mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_wordpca
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.80597014925372
    - type: ap
      value: 34.18495644285039
    - type: f1
      value: 65.12501428730288
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.700325
    - type: ap
      value: 62.841873581522336
    - type: f1
      value: 67.168918887186
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 35.455999999999996
    - type: f1
      value: 34.87747132191852
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 17.354
    - type: map_at_10
      value: 29.286
    - type: map_at_100
      value: 30.514000000000003
    - type: map_at_1000
      value: 30.567
    - type: map_at_3
      value: 25.865
    - type: map_at_5
      value: 27.916999999999998
    - type: mrr_at_1
      value: 18.065
    - type: mrr_at_10
      value: 29.53
    - type: mrr_at_100
      value: 30.758999999999997
    - type: mrr_at_1000
      value: 30.812
    - type: mrr_at_3
      value: 26.090999999999998
    - type: mrr_at_5
      value: 28.16
    - type: ndcg_at_1
      value: 17.354
    - type: ndcg_at_10
      value: 35.658
    - type: ndcg_at_100
      value: 41.638
    - type: ndcg_at_1000
      value: 43.126999999999995
    - type: ndcg_at_3
      value: 28.647
    - type: ndcg_at_5
      value: 32.357
    - type: precision_at_1
      value: 17.354
    - type: precision_at_10
      value: 5.59
    - type: precision_at_100
      value: 0.839
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 12.232999999999999
    - type: precision_at_5
      value: 9.147
    - type: recall_at_1
      value: 17.354
    - type: recall_at_10
      value: 55.903000000000006
    - type: recall_at_100
      value: 83.855
    - type: recall_at_1000
      value: 95.733
    - type: recall_at_3
      value: 36.7
    - type: recall_at_5
      value: 45.733000000000004
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 33.33042693504757
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.879333444188894
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.782491804304975
    - type: mrr
      value: 66.79835553796772
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 71.52968195581401
    - type: cos_sim_spearman
      value: 71.47692985515434
    - type: euclidean_pearson
      value: 71.4263891046911
    - type: euclidean_spearman
      value: 71.47692985515434
    - type: manhattan_pearson
      value: 71.4122663134462
    - type: manhattan_spearman
      value: 72.05405143899608
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 69.31493506493507
    - type: f1
      value: 68.35552609562312
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 31.64074086270642
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 22.03423540035169
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.915
    - type: map_at_10
      value: 27.394000000000002
    - type: map_at_100
      value: 28.451999999999998
    - type: map_at_1000
      value: 28.602
    - type: map_at_3
      value: 24.919
    - type: map_at_5
      value: 26.468999999999998
    - type: mrr_at_1
      value: 26.179999999999996
    - type: mrr_at_10
      value: 32.317
    - type: mrr_at_100
      value: 33.211
    - type: mrr_at_1000
      value: 33.293
    - type: mrr_at_3
      value: 30.329
    - type: mrr_at_5
      value: 31.531
    - type: ndcg_at_1
      value: 26.179999999999996
    - type: ndcg_at_10
      value: 31.744
    - type: ndcg_at_100
      value: 36.684
    - type: ndcg_at_1000
      value: 39.891
    - type: ndcg_at_3
      value: 28.260999999999996
    - type: ndcg_at_5
      value: 30.076000000000004
    - type: precision_at_1
      value: 26.179999999999996
    - type: precision_at_10
      value: 6.0089999999999995
    - type: precision_at_100
      value: 1.043
    - type: precision_at_1000
      value: 0.16199999999999998
    - type: precision_at_3
      value: 13.447999999999999
    - type: precision_at_5
      value: 9.957
    - type: recall_at_1
      value: 20.915
    - type: recall_at_10
      value: 39.377
    - type: recall_at_100
      value: 61.41799999999999
    - type: recall_at_1000
      value: 83.096
    - type: recall_at_3
      value: 28.988000000000003
    - type: recall_at_5
      value: 34.147
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 15.379999999999999
    - type: map_at_10
      value: 20.892
    - type: map_at_100
      value: 21.766
    - type: map_at_1000
      value: 21.877
    - type: map_at_3
      value: 19.064
    - type: map_at_5
      value: 20.072000000000003
    - type: mrr_at_1
      value: 19.872999999999998
    - type: mrr_at_10
      value: 25.34
    - type: mrr_at_100
      value: 26.108999999999998
    - type: mrr_at_1000
      value: 26.177
    - type: mrr_at_3
      value: 23.546
    - type: mrr_at_5
      value: 24.517
    - type: ndcg_at_1
      value: 19.872999999999998
    - type: ndcg_at_10
      value: 24.733
    - type: ndcg_at_100
      value: 28.825
    - type: ndcg_at_1000
      value: 31.56
    - type: ndcg_at_3
      value: 21.685
    - type: ndcg_at_5
      value: 23.047
    - type: precision_at_1
      value: 19.872999999999998
    - type: precision_at_10
      value: 4.726
    - type: precision_at_100
      value: 0.8380000000000001
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 10.488
    - type: precision_at_5
      value: 7.580000000000001
    - type: recall_at_1
      value: 15.379999999999999
    - type: recall_at_10
      value: 31.705
    - type: recall_at_100
      value: 50.019999999999996
    - type: recall_at_1000
      value: 68.948
    - type: recall_at_3
      value: 22.939
    - type: recall_at_5
      value: 26.590999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 23.873
    - type: map_at_10
      value: 32.033
    - type: map_at_100
      value: 33.117000000000004
    - type: map_at_1000
      value: 33.217
    - type: map_at_3
      value: 29.799
    - type: map_at_5
      value: 31.108000000000004
    - type: mrr_at_1
      value: 27.711999999999996
    - type: mrr_at_10
