_5
      value: 6.564
    - type: recall_at_1
      value: 13.664000000000001
    - type: recall_at_10
      value: 29.945
    - type: recall_at_100
      value: 53.376999999999995
    - type: recall_at_1000
      value: 76.566
    - type: recall_at_3
      value: 20.183999999999997
    - type: recall_at_5
      value: 24.331
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.358
    - type: map_at_10
      value: 14.518
    - type: map_at_100
      value: 15.289
    - type: map_at_1000
      value: 15.418999999999999
    - type: map_at_3
      value: 12.818
    - type: map_at_5
      value: 13.750000000000002
    - type: mrr_at_1
      value: 12.9
    - type: mrr_at_10
      value: 17.366
    - type: mrr_at_100
      value: 18.116
    - type: mrr_at_1000
      value: 18.211
    - type: mrr_at_3
      value: 15.772
    - type: mrr_at_5
      value: 16.611
    - type: ndcg_at_1
      value: 12.9
    - type: ndcg_at_10
      value: 17.554
    - type: ndcg_at_100
      value: 21.823
    - type: ndcg_at_1000
      value: 25.258000000000003
    - type: ndcg_at_3
      value: 14.533
    - type: ndcg_at_5
      value: 15.885
    - type: precision_at_1
      value: 12.9
    - type: precision_at_10
      value: 3.39
    - type: precision_at_100
      value: 0.659
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 6.8870000000000005
    - type: precision_at_5
      value: 5.137
    - type: recall_at_1
      value: 10.358
    - type: recall_at_10
      value: 23.904
    - type: recall_at_100
      value: 43.437
    - type: recall_at_1000
      value: 68.142
    - type: recall_at_3
      value: 15.834999999999999
    - type: recall_at_5
      value: 19.201999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 11.687750000000001
    - type: map_at_10
      value: 16.009916666666665
    - type: map_at_100
      value: 16.77191666666667
    - type: map_at_1000
      value: 16.886333333333333
    - type: map_at_3
      value: 14.501916666666665
    - type: map_at_5
      value: 15.308416666666663
    - type: mrr_at_1
      value: 14.372416666666668
    - type: mrr_at_10
      value: 18.827499999999997
    - type: mrr_at_100
      value: 19.551416666666668
    - type: mrr_at_1000
      value: 19.637999999999998
    - type: mrr_at_3
      value: 17.313166666666667
    - type: mrr_at_5
      value: 18.12
    - type: ndcg_at_1
      value: 14.372416666666668
    - type: ndcg_at_10
      value: 19.01425
    - type: ndcg_at_100
      value: 22.99116666666667
    - type: ndcg_at_1000
      value: 26.01925
    - type: ndcg_at_3
      value: 16.268333333333334
    - type: ndcg_at_5
      value: 17.459666666666664
    - type: precision_at_1
      value: 14.372416666666668
    - type: precision_at_10
      value: 3.445166666666666
    - type: precision_at_100
      value: 0.6432499999999998
    - type: precision_at_1000
      value: 0.10583333333333335
    - type: precision_at_3
      value: 7.581499999999999
    - type: precision_at_5
      value: 5.4688333333333325
    - type: recall_at_1
      value: 11.687750000000001
    - type: recall_at_10
      value: 25.38433333333333
    - type: recall_at_100
      value: 43.76141666666666
    - type: recall_at_1000
      value: 65.92333333333332
    - type: recall_at_3
      value: 17.578916666666665
    - type: recall_at_5
      value: 20.69425
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 7.733
    - type: map_at_10
      value: 11.264000000000001
    - type: map_at_100
      value: 11.866
    - type: map_at_1000
      value: 11.953999999999999
    - type: map_at_3
      value: 9.707
    - type: map_at_5
      value: 10.632
    - type: mrr_at_1
      value: 9.663
    - type: mrr_at_10
      value: 13.394
    - type: mrr_at_100
      value: 13.991000000000001
    - type: mrr_at_1000
      value: 14.069999999999999
    - type: mrr_at_3
      value: 11.834999999999999
    - type: mrr_at_5
      value: 12.709999999999999
    - type: ndcg_at_1
      value: 9.663
    - type: ndcg_at_10
      value: 13.956
    - type: ndcg_at_100
      value: 17.143
    - type: ndcg_at_1000
      value: 19.741
    - type: ndcg_at_3
      value: 10.989
    - type: ndcg_at_5
      value: 12.437
    - type: precision_at_1
      value: 9.663
    - type: precision_at_10
      value: 2.561
    - type: precision_at_100
      value: 0.45399999999999996
    - type: precision_at_1000
      value: 0.074
    - type: precision_at_3
      value: 5.164
    - type: precision_at_5
      value: 3.8960000000000004
    - type: recall_at_1
      value: 7.733
    - type: recall_at_10
      value: 20.479
    - type: recall_at_100
      value: 35.349000000000004
    - type: recall_at_1000
      value: 55.38999999999999
    - type: recall_at_3
