mteb model-index region:us
---
tags:
- mteb
model-index:
- name: gte_wordllama_result
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.07462686567165
    - type: ap
      value: 34.03639155919273
    - type: f1
      value: 65.69832537072352
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 69.453025
    - type: ap
      value: 63.87884877644433
    - type: f1
      value: 69.23150048939367
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 36.364
    - type: f1
      value: 35.72067919658383
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 22.546
    - type: map_at_10
      value: 37.411
    - type: map_at_100
      value: 38.582
    - type: map_at_1000
      value: 38.597
    - type: map_at_3
      value: 32.492
    - type: map_at_5
      value: 35.141
    - type: mrr_at_1
      value: 23.186
    - type: mrr_at_10
      value: 37.651
    - type: mrr_at_100
      value: 38.822
    - type: mrr_at_1000
      value: 38.836999999999996
    - type: mrr_at_3
      value: 32.741
    - type: mrr_at_5
      value: 35.408
    - type: ndcg_at_1
      value: 22.546
    - type: ndcg_at_10
      value: 46.012
    - type: ndcg_at_100
      value: 51.197
    - type: ndcg_at_1000
      value: 51.547
    - type: ndcg_at_3
      value: 35.762
    - type: ndcg_at_5
      value: 40.567
    - type: precision_at_1
      value: 22.546
    - type: precision_at_10
      value: 7.367999999999999
    - type: precision_at_100
      value: 0.968
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 15.078
    - type: precision_at_5
      value: 11.394
    - type: recall_at_1
      value: 22.546
    - type: recall_at_10
      value: 73.68400000000001
    - type: recall_at_100
      value: 96.799
    - type: recall_at_1000
      value: 99.431
    - type: recall_at_3
      value: 45.235
    - type: recall_at_5
      value: 56.97
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.643731613769525
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.63510872385387
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.581954717688454
    - type: mrr
      value: 69.65857626522447
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 79.65184787408168
    - type: cos_sim_spearman
      value: 76.59391391898701
    - type: euclidean_pearson
      value: 78.27369147487082
    - type: euclidean_spearman
      value: 76.59391391898701
    - type: manhattan_pearson
      value: 78.35436546555296
    - type: manhattan_spearman
      value: 76.41258448606804
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.67532467532469
    - type: f1
      value: 74.96407787263568
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.80818669258118
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 27.110794795227715
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.831000000000003
    - type: map_at_10
      value: 30.358
    - type: map_at_100
      value: 31.708
    - type: map_at_1000
      value: 31.857999999999997
    - type: map_at_3
      value: 27.721
    - type: map_at_5
      value: 29.054000000000002
    - type: mrr_at_1
      value: 29.041
    - type: mrr_at_10
      value: 36.405
    - type: mrr_at_100
      value: 37.358000000000004
    - type: mrr_at_1000
      value: 37.419999999999995
    - type: mrr_at_3
      value: 34.335
    - type: mrr_at_5
      value: 35.365
    - type: ndcg_at_1
      value: 29.041
    - type: ndcg_at_10
      value: 35.673
    - type: ndcg_at_100
      value: 41.432
    - type: ndcg_at_1000
      value: 44.372
    - type: ndcg_at_3
      value: 31.707
    - type: ndcg_at_5
      value: 33.147999999999996
    - type: precision_at_1
      value: 29.041
    - type: precision_at_10
      value: 6.895999999999999
    - type: precision_at_100
      value: 1.237
    - type: precision_at_1000
      value: 0.181
    - type: precision_at_3
      value: 15.212
    - type: precision_at_5
      value: 10.901
    - type: recall_at_1
      value: 22.831000000000003
    - type: recall_at_10
      value: 45.234
    - type: recall_at_100
      value: 70.658
    - type: recall_at_1000
      value: 90.70700000000001
    - type: recall_at_3
      value: 32.729
    - type: recall_at_5
      value: 37.242
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 18.834
    - type: map_at_10
      value: 25.796999999999997
    - type: map_at_100
      value: 26.881
    - type: map_at_1000
      value: 27.004
    - type: map_at_3
      value: 23.857999999999997
    - type: map_at_5
      value: 24.89
    - type: mrr_at_1
      value: 24.204
    - type: mrr_at_10
      value: 30.529
    - type: mrr_at_100
      value: 31.386999999999997
    - type: mrr_at_1000
      value: 31.456
    - type: mrr_at_3
      value: 28.715000000000003
    - type: mrr_at_5
      value: 29.658
    - type: ndcg_at_1
      value: 24.204
    - type: ndcg_at_10
      value: 30.053
    - type: ndcg_at_100
      value: 34.826
    - type: ndcg_at_1000
      value: 37.557
    - type: ndcg_at_3
      value: 26.927
    - type: ndcg_at_5
      value: 28.205999999999996
    - type: precision_at_1
      value: 24.204
    - type: precision_at_10
      value: 5.561
    - type: precision_at_100
      value: 1.011
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 12.994
    - type: precision_at_5
      value: 9.107999999999999
    - type: recall_at_1
      value: 18.834
    - type: recall_at_10
      value: 38.022
    - type: recall_at_100
      value: 58.587
    - type: recall_at_1000
      value: 76.953
    - type: recall_at_3
      value: 28.777
    - type: recall_at_5
      value: 32.372
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 28.138999999999996
    - type: map_at_10
      value: 37.378
    - type: map_at_100
      value: 38.576
    - type: map_at_1000
      value: 38.673
    - type: map_at_3
      value: 34.733000000000004
    - type: map_at_5
      value: 36.083999999999996
    - type: mrr_at_1
      value: 32.414
    - type: mrr_at_10
      value: 40.589999999999996
    - type: mrr_at_100
      value: 41.519
    - type: mrr_at_1000
      value: 41.577999999999996
    - type: mrr_at_3