      value: 35.186
    - type: mrr_at_100
      value: 36.095
    - type: mrr_at_1000
      value: 36.162
    - type: mrr_at_3
      value: 33.062000000000005
    - type: mrr_at_5
      value: 34.385
    - type: ndcg_at_1
      value: 27.711999999999996
    - type: ndcg_at_10
      value: 36.497
    - type: ndcg_at_100
      value: 41.565000000000005
    - type: ndcg_at_1000
      value: 43.949
    - type: ndcg_at_3
      value: 32.403
    - type: ndcg_at_5
      value: 34.492
    - type: precision_at_1
      value: 27.711999999999996
    - type: precision_at_10
      value: 5.918
    - type: precision_at_100
      value: 0.924
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 14.587
    - type: precision_at_5
      value: 10.169
    - type: recall_at_1
      value: 23.873
    - type: recall_at_10
      value: 46.914
    - type: recall_at_100
      value: 69.527
    - type: recall_at_1000
      value: 86.921
    - type: recall_at_3
      value: 35.843
    - type: recall_at_5
      value: 40.99
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.377
    - type: map_at_10
      value: 13.936000000000002
    - type: map_at_100
      value: 14.731
    - type: map_at_1000
      value: 14.843
    - type: map_at_3
      value: 12.498
    - type: map_at_5
      value: 13.309999999999999
    - type: mrr_at_1
      value: 11.299
    - type: mrr_at_10
      value: 14.951
    - type: mrr_at_100
      value: 15.790000000000001
    - type: mrr_at_1000
      value: 15.891
    - type: mrr_at_3
      value: 13.522
    - type: mrr_at_5
      value: 14.313
    - type: ndcg_at_1
      value: 11.299
    - type: ndcg_at_10
      value: 16.319
    - type: ndcg_at_100
      value: 20.748
    - type: ndcg_at_1000
      value: 24.166999999999998
    - type: ndcg_at_3
      value: 13.413
    - type: ndcg_at_5
      value: 14.828
    - type: precision_at_1
      value: 11.299
    - type: precision_at_10
      value: 2.588
    - type: precision_at_100
      value: 0.513
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 5.499
    - type: precision_at_5
      value: 4.136
    - type: recall_at_1
      value: 10.377
    - type: recall_at_10
      value: 22.837
    - type: recall_at_100
      value: 44.043
    - type: recall_at_1000
      value: 70.935
    - type: recall_at_3
      value: 15.009
    - type: recall_at_5
      value: 18.371000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.729
    - type: map_at_10
      value: 9.216000000000001
    - type: map_at_100
      value: 9.905999999999999
    - type: map_at_1000
      value: 10.019
    - type: map_at_3
      value: 7.996
    - type: map_at_5
      value: 8.602
    - type: mrr_at_1
      value: 7.338
    - type: mrr_at_10
      value: 11.356
    - type: mrr_at_100
      value: 12.102
    - type: mrr_at_1000
      value: 12.197
    - type: mrr_at_3
      value: 9.950000000000001
    - type: mrr_at_5
      value: 10.597
    - type: ndcg_at_1
      value: 7.338
    - type: ndcg_at_10
      value: 11.783000000000001
    - type: ndcg_at_100
      value: 15.506
    - type: ndcg_at_1000
      value: 18.719
    - type: ndcg_at_3
      value: 9.276
    - type: ndcg_at_5
      value: 10.262
    - type: precision_at_1
      value: 7.338
    - type: precision_at_10
      value: 2.3009999999999997
    - type: precision_at_100
      value: 0.48900000000000005
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 4.561
    - type: precision_at_5
      value: 3.383
    - type: recall_at_1
      value: 5.729
    - type: recall_at_10
      value: 17.717
    - type: recall_at_100
      value: 34.410000000000004
    - type: recall_at_1000
      value: 58.165
    - type: recall_at_3
      value: 10.742
    - type: recall_at_5
      value: 13.23
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 14.213999999999999
    - type: map_at_10
      value: 19.731
    - type: map_at_100
      value: 20.784
    - type: map_at_1000
      value: 20.924
    - type: map_at_3
      value: 17.746000000000002
    - type: map_at_5
      value: 18.697
    - type: mrr_at_1
      value: 18.093999999999998
    - type: mrr_at_10
      value: 23.9
    - type: mrr_at_100
      value: 24.804000000000002
    - type: mrr_at_1000
      value: 24.891
    - type: mrr_at_3
      value: 21.72
    - type: mrr_at_5
      value: 22.802
    - type: ndcg_at_1
      value: 18.093999999999998
    - type: ndcg_at_10
      value: 23.834
    - type: ndcg_at_100
      value: 29.294999999999998
    - type: ndcg_at_1000
      value: 32.589
    - type: ndcg_at_3
      value: 20.173
    - type: ndcg_at_5
      value: 21.563
    - type: precision_at_1
      value: 18.093999999999998
    - type: precision_at_10
      value: 4.629
    - type: precision_at_100
      value: 0.894
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 9.593
    - type: precision_at_5
      value: 6.968000000000001
    - type: recall_at_1
      value: 14.213999999999999
    - type: recall_at_10
      value: 32.238
    - type: recall_at_100
      value: 57.096999999999994
    - type: recall_at_1000
      value: 80.284
    - type: recall_at_3
      value: 21.756
    - type: recall_at_5
      value: 25.511
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.9
    - type: map_at_10
      value: 15.719
    - type: map_at_100
      value: 16.699
    - type: map_at_1000
      value: 16.833000000000002
    - type: map_at_3
      value: 14.130999999999998
    - type: map_at_5
      value: 15.011
    - type: mrr_at_1
      value: 13.584
    - type: mrr_at_10
      value: 18.6
    - type: mrr_at_100
      value: 19.607
    - type: mrr_at_1000
      value: 19.692999999999998
    - type: mrr_at_3
      value: 17.085
    - type: mrr_at_5
      value: 17.907
    - type: ndcg_at_1
      value: 13.584
    - type: ndcg_at_10
      value: 18.913
    - type: ndcg_at_100
      value: 24.135
    - type: ndcg_at_1000
      value: 27.590999999999998
    - type: ndcg_at_3
      value: 16.052
    - type: ndcg_at_5
      value: 17.352999999999998
    - type: precision_at_1
      value: 13.584
    - type: precision_at_10