      value: 12.044
    - type: recall_at_5
      value: 15.831999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.382
    - type: map_at_10
      value: 8.177
    - type: map_at_100
      value: 8.715
    - type: map_at_1000
      value: 8.827
    - type: map_at_3
      value: 7.196
    - type: map_at_5
      value: 7.727
    - type: mrr_at_1
      value: 6.917
    - type: mrr_at_10
      value: 10.183
    - type: mrr_at_100
      value: 10.744
    - type: mrr_at_1000
      value: 10.841000000000001
    - type: mrr_at_3
      value: 9.119
    - type: mrr_at_5
      value: 9.654
    - type: ndcg_at_1
      value: 6.917
    - type: ndcg_at_10
      value: 10.203
    - type: ndcg_at_100
      value: 13.214
    - type: ndcg_at_1000
      value: 16.413
    - type: ndcg_at_3
      value: 8.338
    - type: ndcg_at_5
      value: 9.156
    - type: precision_at_1
      value: 6.917
    - type: precision_at_10
      value: 2.003
    - type: precision_at_100
      value: 0.418
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 4.118
    - type: precision_at_5
      value: 3.09
    - type: recall_at_1
      value: 5.382
    - type: recall_at_10
      value: 14.432
    - type: recall_at_100
      value: 28.605000000000004
    - type: recall_at_1000
      value: 52.38699999999999
    - type: recall_at_3
      value: 9.251
    - type: recall_at_5
      value: 11.339
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.106
    - type: map_at_10
      value: 14.943999999999999
    - type: map_at_100
      value: 15.586
    - type: map_at_1000
      value: 15.690999999999999
    - type: map_at_3
      value: 13.722999999999999
    - type: map_at_5
      value: 14.45
    - type: mrr_at_1
      value: 13.433
    - type: mrr_at_10
      value: 17.608999999999998
    - type: mrr_at_100
      value: 18.297
    - type: mrr_at_1000
      value: 18.393
    - type: mrr_at_3
      value: 16.247
    - type: mrr_at_5
      value: 17.063
    - type: ndcg_at_1
      value: 13.433
    - type: ndcg_at_10
      value: 17.563000000000002
    - type: ndcg_at_100
      value: 21.25
    - type: ndcg_at_1000
      value: 24.296
    - type: ndcg_at_3
      value: 15.214
    - type: ndcg_at_5
      value: 16.387999999999998
    - type: precision_at_1
      value: 13.433
    - type: precision_at_10
      value: 2.9010000000000002
    - type: precision_at_100
      value: 0.532
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 6.872
    - type: precision_at_5
      value: 4.907
    - type: recall_at_1
      value: 11.106
    - type: recall_at_10
      value: 23.131
    - type: recall_at_100
      value: 40.505
    - type: recall_at_1000
      value: 63.135
    - type: recall_at_3
      value: 16.511
    - type: recall_at_5
      value: 19.55
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.153
    - type: map_at_10
      value: 16.474
    - type: map_at_100
      value: 17.294
    - type: map_at_1000
      value: 17.443
    - type: map_at_3
      value: 15.345
    - type: map_at_5
      value: 15.787999999999998
    - type: mrr_at_1
      value: 15.415000000000001
    - type: mrr_at_10
      value: 19.62
    - type: mrr_at_100
      value: 20.392
    - type: mrr_at_1000
      value: 20.485999999999997
    - type: mrr_at_3
      value: 18.511
    - type: mrr_at_5
      value: 19.035
    - type: ndcg_at_1
      value: 15.415000000000001
    - type: ndcg_at_10
      value: 19.377
    - type: ndcg_at_100
      value: 23.538999999999998
    - type: ndcg_at_1000
      value: 27.106
    - type: ndcg_at_3
      value: 17.505000000000003
    - type: ndcg_at_5
      value: 17.979
    - type: precision_at_1
      value: 15.415000000000001
    - type: precision_at_10
      value: 3.696
    - type: precision_at_100
      value: 0.8
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 8.432
    - type: precision_at_5
      value: 5.731
    - type: recall_at_1
      value: 12.153
    - type: recall_at_10
      value: 24.393
    - type: recall_at_100
      value: 44.316
    - type: recall_at_1000
      value: 69.236
    - type: recall_at_3
      value: 18.285999999999998
    - type: recall_at_5
      value: 20.032
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.349
    - type: map_at_10
      value: 10.949
    - type: map_at_100
      value: 11.588
    - type: map_at_1000
      value: 11.699
    - type: map_at_3
      value: 9.763
    - type: map_at_5
      value: 10.177
    - type: mrr_at_1
      value: 9.427000000000001
    - type: mrr_at_10
      value: 12.116
    - type: mrr_at_100
      value: 12.778
    - type: mrr_at_1000
      value: 12.878
    - type: mrr_at_3
      value: 10.875
    - type: mrr_at_5
      value: 11.272
    - type: ndcg_at_1
