mteb model-index region:us
---
tags:
- mteb
model-index:
- name: gte_WORDLLAMA_MODEL2VEC_result
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.13432835820896
    - type: ap
      value: 35.167459200441506
    - type: f1
      value: 66.74544259725131
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 71.5158
    - type: ap
      value: 65.87290139797425
    - type: f1
      value: 71.31117308043078
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 37.032
    - type: f1
      value: 36.34554421029957
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 23.541999999999998
    - type: map_at_10
      value: 38.172
    - type: map_at_100
      value: 39.339
    - type: map_at_1000
      value: 39.353
    - type: map_at_3
      value: 33.286
    - type: map_at_5
      value: 35.942
    - type: mrr_at_1
      value: 24.253
    - type: mrr_at_10
      value: 38.423
    - type: mrr_at_100
      value: 39.589
    - type: mrr_at_1000
      value: 39.604
    - type: mrr_at_3
      value: 33.559
    - type: mrr_at_5
      value: 36.169000000000004
    - type: ndcg_at_1
      value: 23.541999999999998
    - type: ndcg_at_10
      value: 46.660000000000004
    - type: ndcg_at_100
      value: 51.800999999999995
    - type: ndcg_at_1000
      value: 52.147
    - type: ndcg_at_3
      value: 36.498000000000005
    - type: ndcg_at_5
      value: 41.309000000000005
    - type: precision_at_1
      value: 23.541999999999998
    - type: precision_at_10
      value: 7.396999999999999
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.268
    - type: precision_at_5
      value: 11.508000000000001
    - type: recall_at_1
      value: 23.541999999999998
    - type: recall_at_10
      value: 73.969
    - type: recall_at_100
      value: 96.871
    - type: recall_at_1000
      value: 99.502
    - type: recall_at_3
      value: 45.804
    - type: recall_at_5
      value: 57.538999999999994
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.8392617925804
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.39147233524174
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.43457632808065
    - type: mrr
      value: 69.7011168271556
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 79.40924171268267
    - type: cos_sim_spearman
      value: 76.48728498335026
    - type: euclidean_pearson
      value: 78.11322656013188
    - type: euclidean_spearman
      value: 76.48728498335026
    - type: manhattan_pearson
      value: 78.39882365124392
    - type: manhattan_spearman
      value: 76.55837094044142
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.63311688311688
    - type: f1
      value: 74.89031278068427
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 34.47759744268641
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 26.72176842867392
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.918000000000003
    - type: map_at_10
      value: 29.912
    - type: map_at_100
      value: 31.205
    - type: map_at_1000
      value: 31.357000000000003
    - type: map_at_3
      value: 27.206000000000003
    - type: map_at_5
      value: 28.613
    - type: mrr_at_1
      value: 27.897
    - type: mrr_at_10
      value: 35.921
    - type: mrr_at_100
      value: 36.825
    - type: mrr_at_1000
      value: 36.894
    - type: mrr_at_3
      value: 33.858
    - type: mrr_at_5
      value: 34.881
    - type: ndcg_at_1
      value: 27.897
    - type: ndcg_at_10
      value: 35.306
    - type: ndcg_at_100
      value: 40.955999999999996
    - type: ndcg_at_1000
      value: 43.909
    - type: ndcg_at_3
      value: 31.422
    - type: ndcg_at_5
      value: 32.89
    - type: precision_at_1
      value: 27.897
    - type: precision_at_10
      value: 6.9239999999999995
    - type: precision_at_100
      value: 1.233
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 15.451
    - type: precision_at_5
      value: 11.044
    - type: recall_at_1
      value: 21.918000000000003
    - type: recall_at_10
      value: 45.171
    - type: recall_at_100
      value: 70.226
    - type: recall_at_1000
      value: 90.279
    - type: recall_at_3
      value: 32.657000000000004
    - type: recall_at_5
      value: 37.372
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 20.456
    - type: map_at_10
      value: 26.596999999999998
    - type: map_at_100
      value: 27.639999999999997
    - type: map_at_1000
      value: 27.766000000000002
    - type: map_at_3
      value: 24.487000000000002
    - type: map_at_5
      value: 25.683
    - type: mrr_at_1
      value: 25.605
    - type: mrr_at_10
      value: 31.326999999999998
    - type: mrr_at_100
      value: 32.133
    - type: mrr_at_1000
      value: 32.198
    - type: mrr_at_3
      value: 29.310000000000002
    - type: mrr_at_5