      value: 3.5839999999999996
    - type: precision_at_100
      value: 0.74
    - type: precision_at_1000
      value: 0.122
    - type: precision_at_3
      value: 7.763000000000001
    - type: precision_at_5
      value: 5.731
    - type: recall_at_1
      value: 10.9
    - type: recall_at_10
      value: 25.680999999999997
    - type: recall_at_100
      value: 49.147999999999996
    - type: recall_at_1000
      value: 73.977
    - type: recall_at_3
      value: 18.043
    - type: recall_at_5
      value: 21.186
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.486
    - type: map_at_10
      value: 17.156583333333334
    - type: map_at_100
      value: 18.013749999999998
    - type: map_at_1000
      value: 18.136999999999997
    - type: map_at_3
      value: 15.558583333333335
    - type: map_at_5
      value: 16.42183333333333
    - type: mrr_at_1
      value: 15.296833333333332
    - type: mrr_at_10
      value: 20.03541666666667
    - type: mrr_at_100
      value: 20.8445
    - type: mrr_at_1000
      value: 20.933333333333334
    - type: mrr_at_3
      value: 18.420333333333335
    - type: mrr_at_5
      value: 19.293499999999998
    - type: ndcg_at_1
      value: 15.296833333333332
    - type: ndcg_at_10
      value: 20.348166666666664
    - type: ndcg_at_100
      value: 24.78708333333334
    - type: ndcg_at_1000
      value: 27.97908333333333
    - type: ndcg_at_3
      value: 17.439750000000004
    - type: ndcg_at_5
      value: 18.722583333333333
    - type: precision_at_1
      value: 15.296833333333332
    - type: precision_at_10
      value: 3.687916666666667
    - type: precision_at_100
      value: 0.7038333333333333
    - type: precision_at_1000
      value: 0.11483333333333334
    - type: precision_at_3
      value: 8.1305
    - type: precision_at_5
      value: 5.888333333333334
    - type: recall_at_1
      value: 12.486
    - type: recall_at_10
      value: 27.169166666666666
    - type: recall_at_100
      value: 47.70375
    - type: recall_at_1000
      value: 70.991
    - type: recall_at_3
      value: 18.94875
    - type: recall_at_5
      value: 22.289749999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 8.32
    - type: map_at_10
      value: 12.171
    - type: map_at_100
      value: 12.847
    - type: map_at_1000
      value: 12.939
    - type: map_at_3
      value: 10.77
    - type: map_at_5
      value: 11.436
    - type: mrr_at_1
      value: 10.428999999999998
    - type: mrr_at_10
      value: 14.285999999999998
    - type: mrr_at_100
      value: 14.981
    - type: mrr_at_1000
      value: 15.057
    - type: mrr_at_3
      value: 12.831999999999999
    - type: mrr_at_5
      value: 13.546
    - type: ndcg_at_1
      value: 10.428999999999998
    - type: ndcg_at_10
      value: 14.896
    - type: ndcg_at_100
      value: 18.603
    - type: ndcg_at_1000
      value: 21.259
    - type: ndcg_at_3
      value: 12.157
    - type: ndcg_at_5
      value: 13.221
    - type: precision_at_1
      value: 10.428999999999998
    - type: precision_at_10
      value: 2.6839999999999997
    - type: precision_at_100
      value: 0.5
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 5.726
    - type: precision_at_5
      value: 4.109999999999999
    - type: recall_at_1
      value: 8.32
    - type: recall_at_10
      value: 21.465999999999998
    - type: recall_at_100
      value: 38.933
    - type: recall_at_1000
      value: 59.223000000000006
    - type: recall_at_3
      value: 13.577
    - type: recall_at_5
      value: 16.397000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.885
    - type: map_at_10
      value: 8.942
    - type: map_at_100
      value: 9.543
    - type: map_at_1000
      value: 9.664
    - type: map_at_3
      value: 7.964
    - type: map_at_5
      value: 8.408
    - type: mrr_at_1
      value: 7.605
    - type: mrr_at_10
      value: 11.072
    - type: mrr_at_100
      value: 11.693000000000001
    - type: mrr_at_1000
      value: 11.797
    - type: mrr_at_3
      value: 9.945
    - type: mrr_at_5
      value: 10.511
    - type: ndcg_at_1
      value: 7.605
    - type: ndcg_at_10
      value: 11.124
    - type: ndcg_at_100
      value: 14.536
    - type: ndcg_at_1000
      value: 18.013
    - type: ndcg_at_3
      value: 9.205
    - type: ndcg_at_5
      value: 9.923
    - type: precision_at_1
      value: 7.605
    - type: precision_at_10
      value: 2.1340000000000003
    - type: precision_at_100
      value: 0.46299999999999997
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 4.496
    - type: precision_at_5
      value: 3.283
    - type: recall_at_1
      value: 5.885
    - type: recall_at_10
      value: 15.742
    - type: recall_at_100
      value: 31.879999999999995
    - type: recall_at_1000
      value: 57.748
    - type: recall_at_3
      value: 10.378
    - type: recall_at_5
      value: 12.181000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.709999999999999
    - type: map_at_10
      value: 15.93
    - type: map_at_100
      value: 16.692
    - type: map_at_1000
      value: 16.804
    - type: map_at_3
      value: 14.729999999999999
    - type: map_at_5
      value: 15.481
    - type: mrr_at_1
      value: 14.272000000000002
    - type: mrr_at_10
      value: 18.820999999999998
    - type: mrr_at_100
      value: 19.588
    - type: mrr_at_1000
      value: 19.682
    - type: mrr_at_3
      value: 17.522
    - type: mrr_at_5
      value: 18.276999999999997
    - type: ndcg_at_1
      value: 14.272000000000002
    - type: ndcg_at_10
      value: 18.747
    - type: ndcg_at_100
      value: 23.092
    - type: ndcg_at_1000
      value: 26.241999999999997
    - type: ndcg_at_3
      value: 16.496
    - type: ndcg_at_5
      value: 17.635
    - type: precision_at_1
      value: 14.272000000000002
    - type: precision_at_10
      value: 3.144
    - type: precision_at_100
      value: 0.598
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 7.587000000000001
    - type: precision_at_5
      value: 5.354
    - type: recall_at_1
      value: 11.709999999999999
