mteb model-index region:us
---
tags:
- mteb
model-index:
- name: fasttext_main_PCA_gcp
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 76.31343283582088
    - type: ap
      value: 39.6402606765834
    - type: f1
      value: 70.3627511633638
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.2898
    - type: ap
      value: 61.87754668001793
    - type: f1
      value: 67.2166271872683
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.116
    - type: f1
      value: 32.58360486720766
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 19.346
    - type: map_at_10
      value: 32.623000000000005
    - type: map_at_100
      value: 33.829
    - type: map_at_1000
      value: 33.857
    - type: map_at_3
      value: 28.307
    - type: map_at_5
      value: 30.523
    - type: mrr_at_1
      value: 19.915
    - type: mrr_at_10
      value: 32.846
    - type: mrr_at_100
      value: 34.050999999999995
    - type: mrr_at_1000
      value: 34.079
    - type: mrr_at_3
      value: 28.497
    - type: mrr_at_5
      value: 30.72
    - type: ndcg_at_1
      value: 19.346
    - type: ndcg_at_10
      value: 40.458
    - type: ndcg_at_100
      value: 46.293
    - type: ndcg_at_1000
      value: 47.043
    - type: ndcg_at_3
      value: 31.381999999999998
    - type: ndcg_at_5
      value: 35.385
    - type: precision_at_1
      value: 19.346
    - type: precision_at_10
      value: 6.572
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 13.442000000000002
    - type: precision_at_5
      value: 10.014000000000001
    - type: recall_at_1
      value: 19.346
    - type: recall_at_10
      value: 65.718
    - type: recall_at_100
      value: 92.959
    - type: recall_at_1000
      value: 98.86200000000001
    - type: recall_at_3
      value: 40.327
    - type: recall_at_5
      value: 50.071
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.28634616254917
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.88368073053745
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 51.46344355474199
    - type: mrr
      value: 64.81851558721364
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 74.25527135158369
    - type: cos_sim_spearman
      value: 70.15762268541177
    - type: euclidean_pearson
      value: 73.6693089435787
    - type: euclidean_spearman
      value: 70.15762268541177
    - type: manhattan_pearson
      value: 75.24108161238829
    - type: manhattan_spearman
      value: 71.50403890658741
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 67.78571428571428
    - type: f1
      value: 66.71649216312889
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.4188358879818
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 26.33046520373852
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.970000000000002
    - type: map_at_10
      value: 25.256
    - type: map_at_100
      value: 26.401000000000003
    - type: map_at_1000
      value: 26.545
    - type: map_at_3
      value: 23.347
    - type: map_at_5
      value: 24.393
    - type: mrr_at_1
      value: 24.464
    - type: mrr_at_10
      value: 30.580000000000002
    - type: mrr_at_100
      value: 31.514999999999997
    - type: mrr_at_1000
      value: 31.594
    - type: mrr_at_3
      value: 28.660000000000004
    - type: mrr_at_5
      value: 29.812
    - type: ndcg_at_1
      value: 24.464
    - type: ndcg_at_10
      value: 29.643000000000004
    - type: ndcg_at_100
      value: 35.012
    - type: ndcg_at_1000
      value: 38.118
    - type: ndcg_at_3
      value: 26.796
    - type: ndcg_at_5
      value: 27.944999999999997
    - type: precision_at_1
      value: 24.464
    - type: precision_at_10
      value: 5.694
    - type: precision_at_100
      value: 1.054
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 13.257
    - type: precision_at_5
      value: 9.413
    - type: recall_at_1
      value: 18.970000000000002
    - type: recall_at_10
      value: 37.131
    - type: recall_at_100
      value: 61.602000000000004
    - type: recall_at_1000
      value: 83.092
    - type: recall_at_3
      value: 27.663
    - type: recall_at_5
      value: 31.499
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.466
    - type: map_at_10
      value: 20.806
    - type: map_at_100
      value: 21.709999999999997
    - type: map_at_1000
      value: 21.831
    - type: map_at_3
      value: 19.035
    - type: map_at_5
      value: 20.058999999999997
    - type: mrr_at_1
      value: 19.744999999999997
    - type: mrr_at_10
      value: 25.237
    - type: mrr_at_100
      value: 25.983
    - type: mrr_at_1000
      value: 26.057000000000002
    - type: mrr_at_3
      value: 23.482
    - type: mrr_at_5
      value: 24.437
    - type: ndcg_at_1
      value: 19.744999999999997
    - type: ndcg_at_10
      value: 24.512999999999998
    - type: ndcg_at_100
      value: 28.669
    - type: ndcg_at_1000
      value: 31.606
    - type: ndcg_at_3
      value: 21.547
    - type: ndcg_at_5
      value: 22.953000000000003
    - type: precision_at_1
      value: 19.744999999999997
    - type: precision_at_10
      value: 4.682
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.531
    - type: precision_at_5
      value: 7.631
    - type: recall_at_1
      value: 15.466
    - type: recall_at_10
      value: 31.183
    - type: recall_at_100
      value: 49.45
    - type: recall_at_1000
      value: 69.92699999999999
    - type: recall_at_3
      value: 22.62
    - type: recall_at_5
      value: 26.331
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 23.147000000000002
    - type: map_at_10
      value: 30.44
    - type: map_at_100
      value: 31.47
    - type: map_at_1000
      value: 31.566
    - type: map_at_3
      value: 28.301
    - type: map_at_5
      value: 29.546
    - type: mrr_at_1
      value: 26.52
    - type: mrr_at_10
      value: 33.45
    - type: mrr_at_100
      value: 34.316
    - type: mrr_at_1000
      value: 34.386
    - type: mrr_at_3
      value: 31.317
    - type: mrr_at_5
      value: 32.605000000000004
    - type: ndcg_at_1
      value: 26.52