      value: 30.431
    - type: ndcg_at_1
      value: 25.605
    - type: ndcg_at_10
      value: 30.728
    - type: ndcg_at_100
      value: 35.318
    - type: ndcg_at_1000
      value: 38.082
    - type: ndcg_at_3
      value: 27.226
    - type: ndcg_at_5
      value: 28.828
    - type: precision_at_1
      value: 25.605
    - type: precision_at_10
      value: 5.561
    - type: precision_at_100
      value: 1.001
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 12.717999999999998
    - type: precision_at_5
      value: 9.134
    - type: recall_at_1
      value: 20.456
    - type: recall_at_10
      value: 38.476
    - type: recall_at_100
      value: 58.120000000000005
    - type: recall_at_1000
      value: 76.793
    - type: recall_at_3
      value: 28.232000000000003
    - type: recall_at_5
      value: 32.53
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 28.088
    - type: map_at_10
      value: 37.584
    - type: map_at_100
      value: 38.75
    - type: map_at_1000
      value: 38.842999999999996
    - type: map_at_3
      value: 34.839999999999996
    - type: map_at_5
      value: 36.352000000000004
    - type: mrr_at_1
      value: 32.476
    - type: mrr_at_10
      value: 40.892
    - type: mrr_at_100
      value: 41.792
    - type: mrr_at_1000
      value: 41.845
    - type: mrr_at_3
      value: 38.474000000000004
    - type: mrr_at_5
      value: 39.818999999999996
    - type: ndcg_at_1
      value: 32.476
    - type: ndcg_at_10
      value: 42.811
    - type: ndcg_at_100
      value: 48.045
    - type: ndcg_at_1000
      value: 50.09400000000001
    - type: ndcg_at_3
      value: 37.830000000000005
    - type: ndcg_at_5
      value: 40.168
    - type: precision_at_1
      value: 32.476
    - type: precision_at_10
      value: 7.034
    - type: precision_at_100
      value: 1.061
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 16.949
    - type: precision_at_5
      value: 11.799
    - type: recall_at_1
      value: 28.088
    - type: recall_at_10
      value: 55.318
    - type: recall_at_100
      value: 78.66499999999999
    - type: recall_at_1000
      value: 93.415
    - type: recall_at_3
      value: 41.865
    - type: recall_at_5
      value: 47.675
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.13
    - type: map_at_10
      value: 18.506
    - type: map_at_100
      value: 19.405
    - type: map_at_1000
      value: 19.516
    - type: map_at_3
      value: 16.821
    - type: map_at_5
      value: 17.782
    - type: mrr_at_1
      value: 14.124
    - type: mrr_at_10
      value: 19.767000000000003
    - type: mrr_at_100
      value: 20.66
    - type: mrr_at_1000
      value: 20.755000000000003
    - type: mrr_at_3
      value: 18.023
    - type: mrr_at_5
      value: 19.0
    - type: ndcg_at_1
      value: 14.124
    - type: ndcg_at_10
      value: 21.728
    - type: ndcg_at_100
      value: 26.422
    - type: ndcg_at_1000
      value: 29.73
    - type: ndcg_at_3
      value: 18.312
    - type: ndcg_at_5
      value: 19.993
    - type: precision_at_1
      value: 14.124
    - type: precision_at_10
      value: 3.4459999999999997
    - type: precision_at_100
      value: 0.617
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.91
    - type: precision_at_5
      value: 5.695
    - type: recall_at_1
      value: 13.13
    - type: recall_at_10
      value: 30.470000000000002
    - type: recall_at_100
      value: 52.449
    - type: recall_at_1000
      value: 78.25
    - type: recall_at_3
      value: 21.209
    - type: recall_at_5
      value: 25.281
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.7
    - type: map_at_10
      value: 12.333
    - type: map_at_100
      value: 13.367999999999999
    - type: map_at_1000
      value: 13.492
    - type: map_at_3
      value: 10.747
    - type: map_at_5
      value: 11.645999999999999
    - type: mrr_at_1
      value: 9.826
    - type: mrr_at_10
      value: 14.81
    - type: mrr_at_100
      value: 15.854
    - type: mrr_at_1000
      value: 15.953000000000001
    - type: mrr_at_3
      value: 13.039000000000001
    - type: mrr_at_5
      value: 14.046
    - type: ndcg_at_1
      value: 9.826
    - type: ndcg_at_10
      value: 15.437000000000001
    - type: ndcg_at_100
      value: 21.009
    - type: ndcg_at_1000
      value: 24.515
    - type: ndcg_at_3
      value: 12.349
    - type: ndcg_at_5
      value: 13.850000000000001
    - type: precision_at_1
      value: 9.826
    - type: precision_at_10
      value: 3.01
    - type: precision_at_100
      value: 0.692
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 6.053
    - type: precision_at_5
      value: 4.577
    - type: recall_at_1
      value: 7.7
    - type: recall_at_10
      value: 22.546