      value: 38.213
    - type: mrr_at_5
      value: 39.428999999999995
    - type: ndcg_at_1
      value: 32.414
    - type: ndcg_at_10
      value: 42.501
    - type: ndcg_at_100
      value: 47.715
    - type: ndcg_at_1000
      value: 49.899
    - type: ndcg_at_3
      value: 37.595
    - type: ndcg_at_5
      value: 39.653
    - type: precision_at_1
      value: 32.414
    - type: precision_at_10
      value: 6.978
    - type: precision_at_100
      value: 1.054
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 16.761
    - type: precision_at_5
      value: 11.498
    - type: recall_at_1
      value: 28.138999999999996
    - type: recall_at_10
      value: 54.803999999999995
    - type: recall_at_100
      value: 77.648
    - type: recall_at_1000
      value: 93.545
    - type: recall_at_3
      value: 41.323
    - type: recall_at_5
      value: 46.489999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.864
    - type: map_at_10
      value: 18.775
    - type: map_at_100
      value: 19.706000000000003
    - type: map_at_1000
      value: 19.822
    - type: map_at_3
      value: 17.314
    - type: map_at_5
      value: 18.028
    - type: mrr_at_1
      value: 14.915000000000001
    - type: mrr_at_10
      value: 20.095
    - type: mrr_at_100
      value: 20.992
    - type: mrr_at_1000
      value: 21.092
    - type: mrr_at_3
      value: 18.587999999999997
    - type: mrr_at_5
      value: 19.271
    - type: ndcg_at_1
      value: 14.915000000000001
    - type: ndcg_at_10
      value: 21.811
    - type: ndcg_at_100
      value: 26.656000000000002
    - type: ndcg_at_1000
      value: 30.009000000000004
    - type: ndcg_at_3
      value: 18.790000000000003
    - type: ndcg_at_5
      value: 20.009
    - type: precision_at_1
      value: 14.915000000000001
    - type: precision_at_10
      value: 3.401
    - type: precision_at_100
      value: 0.623
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 8.06
    - type: precision_at_5
      value: 5.537
    - type: recall_at_1
      value: 13.864
    - type: recall_at_10
      value: 29.914
    - type: recall_at_100
      value: 52.580000000000005
    - type: recall_at_1000
      value: 78.648
    - type: recall_at_3
      value: 21.586
    - type: recall_at_5
      value: 24.58
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.223
    - type: map_at_10
      value: 12.272
    - type: map_at_100
      value: 13.252
    - type: map_at_1000
      value: 13.381000000000002
    - type: map_at_3
      value: 10.610999999999999
    - type: map_at_5
      value: 11.505
    - type: mrr_at_1
      value: 9.203999999999999
    - type: mrr_at_10
      value: 14.639
    - type: mrr_at_100
      value: 15.629000000000001
    - type: mrr_at_1000
      value: 15.733
    - type: mrr_at_3
      value: 12.852
    - type: mrr_at_5
      value: 13.797999999999998
    - type: ndcg_at_1
      value: 9.203999999999999
    - type: ndcg_at_10
      value: 15.543999999999999
    - type: ndcg_at_100
      value: 20.89
    - type: ndcg_at_1000
      value: 24.547
    - type: ndcg_at_3
      value: 12.264
    - type: ndcg_at_5
      value: 13.748
    - type: precision_at_1
      value: 9.203999999999999
    - type: precision_at_10
      value: 3.085
    - type: precision_at_100
      value: 0.688
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 6.095
    - type: precision_at_5
      value: 4.677
    - type: recall_at_1
      value: 7.223
    - type: recall_at_10
      value: 23.268
    - type: recall_at_100
      value: 47.452
    - type: recall_at_1000
      value: 74.69200000000001
    - type: recall_at_3
      value: 14.437
    - type: recall_at_5
      value: 18.007
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 19.661
    - type: map_at_10
      value: 26.145000000000003
    - type: map_at_100
      value: 27.477
    - type: map_at_1000
      value: 27.622999999999998
    - type: map_at_3
      value: 23.315
    - type: map_at_5
      value: 24.87
    - type: mrr_at_1
      value: 24.157999999999998
    - type: mrr_at_10
      value: 31.035
    - type: mrr_at_100
      value: 32.011
    - type: mrr_at_1000
      value: 32.086999999999996
    - type: mrr_at_3
      value: 28.199999999999996
    - type: mrr_at_5
      value: 29.769000000000002
    - type: ndcg_at_1
      value: 24.157999999999998
    - type: ndcg_at_10
      value: 31.249
    - type: ndcg_at_100
      value: 37.319
    - type: ndcg_at_1000
      value: 40.394999999999996
    - type: ndcg_at_3
      value: 26.184
    - type: ndcg_at_5
      value: 28.518
    - type: precision_at_1
      value: 24.157999999999998
    - type: precision_at_10
      value: 5.9479999999999995
    - type: precision_at_100
      value: 1.077
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 12.191
    - type: precision_at_5
      value: 9.142999999999999
    - type: recall_at_1
      value: 19.661
    - type: recall_at_10
      value: 41.959
    - type: recall_at_100
      value: 68.22399999999999
    - type: recall_at_1000
      value: 89.071
    - type: recall_at_3
      value: 27.617000000000004
    - type: recall_at_5
      value: 33.693
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 15.714
    - type: map_at_10
      value: 21.786
    - type: map_at_100
      value: 23.052
    - type: map_at_1000
      value: 23.186999999999998
    - type: map_at_3
      value: 19.286
    - type: map_at_5
      value: 20.699
    - type: mrr_at_1
      value: 19.064
    - type: mrr_at_10
      value: 25.576
    - type: mrr_at_100
      value: 26.613
    - type: mrr_at_1000
      value: 26.697
    - type: mrr_at_3
      value: 23.212
    - type: mrr_at_5
      value: 24.553
    - type: ndcg_at_1
      value: 19.064
    - type: ndcg_at_10
      value: 26.19
    - type: ndcg_at_100
      value: 32.019
    - type: ndcg_at_1000
      value: 35.323
    - type: ndcg_at_3
      value: 21.609
    - type: ndcg_at_5
      value: 23.747
    - type: precision_at_1
      value: 19.064
    - type: precision_at_10
      value: 5.045999999999999