    - type: ndcg_at_10
      value: 34.664
    - type: ndcg_at_100
      value: 39.499
    - type: ndcg_at_1000
      value: 42.076
    - type: ndcg_at_3
      value: 30.564000000000004
    - type: ndcg_at_5
      value: 32.625
    - type: precision_at_1
      value: 26.52
    - type: precision_at_10
      value: 5.592
    - type: precision_at_100
      value: 0.877
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 13.542000000000002
    - type: precision_at_5
      value: 9.53
    - type: recall_at_1
      value: 23.147000000000002
    - type: recall_at_10
      value: 44.563
    - type: recall_at_100
      value: 66.117
    - type: recall_at_1000
      value: 85.48599999999999
    - type: recall_at_3
      value: 33.507999999999996
    - type: recall_at_5
      value: 38.532
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.094
    - type: map_at_10
      value: 14.167
    - type: map_at_100
      value: 14.790000000000001
    - type: map_at_1000
      value: 14.893
    - type: map_at_3
      value: 12.656999999999998
    - type: map_at_5
      value: 13.538
    - type: mrr_at_1
      value: 11.073
    - type: mrr_at_10
      value: 15.293000000000001
    - type: mrr_at_100
      value: 15.931999999999999
    - type: mrr_at_1000
      value: 16.027
    - type: mrr_at_3
      value: 13.729
    - type: mrr_at_5
      value: 14.633
    - type: ndcg_at_1
      value: 11.073
    - type: ndcg_at_10
      value: 16.814
    - type: ndcg_at_100
      value: 20.307
    - type: ndcg_at_1000
      value: 23.468
    - type: ndcg_at_3
      value: 13.780000000000001
    - type: ndcg_at_5
      value: 15.328
    - type: precision_at_1
      value: 11.073
    - type: precision_at_10
      value: 2.734
    - type: precision_at_100
      value: 0.47200000000000003
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 5.951
    - type: precision_at_5
      value: 4.407
    - type: recall_at_1
      value: 10.094
    - type: recall_at_10
      value: 24.031
    - type: recall_at_100
      value: 40.89
    - type: recall_at_1000
      value: 65.644
    - type: recall_at_3
      value: 15.857
    - type: recall_at_5
      value: 19.595000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.864
    - type: map_at_10
      value: 8.579
    - type: map_at_100
      value: 9.216000000000001
    - type: map_at_1000
      value: 9.339
    - type: map_at_3
      value: 7.668
    - type: map_at_5
      value: 8.121
    - type: mrr_at_1
      value: 7.587000000000001
    - type: mrr_at_10
      value: 10.879999999999999
    - type: mrr_at_100
      value: 11.59
    - type: mrr_at_1000
      value: 11.692
    - type: mrr_at_3
      value: 9.783999999999999
    - type: mrr_at_5
      value: 10.344000000000001
    - type: ndcg_at_1
      value: 7.587000000000001
    - type: ndcg_at_10
      value: 10.722
    - type: ndcg_at_100
      value: 14.313999999999998
    - type: ndcg_at_1000
      value: 17.901
    - type: ndcg_at_3
      value: 8.859
    - type: ndcg_at_5
      value: 9.628
    - type: precision_at_1
      value: 7.587000000000001
    - type: precision_at_10
      value: 1.9900000000000002
    - type: precision_at_100
      value: 0.45399999999999996
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 4.312
    - type: precision_at_5
      value: 3.159
    - type: recall_at_1
      value: 5.864
    - type: recall_at_10
      value: 15.261
    - type: recall_at_100
      value: 31.591
    - type: recall_at_1000
      value: 58.426
    - type: recall_at_3
      value: 10.064
    - type: recall_at_5
      value: 11.941
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.870000000000001
    - type: map_at_10
      value: 21.12
    - type: map_at_100
      value: 22.166
    - type: map_at_1000
      value: 22.291
    - type: map_at_3
      value: 19.063
    - type: map_at_5
      value: 20.263
    - type: mrr_at_1
      value: 18.961
    - type: mrr_at_10
      value: 24.798000000000002
    - type: mrr_at_100
      value: 25.678
    - type: mrr_at_1000
      value: 25.758
    - type: mrr_at_3
      value: 22.650000000000002
    - type: mrr_at_5
      value: 23.852999999999998
    - type: ndcg_at_1
      value: 18.961
    - type: ndcg_at_10
      value: 25.009999999999998
    - type: ndcg_at_100
      value: 30.232
    - type: ndcg_at_1000
      value: 33.23
    - type: ndcg_at_3
      value: 21.313
    - type: ndcg_at_5
      value: 23.136000000000003
    - type: precision_at_1
      value: 18.961
    - type: precision_at_10
      value: 4.562
    - type: precision_at_100
      value: 0.885
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 9.785
    - type: precision_at_5
      value: 7.276000000000001
    - type: recall_at_1
      value: 15.870000000000001
    - type: recall_at_10
      value: 33.265
    - type: recall_at_100
      value: 56.367999999999995
    - type: recall_at_1000
      value: 77.34100000000001
    - type: recall_at_3
      value: 22.872999999999998
    - type: recall_at_5
      value: 27.541
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.029
    - type: map_at_10
      value: 16.307
    - type: map_at_100
      value: 17.258000000000003
    - type: map_at_1000
      value: 17.397000000000002
    - type: map_at_3
      value: 14.707999999999998
    - type: map_at_5
      value: 15.476
    - type: mrr_at_1
      value: 13.469999999999999
    - type: mrr_at_10
      value: 19.494
    - type: mrr_at_100
      value: 20.366
    - type: mrr_at_1000
      value: 20.464
    - type: mrr_at_3
      value: 17.751
    - type: mrr_at_5
      value: 18.63
    - type: ndcg_at_1
      value: 13.469999999999999
    - type: ndcg_at_10
      value: 19.863
    - type: ndcg_at_100
      value: 24.613
    - type: ndcg_at_1000
      value: 28.107
    - type: ndcg_at_3
      value: 16.716
    - type: ndcg_at_5
      value: 17.959
    - type: precision_at_1
      value: 13.469999999999999
    - type: precision_at_10
      value: 3.7560000000000002
    - type: precision_at_100
      value: 0.7270000000000001
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 8.105