    - type: recall_at_100
      value: 47.648
    - type: recall_at_1000
      value: 73.655
    - type: recall_at_3
      value: 14.289
    - type: recall_at_5
      value: 17.994
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 19.886
    - type: map_at_10
      value: 26.63
    - type: map_at_100
      value: 27.944999999999997
    - type: map_at_1000
      value: 28.097
    - type: map_at_3
      value: 24.077
    - type: map_at_5
      value: 25.378
    - type: mrr_at_1
      value: 24.254
    - type: mrr_at_10
      value: 31.416
    - type: mrr_at_100
      value: 32.425
    - type: mrr_at_1000
      value: 32.501999999999995
    - type: mrr_at_3
      value: 28.793999999999997
    - type: mrr_at_5
      value: 30.237000000000002
    - type: ndcg_at_1
      value: 24.254
    - type: ndcg_at_10
      value: 31.524
    - type: ndcg_at_100
      value: 37.658
    - type: ndcg_at_1000
      value: 40.722
    - type: ndcg_at_3
      value: 26.953
    - type: ndcg_at_5
      value: 28.919
    - type: precision_at_1
      value: 24.254
    - type: precision_at_10
      value: 5.881
    - type: precision_at_100
      value: 1.072
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 12.479999999999999
    - type: precision_at_5
      value: 9.105
    - type: recall_at_1
      value: 19.886
    - type: recall_at_10
      value: 41.593
    - type: recall_at_100
      value: 68.43599999999999
    - type: recall_at_1000
      value: 89.041
    - type: recall_at_3
      value: 28.723
    - type: recall_at_5
      value: 33.804
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 15.821
    - type: map_at_10
      value: 21.898999999999997
    - type: map_at_100
      value: 23.189
    - type: map_at_1000
      value: 23.323
    - type: map_at_3
      value: 19.634999999999998
    - type: map_at_5
      value: 20.848
    - type: mrr_at_1
      value: 19.064
    - type: mrr_at_10
      value: 25.784000000000002
    - type: mrr_at_100
      value: 26.828999999999997
    - type: mrr_at_1000
      value: 26.904
    - type: mrr_at_3
      value: 23.573
    - type: mrr_at_5
      value: 24.812
    - type: ndcg_at_1
      value: 19.064
    - type: ndcg_at_10
      value: 26.229999999999997
    - type: ndcg_at_100
      value: 32.326
    - type: ndcg_at_1000
      value: 35.435
    - type: ndcg_at_3
      value: 22.070999999999998
    - type: ndcg_at_5
      value: 23.93
    - type: precision_at_1
      value: 19.064
    - type: precision_at_10
      value: 4.966
    - type: precision_at_100
      value: 0.967
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 10.54
    - type: precision_at_5
      value: 7.785
    - type: recall_at_1
      value: 15.821
    - type: recall_at_10
      value: 35.516
    - type: recall_at_100
      value: 61.971
    - type: recall_at_1000
      value: 83.848
    - type: recall_at_3
      value: 23.97
    - type: recall_at_5
      value: 28.662
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.921916666666666
    - type: map_at_10
      value: 21.780166666666666
    - type: map_at_100
      value: 22.84433333333333
    - type: map_at_1000
      value: 22.975916666666667
    - type: map_at_3
      value: 19.735916666666665
    - type: map_at_5
      value: 20.860416666666666
    - type: mrr_at_1
      value: 19.054249999999996
    - type: mrr_at_10
      value: 25.021333333333335
    - type: mrr_at_100
      value: 25.93491666666667
    - type: mrr_at_1000
      value: 26.019166666666667
    - type: mrr_at_3
      value: 23.03583333333333
    - type: mrr_at_5
      value: 24.140000000000004
    - type: ndcg_at_1
      value: 19.054249999999996
    - type: ndcg_at_10
      value: 25.70233333333334
    - type: ndcg_at_100
      value: 30.890500000000003
    - type: ndcg_at_1000
      value: 34.02575
    - type: ndcg_at_3
      value: 22.017666666666663
    - type: ndcg_at_5
      value: 23.718666666666664
    - type: precision_at_1
      value: 19.054249999999996
    - type: precision_at_10
      value: 4.622083333333333
    - type: precision_at_100
      value: 0.86825
    - type: precision_at_1000
      value: 0.13258333333333333
    - type: precision_at_3
      value: 10.176166666666669
    - type: precision_at_5
      value: 7.382749999999999
    - type: recall_at_1
      value: 15.921916666666666
    - type: recall_at_10
      value: 34.314833333333326
    - type: recall_at_100
      value: 57.83341666666667
    - type: recall_at_1000
      value: 80.45625000000001
    - type: recall_at_3
      value: 23.967166666666667
    - type: recall_at_5
      value: 28.36841666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 12.857
    - type: map_at_10
      value: 17.826
    - type: map_at_100
      value: 18.677
    - type: map_at_1000