      value: 9.427000000000001
    - type: ndcg_at_10
      value: 13.006
    - type: ndcg_at_100
      value: 16.869
    - type: ndcg_at_1000
      value: 20.089000000000002
    - type: ndcg_at_3
      value: 10.434000000000001
    - type: ndcg_at_5
      value: 11.131
    - type: precision_at_1
      value: 9.427000000000001
    - type: precision_at_10
      value: 2.144
    - type: precision_at_100
      value: 0.455
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 4.251
    - type: precision_at_5
      value: 2.957
    - type: recall_at_1
      value: 8.349
    - type: recall_at_10
      value: 18.472
    - type: recall_at_100
      value: 37.485
    - type: recall_at_1000
      value: 62.208
    - type: recall_at_3
      value: 11.312
    - type: recall_at_5
      value: 12.914
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 4.817
    - type: map_at_10
      value: 8.848
    - type: map_at_100
      value: 10.052999999999999
    - type: map_at_1000
      value: 10.212
    - type: map_at_3
      value: 7.140000000000001
    - type: map_at_5
      value: 8.04
    - type: mrr_at_1
      value: 11.01
    - type: mrr_at_10
      value: 18.343
    - type: mrr_at_100
      value: 19.442999999999998
    - type: mrr_at_1000
      value: 19.517
    - type: mrr_at_3
      value: 15.733
    - type: mrr_at_5
      value: 17.065
    - type: ndcg_at_1
      value: 11.01
    - type: ndcg_at_10
      value: 13.533000000000001
    - type: ndcg_at_100
      value: 19.312
    - type: ndcg_at_1000
      value: 22.830000000000002
    - type: ndcg_at_3
      value: 10.218
    - type: ndcg_at_5
      value: 11.436
    - type: precision_at_1
      value: 11.01
    - type: precision_at_10
      value: 4.58
    - type: precision_at_100
      value: 1.0699999999999998
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 7.883
    - type: precision_at_5
      value: 6.41
    - type: recall_at_1
      value: 4.817
    - type: recall_at_10
      value: 17.477
    - type: recall_at_100
      value: 38.059
    - type: recall_at_1000
      value: 58.464000000000006
    - type: recall_at_3
      value: 9.588000000000001
    - type: recall_at_5
      value: 12.740000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.213
    - type: map_at_10
      value: 5.106
    - type: map_at_100
      value: 7.088
    - type: map_at_1000
      value: 7.704
    - type: map_at_3
      value: 3.714
    - type: map_at_5
      value: 4.265
    - type: mrr_at_1
      value: 26.0
    - type: mrr_at_10
      value: 36.775999999999996
    - type: mrr_at_100
      value: 37.643
    - type: mrr_at_1000
      value: 37.695
    - type: mrr_at_3
      value: 34.292
    - type: mrr_at_5
      value: 35.754000000000005
    - type: ndcg_at_1
      value: 18.0
    - type: ndcg_at_10
      value: 14.601
    - type: ndcg_at_100
      value: 17.272000000000002
    - type: ndcg_at_1000
      value: 23.013
    - type: ndcg_at_3
      value: 16.767000000000003
    - type: ndcg_at_5
      value: 15.622
    - type: precision_at_1
      value: 26.0
    - type: precision_at_10
      value: 13.15
    - type: precision_at_100
      value: 4.495
    - type: precision_at_1000
      value: 1.0370000000000001
    - type: precision_at_3
      value: 21.333
    - type: precision_at_5
      value: 17.599999999999998
    - type: recall_at_1
      value: 2.213
    - type: recall_at_10
      value: 8.852
    - type: recall_at_100
      value: 22.954
    - type: recall_at_1000
      value: 42.836
    - type: recall_at_3
      value: 4.753
    - type: recall_at_5
      value: 5.957
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 38.765
    - type: f1
      value: 35.41826314285653
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.147
    - type: map_at_10
      value: 17.898
    - type: map_at_100
      value: 18.756
    - type: map_at_1000
      value: 18.843
    - type: map_at_3
      value: 15.85
    - type: map_at_5
      value: 17.008000000000003
    - type: mrr_at_1
      value: 12.870999999999999
    - type: mrr_at_10
      value: 18.928
    - type: mrr_at_100
      value: 19.802
    - type: mrr_at_1000
      value: 19.884
    - type: mrr_at_3
      value: 16.804
    - type: mrr_at_5
      value: 18.0
    - type: ndcg_at_1
      value: 12.870999999999999
    - type: ndcg_at_10
      value: 21.579
    - type: ndcg_at_100
      value: 26.144000000000002
    - type: ndcg_at_1000
      value: 28.698
    - type: ndcg_at_3
      value: 17.339
    - type: ndcg_at_5
      value: 19.419
    - type: precision_at_1
      value: 12.870999999999999
    - type: precision_at_10
      value: 3.4819999999999998
    - type: precision_at_100
      value: 0.596
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 7.396