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 10.16
    - type: precision_at_5
      value: 7.693999999999999
    - type: recall_at_1
      value: 15.714
    - type: recall_at_10
      value: 35.846000000000004
    - type: recall_at_100
      value: 60.885
    - type: recall_at_1000
      value: 84.437
    - type: recall_at_3
      value: 23.357
    - type: recall_at_5
      value: 28.698
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.797416666666667
    - type: map_at_10
      value: 21.674916666666668
    - type: map_at_100
      value: 22.73633333333333
    - type: map_at_1000
      value: 22.868583333333333
    - type: map_at_3
      value: 19.66508333333333
    - type: map_at_5
      value: 20.75133333333333
    - type: mrr_at_1
      value: 19.052333333333333
    - type: mrr_at_10
      value: 24.958083333333335
    - type: mrr_at_100
      value: 25.862666666666666
    - type: mrr_at_1000
      value: 25.95
    - type: mrr_at_3
      value: 23.02525
    - type: mrr_at_5
      value: 24.053166666666666
    - type: ndcg_at_1
      value: 19.052333333333333
    - type: ndcg_at_10
      value: 25.618249999999996
    - type: ndcg_at_100
      value: 30.751666666666665
    - type: ndcg_at_1000
      value: 33.93783333333333
    - type: ndcg_at_3
      value: 21.966166666666666
    - type: ndcg_at_5
      value: 23.569333333333333
    - type: precision_at_1
      value: 19.052333333333333
    - type: precision_at_10
      value: 4.6321666666666665
    - type: precision_at_100
      value: 0.8673333333333333
    - type: precision_at_1000
      value: 0.13283333333333333
    - type: precision_at_3
      value: 10.15075
    - type: precision_at_5
      value: 7.330416666666667
    - type: recall_at_1
      value: 15.797416666666667
    - type: recall_at_10
      value: 34.28000000000001
    - type: recall_at_100
      value: 57.498416666666664
    - type: recall_at_1000
      value: 80.52425000000001
    - type: recall_at_3
      value: 23.929416666666665
    - type: recall_at_5
      value: 28.09466666666667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.323
    - type: map_at_10
      value: 17.07
    - type: map_at_100
      value: 17.849999999999998
    - type: map_at_1000
      value: 17.957
    - type: map_at_3
      value: 15.414
    - type: map_at_5
      value: 16.431
    - type: mrr_at_1
      value: 13.497
    - type: mrr_at_10
      value: 19.188
    - type: mrr_at_100
      value: 19.978
    - type: mrr_at_1000
      value: 20.071
    - type: mrr_at_3
      value: 17.663999999999998
    - type: mrr_at_5
      value: 18.538
    - type: ndcg_at_1
      value: 13.497
    - type: ndcg_at_10
      value: 20.485999999999997
    - type: ndcg_at_100
      value: 24.855
    - type: ndcg_at_1000
      value: 27.773999999999997
    - type: ndcg_at_3
      value: 17.399
    - type: ndcg_at_5
      value: 18.988
    - type: precision_at_1
      value: 13.497
    - type: precision_at_10
      value: 3.5740000000000003
    - type: precision_at_100
      value: 0.63
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 8.129
    - type: precision_at_5
      value: 5.92
    - type: recall_at_1
      value: 11.323
    - type: recall_at_10
      value: 28.92
    - type: recall_at_100
      value: 49.75
    - type: recall_at_1000
      value: 71.492
    - type: recall_at_3
      value: 20.452
    - type: recall_at_5
      value: 24.346
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.625
    - type: map_at_10
      value: 12.41
    - type: map_at_100
      value: 13.200999999999999
    - type: map_at_1000
      value: 13.333999999999998
    - type: map_at_3
      value: 11.141
    - type: map_at_5
      value: 11.776
    - type: mrr_at_1
      value: 10.805
    - type: mrr_at_10
      value: 14.979999999999999
    - type: mrr_at_100
      value: 15.759
    - type: mrr_at_1000
      value: 15.867
    - type: mrr_at_3
      value: 13.569999999999999
    - type: mrr_at_5
      value: 14.316
    - type: ndcg_at_1
      value: 10.805
    - type: ndcg_at_10
      value: 15.129999999999999
    - type: ndcg_at_100
      value: 19.339000000000002
    - type: ndcg_at_1000
      value: 23.034
    - type: ndcg_at_3
      value: 12.661
    - type: ndcg_at_5
      value: 13.664000000000001
    - type: precision_at_1
      value: 10.805
    - type: precision_at_10
      value: 2.88
    - type: precision_at_100
      value: 0.5950000000000001
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 6.091
    - type: precision_at_5
      value: 4.4319999999999995
    - type: recall_at_1
      value: 8.625
    - type: recall_at_10
      value: 20.924
    - type: recall_at_100
      value: 40.343
    - type: recall_at_1000
      value: 67.60199999999999
    - type: recall_at_3
      value: 13.963000000000001
    - type: recall_at_5
      value: 16.558999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 15.116999999999999
    - type: map_at_10
      value: 20.283
    - type: map_at_100
      value: 21.181
    - type: map_at_1000
      value: 21.318
    - type: map_at_3
      value: 18.528
    - type: map_at_5
      value: 19.506
    - type: mrr_at_1
      value: 17.91
    - type: mrr_at_10
      value: 23.399
    - type: mrr_at_100
      value: 24.254
    - type: mrr_at_1000
      value: 24.36
    - type: mrr_at_3
      value: 21.502
    - type: mrr_at_5
      value: 22.617
    - type: ndcg_at_1
      value: 17.91
    - type: ndcg_at_10
      value: 23.848
    - type: ndcg_at_100
      value: 28.63
    - type: ndcg_at_1000
      value: 32.236
    - type: ndcg_at_3
      value: 20.351
    - type: ndcg_at_5
      value: 21.992
    - type: precision_at_1
      value: 17.91
    - type: precision_at_10
      value: 4.011
    - type: precision_at_100
      value: 0.722
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 9.049
    - type: precision_at_5
      value: 6.455
    - type: recall_at_1
      value: 15.116999999999999
    - type: recall_at_10
      value: 31.911
    - type: recall_at_100
      value: 53.791999999999994
    - type: recall_at_1000
      value: 79.997