      value: 18.775
    - type: map_at_3
      value: 16.227
    - type: map_at_5
      value: 17.168
    - type: mrr_at_1
      value: 14.877
    - type: mrr_at_10
      value: 19.784
    - type: mrr_at_100
      value: 20.662
    - type: mrr_at_1000
      value: 20.746000000000002
    - type: mrr_at_3
      value: 18.175
    - type: mrr_at_5
      value: 19.08
    - type: ndcg_at_1
      value: 14.877
    - type: ndcg_at_10
      value: 20.987000000000002
    - type: ndcg_at_100
      value: 25.654
    - type: ndcg_at_1000
      value: 28.360000000000003
    - type: ndcg_at_3
      value: 17.919
    - type: ndcg_at_5
      value: 19.404
    - type: precision_at_1
      value: 14.877
    - type: precision_at_10
      value: 3.528
    - type: precision_at_100
      value: 0.641
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 8.129
    - type: precision_at_5
      value: 5.798
    - type: recall_at_1
      value: 12.857
    - type: recall_at_10
      value: 28.864
    - type: recall_at_100
      value: 50.943000000000005
    - type: recall_at_1000
      value: 71.158
    - type: recall_at_3
      value: 20.330000000000002
    - type: recall_at_5
      value: 24.03
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.823
    - type: map_at_10
      value: 12.664
    - type: map_at_100
      value: 13.447000000000001
    - type: map_at_1000
      value: 13.58
    - type: map_at_3
      value: 11.372
    - type: map_at_5
      value: 12.052
    - type: mrr_at_1
      value: 10.84
    - type: mrr_at_10
      value: 15.135000000000002
    - type: mrr_at_100
      value: 15.919
    - type: mrr_at_1000
      value: 16.026
    - type: mrr_at_3
      value: 13.702
    - type: mrr_at_5
      value: 14.496
    - type: ndcg_at_1
      value: 10.84
    - type: ndcg_at_10
      value: 15.375
    - type: ndcg_at_100
      value: 19.612
    - type: ndcg_at_1000
      value: 23.305
    - type: ndcg_at_3
      value: 12.879999999999999
    - type: ndcg_at_5
      value: 13.980999999999998
    - type: precision_at_1
      value: 10.84
    - type: precision_at_10
      value: 2.887
    - type: precision_at_100
      value: 0.599
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 6.171
    - type: precision_at_5
      value: 4.522
    - type: recall_at_1
      value: 8.823
    - type: recall_at_10
      value: 21.19
    - type: recall_at_100
      value: 40.843
    - type: recall_at_1000
      value: 68.118
    - type: recall_at_3
      value: 14.219000000000001
    - type: recall_at_5
      value: 17.061
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 14.841999999999999
    - type: map_at_10
      value: 19.807
    - type: map_at_100
      value: 20.646
    - type: map_at_1000
      value: 20.782
    - type: map_at_3
      value: 17.881
    - type: map_at_5
      value: 18.94
    - type: mrr_at_1
      value: 17.631
    - type: mrr_at_10
      value: 22.949
    - type: mrr_at_100
      value: 23.727
    - type: mrr_at_1000
      value: 23.829
    - type: mrr_at_3
      value: 20.896
    - type: mrr_at_5
      value: 21.964
    - type: ndcg_at_1
      value: 17.631
    - type: ndcg_at_10
      value: 23.544999999999998
    - type: ndcg_at_100
      value: 28.042
    - type: ndcg_at_1000
      value: 31.66
    - type: ndcg_at_3
      value: 19.697
    - type: ndcg_at_5
      value: 21.467
    - type: precision_at_1
      value: 17.631
    - type: precision_at_10
      value: 4.039000000000001
    - type: precision_at_100
      value: 0.7080000000000001
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 8.831
    - type: precision_at_5
      value: 6.381
    - type: recall_at_1
      value: 14.841999999999999
    - type: recall_at_10
      value: 32.144
    - type: recall_at_100
      value: 52.896
    - type: recall_at_1000
      value: 79.3
    - type: recall_at_3
      value: 21.64
    - type: recall_at_5
      value: 26.127
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.182
    - type: map_at_10
      value: 21.423000000000002
    - type: map_at_100
      value: 22.766000000000002
    - type: map_at_1000
      value: 22.966
    - type: map_at_3
      value: 19.096
    - type: map_at_5
      value: 20.514
    - type: mrr_at_1
      value: 18.379
    - type: mrr_at_10
      value: 24.834999999999997
    - type: mrr_at_100
      value: 25.818
    - type: mrr_at_1000
      value: 25.893
    - type: mrr_at_3
      value: 22.628
    - type: mrr_at_5
      value: 24.032
    - type: ndcg_at_1
      value: 18.379
    - type: ndcg_at_10
      value: 25.766
    - type: ndcg_at_100
      value: 31.677
    - type: ndcg_at_1000
      value: 35.024
    - type: ndcg_at_3
      value: 22.027
    - type: ndcg_at_5
      value: 24.046
    - type: precision_at_1
      value: 18.379