    - type: recall_at_10
      value: 24.62
    - type: recall_at_100
      value: 45.26
    - type: recall_at_1000
      value: 68.479
    - type: recall_at_3
      value: 18.187
    - type: recall_at_5
      value: 21.233
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.626
    - type: map_at_10
      value: 17.95
    - type: map_at_100
      value: 18.917
    - type: map_at_1000
      value: 19.1
    - type: map_at_3
      value: 16.309
    - type: map_at_5
      value: 17.148
    - type: mrr_at_1
      value: 17.194000000000003
    - type: mrr_at_10
      value: 21.473
    - type: mrr_at_100
      value: 22.273
    - type: mrr_at_1000
      value: 22.377
    - type: mrr_at_3
      value: 19.763
    - type: mrr_at_5
      value: 20.721
    - type: ndcg_at_1
      value: 17.194000000000003
    - type: ndcg_at_10
      value: 21.358
    - type: ndcg_at_100
      value: 25.884
    - type: ndcg_at_1000
      value: 29.852
    - type: ndcg_at_3
      value: 18.528
    - type: ndcg_at_5
      value: 19.628
    - type: precision_at_1
      value: 17.194000000000003
    - type: precision_at_10
      value: 4.19
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.178
    - type: precision_at_3
      value: 8.827
    - type: precision_at_5
      value: 6.4030000000000005
    - type: recall_at_1
      value: 13.626
    - type: recall_at_10
      value: 27.439999999999998
    - type: recall_at_100
      value: 49.178
    - type: recall_at_1000
      value: 76.681
    - type: recall_at_3
      value: 18.848000000000003
    - type: recall_at_5
      value: 22.064
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.903
    - type: map_at_10
      value: 11.965
    - type: map_at_100
      value: 12.711
    - type: map_at_1000
      value: 12.822
    - type: map_at_3
      value: 10.777000000000001
    - type: map_at_5
      value: 11.32
    - type: mrr_at_1
      value: 9.982000000000001
    - type: mrr_at_10
      value: 13.123000000000001
    - type: mrr_at_100
      value: 13.880999999999998
    - type: mrr_at_1000
      value: 13.983
    - type: mrr_at_3
      value: 11.768
    - type: mrr_at_5
      value: 12.415
    - type: ndcg_at_1
      value: 9.982000000000001
    - type: ndcg_at_10
      value: 14.23
    - type: ndcg_at_100
      value: 18.572
    - type: ndcg_at_1000
      value: 21.917
    - type: ndcg_at_3
      value: 11.628
    - type: ndcg_at_5
      value: 12.642999999999999
    - type: precision_at_1
      value: 9.982000000000001
    - type: precision_at_10
      value: 2.348
    - type: precision_at_100
      value: 0.49899999999999994
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 4.9910000000000005
    - type: precision_at_5
      value: 3.5860000000000003
    - type: recall_at_1
      value: 8.903
    - type: recall_at_10
      value: 20.293
    - type: recall_at_100
      value: 41.531
    - type: recall_at_1000
      value: 67.435
    - type: recall_at_3
      value: 13.075000000000001
    - type: recall_at_5
      value: 15.576
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.4510000000000005
    - type: map_at_10
      value: 9.776
    - type: map_at_100
      value: 11.106
    - type: map_at_1000
      value: 11.289
    - type: map_at_3
      value: 8.039
    - type: map_at_5
      value: 8.822000000000001
    - type: mrr_at_1
      value: 12.313
    - type: mrr_at_10
      value: 19.846
    - type: mrr_at_100
      value: 21.035999999999998
    - type: mrr_at_1000
      value: 21.108
    - type: mrr_at_3
      value: 17.264
    - type: mrr_at_5
      value: 18.554000000000002
    - type: ndcg_at_1
      value: 12.313
    - type: ndcg_at_10
      value: 14.763000000000002
    - type: ndcg_at_100
      value: 21.182000000000002
    - type: ndcg_at_1000
      value: 24.98
    - type: ndcg_at_3
      value: 11.418000000000001
    - type: ndcg_at_5
      value: 12.434000000000001
    - type: precision_at_1
      value: 12.313
    - type: precision_at_10
      value: 4.932
    - type: precision_at_100
      value: 1.18
    - type: precision_at_1000
      value: 0.187
    - type: precision_at_3
      value: 8.795
    - type: precision_at_5
      value: 6.84
    - type: recall_at_1
      value: 5.4510000000000005
    - type: recall_at_10
      value: 18.998
    - type: recall_at_100
      value: 41.927
    - type: recall_at_1000
      value: 63.660000000000004
    - type: recall_at_3
      value: 10.91
    - type: recall_at_5
      value: 13.700000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.902
    - type: map_at_10
      value: 6.98
    - type: map_at_100
      value: 9.789
    - type: map_at_1000
      value: 10.602
    - type: map_at_3
      value: 5.008
    - type: map_at_5
      value: 5.8069999999999995
    - type: mrr_at_1
      value: 31.75
    - type: mrr_at_10
      value: 42.102000000000004
    - type: mrr_at_100
      value: 43.01
    - type: mrr_at_1000
      value: 43.047000000000004
    - type: mrr_at_3
      value: 39.292
    - type: mrr_at_5
      value: 40.879
    - type: ndcg_at_1
      value: 23.375
    - type: ndcg_at_10
      value: 18.685
    - type: ndcg_at_100
      value: 21.818
    - type: ndcg_at_1000
      value: 28.37
    - type: ndcg_at_3
      value: 21.13
    - type: ndcg_at_5
      value: 19.716
    - type: precision_at_1
      value: 31.75
    - type: precision_at_10
      value: 16.85
    - type: precision_at_100
      value: 5.577
    - type: precision_at_1000
      value: 1.239
    - type: precision_at_3
      value: 25.25
    - type: precision_at_5
      value: 21.45
    - type: recall_at_1
      value: 2.902
    - type: recall_at_10
      value: 11.200000000000001
    - type: recall_at_100
      value: 28.299000000000003
    - type: recall_at_1000
      value: 50.495999999999995
    - type: recall_at_3
      value: 6.273
    - type: recall_at_5
      value: 7.901
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 40.385
    - type: f1
      value: 37.518235927886295
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.325999999999999
    - type: map_at_10
      value: 19.023