    - type: recall_at_3
      value: 22.229
    - type: recall_at_5
      value: 26.366
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.415999999999999
    - type: map_at_10
      value: 21.364
    - type: map_at_100
      value: 22.631
    - type: map_at_1000
      value: 22.832
    - type: map_at_3
      value: 19.139999999999997
    - type: map_at_5
      value: 20.549
    - type: mrr_at_1
      value: 19.368
    - type: mrr_at_10
      value: 25.218
    - type: mrr_at_100
      value: 26.135
    - type: mrr_at_1000
      value: 26.218999999999998
    - type: mrr_at_3
      value: 23.155
    - type: mrr_at_5
      value: 24.371000000000002
    - type: ndcg_at_1
      value: 19.368
    - type: ndcg_at_10
      value: 25.715
    - type: ndcg_at_100
      value: 31.291999999999998
    - type: ndcg_at_1000
      value: 34.757
    - type: ndcg_at_3
      value: 22.131999999999998
    - type: ndcg_at_5
      value: 24.018
    - type: precision_at_1
      value: 19.368
    - type: precision_at_10
      value: 5.138
    - type: precision_at_100
      value: 1.229
    - type: precision_at_1000
      value: 0.209
    - type: precision_at_3
      value: 10.474
    - type: precision_at_5
      value: 7.904999999999999
    - type: recall_at_1
      value: 15.415999999999999
    - type: recall_at_10
      value: 33.83
    - type: recall_at_100
      value: 60.19799999999999
    - type: recall_at_1000
      value: 83.88600000000001
    - type: recall_at_3
      value: 23.018
    - type: recall_at_5
      value: 28.37
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.822
    - type: map_at_10
      value: 16.461000000000002
    - type: map_at_100
      value: 17.321
    - type: map_at_1000
      value: 17.434
    - type: map_at_3
      value: 14.92
    - type: map_at_5
      value: 15.623999999999999
    - type: mrr_at_1
      value: 14.048
    - type: mrr_at_10
      value: 17.843
    - type: mrr_at_100
      value: 18.717
    - type: mrr_at_1000
      value: 18.82
    - type: mrr_at_3
      value: 16.297
    - type: mrr_at_5
      value: 16.953
    - type: ndcg_at_1
      value: 14.048
    - type: ndcg_at_10
      value: 19.219
    - type: ndcg_at_100
      value: 24.047
    - type: ndcg_at_1000
      value: 27.351
    - type: ndcg_at_3
      value: 15.975
    - type: ndcg_at_5
      value: 17.141000000000002
    - type: precision_at_1
      value: 14.048
    - type: precision_at_10
      value: 3.068
    - type: precision_at_100
      value: 0.5950000000000001
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.593
    - type: precision_at_5
      value: 4.695
    - type: recall_at_1
      value: 12.822
    - type: recall_at_10
      value: 26.728
    - type: recall_at_100
      value: 49.864000000000004
    - type: recall_at_1000
      value: 75.261
    - type: recall_at_3
      value: 17.665
    - type: recall_at_5
      value: 20.413
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 8.301
    - type: map_at_10
      value: 14.709
    - type: map_at_100
      value: 16.396
    - type: map_at_1000
      value: 16.606
    - type: map_at_3
      value: 11.987
    - type: map_at_5
      value: 13.401
    - type: mrr_at_1
      value: 19.088
    - type: mrr_at_10
      value: 29.421999999999997
    - type: mrr_at_100
      value: 30.517
    - type: mrr_at_1000
      value: 30.568
    - type: mrr_at_3
      value: 25.646
    - type: mrr_at_5
      value: 27.897
    - type: ndcg_at_1
      value: 19.088
    - type: ndcg_at_10
      value: 21.851000000000003
    - type: ndcg_at_100
      value: 29.093999999999998
    - type: ndcg_at_1000
      value: 33.101
    - type: ndcg_at_3
      value: 16.862
    - type: ndcg_at_5
      value: 18.790000000000003
    - type: precision_at_1
      value: 19.088
    - type: precision_at_10
      value: 7.244000000000001
    - type: precision_at_100
      value: 1.496
    - type: precision_at_1000
      value: 0.22300000000000003
    - type: precision_at_3
      value: 12.812000000000001
    - type: precision_at_5
      value: 10.41
    - type: recall_at_1
      value: 8.301
    - type: recall_at_10
      value: 27.49
    - type: recall_at_100
      value: 52.937999999999995
    - type: recall_at_1000
      value: 75.79599999999999
    - type: recall_at_3
      value: 15.603
    - type: recall_at_5
      value: 20.612
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 5.576
    - type: map_at_10
      value: 11.394
    - type: map_at_100
      value: 16.276
    - type: map_at_1000
      value: 17.459
    - type: map_at_3
      value: 8.269
    - type: map_at_5
      value: 9.711
    - type: mrr_at_1
      value: 47.25
    - type: mrr_at_10
      value: 57.201
    - type: mrr_at_100
      value: 57.727
    - type: mrr_at_1000
      value: 57.751
    - type: mrr_at_3
      value: 54.458
    - type: mrr_at_5
      value: 56.421
    - type: ndcg_at_1
      value: 35.25
    - type: ndcg_at_10
      value: 26.617
    - type: ndcg_at_100
      value: 30.952
    - type: ndcg_at_1000
      value: 38.287
    - type: ndcg_at_3
      value: 29.814
    - type: ndcg_at_5
      value: 28.436
    - type: precision_at_1
      value: 47.25
    - type: precision_at_10
      value: 23.175
    - type: precision_at_100
      value: 7.6450000000000005
    - type: precision_at_1000
      value: 1.624
    - type: precision_at_3
      value: 35.667
    - type: precision_at_5
      value: 30.65
    - type: recall_at_1
      value: 5.576
    - type: recall_at_10
      value: 15.804000000000002
    - type: recall_at_100
      value: 38.086
    - type: recall_at_1000
      value: 63.034
    - type: recall_at_3
      value: 9.407
    - type: recall_at_5
      value: 12.247
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 47.21
    - type: f1
      value: 43.021356364911156
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 17.775
    - type: map_at_10
      value: 27.131
    - type: map_at_100
      value: 28.186
    - type: map_at_1000
      value: 28.255999999999997
    - type: map_at_3
      value: 24.198
    - type: map_at_5
      value: 25.907000000000004