    - type: precision_at_10
      value: 5.158
    - type: precision_at_100
      value: 1.2309999999999999
    - type: precision_at_1000
      value: 0.211
    - type: precision_at_3
      value: 10.474
    - type: precision_at_5
      value: 7.983999999999999
    - type: recall_at_1
      value: 15.182
    - type: recall_at_10
      value: 34.008
    - type: recall_at_100
      value: 61.882000000000005
    - type: recall_at_1000
      value: 84.635
    - type: recall_at_3
      value: 23.3
    - type: recall_at_5
      value: 28.732999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.36
    - type: map_at_10
      value: 16.181
    - type: map_at_100
      value: 17.094
    - type: map_at_1000
      value: 17.214
    - type: map_at_3
      value: 14.442
    - type: map_at_5
      value: 15.348999999999998
    - type: mrr_at_1
      value: 13.678
    - type: mrr_at_10
      value: 17.636
    - type: mrr_at_100
      value: 18.575
    - type: mrr_at_1000
      value: 18.685
    - type: mrr_at_3
      value: 15.958
    - type: mrr_at_5
      value: 16.882
    - type: ndcg_at_1
      value: 13.678
    - type: ndcg_at_10
      value: 18.991
    - type: ndcg_at_100
      value: 23.967
    - type: ndcg_at_1000
      value: 27.473
    - type: ndcg_at_3
      value: 15.526000000000002
    - type: ndcg_at_5
      value: 17.148
    - type: precision_at_1
      value: 13.678
    - type: precision_at_10
      value: 3.031
    - type: precision_at_100
      value: 0.597
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.4079999999999995
    - type: precision_at_5
      value: 4.769
    - type: recall_at_1
      value: 12.36
    - type: recall_at_10
      value: 26.482
    - type: recall_at_100
      value: 49.922
    - type: recall_at_1000
      value: 76.983
    - type: recall_at_3
      value: 17.172
    - type: recall_at_5
      value: 21.152
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 8.464
    - type: map_at_10
      value: 14.78
    - type: map_at_100
      value: 16.436999999999998
    - type: map_at_1000
      value: 16.650000000000002
    - type: map_at_3
      value: 12.027000000000001
    - type: map_at_5
      value: 13.428999999999998
    - type: mrr_at_1
      value: 19.544
    - type: mrr_at_10
      value: 29.537999999999997
    - type: mrr_at_100
      value: 30.653000000000002
    - type: mrr_at_1000
      value: 30.708000000000002
    - type: mrr_at_3
      value: 25.798
    - type: mrr_at_5
      value: 28.072000000000003
    - type: ndcg_at_1
      value: 19.544
    - type: ndcg_at_10
      value: 21.953
    - type: ndcg_at_100
      value: 29.188
    - type: ndcg_at_1000
      value: 33.222
    - type: ndcg_at_3
      value: 16.89
    - type: ndcg_at_5
      value: 18.825
    - type: precision_at_1
      value: 19.544
    - type: precision_at_10
      value: 7.277
    - type: precision_at_100
      value: 1.506
    - type: precision_at_1000
      value: 0.22399999999999998
    - type: precision_at_3
      value: 12.834000000000001
    - type: precision_at_5
      value: 10.488999999999999
    - type: recall_at_1
      value: 8.464
    - type: recall_at_10
      value: 27.762999999999998
    - type: recall_at_100
      value: 53.147999999999996
    - type: recall_at_1000
      value: 76.183
    - type: recall_at_3
      value: 15.642
    - type: recall_at_5
      value: 20.593
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 5.676
    - type: map_at_10
      value: 11.847000000000001
    - type: map_at_100
      value: 16.875999999999998
    - type: map_at_1000
      value: 18.081
    - type: map_at_3
      value: 8.512
    - type: map_at_5
      value: 9.956
    - type: mrr_at_1
      value: 48.0
    - type: mrr_at_10
      value: 57.928000000000004
    - type: mrr_at_100
      value: 58.52
    - type: mrr_at_1000
      value: 58.544
    - type: mrr_at_3
      value: 55.333
    - type: mrr_at_5
      value: 56.958
    - type: ndcg_at_1
      value: 35.875
    - type: ndcg_at_10
      value: 27.221
    - type: ndcg_at_100
      value: 31.808999999999997
    - type: ndcg_at_1000
      value: 39.199
    - type: ndcg_at_3
      value: 30.274
    - type: ndcg_at_5
      value: 28.785
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 23.65
    - type: precision_at_100
      value: 7.818
    - type: precision_at_1000
      value: 1.651
    - type: precision_at_3
      value: 35.833
    - type: precision_at_5
      value: 31.0
    - type: recall_at_1
      value: 5.676
    - type: recall_at_10
      value: 16.619
    - type: recall_at_100
      value: 39.422000000000004
    - type: recall_at_1000
      value: 64.095
    - type: recall_at_3
      value: 9.608
    - type: recall_at_5
      value: 12.277000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 49.185