    - type: map_at_100
      value: 19.965
    - type: map_at_1000
      value: 20.055
    - type: map_at_3
      value: 16.788
    - type: map_at_5
      value: 18.037
    - type: mrr_at_1
      value: 13.096
    - type: mrr_at_10
      value: 20.149
    - type: mrr_at_100
      value: 21.109
    - type: mrr_at_1000
      value: 21.191
    - type: mrr_at_3
      value: 17.843999999999998
    - type: mrr_at_5
      value: 19.121
    - type: ndcg_at_1
      value: 13.096
    - type: ndcg_at_10
      value: 23.192
    - type: ndcg_at_100
      value: 28.174
    - type: ndcg_at_1000
      value: 30.682
    - type: ndcg_at_3
      value: 18.566
    - type: ndcg_at_5
      value: 20.806
    - type: precision_at_1
      value: 13.096
    - type: precision_at_10
      value: 3.8150000000000004
    - type: precision_at_100
      value: 0.654
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 8.136000000000001
    - type: precision_at_5
      value: 6.034
    - type: recall_at_1
      value: 12.325999999999999
    - type: recall_at_10
      value: 35.248000000000005
    - type: recall_at_100
      value: 58.819
    - type: recall_at_1000
      value: 78.278
    - type: recall_at_3
      value: 22.657
    - type: recall_at_5
      value: 28.038
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.789
    - type: map_at_10
      value: 9.142999999999999
    - type: map_at_100
      value: 10.02
    - type: map_at_1000
      value: 10.222000000000001
    - type: map_at_3
      value: 7.712
    - type: map_at_5
      value: 8.491999999999999
    - type: mrr_at_1
      value: 11.574
    - type: mrr_at_10
      value: 16.428
    - type: mrr_at_100
      value: 17.268
    - type: mrr_at_1000
      value: 17.380000000000003
    - type: mrr_at_3
      value: 14.609
    - type: mrr_at_5
      value: 15.651000000000002
    - type: ndcg_at_1
      value: 11.574
    - type: ndcg_at_10
      value: 12.687000000000001
    - type: ndcg_at_100
      value: 17.380000000000003
    - type: ndcg_at_1000
      value: 22.247
    - type: ndcg_at_3
      value: 10.411
    - type: ndcg_at_5
      value: 11.379
    - type: precision_at_1
      value: 11.574
    - type: precision_at_10
      value: 3.688
    - type: precision_at_100
      value: 0.836
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 6.842
    - type: precision_at_5
      value: 5.432
    - type: recall_at_1
      value: 5.789
    - type: recall_at_10
      value: 16.134
    - type: recall_at_100
      value: 35.082
    - type: recall_at_1000
      value: 65.85600000000001
    - type: recall_at_3
      value: 9.429
    - type: recall_at_5
      value: 12.508
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 15.253
    - type: map_at_10
      value: 21.166
    - type: map_at_100
      value: 21.94
    - type: map_at_1000
      value: 22.039
    - type: map_at_3
      value: 19.431
    - type: map_at_5
      value: 20.415
    - type: mrr_at_1
      value: 30.506
    - type: mrr_at_10
      value: 36.767
    - type: mrr_at_100
      value: 37.452999999999996
    - type: mrr_at_1000
      value: 37.511
    - type: mrr_at_3
      value: 34.855000000000004
    - type: mrr_at_5
      value: 35.913000000000004
    - type: ndcg_at_1
      value: 30.506
    - type: ndcg_at_10
      value: 27.310000000000002
    - type: ndcg_at_100
      value: 31.094
    - type: ndcg_at_1000
      value: 33.617999999999995
    - type: ndcg_at_3
      value: 23.880000000000003
    - type: ndcg_at_5
      value: 25.557000000000002
    - type: precision_at_1
      value: 30.506
    - type: precision_at_10
      value: 6.05
    - type: precision_at_100
      value: 0.911
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 14.999
    - type: precision_at_5
      value: 10.331
    - type: recall_at_1
      value: 15.253
    - type: recall_at_10
      value: 30.25
    - type: recall_at_100
      value: 45.550000000000004
    - type: recall_at_1000
      value: 62.532
    - type: recall_at_3
      value: 22.498
    - type: recall_at_5
      value: 25.826999999999998
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 66.13080000000001
    - type: ap
      value: 61.19755857703731
    - type: f1
      value: 65.75830761955302
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.17
    - type: map_at_10
      value: 10.051
    - type: map_at_100
      value: 10.888
    - type: map_at_1000
      value: 10.987
    - type: map_at_3
      value: 8.546
    - type: map_at_5
      value: 9.314
    - type: mrr_at_1
      value: 6.39
    - type: mrr_at_10
      value: 10.345
    - type: mrr_at_100
      value: 11.190999999999999
    - type: mrr_at_1000
      value: 11.286999999999999
    - type: mrr_at_3
      value: 8.818
    - type: mrr_at_5
      value: 9.604
    - type: ndcg_at_1
      value: 6.361
    - type: ndcg_at_10
      value: 12.613
    - type: ndcg_at_100
      value: 17.196
    - type: ndcg_at_1000
      value: 20.202
    - type: ndcg_at_3
      value: 9.419
    - type: ndcg_at_5
      value: 10.82
    - type: precision_at_1
      value: 6.361
    - type: precision_at_10
      value: 2.138
    - type: precision_at_100
      value: 0.45199999999999996
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 4.05
    - type: precision_at_5
      value: 3.132
    - type: recall_at_1
      value: 6.17
    - type: recall_at_10
      value: 20.628
    - type: recall_at_100
      value: 42.955
    - type: recall_at_1000
      value: 67.167
    - type: recall_at_3
      value: 11.706999999999999
    - type: recall_at_5
      value: 15.112
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.82124943000456
    - type: f1
      value: 88.09169902063448
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 57.64249886000912
    - type: f1
      value: 40.11976416066169
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.71149966375251
    - type: f1
      value: 59.327545383480526
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.3476798924008
    - type: f1
      value: 67.85719000199948
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.702180003024456