    - type: precision_at_5
      value: 5.845000000000001
    - type: recall_at_1
      value: 11.029
    - type: recall_at_10
      value: 27.633000000000003
    - type: recall_at_100
      value: 48.532
    - type: recall_at_1000
      value: 73.16
    - type: recall_at_3
      value: 18.834
    - type: recall_at_5
      value: 21.919
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.789666666666665
    - type: map_at_10
      value: 17.44066666666667
    - type: map_at_100
      value: 18.274416666666664
    - type: map_at_1000
      value: 18.397666666666666
    - type: map_at_3
      value: 15.894749999999998
    - type: map_at_5
      value: 16.714249999999996
    - type: mrr_at_1
      value: 15.513749999999998
    - type: mrr_at_10
      value: 20.397250000000003
    - type: mrr_at_100
      value: 21.16466666666667
    - type: mrr_at_1000
      value: 21.25375
    - type: mrr_at_3
      value: 18.7975
    - type: mrr_at_5
      value: 19.643333333333338
    - type: ndcg_at_1
      value: 15.513749999999998
    - type: ndcg_at_10
      value: 20.66291666666667
    - type: ndcg_at_100
      value: 24.884500000000003
    - type: ndcg_at_1000
      value: 28.035583333333335
    - type: ndcg_at_3
      value: 17.804
    - type: ndcg_at_5
      value: 19.046333333333333
    - type: precision_at_1
      value: 15.513749999999998
    - type: precision_at_10
      value: 3.7079999999999993
    - type: precision_at_100
      value: 0.6968333333333332
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 8.267916666666668
    - type: precision_at_5
      value: 5.9515
    - type: recall_at_1
      value: 12.789666666666665
    - type: recall_at_10
      value: 27.520416666666662
    - type: recall_at_100
      value: 46.91583333333334
    - type: recall_at_1000
      value: 69.91024999999999
    - type: recall_at_3
      value: 19.35025
    - type: recall_at_5
      value: 22.548583333333337
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.551
    - type: map_at_10
      value: 13.431999999999999
    - type: map_at_100
      value: 14.13
    - type: map_at_1000
      value: 14.213999999999999
    - type: map_at_3
      value: 12.015
    - type: map_at_5
      value: 12.708
    - type: mrr_at_1
      value: 11.35
    - type: mrr_at_10
      value: 15.35
    - type: mrr_at_100
      value: 16.037000000000003
    - type: mrr_at_1000
      value: 16.111
    - type: mrr_at_3
      value: 13.88
    - type: mrr_at_5
      value: 14.616999999999999
    - type: ndcg_at_1
      value: 11.35
    - type: ndcg_at_10
      value: 16.082
    - type: ndcg_at_100
      value: 19.875
    - type: ndcg_at_1000
      value: 22.219
    - type: ndcg_at_3
      value: 13.306000000000001
    - type: ndcg_at_5
      value: 14.413
    - type: precision_at_1
      value: 11.35
    - type: precision_at_10
      value: 2.8369999999999997
    - type: precision_at_100
      value: 0.509
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 6.084
    - type: precision_at_5
      value: 4.324999999999999
    - type: recall_at_1
      value: 9.551
    - type: recall_at_10
      value: 22.461000000000002
    - type: recall_at_100
      value: 40.611000000000004
    - type: recall_at_1000
      value: 58.172999999999995
    - type: recall_at_3
      value: 14.732000000000001
    - type: recall_at_5
      value: 17.524
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.572
    - type: map_at_10
      value: 9.33
    - type: map_at_100
      value: 9.933
    - type: map_at_1000
      value: 10.035
    - type: map_at_3
      value: 8.399
    - type: map_at_5
      value: 8.863999999999999
    - type: mrr_at_1
      value: 8.396
    - type: mrr_at_10
      value: 11.518
    - type: mrr_at_100
      value: 12.135
    - type: mrr_at_1000
      value: 12.223
    - type: mrr_at_3
      value: 10.415000000000001
    - type: mrr_at_5
      value: 10.952
    - type: ndcg_at_1
      value: 8.396
    - type: ndcg_at_10
      value: 11.439
    - type: ndcg_at_100
      value: 14.616000000000001
    - type: ndcg_at_1000
      value: 17.66
    - type: ndcg_at_3
      value: 9.613
    - type: ndcg_at_5
      value: 10.324
    - type: precision_at_1
      value: 8.396
    - type: precision_at_10
      value: 2.185
    - type: precision_at_100
      value: 0.447
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 4.646
    - type: precision_at_5
      value: 3.372
    - type: recall_at_1
      value: 6.572
    - type: recall_at_10
      value: 15.811
    - type: recall_at_100
      value: 30.384
    - type: recall_at_1000
      value: 53.134
    - type: recall_at_3
      value: 10.5
    - type: recall_at_5
      value: 12.385
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.595999999999998
    - type: map_at_10
      value: 16.471
    - type: map_at_100
      value: 17.189
    - type: map_at_1000
      value: 17.307
    - type: map_at_3
      value: 15.207
    - type: map_at_5
      value: 15.745999999999999
    - type: mrr_at_1
      value: 15.204999999999998
    - type: mrr_at_10
      value: 19.536
    - type: mrr_at_100
      value: 20.216
    - type: mrr_at_1000
      value: 20.319000000000003
    - type: mrr_at_3
      value: 18.113
    - type: mrr_at_5
      value: 18.752
    - type: ndcg_at_1
      value: 15.204999999999998
    - type: ndcg_at_10
      value: 19.422
    - type: ndcg_at_100
      value: 23.462
    - type: ndcg_at_1000
      value: 26.861
    - type: ndcg_at_3
      value: 16.869999999999997
    - type: ndcg_at_5
      value: 17.692
    - type: precision_at_1
      value: 15.204999999999998
    - type: precision_at_10
      value: 3.274
    - type: precision_at_100
      value: 0.598
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 7.617999999999999
    - type: precision_at_5
      value: 5.167999999999999
    - type: recall_at_1
      value: 12.595999999999998
    - type: recall_at_10
      value: 25.753999999999998
    - type: recall_at_100
      value: 44.803
    - type: recall_at_1000
      value: 69.986
    - type: recall_at_3