    - type: precision_at_5
      value: 5.506
    - type: recall_at_1
      value: 12.147
    - type: recall_at_10
      value: 32.232
    - type: recall_at_100
      value: 53.911
    - type: recall_at_1000
      value: 73.883
    - type: recall_at_3
      value: 20.694000000000003
    - type: recall_at_5
      value: 25.689
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.649
    - type: map_at_10
      value: 8.784
    - type: map_at_100
      value: 9.571
    - type: map_at_1000
      value: 9.75
    - type: map_at_3
      value: 7.442
    - type: map_at_5
      value: 8.144
    - type: mrr_at_1
      value: 11.111
    - type: mrr_at_10
      value: 15.584999999999999
    - type: mrr_at_100
      value: 16.356
    - type: mrr_at_1000
      value: 16.471
    - type: mrr_at_3
      value: 13.889000000000001
    - type: mrr_at_5
      value: 14.823
    - type: ndcg_at_1
      value: 11.111
    - type: ndcg_at_10
      value: 12.137
    - type: ndcg_at_100
      value: 16.381
    - type: ndcg_at_1000
      value: 20.915
    - type: ndcg_at_3
      value: 10.045
    - type: ndcg_at_5
      value: 10.850999999999999
    - type: precision_at_1
      value: 11.111
    - type: precision_at_10
      value: 3.4410000000000003
    - type: precision_at_100
      value: 0.7779999999999999
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 6.481000000000001
    - type: precision_at_5
      value: 5.122999999999999
    - type: recall_at_1
      value: 5.649
    - type: recall_at_10
      value: 15.611
    - type: recall_at_100
      value: 32.497
    - type: recall_at_1000
      value: 61.314
    - type: recall_at_3
      value: 9.363000000000001
    - type: recall_at_5
      value: 11.781
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 12.950999999999999
    - type: map_at_10
      value: 17.712
    - type: map_at_100
      value: 18.362000000000002
    - type: map_at_1000
      value: 18.45
    - type: map_at_3
      value: 16.325
    - type: map_at_5
      value: 17.071
    - type: mrr_at_1
      value: 25.901000000000003
    - type: mrr_at_10
      value: 31.275
    - type: mrr_at_100
      value: 31.924999999999997
    - type: mrr_at_1000
      value: 31.988
    - type: mrr_at_3
      value: 29.709999999999997
    - type: mrr_at_5
      value: 30.553
    - type: ndcg_at_1
      value: 25.901000000000003
    - type: ndcg_at_10
      value: 22.958000000000002
    - type: ndcg_at_100
      value: 26.253
    - type: ndcg_at_1000
      value: 28.573999999999998
    - type: ndcg_at_3
      value: 20.175
    - type: ndcg_at_5
      value: 21.468
    - type: precision_at_1
      value: 25.901000000000003
    - type: precision_at_10
      value: 5.055
    - type: precision_at_100
      value: 0.772
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 12.631
    - type: precision_at_5
      value: 8.605
    - type: recall_at_1
      value: 12.950999999999999
    - type: recall_at_10
      value: 25.273
    - type: recall_at_100
      value: 38.589
    - type: recall_at_1000
      value: 54.159
    - type: recall_at_3
      value: 18.947
    - type: recall_at_5
      value: 21.512
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 66.6856
    - type: ap
      value: 61.623516914776424
    - type: f1
      value: 66.36169217459741
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.1339999999999995
    - type: map_at_10
      value: 8.908000000000001
    - type: map_at_100
      value: 9.722999999999999
    - type: map_at_1000
      value: 9.817
    - type: map_at_3
      value: 7.509
    - type: map_at_5
      value: 8.198
    - type: mrr_at_1
      value: 5.3580000000000005
    - type: mrr_at_10
      value: 9.188
    - type: mrr_at_100
      value: 10.012
    - type: mrr_at_1000
      value: 10.104000000000001
    - type: mrr_at_3
      value: 7.758
    - type: mrr_at_5
      value: 8.466
    - type: ndcg_at_1
      value: 5.315
    - type: ndcg_at_10
      value: 11.344
    - type: ndcg_at_100
      value: 15.823
    - type: ndcg_at_1000
      value: 18.701
    - type: ndcg_at_3
      value: 8.372
    - type: ndcg_at_5
      value: 9.625
    - type: precision_at_1
      value: 5.315
    - type: precision_at_10
      value: 1.966
    - type: precision_at_100
      value: 0.42900000000000005
    - type: precision_at_1000
      value: 0.068
    - type: precision_at_3
      value: 3.682
    - type: precision_at_5
      value: 2.834
    - type: recall_at_1
      value: 5.1339999999999995
    - type: recall_at_10
      value: 18.948
    - type: recall_at_100
      value: 40.849999999999994
    - type: recall_at_1000
      value: 64.048
    - type: recall_at_3
      value: 10.659
    - type: recall_at_5
      value: 13.691