    - type: f1
      value: 44.87033813298503
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 18.904
    - type: map_at_10
      value: 28.435
    - type: map_at_100
      value: 29.498
    - type: map_at_1000
      value: 29.567
    - type: map_at_3
      value: 25.319000000000003
    - type: map_at_5
      value: 27.13
    - type: mrr_at_1
      value: 20.116999999999997
    - type: mrr_at_10
      value: 30.112
    - type: mrr_at_100
      value: 31.155
    - type: mrr_at_1000
      value: 31.213
    - type: mrr_at_3
      value: 26.895000000000003
    - type: mrr_at_5
      value: 28.793000000000003
    - type: ndcg_at_1
      value: 20.116999999999997
    - type: ndcg_at_10
      value: 34.244
    - type: ndcg_at_100
      value: 39.409
    - type: ndcg_at_1000
      value: 41.195
    - type: ndcg_at_3
      value: 27.872000000000003
    - type: ndcg_at_5
      value: 31.128
    - type: precision_at_1
      value: 20.116999999999997
    - type: precision_at_10
      value: 5.534
    - type: precision_at_100
      value: 0.828
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 12.076
    - type: precision_at_5
      value: 8.965
    - type: recall_at_1
      value: 18.904
    - type: recall_at_10
      value: 50.858000000000004
    - type: recall_at_100
      value: 74.42
    - type: recall_at_1000
      value: 88.023
    - type: recall_at_3
      value: 33.675
    - type: recall_at_5
      value: 41.449999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 8.892
    - type: map_at_10
      value: 14.363000000000001
    - type: map_at_100
      value: 15.75
    - type: map_at_1000
      value: 15.959000000000001
    - type: map_at_3
      value: 12.25
    - type: map_at_5
      value: 13.286999999999999
    - type: mrr_at_1
      value: 16.821
    - type: mrr_at_10
      value: 23.425
    - type: mrr_at_100
      value: 24.556
    - type: mrr_at_1000
      value: 24.637
    - type: mrr_at_3
      value: 20.885
    - type: mrr_at_5
      value: 22.127
    - type: ndcg_at_1
      value: 16.821
    - type: ndcg_at_10
      value: 19.412
    - type: ndcg_at_100
      value: 25.836
    - type: ndcg_at_1000
      value: 30.131000000000004
    - type: ndcg_at_3
      value: 16.198
    - type: ndcg_at_5
      value: 17.185
    - type: precision_at_1
      value: 16.821
    - type: precision_at_10
      value: 5.556
    - type: precision_at_100
      value: 1.1820000000000002
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 10.545
    - type: precision_at_5
      value: 8.056000000000001
    - type: recall_at_1
      value: 8.892
    - type: recall_at_10
      value: 25.249
    - type: recall_at_100
      value: 50.263000000000005
    - type: recall_at_1000
      value: 76.43299999999999
    - type: recall_at_3
      value: 15.094
    - type: recall_at_5
      value: 18.673000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 20.831
    - type: map_at_10
      value: 29.959999999999997
    - type: map_at_100
      value: 30.959999999999997
    - type: map_at_1000
      value: 31.069000000000003
    - type: map_at_3
      value: 27.453
    - type: map_at_5
      value: 28.838
    - type: mrr_at_1
      value: 41.661
    - type: mrr_at_10
      value: 49.647999999999996
    - type: mrr_at_100
      value: 50.304
    - type: mrr_at_1000
      value: 50.352
    - type: mrr_at_3
      value: 47.403
    - type: mrr_at_5
      value: 48.657000000000004
    - type: ndcg_at_1
      value: 41.661
    - type: ndcg_at_10
      value: 37.854
    - type: ndcg_at_100
      value: 42.248999999999995
    - type: ndcg_at_1000
      value: 44.756
    - type: ndcg_at_3
      value: 33.243
    - type: ndcg_at_5
      value: 35.467
    - type: precision_at_1
      value: 41.661
    - type: precision_at_10
      value: 8.386000000000001
    - type: precision_at_100
      value: 1.1900000000000002
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 21.022
    - type: precision_at_5
      value: 14.377
    - type: recall_at_1
      value: 20.831
    - type: recall_at_10
      value: 41.931000000000004
    - type: recall_at_100
      value: 59.507
    - type: recall_at_1000
      value: 76.232
    - type: recall_at_3
      value: 31.533
    - type: recall_at_5
      value: 35.942
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 70.2136
    - type: ap
      value: 64.38274263735502
    - type: f1
      value: 70.02577813394484
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 7.542999999999999
    - type: map_at_10
      value: 13.229
    - type: map_at_100
      value: 14.283999999999999
    - type: map_at_1000
      value: 14.396
    - type: map_at_3
      value: 11.139000000000001
    - type: map_at_5
      value: 12.259
    - type: mrr_at_1