      value: 18.406
    - type: recall_at_5
      value: 20.584
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.288
    - type: map_at_10
      value: 18.784
    - type: map_at_100
      value: 19.769000000000002
    - type: map_at_1000
      value: 19.976
    - type: map_at_3
      value: 16.773
    - type: map_at_5
      value: 17.809
    - type: mrr_at_1
      value: 17.194000000000003
    - type: mrr_at_10
      value: 22.591
    - type: mrr_at_100
      value: 23.51
    - type: mrr_at_1000
      value: 23.602999999999998
    - type: mrr_at_3
      value: 20.817
    - type: mrr_at_5
      value: 21.706
    - type: ndcg_at_1
      value: 17.194000000000003
    - type: ndcg_at_10
      value: 22.887
    - type: ndcg_at_100
      value: 27.337
    - type: ndcg_at_1000
      value: 31.064000000000004
    - type: ndcg_at_3
      value: 19.554
    - type: ndcg_at_5
      value: 21.060000000000002
    - type: precision_at_1
      value: 17.194000000000003
    - type: precision_at_10
      value: 4.565
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.193
    - type: precision_at_3
      value: 9.223
    - type: precision_at_5
      value: 7.115
    - type: recall_at_1
      value: 13.288
    - type: recall_at_10
      value: 30.520999999999997
    - type: recall_at_100
      value: 51.746
    - type: recall_at_1000
      value: 77.274
    - type: recall_at_3
      value: 20.405
    - type: recall_at_5
      value: 24.266
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.029
    - type: map_at_10
      value: 14.596
    - type: map_at_100
      value: 15.261
    - type: map_at_1000
      value: 15.378
    - type: map_at_3
      value: 13.564000000000002
    - type: map_at_5
      value: 14.048
    - type: mrr_at_1
      value: 12.2
    - type: mrr_at_10
      value: 16.04
    - type: mrr_at_100
      value: 16.698
    - type: mrr_at_1000
      value: 16.811
    - type: mrr_at_3
      value: 14.972
    - type: mrr_at_5
      value: 15.379000000000001
    - type: ndcg_at_1
      value: 12.2
    - type: ndcg_at_10
      value: 16.896
    - type: ndcg_at_100
      value: 20.678
    - type: ndcg_at_1000
      value: 24.117
    - type: ndcg_at_3
      value: 14.729999999999999
    - type: ndcg_at_5
      value: 15.493000000000002
    - type: precision_at_1
      value: 12.2
    - type: precision_at_10
      value: 2.625
    - type: precision_at_100
      value: 0.486
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.161
    - type: precision_at_5
      value: 4.1770000000000005
    - type: recall_at_1
      value: 11.029
    - type: recall_at_10
      value: 22.631
    - type: recall_at_100
      value: 40.896
    - type: recall_at_1000
      value: 67.28
    - type: recall_at_3
      value: 16.741
    - type: recall_at_5
      value: 18.465999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.7540000000000004
    - type: map_at_10
      value: 11.886
    - type: map_at_100
      value: 13.389999999999999
    - type: map_at_1000
      value: 13.586
    - type: map_at_3
      value: 9.657
    - type: map_at_5
      value: 10.859
    - type: mrr_at_1
      value: 15.895999999999999
    - type: mrr_at_10
      value: 24.598
    - type: mrr_at_100
      value: 25.740000000000002
    - type: mrr_at_1000
      value: 25.802999999999997
    - type: mrr_at_3
      value: 21.488
    - type: mrr_at_5
      value: 23.224
    - type: ndcg_at_1
      value: 15.895999999999999
    - type: ndcg_at_10
      value: 17.952
    - type: ndcg_at_100
      value: 24.755
    - type: ndcg_at_1000
      value: 28.666999999999998
    - type: ndcg_at_3
      value: 13.84
    - type: ndcg_at_5
      value: 15.426
    - type: precision_at_1
      value: 15.895999999999999
    - type: precision_at_10
      value: 5.928
    - type: precision_at_100
      value: 1.322
    - type: precision_at_1000
      value: 0.203
    - type: precision_at_3
      value: 10.488999999999999
    - type: precision_at_5
      value: 8.508000000000001
    - type: recall_at_1
      value: 6.7540000000000004
    - type: recall_at_10
      value: 22.767
    - type: recall_at_100
      value: 46.748
    - type: recall_at_1000
      value: 69.135
    - type: recall_at_3
      value: 12.923000000000002
    - type: recall_at_5
      value: 17.092
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.406
    - type: map_at_10
      value: 5.536
    - type: map_at_100
      value: 8.086
    - type: map_at_1000
      value: 8.802999999999999
    - type: map_at_3
      value: 3.718
    - type: map_at_5
      value: 4.536
    - type: mrr_at_1
      value: 29.75
    - type: mrr_at_10
      value: 38.872
    - type: mrr_at_100
      value: 39.656000000000006
    - type: mrr_at_1000
      value: 39.705
    - type: mrr_at_3
      value: 36.042
    - type: mrr_at_5
      value: 37.592
    - type: ndcg_at_1
      value: 21.75
    - type: ndcg_at_10
      value: 16.145
    - type: ndcg_at_100
      value: 18.795
    - type: ndcg_at_1000
      value: 25.217
    - type: ndcg_at_3
      value: 18.021
    - type: ndcg_at_5
      value: 17.213
    - type: precision_at_1
      value: 29.75
    - type: precision_at_10
      value: 15.225
    - type: precision_at_100
      value: 4.907
    - type: precision_at_1000
      value: 1.114
    - type: precision_at_3
      value: 22.083
    - type: precision_at_5
      value: 19.2
    - type: recall_at_1
      value: 2.406
    - type: recall_at_10
      value: 9.638
    - type: recall_at_100
      value: 24.758
    - type: recall_at_1000
      value: 47.137
    - type: recall_at_3
      value: 4.61
    - type: recall_at_5
      value: 6.660000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 37.135
    - type: f1
      value: 33.97265311696195
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.610000000000001
    - type: map_at_10
      value: 21.112000000000002
    - type: map_at_100
      value: 21.921
    - type: map_at_1000
      value: 21.996
    - type: map_at_3
      value: 19.064
    - type: map_at_5
      value: 20.191
    - type: mrr_at_1
      value: 15.601999999999999