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.54947560419517
    - type: f1
      value: 84.8242629182151
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 50.348837209302324
    - type: f1
      value: 33.552311863643
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 56.76529926025555
    - type: f1
      value: 53.50819461312456
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.64425016812373
    - type: f1
      value: 64.67534424488329
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.33530655295464
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.27607219103413
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 27.082984442235798
    - type: mrr
      value: 27.558608635217794
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.622
    - type: map_at_10
      value: 5.769
    - type: map_at_100
      value: 7.276000000000001
    - type: map_at_1000
      value: 8.394
    - type: map_at_3
      value: 4.566
    - type: map_at_5
      value: 5.1979999999999995
    - type: mrr_at_1
      value: 26.935
    - type: mrr_at_10
      value: 37.354
    - type: mrr_at_100
      value: 38.151
    - type: mrr_at_1000
      value: 38.224000000000004
    - type: mrr_at_3
      value: 34.778
    - type: mrr_at_5
      value: 36.342
    - type: ndcg_at_1
      value: 25.386999999999997
    - type: ndcg_at_10
      value: 19.151
    - type: ndcg_at_100
      value: 18.927
    - type: ndcg_at_1000
      value: 28.666999999999998
    - type: ndcg_at_3
      value: 22.261
    - type: ndcg_at_5
      value: 20.921
    - type: precision_at_1
      value: 26.935
    - type: precision_at_10
      value: 13.715
    - type: precision_at_100
      value: 5.276
    - type: precision_at_1000
      value: 1.8270000000000002
    - type: precision_at_3
      value: 20.64
    - type: precision_at_5
      value: 17.337
    - type: recall_at_1
      value: 2.622
    - type: recall_at_10
      value: 9.516
    - type: recall_at_100
      value: 22.083
    - type: recall_at_1000
      value: 55.879999999999995
    - type: recall_at_3
      value: 6.051
    - type: recall_at_5
      value: 7.738
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.020999999999999
    - type: map_at_10
      value: 14.432
    - type: map_at_100
      value: 15.384
    - type: map_at_1000
      value: 15.473
    - type: map_at_3
      value: 12.362
    - type: map_at_5
      value: 13.397
    - type: mrr_at_1
      value: 10.197000000000001
    - type: mrr_at_10
      value: 15.914
    - type: mrr_at_100
      value: 16.814
    - type: mrr_at_1000
      value: 16.892
    - type: mrr_at_3
      value: 13.764999999999999
    - type: mrr_at_5
      value: 14.838000000000001
    - type: ndcg_at_1
      value: 10.197000000000001
    - type: ndcg_at_10
      value: 18.109
    - type: ndcg_at_100
      value: 23.055999999999997
    - type: ndcg_at_1000
      value: 25.569999999999997
    - type: ndcg_at_3
      value: 13.771
    - type: ndcg_at_5
      value: 15.618000000000002
    - type: precision_at_1
      value: 10.197000000000001
    - type: precision_at_10
      value: 3.305
    - type: precision_at_100
      value: 0.615
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.354
    - type: precision_at_5
      value: 4.855
    - type: recall_at_1
      value: 9.020999999999999
    - type: recall_at_10
      value: 28.153
    - type: recall_at_100
      value: 51.278999999999996
    - type: recall_at_1000
      value: 70.742
    - type: recall_at_3
      value: 16.478
    - type: recall_at_5
      value: 20.766000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.165
    - type: map_at_10
      value: 69.596
    - type: map_at_100
      value: 70.317
    - type: map_at_1000
      value: 70.358
    - type: map_at_3
      value: 66.952
    - type: map_at_5
      value: 68.57600000000001
    - type: mrr_at_1
      value: 67.09
    - type: mrr_at_10
      value: 74.236
    - type: mrr_at_100
      value: 74.541
    - type: mrr_at_1000
      value: 74.554
    - type: mrr_at_3
      value: 72.815
    - type: mrr_at_5
      value: 73.719
    - type: ndcg_at_1
      value: 67.16
    - type: ndcg_at_10
      value: 74.18299999999999
    - type: ndcg_at_100
      value: 76.452
    - type: ndcg_at_1000
      value: 77.105
    - type: ndcg_at_3
      value: 70.881
    - type: ndcg_at_5
      value: 72.603
    - type: precision_at_1
      value: 67.16
    - type: precision_at_10
      value: 11.115
    - type: precision_at_100
      value: 1.3379999999999999
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 30.607
    - type: precision_at_5
      value: 20.214
    - type: recall_at_1
      value: 58.165
    - type: recall_at_10
      value: 82.73700000000001