    - type: mrr_at_1
      value: 19.006999999999998
    - type: mrr_at_10
      value: 28.769
    - type: mrr_at_100
      value: 29.809
    - type: mrr_at_1000
      value: 29.866
    - type: mrr_at_3
      value: 25.773000000000003
    - type: mrr_at_5
      value: 27.51
    - type: ndcg_at_1
      value: 19.006999999999998
    - type: ndcg_at_10
      value: 32.698
    - type: ndcg_at_100
      value: 37.891999999999996
    - type: ndcg_at_1000
      value: 39.728
    - type: ndcg_at_3
      value: 26.680999999999997
    - type: ndcg_at_5
      value: 29.73
    - type: precision_at_1
      value: 19.006999999999998
    - type: precision_at_10
      value: 5.2909999999999995
    - type: precision_at_100
      value: 0.8049999999999999
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 11.616
    - type: precision_at_5
      value: 8.554
    - type: recall_at_1
      value: 17.775
    - type: recall_at_10
      value: 48.603
    - type: recall_at_100
      value: 72.465
    - type: recall_at_1000
      value: 86.509
    - type: recall_at_3
      value: 32.26
    - type: recall_at_5
      value: 39.589999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 8.584
    - type: map_at_10
      value: 13.774000000000001
    - type: map_at_100
      value: 15.247
    - type: map_at_1000
      value: 15.468000000000002
    - type: map_at_3
      value: 11.779
    - type: map_at_5
      value: 12.732
    - type: mrr_at_1
      value: 16.512
    - type: mrr_at_10
      value: 23.016000000000002
    - type: mrr_at_100
      value: 24.276
    - type: mrr_at_1000
      value: 24.362000000000002
    - type: mrr_at_3
      value: 20.756
    - type: mrr_at_5
      value: 21.852
    - type: ndcg_at_1
      value: 16.512
    - type: ndcg_at_10
      value: 18.604000000000003
    - type: ndcg_at_100
      value: 25.298
    - type: ndcg_at_1000
      value: 29.803
    - type: ndcg_at_3
      value: 15.790000000000001
    - type: ndcg_at_5
      value: 16.614
    - type: precision_at_1
      value: 16.512
    - type: precision_at_10
      value: 5.293
    - type: precision_at_100
      value: 1.17
    - type: precision_at_1000
      value: 0.196
    - type: precision_at_3
      value: 10.237
    - type: precision_at_5
      value: 7.7780000000000005
    - type: recall_at_1
      value: 8.584
    - type: recall_at_10
      value: 23.685000000000002
    - type: recall_at_100
      value: 49.461
    - type: recall_at_1000
      value: 76.972
    - type: recall_at_3
      value: 14.657
    - type: recall_at_5
      value: 17.861
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 19.662
    - type: map_at_10
      value: 28.195999999999998
    - type: map_at_100
      value: 29.21
    - type: map_at_1000
      value: 29.322
    - type: map_at_3
      value: 25.852999999999998
    - type: map_at_5
      value: 27.121000000000002
    - type: mrr_at_1
      value: 39.324999999999996
    - type: mrr_at_10
      value: 47.083999999999996
    - type: mrr_at_100
      value: 47.805
    - type: mrr_at_1000
      value: 47.853
    - type: mrr_at_3
      value: 44.913
    - type: mrr_at_5
      value: 46.132
    - type: ndcg_at_1
      value: 39.324999999999996
    - type: ndcg_at_10
      value: 35.766999999999996
    - type: ndcg_at_100
      value: 40.306
    - type: ndcg_at_1000
      value: 42.870000000000005
    - type: ndcg_at_3
      value: 31.395
    - type: ndcg_at_5
      value: 33.469
    - type: precision_at_1
      value: 39.324999999999996
    - type: precision_at_10
      value: 7.933999999999999
    - type: precision_at_100
      value: 1.157
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 19.855999999999998
    - type: precision_at_5
      value: 13.556000000000001
    - type: recall_at_1
      value: 19.662
    - type: recall_at_10
      value: 39.669
    - type: recall_at_100
      value: 57.833
    - type: recall_at_1000
      value: 74.929
    - type: recall_at_3
      value: 29.784
    - type: recall_at_5
      value: 33.889
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 68.03079999999999
    - type: ap
      value: 62.45465282637356
    - type: f1
      value: 67.82133366706746
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 7.297
    - type: map_at_10
      value: 12.847
    - type: map_at_100
      value: 13.872000000000002
    - type: map_at_1000
      value: 13.987
    - type: map_at_3
      value: 10.741
    - type: map_at_5
      value: 11.838999999999999
    - type: mrr_at_1
      value: 7.536
    - type: mrr_at_10
      value: 13.157
    - type: mrr_at_100
      value: 14.184
    - type: mrr_at_1000
      value: 14.295
    - type: mrr_at_3
      value: 11.020000000000001
    - type: mrr_at_5
      value: 12.133
    - type: ndcg_at_1
      value: 7.507
    - type: ndcg_at_10
      value: 16.374
    - type: ndcg_at_100
      value: 22.039
    - type: ndcg_at_1000
      value: 25.380999999999997
    - type: ndcg_at_3
      value: 11.935
    - type: ndcg_at_5
      value: 13.919999999999998
    - type: precision_at_1
      value: 7.507
    - type: precision_at_10
      value: 2.8449999999999998
    - type: precision_at_100
      value: 0.581
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 5.191
    - type: precision_at_5
      value: 4.112
    - type: recall_at_1
      value: 7.297
    - type: recall_at_10
      value: 27.450999999999997
    - type: recall_at_100
      value: 55.215
    - type: recall_at_1000
      value: 81.878
    - type: recall_at_3
      value: 15.143
    - type: recall_at_5
      value: 19.922
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.23347013223893
    - type: f1
      value: 90.37745005574784
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.43775649794802
    - type: f1
      value: 41.826394298669705
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.53799596503026
    - type: f1
      value: 63.37514998537075
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.92535305985206
    - type: f1
      value: 72.01043365342854
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.093053205851135