    - type: mrr_at_10
      value: 22.404
    - type: mrr_at_100
      value: 23.205000000000002
    - type: mrr_at_1000
      value: 23.273
    - type: mrr_at_3
      value: 20.247
    - type: mrr_at_5
      value: 21.436
    - type: ndcg_at_1
      value: 15.601999999999999
    - type: ndcg_at_10
      value: 25.064999999999998
    - type: ndcg_at_100
      value: 29.319
    - type: ndcg_at_1000
      value: 31.456
    - type: ndcg_at_3
      value: 20.801
    - type: ndcg_at_5
      value: 22.835
    - type: precision_at_1
      value: 15.601999999999999
    - type: precision_at_10
      value: 3.936
    - type: precision_at_100
      value: 0.626
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 8.821
    - type: precision_at_5
      value: 6.372999999999999
    - type: recall_at_1
      value: 14.610000000000001
    - type: recall_at_10
      value: 36.260999999999996
    - type: recall_at_100
      value: 56.433
    - type: recall_at_1000
      value: 73.064
    - type: recall_at_3
      value: 24.634
    - type: recall_at_5
      value: 29.520000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.639
    - type: map_at_10
      value: 9.072
    - type: map_at_100
      value: 10.041
    - type: map_at_1000
      value: 10.224
    - type: map_at_3
      value: 7.627000000000001
    - type: map_at_5
      value: 8.376999999999999
    - type: mrr_at_1
      value: 10.802
    - type: mrr_at_10
      value: 16.269
    - type: mrr_at_100
      value: 17.209
    - type: mrr_at_1000
      value: 17.313000000000002
    - type: mrr_at_3
      value: 14.299999999999999
    - type: mrr_at_5
      value: 15.35
    - type: ndcg_at_1
      value: 10.802
    - type: ndcg_at_10
      value: 12.826
    - type: ndcg_at_100
      value: 17.979
    - type: ndcg_at_1000
      value: 22.305
    - type: ndcg_at_3
      value: 10.365
    - type: ndcg_at_5
      value: 11.242
    - type: precision_at_1
      value: 10.802
    - type: precision_at_10
      value: 3.688
    - type: precision_at_100
      value: 0.864
    - type: precision_at_1000
      value: 0.16199999999999998
    - type: precision_at_3
      value: 6.893000000000001
    - type: precision_at_5
      value: 5.432
    - type: recall_at_1
      value: 5.639
    - type: recall_at_10
      value: 16.936999999999998
    - type: recall_at_100
      value: 37.964999999999996
    - type: recall_at_1000
      value: 64.747
    - type: recall_at_3
      value: 9.655
    - type: recall_at_5
      value: 12.361
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 13.794999999999998
    - type: map_at_10
      value: 19.503
    - type: map_at_100
      value: 20.301
    - type: map_at_1000
      value: 20.403
    - type: map_at_3
      value: 17.865000000000002
    - type: map_at_5
      value: 18.762
    - type: mrr_at_1
      value: 27.589000000000002
    - type: mrr_at_10
      value: 34.12
    - type: mrr_at_100
      value: 34.855000000000004
    - type: mrr_at_1000
      value: 34.917
    - type: mrr_at_3
      value: 32.305
    - type: mrr_at_5
      value: 33.263999999999996
    - type: ndcg_at_1
      value: 27.589000000000002
    - type: ndcg_at_10
      value: 25.378
    - type: ndcg_at_100
      value: 29.279
    - type: ndcg_at_1000
      value: 31.867
    - type: ndcg_at_3
      value: 22.131999999999998
    - type: ndcg_at_5
      value: 23.655
    - type: precision_at_1
      value: 27.589000000000002
    - type: precision_at_10
      value: 5.679
    - type: precision_at_100
      value: 0.882
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 14.036000000000001
    - type: precision_at_5
      value: 9.629
    - type: recall_at_1
      value: 13.794999999999998
    - type: recall_at_10
      value: 28.393
    - type: recall_at_100
      value: 44.092
    - type: recall_at_1000
      value: 61.458
    - type: recall_at_3
      value: 21.053
    - type: recall_at_5
      value: 24.072
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 67.62120000000002
    - type: ap
      value: 61.977838836960366
    - type: f1
      value: 67.4139917360422
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 3.5409999999999995
    - type: map_at_10
      value: 6.231
    - type: map_at_100
      value: 6.872
    - type: map_at_1000
      value: 6.970999999999999
    - type: map_at_3
      value: 5.106999999999999
    - type: map_at_5
      value: 5.698
    - type: mrr_at_1
      value: 3.567
    - type: mrr_at_10
      value: 6.356000000000001
    - type: mrr_at_100
      value: 7.0040000000000004
    - type: mrr_at_1000
      value: 7.101
    - type: mrr_at_3
      value: 5.193
    - type: mrr_at_5
      value: 5.804
    - type: ndcg_at_1
      value: 3.567
    - type: ndcg_at_10
      value: 8.045
    - type: ndcg_at_100
      value: 11.846
    - type: ndcg_at_1000
      value: 14.926
    - type: ndcg_at_3
      value: 5.6610000000000005
    - type: ndcg_at_5
      value: 6.737
    - type: precision_at_1
      value: 3.567
    - type: precision_at_10
      value: 1.43
    - type: precision_at_100
      value: 0.345
    - type: precision_at_1000
      value: 0.061
    - type: precision_at_3
      value: 2.45
    - type: precision_at_5
      value: 2.0140000000000002
    - type: recall_at_1
      value: 3.5409999999999995
    - type: recall_at_10
      value: 13.794
    - type: recall_at_100
      value: 32.921
    - type: recall_at_1000
      value: 57.863
    - type: recall_at_3
      value: 7.175
    - type: recall_at_5
      value: 9.768
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.63337893296853
    - type: f1
      value: 87.08830964839531
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 63.12585499316006
    - type: f1
      value: 43.45902259676137
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.41223940820444
    - type: f1
      value: 58.47877966227865
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.21788836583725
    - type: f1
      value: 66.63251304134974
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.886280318557983