    - type: recall_at_100
      value: 91.767
    - type: recall_at_1000
      value: 95.94500000000001
    - type: recall_at_3
      value: 73.134
    - type: recall_at_5
      value: 77.98
    - type: map_at_1
      value: 2.0500000000000003
    - type: map_at_10
      value: 5.06
    - type: map_at_100
      value: 6.146999999999999
    - type: map_at_1000
      value: 6.368
    - type: map_at_3
      value: 3.6220000000000003
    - type: map_at_5
      value: 4.324999999999999
    - type: mrr_at_1
      value: 10.100000000000001
    - type: mrr_at_10
      value: 17.000999999999998
    - type: mrr_at_100
      value: 18.223
    - type: mrr_at_1000
      value: 18.329
    - type: mrr_at_3
      value: 14.267
    - type: mrr_at_5
      value: 15.626999999999999
    - type: ndcg_at_1
      value: 10.100000000000001
    - type: ndcg_at_10
      value: 9.467
    - type: ndcg_at_100
      value: 14.862
    - type: ndcg_at_1000
      value: 19.794999999999998
    - type: ndcg_at_3
      value: 8.405999999999999
    - type: ndcg_at_5
      value: 7.539
    - type: precision_at_1
      value: 10.100000000000001
    - type: precision_at_10
      value: 5.12
    - type: precision_at_100
      value: 1.3
    - type: precision_at_1000
      value: 0.249
    - type: precision_at_3
      value: 7.832999999999999
    - type: precision_at_5
      value: 6.72
    - type: recall_at_1
      value: 2.0500000000000003
    - type: recall_at_10
      value: 10.388
    - type: recall_at_100
      value: 26.401999999999997
    - type: recall_at_1000
      value: 50.707
    - type: recall_at_3
      value: 4.760000000000001
    - type: recall_at_5
      value: 6.8180000000000005
    - type: map_at_1
      value: 0.149
    - type: map_at_10
      value: 0.8999999999999999
    - type: map_at_100
      value: 3.943
    - type: map_at_1000
      value: 9.314
    - type: map_at_3
      value: 0.366
    - type: map_at_5
      value: 0.521
    - type: mrr_at_1
      value: 64.0
    - type: mrr_at_10
      value: 75.102
    - type: mrr_at_100
      value: 75.48
    - type: mrr_at_1000
      value: 75.48
    - type: mrr_at_3
      value: 73.333
    - type: mrr_at_5
      value: 74.233
    - type: ndcg_at_1
      value: 57.99999999999999
    - type: ndcg_at_10
      value: 49.122
    - type: ndcg_at_100
      value: 32.473
    - type: ndcg_at_1000
      value: 27.815
    - type: ndcg_at_3
      value: 55.00000000000001
    - type: ndcg_at_5
      value: 51.571
    - type: precision_at_1
      value: 64.0
    - type: precision_at_10
      value: 53.0
    - type: precision_at_100
      value: 33.2
    - type: precision_at_1000
      value: 13.308
    - type: precision_at_3
      value: 61.333000000000006
    - type: precision_at_5
      value: 56.00000000000001
    - type: recall_at_1
      value: 0.149
    - type: recall_at_10
      value: 1.176
    - type: recall_at_100
      value: 7.074
    - type: recall_at_1000
      value: 26.454
    - type: recall_at_3
      value: 0.406
    - type: recall_at_5
      value: 0.617
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 24.5493374372718
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 38.00016239175056
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 71.89984343607804
    - type: cos_sim_spearman
      value: 63.43467385580481
    - type: euclidean_pearson
      value: 69.73579823240381
    - type: euclidean_spearman
      value: 63.43475730968674
    - type: manhattan_pearson
      value: 69.8228923194184
    - type: manhattan_spearman
      value: 63.58845076244296
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 65.4759399816162
    - type: cos_sim_spearman
      value: 65.35498422056574
    - type: euclidean_pearson
      value: 68.36154404872667
    - type: euclidean_spearman
      value: 65.35640076124622
    - type: manhattan_pearson
      value: 68.40246600630756
    - type: manhattan_spearman
      value: 65.42497257424823
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 55.68971853486872
    - type: cos_sim_spearman
      value: 59.06834913713076
    - type: euclidean_pearson
      value: 59.706488047671044
    - type: euclidean_spearman
      value: 59.06838710110628
    - type: manhattan_pearson
      value: 60.072587773127125
    - type: manhattan_spearman
      value: 59.50320399915506
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 57.557307550750295
    - type: cos_sim_spearman
      value: 60.68273711090555
    - type: euclidean_pearson
      value: 60.20869968120602
    - type: euclidean_spearman
      value: 60.68272743643783
    - type: manhattan_pearson
      value: 60.50545955587273
    - type: manhattan_spearman
      value: 60.95213012572679