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.104912750356256
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.708351836889097
    - type: mrr
      value: 29.434552059097435
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.0969999999999995
    - type: map_at_10
      value: 7.6259999999999994
    - type: map_at_100
      value: 9.526
    - type: map_at_1000
      value: 10.785
    - type: map_at_3
      value: 6.010999999999999
    - type: map_at_5
      value: 6.707000000000001
    - type: mrr_at_1
      value: 32.198
    - type: mrr_at_10
      value: 41.882000000000005
    - type: mrr_at_100
      value: 42.63
    - type: mrr_at_1000
      value: 42.692
    - type: mrr_at_3
      value: 39.628
    - type: mrr_at_5
      value: 41.146
    - type: ndcg_at_1
      value: 30.65
    - type: ndcg_at_10
      value: 23.419
    - type: ndcg_at_100
      value: 22.442
    - type: ndcg_at_1000
      value: 31.927
    - type: ndcg_at_3
      value: 27.173000000000002
    - type: ndcg_at_5
      value: 25.375999999999998
    - type: precision_at_1
      value: 32.198
    - type: precision_at_10
      value: 17.214
    - type: precision_at_100
      value: 6.183000000000001
    - type: precision_at_1000
      value: 1.94
    - type: precision_at_3
      value: 25.697
    - type: precision_at_5
      value: 21.672
    - type: recall_at_1
      value: 4.0969999999999995
    - type: recall_at_10
      value: 11.239
    - type: recall_at_100
      value: 24.912
    - type: recall_at_1000
      value: 58.303000000000004
    - type: recall_at_3
      value: 7.1370000000000005
    - type: recall_at_5
      value: 8.756
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.871
    - type: map_at_10
      value: 15.822
    - type: map_at_100
      value: 16.885
    - type: map_at_1000
      value: 16.980999999999998
    - type: map_at_3
      value: 13.438
    - type: map_at_5
      value: 14.802000000000001
    - type: mrr_at_1
      value: 11.153
    - type: mrr_at_10
      value: 17.427999999999997
    - type: mrr_at_100
      value: 18.424
    - type: mrr_at_1000
      value: 18.506
    - type: mrr_at_3
      value: 14.976999999999999
    - type: mrr_at_5
      value: 16.39
    - type: ndcg_at_1
      value: 11.153
    - type: ndcg_at_10
      value: 19.842000000000002
    - type: ndcg_at_100
      value: 25.312
    - type: ndcg_at_1000
      value: 27.937
    - type: ndcg_at_3
      value: 14.979999999999999
    - type: ndcg_at_5
      value: 17.407
    - type: precision_at_1
      value: 11.153
    - type: precision_at_10
      value: 3.644
    - type: precision_at_100
      value: 0.675
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 6.914
    - type: precision_at_5
      value: 5.487
    - type: recall_at_1
      value: 9.871
    - type: recall_at_10
      value: 30.743
    - type: recall_at_100
      value: 56.330000000000005
    - type: recall_at_1000
      value: 76.545
    - type: recall_at_3
      value: 17.951
    - type: recall_at_5
      value: 23.597
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.153
    - type: map_at_10
      value: 72.152
    - type: map_at_100
      value: 72.92
    - type: map_at_1000
      value: 72.961
    - type: map_at_3
      value: 69.403
    - type: map_at_5
      value: 71.066
    - type: mrr_at_1
      value: 69.28
    - type: mrr_at_10
      value: 76.671
    - type: mrr_at_100
      value: 76.968
    - type: mrr_at_1000
      value: 76.98
    - type: mrr_at_3
      value: 75.253
    - type: mrr_at_5
      value: 76.127
    - type: ndcg_at_1
      value: 69.35
    - type: ndcg_at_10
      value: 76.818
    - type: ndcg_at_100
      value: 79.143
    - type: ndcg_at_1000
      value: 79.726
    - type: ndcg_at_3
      value: 73.393
    - type: ndcg_at_5
      value: 75.122
    - type: precision_at_1
      value: 69.35
    - type: precision_at_10
      value: 11.533
    - type: precision_at_100
      value: 1.396
    - type: precision_at_1000
      value: 0.151
    - type: precision_at_3
      value: 31.703
    - type: precision_at_5
      value: 20.942
    - type: recall_at_1
      value: 60.153
    - type: recall_at_10
      value: 85.668
    - type: recall_at_100
      value: 94.722
    - type: recall_at_1000
      value: 98.285
    - type: recall_at_3
      value: 75.779
    - type: recall_at_5
      value: 80.593
    - type: map_at_1
      value: 2.435
    - type: map_at_10
      value: 5.885
    - type: map_at_100
      value: 7.172000000000001
    - type: map_at_1000
      value: 7.412000000000001
    - type: map_at_3
      value: 4.273
    - type: map_at_5
      value: 5.050000000000001
    - type: mrr_at_1
      value: 12.0
    - type: mrr_at_10
      value: 19.368
    - type: mrr_at_100
      value: 20.602
    - type: mrr_at_1000
      value: 20.697
    - type: mrr_at_3
      value: 16.5
    - type: mrr_at_5
      value: 18.18
    - type: ndcg_at_1
      value: 12.0
    - type: ndcg_at_10
      value: 10.783
    - type: ndcg_at_100
      value: 16.857
    - type: ndcg_at_1000
      value: 21.995
    - type: ndcg_at_3
      value: 9.855
    - type: ndcg_at_5
      value: 8.763
    - type: precision_at_1
      value: 12.0
    - type: precision_at_10
      value: 5.75
    - type: precision_at_100
      value: 1.464
    - type: precision_at_1000
      value: 0.271
    - type: precision_at_3
      value: 9.267
    - type: precision_at_5
      value: 7.8
    - type: recall_at_1
      value: 2.435
    - type: recall_at_10
      value: 11.677
    - type: recall_at_100
      value: 29.727999999999998
    - type: recall_at_1000
      value: 55.01200000000001
    - type: recall_at_3
      value: 5.625
    - type: recall_at_5
      value: 7.927
    - type: map_at_1
      value: 0.13
    - type: map_at_10
      value: 0.91
    - type: map_at_100
      value: 4.061
    - type: map_at_1000
      value: 9.881
    - type: map_at_3
      value: 0.363
    - type: map_at_5
      value: 0.541
    - type: mrr_at_1
      value: 60.0
    - type: mrr_at_10
      value: 71.869