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.838169401102558
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.012335830272843
    - type: mrr
      value: 32.04656357642063
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.865
    - type: map_at_10
      value: 9.599
    - type: map_at_100
      value: 12.466000000000001
    - type: map_at_1000
      value: 13.935
    - type: map_at_3
      value: 7.260999999999999
    - type: map_at_5
      value: 8.526
    - type: mrr_at_1
      value: 38.080000000000005
    - type: mrr_at_10
      value: 47.695
    - type: mrr_at_100
      value: 48.304
    - type: mrr_at_1000
      value: 48.351
    - type: mrr_at_3
      value: 45.098
    - type: mrr_at_5
      value: 46.569
    - type: ndcg_at_1
      value: 36.223
    - type: ndcg_at_10
      value: 28.582
    - type: ndcg_at_100
      value: 27.229
    - type: ndcg_at_1000
      value: 36.643
    - type: ndcg_at_3
      value: 32.653
    - type: ndcg_at_5
      value: 31.215
    - type: precision_at_1
      value: 38.080000000000005
    - type: precision_at_10
      value: 21.207
    - type: precision_at_100
      value: 7.498
    - type: precision_at_1000
      value: 2.104
    - type: precision_at_3
      value: 30.65
    - type: precision_at_5
      value: 27.059
    - type: recall_at_1
      value: 4.865
    - type: recall_at_10
      value: 13.614
    - type: recall_at_100
      value: 29.659999999999997
    - type: recall_at_1000
      value: 63.172
    - type: recall_at_3
      value: 8.248
    - type: recall_at_5
      value: 10.684000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.581
    - type: map_at_10
      value: 18.221
    - type: map_at_100
      value: 19.637999999999998
    - type: map_at_1000
      value: 19.737
    - type: map_at_3
      value: 15.341
    - type: map_at_5
      value: 16.943
    - type: mrr_at_1
      value: 12.051
    - type: mrr_at_10
      value: 20.102
    - type: mrr_at_100
      value: 21.385
    - type: mrr_at_1000
      value: 21.465
    - type: mrr_at_3
      value: 17.159
    - type: mrr_at_5
      value: 18.851000000000003
    - type: ndcg_at_1
      value: 12.051
    - type: ndcg_at_10
      value: 23.267
    - type: ndcg_at_100
      value: 30.211
    - type: ndcg_at_1000
      value: 32.878
    - type: ndcg_at_3
      value: 17.354
    - type: ndcg_at_5
      value: 20.247999999999998
    - type: precision_at_1
      value: 12.051
    - type: precision_at_10
      value: 4.356999999999999
    - type: precision_at_100
      value: 0.827
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 8.266
    - type: precision_at_5
      value: 6.553000000000001
    - type: recall_at_1
      value: 10.581
    - type: recall_at_10
      value: 37.119
    - type: recall_at_100
      value: 68.89699999999999
    - type: recall_at_1000
      value: 89.354
    - type: recall_at_3
      value: 21.404999999999998
    - type: recall_at_5
      value: 28.194000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 66.119
    - type: map_at_10
      value: 79.611
    - type: map_at_100
      value: 80.354
    - type: map_at_1000
      value: 80.38
    - type: map_at_3
      value: 76.606
    - type: map_at_5
      value: 78.485
    - type: mrr_at_1
      value: 76.12
    - type: mrr_at_10
      value: 83.328
    - type: mrr_at_100
      value: 83.499
    - type: mrr_at_1000
      value: 83.502
    - type: mrr_at_3
      value: 82.00699999999999
    - type: mrr_at_5
      value: 82.89699999999999
    - type: ndcg_at_1
      value: 76.22
    - type: ndcg_at_10
      value: 84.051
    - type: ndcg_at_100
      value: 85.797
    - type: ndcg_at_1000
      value: 86.007
    - type: ndcg_at_3
      value: 80.646
    - type: ndcg_at_5
      value: 82.50800000000001
    - type: precision_at_1
      value: 76.22
    - type: precision_at_10
      value: 12.76
    - type: precision_at_100
      value: 1.5010000000000001
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 35.160000000000004
    - type: precision_at_5
      value: 23.264000000000003
    - type: recall_at_1
      value: 66.119
    - type: recall_at_10
      value: 92.664
    - type: recall_at_100
      value: 98.863
    - type: recall_at_1000
      value: 99.91
    - type: recall_at_3
      value: 82.994
    - type: recall_at_5
      value: 88.119
    - type: map_at_1
      value: 3.2680000000000002
    - type: map_at_10
      value: 8.579
    - type: map_at_100
      value: 10.421999999999999
    - type: map_at_1000
      value: 10.737
    - type: map_at_3
      value: 6.0040000000000004
    - type: map_at_5
      value: 7.26
    - type: mrr_at_1
      value: 16.0
    - type: mrr_at_10
      value: 26.185000000000002
    - type: mrr_at_100
      value: 27.439000000000004
    - type: mrr_at_1000
      value: 27.511999999999997
    - type: mrr_at_3
      value: 22.917
    - type: mrr_at_5
      value: 24.642
    - type: ndcg_at_1
      value: 16.0
    - type: ndcg_at_10
      value: 15.232000000000001
    - type: ndcg_at_100
      value: 23.047
    - type: ndcg_at_1000
      value: 28.774
    - type: ndcg_at_3
      value: 13.834
    - type: ndcg_at_5
      value: 12.304
    - type: precision_at_1
      value: 16.0
    - type: precision_at_10
      value: 8.19
    - type: precision_at_100
      value: 1.958
    - type: precision_at_1000
      value: 0.333
    - type: precision_at_3
      value: 13.167000000000002
    - type: precision_at_5
      value: 11.06
    - type: recall_at_1
      value: 3.2680000000000002
    - type: recall_at_10
      value: 16.563
    - type: recall_at_100
      value: 39.708
    - type: recall_at_1000
      value: 67.60199999999999
    - type: recall_at_3
      value: 8.018
    - type: recall_at_5
      value: 11.193
    - type: map_at_1
      value: 0.161
    - type: map_at_10
      value: 1.171
    - type: map_at_100
      value: 6.306000000000001
    - type: map_at_1000
      value: 16.732
    - type: map_at_3
      value: 0.432
    - type: map_at_5
      value: 0.645
    - type: mrr_at_1