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 58.18042156345806
    - type: cos_sim_spearman
      value: 65.32579360012554
    - type: euclidean_pearson
      value: 64.31792924588922
    - type: euclidean_spearman
      value: 65.32579038611287
    - type: manhattan_pearson
      value: 64.40233473846389
    - type: manhattan_spearman
      value: 65.40214278585312
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 44.50178221672106
    - type: cos_sim_spearman
      value: 55.784111367310665
    - type: euclidean_pearson
      value: 53.41468235269096
    - type: euclidean_spearman
      value: 55.784384888922425
    - type: manhattan_pearson
      value: 53.53280905200817
    - type: manhattan_spearman
      value: 55.88198774771714
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 55.13631567761868
    - type: cos_sim_spearman
      value: 65.57248978406166
    - type: euclidean_pearson
      value: 64.03946971471025
    - type: euclidean_spearman
      value: 65.57337456557754
    - type: manhattan_pearson
      value: 63.61261893563087
    - type: manhattan_spearman
      value: 65.1385835431766
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 29.45864805131749
    - type: cos_sim_spearman
      value: 50.95973110970679
    - type: euclidean_pearson
      value: 40.95705582088806
    - type: euclidean_spearman
      value: 50.95973110970679
    - type: manhattan_pearson
      value: 41.674733184754345
    - type: manhattan_spearman
      value: 51.614159713070464
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 56.77386223789116
    - type: cos_sim_spearman
      value: 59.293606859595485
    - type: euclidean_pearson
      value: 60.19020154248288
    - type: euclidean_spearman
      value: 59.29359527035356
    - type: manhattan_pearson
      value: 60.282114876575186
    - type: manhattan_spearman
      value: 59.37212976911096
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 61.571833060295766
    - type: mrr
      value: 85.19842267391286
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 31.556
    - type: map_at_10
      value: 38.556000000000004
    - type: map_at_100
      value: 39.701
    - type: map_at_1000
      value: 39.775
    - type: map_at_3
      value: 36.342999999999996
    - type: map_at_5
      value: 37.702000000000005
    - type: mrr_at_1
      value: 33.0
    - type: mrr_at_10
      value: 40.035
    - type: mrr_at_100
      value: 41.053
    - type: mrr_at_1000
      value: 41.115
    - type: mrr_at_3
      value: 38.0
    - type: mrr_at_5
      value: 39.333
    - type: ndcg_at_1
      value: 33.0
    - type: ndcg_at_10
      value: 42.512
    - type: ndcg_at_100
      value: 48.231
    - type: ndcg_at_1000
      value: 50.283
    - type: ndcg_at_3
      value: 38.272
    - type: ndcg_at_5
      value: 40.589
    - type: precision_at_1
      value: 33.0
    - type: precision_at_10
      value: 5.867
    - type: precision_at_100
      value: 0.903
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 15.0
    - type: precision_at_5
      value: 10.333
    - type: recall_at_1
      value: 31.556
    - type: recall_at_10
      value: 53.261
    - type: recall_at_100
      value: 80.072
    - type: recall_at_1000
      value: 96.39999999999999
    - type: recall_at_3
      value: 42.111
    - type: recall_at_5
      value: 47.556
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.28217821782178
    - type: cos_sim_ap
      value: 52.992820561773925
    - type: cos_sim_f1
      value: 53.79000561482312
    - type: cos_sim_precision
      value: 61.33162612035852
    - type: cos_sim_recall
      value: 47.9
    - type: dot_accuracy
      value: 99.28217821782178
    - type: dot_ap
      value: 52.992820561773925
    - type: dot_f1
      value: 53.79000561482312
    - type: dot_precision
      value: 61.33162612035852
    - type: dot_recall
      value: 47.9
    - type: euclidean_accuracy
      value: 99.28217821782178
    - type: euclidean_ap
      value: 52.992820561773925
    - type: euclidean_f1
      value: 53.79000561482312
    - type: euclidean_precision
      value: 61.33162612035852
    - type: euclidean_recall
      value: 47.9
    - type: manhattan_accuracy
      value: 99.2871287128713
    - type: manhattan_ap
      value: 53.606023555965066
    - type: manhattan_f1
      value: 54.131054131054135
    - type: manhattan_precision
      value: 62.913907284768214
    - type: manhattan_recall
      value: 47.5
    - type: max_accuracy
      value: 99.2871287128713
    - type: max_ap
      value: 53.606023555965066
    - type: max_f1
      value: 54.131054131054135
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 36.32857312142378
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.504144051226