      value: 7.808
    - type: mrr_at_10
      value: 13.577
    - type: mrr_at_100
      value: 14.625
    - type: mrr_at_1000
      value: 14.732000000000001
    - type: mrr_at_3
      value: 11.464
    - type: mrr_at_5
      value: 12.584999999999999
    - type: ndcg_at_1
      value: 7.779
    - type: ndcg_at_10
      value: 16.793
    - type: ndcg_at_100
      value: 22.564
    - type: ndcg_at_1000
      value: 25.799
    - type: ndcg_at_3
      value: 12.431000000000001
    - type: ndcg_at_5
      value: 14.442
    - type: precision_at_1
      value: 7.779
    - type: precision_at_10
      value: 2.894
    - type: precision_at_100
      value: 0.59
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 5.454
    - type: precision_at_5
      value: 4.278
    - type: recall_at_1
      value: 7.542999999999999
    - type: recall_at_10
      value: 27.907
    - type: recall_at_100
      value: 56.13399999999999
    - type: recall_at_1000
      value: 81.877
    - type: recall_at_3
      value: 15.878999999999998
    - type: recall_at_5
      value: 20.726
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.68490652074783
    - type: f1
      value: 90.90009716586837
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 61.33150934792522
    - type: f1
      value: 42.414995407585955
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 66.29455279085406
    - type: f1
      value: 64.0154454215856
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.91055817081372
    - type: f1
      value: 72.79505573377739
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.478611587568
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.395691978780366
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.75504868917307
    - type: mrr
      value: 31.723412508217553
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.739
    - type: map_at_10
      value: 9.419
    - type: map_at_100
      value: 12.209
    - type: map_at_1000
      value: 13.653
    - type: map_at_3
      value: 7.292999999999999
    - type: map_at_5
      value: 8.291
    - type: mrr_at_1
      value: 38.7
    - type: mrr_at_10
      value: 47.934
    - type: mrr_at_100
      value: 48.605
    - type: mrr_at_1000
      value: 48.646
    - type: mrr_at_3
      value: 45.717
    - type: mrr_at_5
      value: 47.157
    - type: ndcg_at_1
      value: 36.842000000000006
    - type: ndcg_at_10
      value: 28.077
    - type: ndcg_at_100
      value: 26.83
    - type: ndcg_at_1000
      value: 36.272
    - type: ndcg_at_3
      value: 32.429
    - type: ndcg_at_5
      value: 30.823
    - type: precision_at_1
      value: 38.7
    - type: precision_at_10
      value: 20.774
    - type: precision_at_100
      value: 7.331
    - type: precision_at_1000
      value: 2.085
    - type: precision_at_3
      value: 30.341
    - type: precision_at_5
      value: 26.502
    - type: recall_at_1
      value: 4.739
    - type: recall_at_10
      value: 13.065999999999999
    - type: recall_at_100
      value: 28.875
    - type: recall_at_1000
      value: 62.751000000000005
    - type: recall_at_3
      value: 8.338
    - type: recall_at_5
      value: 10.211
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.764
    - type: map_at_10
      value: 18.582
    - type: map_at_100
      value: 19.953000000000003
    - type: map_at_1000
      value: 20.049
    - type: map_at_3
      value: 15.551
    - type: map_at_5
      value: 17.143
    - type: mrr_at_1
      value: 12.283
    - type: mrr_at_10
      value: 20.507
    - type: mrr_at_100
      value: 21.724
    - type: mrr_at_1000
      value: 21.801000000000002
    - type: mrr_at_3
      value: 17.434
    - type: mrr_at_5
      value: 19.097
    - type: ndcg_at_1
      value: 12.254
    - type: ndcg_at_10
      value: 23.818
    - type: ndcg_at_100
      value: 30.652
    - type: ndcg_at_1000
      value: 33.25
    - type: ndcg_at_3
      value: 17.577
    - type: ndcg_at_5
      value: 20.43
    - type: precision_at_1
      value: 12.254
    - type: precision_at_10
      value: 4.492999999999999
    - type: precision_at_100
      value: 0.8370000000000001
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 8.333
    - type: precision_at_5
      value: 6.593
    - type: recall_at_1
      value: 10.764
    - type: recall_at_10
      value: 38.279999999999994
    - type: recall_at_100
      value: 69.77600000000001
    - type: recall_at_1000
      value: 89.75
    - type: recall_at_3
      value: 21.608
    - type: recall_at_5
      value: 28.247
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 66.238
    - type: map_at_10
      value: 79.61
    - type: map_at_100
      value: 80.339
    - type: map_at_1000
      value: 80.366
    - type: map_at_3
      value: 76.572