    - type: mrr_at_100
      value: 72.217
    - type: mrr_at_1000
      value: 72.217
    - type: mrr_at_3
      value: 69.333
    - type: mrr_at_5
      value: 71.333
    - type: ndcg_at_1
      value: 55.00000000000001
    - type: ndcg_at_10
      value: 49.476
    - type: ndcg_at_100
      value: 33.626
    - type: ndcg_at_1000
      value: 28.644
    - type: ndcg_at_3
      value: 54.173
    - type: ndcg_at_5
      value: 52.842999999999996
    - type: precision_at_1
      value: 60.0
    - type: precision_at_10
      value: 54.6
    - type: precision_at_100
      value: 34.52
    - type: precision_at_1000
      value: 13.786000000000001
    - type: precision_at_3
      value: 62.0
    - type: precision_at_5
      value: 58.8
    - type: recall_at_1
      value: 0.13
    - type: recall_at_10
      value: 1.196
    - type: recall_at_100
      value: 7.231999999999999
    - type: recall_at_1000
      value: 27.297
    - type: recall_at_3
      value: 0.407
    - type: recall_at_5
      value: 0.652
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 30.46199403095774
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 40.06790279282052
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.88374517260094
    - type: cos_sim_spearman
      value: 66.8146599530933
    - type: euclidean_pearson
      value: 72.16677058950762
    - type: euclidean_spearman
      value: 66.81475088977015
    - type: manhattan_pearson
      value: 70.5972960748393
    - type: manhattan_spearman
      value: 66.06419798937156
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 75.2563114595583
    - type: cos_sim_spearman
      value: 69.24367278736064
    - type: euclidean_pearson
      value: 72.40292269474219
    - type: euclidean_spearman
      value: 69.24502332361118
    - type: manhattan_pearson
      value: 68.50078537054152
    - type: manhattan_spearman
      value: 66.50598323215404
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 74.10242500284477
    - type: cos_sim_spearman
      value: 75.84987612154318
    - type: euclidean_pearson
      value: 75.52353979614497
    - type: euclidean_spearman
      value: 75.84988832691806
    - type: manhattan_pearson
      value: 74.8413761626873
    - type: manhattan_spearman
      value: 75.04964152928419
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 72.1575774985217
    - type: cos_sim_spearman
      value: 70.90141314189984
    - type: euclidean_pearson
      value: 71.9156106526078
    - type: euclidean_spearman
      value: 70.90140345522423
    - type: manhattan_pearson
      value: 70.72340581042884
    - type: manhattan_spearman
      value: 69.85236236925924
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 77.83919307142013
    - type: cos_sim_spearman
      value: 79.47682153516034
    - type: euclidean_pearson
      value: 79.2973167726878
    - type: euclidean_spearman
      value: 79.47681228883974
    - type: manhattan_pearson
      value: 78.92171052296403
    - type: manhattan_spearman
      value: 78.99217076956664
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 63.90192110994575
    - type: cos_sim_spearman
      value: 68.13219488213686
    - type: euclidean_pearson
      value: 67.85714382223736
    - type: euclidean_spearman
      value: 68.13246724904525
    - type: manhattan_pearson
      value: 67.80188617868961
    - type: manhattan_spearman
      value: 67.86053448092125
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.36473244186939
    - type: cos_sim_spearman
      value: 80.08243286023296
    - type: euclidean_pearson
      value: 80.1819164297702
    - type: euclidean_spearman
      value: 80.08330928388227
    - type: manhattan_pearson
      value: 79.60834848379639
    - type: manhattan_spearman
      value: 79.69333890794226
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 42.32641436292012
    - type: cos_sim_spearman
      value: 54.83877303154732
    - type: euclidean_pearson
      value: 49.38508638773706
    - type: euclidean_spearman
      value: 54.83877303154732
    - type: manhattan_pearson
      value: 46.92414915855828
    - type: manhattan_spearman
      value: 52.95296714067058
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 69.58492214466642
    - type: cos_sim_spearman
      value: 68.91907567009618
    - type: euclidean_pearson
      value: 70.72812327953963
    - type: euclidean_spearman
      value: 68.91912423326409
    - type: manhattan_pearson
      value: 70.14796745095204
    - type: manhattan_spearman
      value: 68.65856703154975
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.52992055140923
    - type: mrr
      value: 90.19458210634681
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 35.056
    - type: map_at_10
      value: 42.204
    - type: map_at_100
      value: 43.478
    - type: map_at_1000
      value: 43.541999999999994
    - type: map_at_3
      value: 39.781
    - type: map_at_5
      value: 41.225
    - type: mrr_at_1
      value: 36.333
    - type: mrr_at_10
      value: 43.666
    - type: mrr_at_100
      value: 44.773
    - type: mrr_at_1000
      value: 44.824000000000005
    - type: mrr_at_3
      value: 41.5
    - type: mrr_at_5
      value: 42.766999999999996
    - type: ndcg_at_1
      value: 36.333
    - type: ndcg_at_10
      value: 46.202
    - type: ndcg_at_100
      value: 52.236000000000004
    - type: ndcg_at_1000
      value: 53.803999999999995
    - type: ndcg_at_3
      value: 41.661
    - type: ndcg_at_5
      value: 44.019000000000005
    - type: precision_at_1
      value: 36.333
    - type: precision_at_10
      value: 6.3
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 16.111
    - type: precision_at_5
      value: 11.067
    - type: recall_at_1
      value: 35.056
    - type: recall_at_10
      value: 57.077999999999996
    - type: recall_at_100
      value: 84.88900000000001
    - type: recall_at_1000
      value: 96.933
    - type: recall_at_3
      value: 45.178000000000004
    - type: recall_at_5
      value: 50.733
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.54950495049505