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.031171971800816
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 27.38298623223962
    - type: mrr
      value: 27.842813890242628
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.2700000000000005
    - type: map_at_10
      value: 8.479000000000001
    - type: map_at_100
      value: 10.402000000000001
    - type: map_at_1000
      value: 11.612
    - type: map_at_3
      value: 6.761
    - type: map_at_5
      value: 7.489
    - type: mrr_at_1
      value: 31.269000000000002
    - type: mrr_at_10
      value: 40.519
    - type: mrr_at_100
      value: 41.388000000000005
    - type: mrr_at_1000
      value: 41.453
    - type: mrr_at_3
      value: 38.029
    - type: mrr_at_5
      value: 39.546
    - type: ndcg_at_1
      value: 29.876
    - type: ndcg_at_10
      value: 23.665
    - type: ndcg_at_100
      value: 22.468
    - type: ndcg_at_1000
      value: 32.029999999999994
    - type: ndcg_at_3
      value: 26.968999999999998
    - type: ndcg_at_5
      value: 25.763
    - type: precision_at_1
      value: 31.269000000000002
    - type: precision_at_10
      value: 17.183
    - type: precision_at_100
      value: 6.003
    - type: precision_at_1000
      value: 1.925
    - type: precision_at_3
      value: 24.871
    - type: precision_at_5
      value: 21.981
    - type: recall_at_1
      value: 4.2700000000000005
    - type: recall_at_10
      value: 12.097
    - type: recall_at_100
      value: 24.349
    - type: recall_at_1000
      value: 58.178
    - type: recall_at_3
      value: 8.256
    - type: recall_at_5
      value: 9.498
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 5.685
    - type: map_at_10
      value: 9.511
    - type: map_at_100
      value: 10.421
    - type: map_at_1000
      value: 10.531
    - type: map_at_3
      value: 8.007
    - type: map_at_5
      value: 8.815000000000001
    - type: mrr_at_1
      value: 6.6339999999999995
    - type: mrr_at_10
      value: 10.767
    - type: mrr_at_100
      value: 11.65
    - type: mrr_at_1000
      value: 11.748
    - type: mrr_at_3
      value: 9.231
    - type: mrr_at_5
      value: 10.056
    - type: ndcg_at_1
      value: 6.6339999999999995
    - type: ndcg_at_10
      value: 12.200999999999999
    - type: ndcg_at_100
      value: 17.013
    - type: ndcg_at_1000
      value: 20.108999999999998
    - type: ndcg_at_3
      value: 9.09
    - type: ndcg_at_5
      value: 10.520999999999999
    - type: precision_at_1
      value: 6.6339999999999995
    - type: precision_at_10
      value: 2.335
    - type: precision_at_100
      value: 0.508
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_3
      value: 4.365
    - type: precision_at_5
      value: 3.418
    - type: recall_at_1
      value: 5.685
    - type: recall_at_10
      value: 19.325
    - type: recall_at_100
      value: 41.971000000000004
    - type: recall_at_1000
      value: 65.877
    - type: recall_at_3
      value: 11.03
    - type: recall_at_5
      value: 14.360999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 56.274
    - type: map_at_10
      value: 68.382
    - type: map_at_100
      value: 69.24
    - type: map_at_1000
      value: 69.286
    - type: map_at_3
      value: 65.36999999999999
    - type: map_at_5
      value: 67.163
    - type: mrr_at_1
      value: 64.8
    - type: mrr_at_10
      value: 73.11800000000001
    - type: mrr_at_100
      value: 73.478
    - type: mrr_at_1000
      value: 73.489
    - type: mrr_at_3
      value: 71.307
    - type: mrr_at_5
      value: 72.42
    - type: ndcg_at_1
      value: 64.85
    - type: ndcg_at_10
      value: 73.656
    - type: ndcg_at_100
      value: 76.44800000000001
    - type: ndcg_at_1000
      value: 77.066
    - type: ndcg_at_3
      value: 69.478
    - type: ndcg_at_5
      value: 71.577
    - type: precision_at_1
      value: 64.85
    - type: precision_at_10
      value: 11.246
    - type: precision_at_100
      value: 1.399
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 30.197000000000003
    - type: precision_at_5
      value: 20.122
    - type: recall_at_1
      value: 56.274
    - type: recall_at_10
      value: 84.25200000000001
    - type: recall_at_100
      value: 95.269
    - type: recall_at_1000
      value: 99.007
    - type: recall_at_3
      value: 72.452
    - type: recall_at_5
      value: 78.108
    - type: map_at_1
      value: 1.778
    - type: map_at_10
      value: 3.9440000000000004
    - type: map_at_100
      value: 4.835
    - type: map_at_1000
      value: 5.065
    - type: map_at_3
      value: 2.935
    - type: map_at_5
      value: 3.427
    - type: mrr_at_1
      value: 8.7
    - type: mrr_at_10
      value: 13.711
    - type: mrr_at_100
      value: 14.748
    - type: mrr_at_1000
      value: 14.901
    - type: mrr_at_3
      value: 11.683
    - type: mrr_at_5
      value: 12.793
    - type: ndcg_at_1
      value: 8.7
    - type: ndcg_at_10
      value: 7.3389999999999995
    - type: ndcg_at_100
      value: 12.021999999999998
    - type: ndcg_at_1000
      value: 17.527
    - type: ndcg_at_3
      value: 6.797000000000001
    - type: ndcg_at_5
      value: 6.0040000000000004
    - type: precision_at_1
      value: 8.7
    - type: precision_at_10
      value: 3.83
    - type: precision_at_100
      value: 1.082
    - type: precision_at_1000
      value: 0.242
    - type: precision_at_3
      value: 6.267
    - type: precision_at_5
      value: 5.220000000000001
    - type: recall_at_1
      value: 1.778
    - type: recall_at_10
      value: 7.786999999999999
    - type: recall_at_100
      value: 21.995
    - type: recall_at_1000
      value: 49.128
    - type: recall_at_3
      value: 3.823
    - type: recall_at_5
      value: 5.327
    - type: map_at_1
      value: 0.146
    - type: map_at_10
      value: 0.853
    - type: map_at_100
      value: 4.044
    - type: map_at_1000
      value: 9.74
    - type: map_at_3
      value: 0.35000000000000003
    - type: map_at_5
      value: 0.498
    - type: mrr_at_1
      value: 57.99999999999999