      value: 57.99999999999999
    - type: mrr_at_10
      value: 72.32499999999999
    - type: mrr_at_100
      value: 72.458
    - type: mrr_at_1000
      value: 72.458
    - type: mrr_at_3
      value: 69.667
    - type: mrr_at_5
      value: 71.56700000000001
    - type: ndcg_at_1
      value: 53.0
    - type: ndcg_at_10
      value: 52.207
    - type: ndcg_at_100
      value: 40.717
    - type: ndcg_at_1000
      value: 38.254
    - type: ndcg_at_3
      value: 57.553
    - type: ndcg_at_5
      value: 53.795
    - type: precision_at_1
      value: 60.0
    - type: precision_at_10
      value: 56.599999999999994
    - type: precision_at_100
      value: 42.84
    - type: precision_at_1000
      value: 18.386
    - type: precision_at_3
      value: 63.333
    - type: precision_at_5
      value: 57.99999999999999
    - type: recall_at_1
      value: 0.161
    - type: recall_at_10
      value: 1.434
    - type: recall_at_100
      value: 9.454
    - type: recall_at_1000
      value: 37.175000000000004
    - type: recall_at_3
      value: 0.477
    - type: recall_at_5
      value: 0.735
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.342566470284666
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 51.11469484366251
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 78.76771912274579
    - type: cos_sim_spearman
      value: 68.21965433585433
    - type: euclidean_pearson
      value: 73.41725536408647
    - type: euclidean_spearman
      value: 68.21970849513703
    - type: manhattan_pearson
      value: 73.07310010299138
    - type: manhattan_spearman
      value: 68.02842343011922
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 77.24856339472711
    - type: cos_sim_spearman
      value: 68.13233535199409
    - type: euclidean_pearson
      value: 72.83173400932682
    - type: euclidean_spearman
      value: 68.13353961544857
    - type: manhattan_pearson
      value: 72.364020033214
    - type: manhattan_spearman
      value: 67.96817473009628
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.11822706559114
    - type: cos_sim_spearman
      value: 78.82692788488787
    - type: euclidean_pearson
      value: 78.42176146428962
    - type: euclidean_spearman
      value: 78.82696569079468
    - type: manhattan_pearson
      value: 77.94207608371939
    - type: manhattan_spearman
      value: 78.30672557882981
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 79.37520382719511
    - type: cos_sim_spearman
      value: 75.09236770903914
    - type: euclidean_pearson
      value: 77.94076407783429
    - type: euclidean_spearman
      value: 75.0923580173567
    - type: manhattan_pearson
      value: 77.739191296084
    - type: manhattan_spearman
      value: 74.9480210937594
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 82.9584878497231
    - type: cos_sim_spearman
      value: 83.58865804953194
    - type: euclidean_pearson
      value: 83.32064366874845
    - type: euclidean_spearman
      value: 83.58865650778534
    - type: manhattan_pearson
      value: 83.17898835151296
    - type: manhattan_spearman
      value: 83.45146824277634
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.40206220271352
    - type: cos_sim_spearman
      value: 78.18587292841029
    - type: euclidean_pearson
      value: 77.63109474603048
    - type: euclidean_spearman
      value: 78.18586561703366
    - type: manhattan_pearson
      value: 77.56336963431791
    - type: manhattan_spearman
      value: 78.13426002359485
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 86.28987235462407
    - type: cos_sim_spearman
      value: 86.91762382232156
    - type: euclidean_pearson
      value: 86.05340443036164
    - type: euclidean_spearman
      value: 86.91849630883524
    - type: manhattan_pearson
      value: 85.98189959096196
    - type: manhattan_spearman
      value: 86.94471215865201
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.248533592592025
    - type: cos_sim_spearman
      value: 61.25674726411208
    - type: euclidean_pearson
      value: 62.668232482670724
    - type: euclidean_spearman
      value: 61.25674726411208
    - type: manhattan_pearson
      value: 62.217580952381915
    - type: manhattan_spearman
      value: 60.77021894786932
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 80.84077621570408
    - type: cos_sim_spearman
      value: 79.26302777438052
    - type: euclidean_pearson
      value: 80.5028036765331
    - type: euclidean_spearman
      value: 79.26304623849835
    - type: manhattan_pearson
      value: 80.45325721545979
    - type: manhattan_spearman
      value: 79.22021810584245
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.71971528163719
    - type: mrr
      value: 94.15308003543299
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 36.611
    - type: map_at_10
      value: 46.424
    - type: map_at_100
      value: 47.347
    - type: map_at_1000
      value: 47.404
    - type: map_at_3
      value: 43.153000000000006
    - type: map_at_5
      value: 45.024
    - type: mrr_at_1
      value: 39.0
    - type: mrr_at_10
      value: 48.423
    - type: mrr_at_100
      value: 49.126
    - type: mrr_at_1000
      value: 49.179
    - type: mrr_at_3
      value: 45.389
    - type: mrr_at_5
      value: 47.221999999999994
    - type: ndcg_at_1
      value: 39.0
    - type: ndcg_at_10
      value: 52.142999999999994
    - type: ndcg_at_100
      value: 56.606
    - type: ndcg_at_1000
      value: 57.894
    - type: ndcg_at_3
      value: 45.611000000000004
    - type: ndcg_at_5
      value: 48.85
    - type: precision_at_1
      value: 39.0
    - type: precision_at_10
      value: 7.467
    - type: precision_at_100
      value: 1.0030000000000001
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 18.111
    - type: precision_at_5
      value: 12.6
    - type: recall_at_1
      value: 36.611
    - type: recall_at_10
      value: 68.289
    - type: recall_at_100
      value: 89.267
    - type: recall_at_1000
      value: 98.867
    - type: recall_at_3
      value: 50.471999999999994