    - type: cos_sim_ap
      value: 81.41161204735187
    - type: cos_sim_f1
      value: 74.35610302351624
    - type: cos_sim_precision
      value: 84.47837150127226
    - type: cos_sim_recall
      value: 66.4
    - type: dot_accuracy
      value: 99.54950495049505
    - type: dot_ap
      value: 81.41161204735187
    - type: dot_f1
      value: 74.35610302351624
    - type: dot_precision
      value: 84.47837150127226
    - type: dot_recall
      value: 66.4
    - type: euclidean_accuracy
      value: 99.54950495049505
    - type: euclidean_ap
      value: 81.41161204735187
    - type: euclidean_f1
      value: 74.35610302351624
    - type: euclidean_precision
      value: 84.47837150127226
    - type: euclidean_recall
      value: 66.4
    - type: manhattan_accuracy
      value: 99.51089108910891
    - type: manhattan_ap
      value: 78.54741188045705
    - type: manhattan_f1
      value: 71.88732394366198
    - type: manhattan_precision
      value: 82.3225806451613
    - type: manhattan_recall
      value: 63.800000000000004
    - type: max_accuracy
      value: 99.54950495049505
    - type: max_ap
      value: 81.41161204735187
    - type: max_f1
      value: 74.35610302351624
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 36.91417149931838
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.018095001166785
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.028503758530526
    - type: mrr
      value: 43.540539321789325
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.929163871560323
    - type: cos_sim_spearman
      value: 32.48633854394627
    - type: dot_pearson
      value: 30.92916389419323
    - type: dot_spearman
      value: 32.333874007816924
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.68
    - type: map_at_10
      value: 5.285
    - type: map_at_100
      value: 8.16
    - type: map_at_1000
      value: 9.572
    - type: map_at_3
      value: 3.27
    - type: map_at_5
      value: 3.823
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 33.477000000000004
    - type: mrr_at_100
      value: 35.096
    - type: mrr_at_1000
      value: 35.111
    - type: mrr_at_3
      value: 30.612000000000002
    - type: mrr_at_5
      value: 31.531
    - type: ndcg_at_1
      value: 22.448999999999998
    - type: ndcg_at_10
      value: 14.738000000000001
    - type: ndcg_at_100
      value: 23.663
    - type: ndcg_at_1000
      value: 36.577
    - type: ndcg_at_3
      value: 18.826999999999998
    - type: ndcg_at_5
      value: 15.842
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 13.061
    - type: precision_at_100
      value: 5.327
    - type: precision_at_1000
      value: 1.333
    - type: precision_at_3
      value: 19.728
    - type: precision_at_5
      value: 15.509999999999998
    - type: recall_at_1
      value: 1.68
    - type: recall_at_10
      value: 9.515
    - type: recall_at_100
      value: 32.824
    - type: recall_at_1000
      value: 72.975
    - type: recall_at_3
      value: 4.314
    - type: recall_at_5
      value: 5.4879999999999995
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 68.95299999999999
    - type: ap
      value: 12.037260089647054
    - type: f1
      value: 51.98429371477145
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.339558573853985
    - type: f1
      value: 55.58929521718743
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 31.17109985455679
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.59659057042379
    - type: cos_sim_ap
      value: 65.22209138338175
    - type: cos_sim_f1
      value: 61.509575666541494
    - type: cos_sim_precision
      value: 58.51393188854489
    - type: cos_sim_recall
      value: 64.82849604221636
    - type: dot_accuracy
      value: 83.59659057042379
    - type: dot_ap
      value: 65.22209138338175
    - type: dot_f1
      value: 61.509575666541494
    - type: dot_precision
      value: 58.51393188854489
    - type: dot_recall
      value: 64.82849604221636
    - type: euclidean_accuracy
      value: 83.59659057042379
    - type: euclidean_ap
      value: 65.22209138338175
    - type: euclidean_f1
      value: 61.509575666541494
    - type: euclidean_precision
      value: 58.51393188854489
    - type: euclidean_recall
      value: 64.82849604221636
    - type: manhattan_accuracy
      value: 83.93634141980093
    - type: manhattan_ap
      value: 66.46758652590019
    - type: manhattan_f1
      value: 62.471089470480834
    - type: manhattan_precision
      value: 57.98870056497175
    - type: manhattan_recall
      value: 67.70448548812665
    - type: max_accuracy
      value: 83.93634141980093
    - type: max_ap
      value: 66.46758652590019
    - type: max_f1
      value: 62.471089470480834
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.49435324251951
    - type: cos_sim_ap
      value: 80.34673925701317
    - type: cos_sim_f1
      value: 72.30198298159463
    - type: cos_sim_precision
      value: 70.45072686098327
    - type: cos_sim_recall
      value: 74.25315676008624
    - type: dot_accuracy
      value: 86.49435324251951
    - type: dot_ap
      value: 80.3467395332787
    - type: dot_f1
      value: 72.30198298159463
    - type: dot_precision
      value: 70.45072686098327
    - type: dot_recall
      value: 74.25315676008624
    - type: euclidean_accuracy
      value: 86.49435324251951
    - type: euclidean_ap
      value: 80.34673942500022
    - type: euclidean_f1
      value: 72.30198298159463
    - type: euclidean_precision
      value: 70.45072686098327
    - type: euclidean_recall
      value: 74.25315676008624
    - type: manhattan_accuracy
      value: 86.80288741413436
    - type: manhattan_ap
      value: 80.73771278278036
    - type: manhattan_f1
      value: 72.67159608633953
    - type: manhattan_precision
      value: 70.55837563451777
    - type: manhattan_recall
      value: 74.91530643671081
    - type: max_accuracy
      value: 86.80288741413436
    - type: max_ap
      value: 80.73771278278036
    - type: max_f1
      value: 72.67159608633953
---