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 40.76457049974378
    - type: mrr
      value: 41.07083174178763
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.243788760312984
    - type: cos_sim_spearman
      value: 31.03280248261321
    - type: dot_pearson
      value: 30.243788764677664
    - type: dot_spearman
      value: 31.061614308694534
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.6129999999999998
    - type: map_at_10
      value: 4.543
    - type: map_at_100
      value: 7.212000000000001
    - type: map_at_1000
      value: 8.495
    - type: map_at_3
      value: 2.6069999999999998
    - type: map_at_5
      value: 3.451
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 32.638
    - type: mrr_at_100
      value: 34.361000000000004
    - type: mrr_at_1000
      value: 34.39
    - type: mrr_at_3
      value: 28.912
    - type: mrr_at_5
      value: 31.156
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 13.056000000000001
    - type: ndcg_at_100
      value: 22.066
    - type: ndcg_at_1000
      value: 34.38
    - type: ndcg_at_3
      value: 16.495
    - type: ndcg_at_5
      value: 15.158
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 11.224
    - type: precision_at_100
      value: 5.061
    - type: precision_at_1000
      value: 1.2630000000000001
    - type: precision_at_3
      value: 15.645999999999999
    - type: precision_at_5
      value: 15.101999999999999
    - type: recall_at_1
      value: 1.6129999999999998
    - type: recall_at_10
      value: 8.486
    - type: recall_at_100
      value: 31.317
    - type: recall_at_1000
      value: 69.62899999999999
    - type: recall_at_3
      value: 3.421
    - type: recall_at_5
      value: 5.328
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.8716
    - type: ap
      value: 13.588164805433928
    - type: f1
      value: 54.41439485369954
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 57.06564799094511
    - type: f1
      value: 57.20282472039746
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 23.406257160147327
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.0037551409668
    - type: cos_sim_ap
      value: 55.47970632502296
    - type: cos_sim_f1
      value: 53.07814214311838
    - type: cos_sim_precision
      value: 49.33152050759121
    - type: cos_sim_recall
      value: 57.440633245382585
    - type: dot_accuracy
      value: 81.0037551409668
    - type: dot_ap
      value: 55.47970632502296
    - type: dot_f1
      value: 53.07814214311838
    - type: dot_precision
      value: 49.33152050759121
    - type: dot_recall
      value: 57.440633245382585
    - type: euclidean_accuracy
      value: 81.0037551409668
    - type: euclidean_ap
      value: 55.47970632502296
    - type: euclidean_f1
      value: 53.07814214311838
    - type: euclidean_precision
      value: 49.33152050759121
    - type: euclidean_recall
      value: 57.440633245382585
    - type: manhattan_accuracy
      value: 81.0037551409668
    - type: manhattan_ap
      value: 55.80897704541587
    - type: manhattan_f1
      value: 53.43965722447036
    - type: manhattan_precision
      value: 48.67736339982654
    - type: manhattan_recall
      value: 59.23482849604221
    - type: max_accuracy
      value: 81.0037551409668
    - type: max_ap
      value: 55.80897704541587
    - type: max_f1
      value: 53.43965722447036
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 83.57783211083944
    - type: cos_sim_ap
      value: 71.5815660869356
    - type: cos_sim_f1
      value: 63.43217907021236
    - type: cos_sim_precision
      value: 63.04860424431429
    - type: cos_sim_recall
      value: 63.82044964582691
    - type: dot_accuracy
      value: 83.57783211083944
    - type: dot_ap
      value: 71.58156546802053
    - type: dot_f1
      value: 63.43217907021236
    - type: dot_precision
      value: 63.04860424431429
    - type: dot_recall
      value: 63.82044964582691
    - type: euclidean_accuracy
      value: 83.57783211083944
    - type: euclidean_ap
      value: 71.5815657331584
    - type: euclidean_f1
      value: 63.43217907021236
    - type: euclidean_precision
      value: 63.04860424431429
    - type: euclidean_recall
      value: 63.82044964582691
    - type: manhattan_accuracy
      value: 83.69231963363993
    - type: manhattan_ap
      value: 71.80465347479418
    - type: manhattan_f1
      value: 63.49836524988323
    - type: manhattan_precision
      value: 64.2081234256927
    - type: manhattan_recall
      value: 62.804126886356634
    - type: max_accuracy
      value: 83.69231963363993
    - type: max_ap
      value: 71.80465347479418
    - type: max_f1
      value: 63.49836524988323
---