    - type: recall_at_5
      value: 58.289
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.72475247524753
    - type: cos_sim_ap
      value: 92.0612887387195
    - type: cos_sim_f1
      value: 85.78528827037775
    - type: cos_sim_precision
      value: 85.27667984189723
    - type: cos_sim_recall
      value: 86.3
    - type: dot_accuracy
      value: 99.72475247524753
    - type: dot_ap
      value: 92.0612887387195
    - type: dot_f1
      value: 85.78528827037775
    - type: dot_precision
      value: 85.27667984189723
    - type: dot_recall
      value: 86.3
    - type: euclidean_accuracy
      value: 99.72475247524753
    - type: euclidean_ap
      value: 92.0612887387195
    - type: euclidean_f1
      value: 85.78528827037775
    - type: euclidean_precision
      value: 85.27667984189723
    - type: euclidean_recall
      value: 86.3
    - type: manhattan_accuracy
      value: 99.72475247524753
    - type: manhattan_ap
      value: 92.11384029855155
    - type: manhattan_f1
      value: 85.75595527467186
    - type: manhattan_precision
      value: 83.44370860927152
    - type: manhattan_recall
      value: 88.2
    - type: max_accuracy
      value: 99.72475247524753
    - type: max_ap
      value: 92.11384029855155
    - type: max_f1
      value: 85.78528827037775
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 51.43694167734459
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.99750013836291
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 44.11670648850121
    - type: mrr
      value: 44.651265809354044
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.82538139718491
    - type: cos_sim_spearman
      value: 30.223708279486612
    - type: dot_pearson
      value: 29.8253813971849
    - type: dot_spearman
      value: 30.26388644272319
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.144
    - type: map_at_10
      value: 8.538
    - type: map_at_100
      value: 14.526
    - type: map_at_1000
      value: 16.253
    - type: map_at_3
      value: 3.721
    - type: map_at_5
      value: 5.979
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 41.553000000000004
    - type: mrr_at_100
      value: 42.672
    - type: mrr_at_1000
      value: 42.672
    - type: mrr_at_3
      value: 35.714
    - type: mrr_at_5
      value: 40.306
    - type: ndcg_at_1
      value: 21.429000000000002
    - type: ndcg_at_10
      value: 21.421
    - type: ndcg_at_100
      value: 35.417
    - type: ndcg_at_1000
      value: 47.281
    - type: ndcg_at_3
      value: 20.107
    - type: ndcg_at_5
      value: 23.012
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 21.02
    - type: precision_at_100
      value: 8.245
    - type: precision_at_1000
      value: 1.608
    - type: precision_at_3
      value: 22.448999999999998
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 2.144
    - type: recall_at_10
      value: 15.318999999999999
    - type: recall_at_100
      value: 50.608
    - type: recall_at_1000
      value: 86.652
    - type: recall_at_3
      value: 4.65
    - type: recall_at_5
      value: 9.286
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 76.1994
    - type: ap
      value: 17.166874536029024
    - type: f1
      value: 58.91563395048056
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.56140350877194
    - type: f1
      value: 59.83462102375279
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 42.717753205468256
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.51177206890385
    - type: cos_sim_ap
      value: 61.880585258206324
    - type: cos_sim_f1
      value: 59.29389759176994
    - type: cos_sim_precision
      value: 53.232577665827044
    - type: cos_sim_recall
      value: 66.91292875989447
    - type: dot_accuracy
      value: 82.51177206890385
    - type: dot_ap
      value: 61.880585258206324
    - type: dot_f1
      value: 59.29389759176994
    - type: dot_precision
      value: 53.232577665827044
    - type: dot_recall
      value: 66.91292875989447
    - type: euclidean_accuracy
      value: 82.51177206890385
    - type: euclidean_ap
      value: 61.880585258206324
    - type: euclidean_f1
      value: 59.29389759176994
    - type: euclidean_precision
      value: 53.232577665827044
    - type: euclidean_recall
      value: 66.91292875989447
    - type: manhattan_accuracy
      value: 82.41044286821243
    - type: manhattan_ap
      value: 61.69366003781778
    - type: manhattan_f1
      value: 59.267976933035186
    - type: manhattan_precision
      value: 53.494794986190776
    - type: manhattan_recall
      value: 66.43799472295514
    - type: max_accuracy
      value: 82.51177206890385
    - type: max_ap
      value: 61.880585258206324
    - type: max_f1
      value: 59.29389759176994
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.58683587534443
    - type: cos_sim_ap
      value: 83.41906537158532
    - type: cos_sim_f1
      value: 75.80436150912658
    - type: cos_sim_precision
      value: 73.01191070537052
    - type: cos_sim_recall
      value: 78.81890976285803
    - type: dot_accuracy
      value: 87.58683587534443
    - type: dot_ap
      value: 83.41906537158532
    - type: dot_f1
      value: 75.80436150912658
    - type: dot_precision
      value: 73.01191070537052
    - type: dot_recall
      value: 78.81890976285803
    - type: euclidean_accuracy
      value: 87.58683587534443
    - type: euclidean_ap
      value: 83.41906537158532
    - type: euclidean_f1
      value: 75.80436150912658
    - type: euclidean_precision
      value: 73.01191070537052
    - type: euclidean_recall
      value: 78.81890976285803
    - type: manhattan_accuracy
      value: 87.55190747855785
    - type: manhattan_ap
      value: 83.37075875688966
    - type: manhattan_f1
      value: 75.71862755868028
    - type: manhattan_precision
      value: 72.19467914251798
    - type: manhattan_recall
      value: 79.60425007699415
    - type: max_accuracy
      value: 87.58683587534443
    - type: max_ap
      value: 83.41906537158532
    - type: max_f1
      value: 75.80436150912658
---