    - type: mrr_at_10
      value: 67.786
    - type: mrr_at_100
      value: 68.221
    - type: mrr_at_1000
      value: 68.221
    - type: mrr_at_3
      value: 64.667
    - type: mrr_at_5
      value: 66.967
    - type: ndcg_at_1
      value: 48.0
    - type: ndcg_at_10
      value: 42.696
    - type: ndcg_at_100
      value: 30.304
    - type: ndcg_at_1000
      value: 27.717000000000002
    - type: ndcg_at_3
      value: 45.765
    - type: ndcg_at_5
      value: 44.635000000000005
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 46.6
    - type: precision_at_100
      value: 31.879999999999995
    - type: precision_at_1000
      value: 13.514000000000001
    - type: precision_at_3
      value: 51.333
    - type: precision_at_5
      value: 50.4
    - type: recall_at_1
      value: 0.146
    - type: recall_at_10
      value: 1.094
    - type: recall_at_100
      value: 7.049999999999999
    - type: recall_at_1000
      value: 27.473
    - type: recall_at_3
      value: 0.382
    - type: recall_at_5
      value: 0.577
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 37.28513797770202
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 44.91884744639453
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 70.47406828053933
    - type: cos_sim_spearman
      value: 61.458973019024654
    - type: euclidean_pearson
      value: 65.8472323185386
    - type: euclidean_spearman
      value: 61.45905802077228
    - type: manhattan_pearson
      value: 66.6819317121732
    - type: manhattan_spearman
      value: 61.97831416291467
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 59.32490921670001
    - type: cos_sim_spearman
      value: 53.34536574314851
    - type: euclidean_pearson
      value: 56.93037980583926
    - type: euclidean_spearman
      value: 53.34545415668656
    - type: manhattan_pearson
      value: 60.418057231064346
    - type: manhattan_spearman
      value: 56.191657563671406
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 69.44381319090809
    - type: cos_sim_spearman
      value: 71.89239151101017
    - type: euclidean_pearson
      value: 71.08466353671255
    - type: euclidean_spearman
      value: 71.8923431546743
    - type: manhattan_pearson
      value: 72.82399635347963
    - type: manhattan_spearman
      value: 73.46471776869852
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 69.59255573008079
    - type: cos_sim_spearman
      value: 66.62913411736977
    - type: euclidean_pearson
      value: 68.95610510950463
    - type: euclidean_spearman
      value: 66.62909813588546
    - type: manhattan_pearson
      value: 69.84273035920991
    - type: manhattan_spearman
      value: 67.48063231044473
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 73.45619996226283
    - type: cos_sim_spearman
      value: 74.83055449232837
    - type: euclidean_pearson
      value: 74.62134064628388
    - type: euclidean_spearman
      value: 74.83054707684443
    - type: manhattan_pearson
      value: 76.61314608080133
    - type: manhattan_spearman
      value: 76.86877561306177
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 72.63938715237121
    - type: cos_sim_spearman
      value: 73.94101941299299
    - type: euclidean_pearson
      value: 73.1193483863693
    - type: euclidean_spearman
      value: 73.94156997484005
    - type: manhattan_pearson
      value: 74.19841840522552
    - type: manhattan_spearman
      value: 75.04135720147993
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 75.09546255206122
    - type: cos_sim_spearman
      value: 77.70366353790475
    - type: euclidean_pearson
      value: 76.32709309757098
    - type: euclidean_spearman
      value: 77.70366353790475
    - type: manhattan_pearson
      value: 76.94194479561031
    - type: manhattan_spearman
      value: 78.46592204504032
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 58.49441445114376
    - type: cos_sim_spearman
      value: 59.05955673992238
    - type: euclidean_pearson
      value: 60.158391183785994
    - type: euclidean_spearman
      value: 59.05955673992238
    - type: manhattan_pearson
      value: 61.0421570895761
    - type: manhattan_spearman
      value: 59.192623617984765
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 67.22940000979654
    - type: cos_sim_spearman
      value: 65.01437530414441
    - type: euclidean_pearson
      value: 66.45644685287122
    - type: euclidean_spearman
      value: 65.01439378456281
    - type: manhattan_pearson
      value: 68.55942824733042
    - type: manhattan_spearman
      value: 67.0638150575607
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 65.91428709750188
    - type: mrr
      value: 87.6550990766677
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 34.75
    - type: map_at_10
      value: 45.217
    - type: map_at_100
      value: 46.12
    - type: map_at_1000
      value: 46.174
    - type: map_at_3
      value: 42.638999999999996
    - type: map_at_5
      value: 44.025
    - type: mrr_at_1
      value: 36.333
    - type: mrr_at_10
      value: 46.498
    - type: mrr_at_100
      value: 47.21
    - type: mrr_at_1000
      value: 47.254000000000005
    - type: mrr_at_3
      value: 44.0
    - type: mrr_at_5
      value: 45.283
    - type: ndcg_at_1
      value: 36.333
    - type: ndcg_at_10
      value: 50.782000000000004
    - type: ndcg_at_100
      value: 55.010999999999996
    - type: ndcg_at_1000
      value: 56.486000000000004
    - type: ndcg_at_3
      value: 45.511
    - type: ndcg_at_5
      value: 47.867
    - type: precision_at_1
      value: 36.333
    - type: precision_at_10
      value: 7.3
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 18.556
    - type: precision_at_5
      value: 12.467
    - type: recall_at_1
      value: 34.75
    - type: recall_at_10
      value: 66.75
    - type: recall_at_100
      value: 86.406
    - type: recall_at_1000
      value: 97.833
    - type: recall_at_3
      value: 52.333
    - type: recall_at_5
      value: 57.972
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.609900990099
    - type: cos_sim_ap
      value: 84.84797689028449
    - type: cos_sim_f1
      value: 78.88531618435157
    - type: cos_sim_precision
      value: 84.98845265588915
    - type: cos_sim_recall
      value: 73.6
    - type: dot_accuracy
      value: 99.609900990099
    - type: dot_ap
      value: 84.84797689028449
    - type: dot_f1
      value: 78.88531618435157
    - type: dot_precision
      value: 84.98845265588915
    - type: dot_recall
      value: 73.6
    - type: euclidean_accuracy
      value: 99.609900990099
    - type: euclidean_ap
      value: 84.84797689028449
    - type: euclidean_f1
      value: 78.88531618435157
    - type: euclidean_precision
      value: 84.98845265588915
    - type: euclidean_recall
      value: 73.6
    - type: manhattan_accuracy
      value: 99.65544554455445
    - type: manhattan_ap
      value: 87.87137216622611
    - type: manhattan_f1
      value: 81.47757255936675
    - type: manhattan_precision
      value: 86.25698324022346
    - type: manhattan_recall
      value: 77.2
    - type: max_accuracy
      value: 99.65544554455445
    - type: max_ap
      value: 87.87137216622611
    - type: max_f1
      value: 81.47757255936675
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 48.25386667167564
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.471037924796036
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 39.18682846959484
    - type: mrr
      value: 39.50644841269841
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 28.946936299379463
    - type: cos_sim_spearman
      value: 30.066436215046654
    - type: dot_pearson
      value: 28.946936196147593
    - type: dot_spearman
      value: 30.018099216048675
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.7080000000000002
    - type: map_at_10
      value: 7.288
    - type: map_at_100
      value: 11.64
    - type: map_at_1000
      value: 13.227
    - type: map_at_3
      value: 3.6769999999999996
    - type: map_at_5
      value: 5.559
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 37.412
    - type: mrr_at_100
      value: 38.509
    - type: mrr_at_1000
      value: 38.513999999999996
    - type: mrr_at_3
      value: 31.633
    - type: mrr_at_5
      value: 35.306
    - type: ndcg_at_1
      value: 18.367
    - type: ndcg_at_10
      value: 19.139999999999997
    - type: ndcg_at_100
      value: 29.513
    - type: ndcg_at_1000
      value: 41.931000000000004
    - type: ndcg_at_3
      value: 18.381
    - type: ndcg_at_5
      value: 20.009
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 18.570999999999998
    - type: precision_at_100
      value: 6.796
    - type: precision_at_1000
      value: 1.461
    - type: precision_at_3
      value: 21.088
    - type: precision_at_5
      value: 22.857
    - type: recall_at_1
      value: 1.7080000000000002
    - type: recall_at_10
      value: 12.484
    - type: recall_at_100
      value: 40.387
    - type: recall_at_1000
      value: 78.199
    - type: recall_at_3
      value: 4.5969999999999995
    - type: recall_at_5
      value: 8.273
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.0384
    - type: ap
      value: 14.428610751309057
    - type: f1
      value: 54.76005976202749
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.79003961516695
    - type: f1
      value: 52.98288621191831
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 36.071952470860104
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 80.92030756392681
    - type: cos_sim_ap
      value: 53.647013401002674
    - type: cos_sim_f1
      value: 53.12840372745977
    - type: cos_sim_precision
      value: 49.07221104404203
    - type: cos_sim_recall
      value: 57.9155672823219
    - type: dot_accuracy
      value: 80.92030756392681
    - type: dot_ap
      value: 53.647013401002674
    - type: dot_f1
      value: 53.12840372745977
    - type: dot_precision
      value: 49.07221104404203
    - type: dot_recall
      value: 57.9155672823219
    - type: euclidean_accuracy
      value: 80.92030756392681
    - type: euclidean_ap
      value: 53.647013401002674
    - type: euclidean_f1
      value: 53.12840372745977
    - type: euclidean_precision
      value: 49.07221104404203
    - type: euclidean_recall
      value: 57.9155672823219
    - type: manhattan_accuracy
      value: 80.9322286463611
    - type: manhattan_ap
      value: 52.933397134497554
    - type: manhattan_f1
      value: 51.88005711565922
    - type: manhattan_precision
      value: 47.247507585609014
    - type: manhattan_recall
      value: 57.519788918205805
    - type: max_accuracy
      value: 80.9322286463611
    - type: max_ap
      value: 53.647013401002674
    - type: max_f1
      value: 53.12840372745977
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 85.58427445958007
    - type: cos_sim_ap
      value: 77.9469627905898
    - type: cos_sim_f1
      value: 70.96631205673759
    - type: cos_sim_precision
      value: 68.20505538199374
    - type: cos_sim_recall
      value: 73.9605789959963
    - type: dot_accuracy
      value: 85.58427445958007
    - type: dot_ap
      value: 77.94696228563409
    - type: dot_f1
      value: 70.96631205673759
    - type: dot_precision
      value: 68.20505538199374
    - type: dot_recall
      value: 73.9605789959963
    - type: euclidean_accuracy
      value: 85.58427445958007
    - type: euclidean_ap
      value: 77.94696250005988
    - type: euclidean_f1
      value: 70.96631205673759
    - type: euclidean_precision
      value: 68.20505538199374
    - type: euclidean_recall
      value: 73.9605789959963
    - type: manhattan_accuracy
      value: 86.07521248108046
    - type: manhattan_ap
      value: 78.88285193661817
    - type: manhattan_f1
      value: 71.94010876474329
    - type: manhattan_precision
      value: 66.44487932159166
    - type: manhattan_recall
      value: 78.42623960578996
    - type: max_accuracy
      value: 86.07521248108046
    - type: max_ap
      value: 78.88285193661817
    - type: max_f1
      value: 71.94010876474329
---