    - type: map_at_5
      value: 78.45100000000001
    - type: mrr_at_1
      value: 76.18
    - type: mrr_at_10
      value: 83.319
    - type: mrr_at_100
      value: 83.492
    - type: mrr_at_1000
      value: 83.49499999999999
    - type: mrr_at_3
      value: 82.002
    - type: mrr_at_5
      value: 82.88
    - type: ndcg_at_1
      value: 76.24
    - type: ndcg_at_10
      value: 84.048
    - type: ndcg_at_100
      value: 85.76700000000001
    - type: ndcg_at_1000
      value: 85.989
    - type: ndcg_at_3
      value: 80.608
    - type: ndcg_at_5
      value: 82.45
    - type: precision_at_1
      value: 76.24
    - type: precision_at_10
      value: 12.775
    - type: precision_at_100
      value: 1.498
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 35.107
    - type: precision_at_5
      value: 23.198
    - type: recall_at_1
      value: 66.238
    - type: recall_at_10
      value: 92.655
    - type: recall_at_100
      value: 98.79599999999999
    - type: recall_at_1000
      value: 99.914
    - type: recall_at_3
      value: 82.818
    - type: recall_at_5
      value: 87.985
    - type: map_at_1
      value: 3.3029999999999995
    - type: map_at_10
      value: 8.534
    - type: map_at_100
      value: 10.269
    - type: map_at_1000
      value: 10.569
    - type: map_at_3
      value: 6.02
    - type: map_at_5
      value: 7.3
    - type: mrr_at_1
      value: 16.2
    - type: mrr_at_10
      value: 26.048
    - type: mrr_at_100
      value: 27.229
    - type: mrr_at_1000
      value: 27.307
    - type: mrr_at_3
      value: 22.8
    - type: mrr_at_5
      value: 24.555
    - type: ndcg_at_1
      value: 16.2
    - type: ndcg_at_10
      value: 15.152
    - type: ndcg_at_100
      value: 22.692999999999998
    - type: ndcg_at_1000
      value: 28.283
    - type: ndcg_at_3
      value: 13.831
    - type: ndcg_at_5
      value: 12.383
    - type: precision_at_1
      value: 16.2
    - type: precision_at_10
      value: 8.15
    - type: precision_at_100
      value: 1.921
    - type: precision_at_1000
      value: 0.326
    - type: precision_at_3
      value: 13.167000000000002
    - type: precision_at_5
      value: 11.200000000000001
    - type: recall_at_1
      value: 3.3029999999999995
    - type: recall_at_10
      value: 16.463
    - type: recall_at_100
      value: 38.968
    - type: recall_at_1000
      value: 66.208
    - type: recall_at_3
      value: 8.023
    - type: recall_at_5
      value: 11.338
    - type: map_at_1
      value: 0.154
    - type: map_at_10
      value: 1.216
    - type: map_at_100
      value: 6.401
    - type: map_at_1000
      value: 16.882
    - type: map_at_3
      value: 0.418
    - type: map_at_5
      value: 0.7040000000000001
    - type: mrr_at_1
      value: 62.0
    - type: mrr_at_10
      value: 75.319
    - type: mrr_at_100
      value: 75.435
    - type: mrr_at_1000
      value: 75.435
    - type: mrr_at_3
      value: 73.333
    - type: mrr_at_5
      value: 75.033
    - type: ndcg_at_1
      value: 56.00000000000001
    - type: ndcg_at_10
      value: 54.176
    - type: ndcg_at_100
      value: 40.741
    - type: ndcg_at_1000
      value: 38.385000000000005
    - type: ndcg_at_3
      value: 57.676
    - type: ndcg_at_5
      value: 57.867000000000004
    - type: precision_at_1
      value: 62.0
    - type: precision_at_10
      value: 57.8
    - type: precision_at_100
      value: 42.68
    - type: precision_at_1000
      value: 18.478
    - type: precision_at_3
      value: 61.333000000000006
    - type: precision_at_5
      value: 63.6
    - type: recall_at_1
      value: 0.154
    - type: recall_at_10
      value: 1.468
    - type: recall_at_100
      value: 9.541
    - type: recall_at_1000
      value: 37.218
    - type: recall_at_3
      value: 0.46299999999999997
    - type: recall_at_5
      value: 0.8340000000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 45.96790773164943
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 51.114201492992976
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 78.21858054391086
    - type: cos_sim_spearman
      value: 67.3365618536054
    - type: euclidean_pearson
      value: 72.40963340986721
    - type: euclidean_spearman
      value: 67.336666949735
    - type: manhattan_pearson
      value: 72.14690674984998
    - type: manhattan_spearman
      value: 67.32922820760339
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 76.49003508454533
    - type: cos_sim_spearman
      value: 66.84152843358724
    - type: euclidean_pearson
      value: 72.00905568823764
    - type: euclidean_spearman
      value: 66.8427445518875
    - type: manhattan_pearson
      value: 71.33279968302561
    - type: manhattan_spearman
      value: 66.63248621937453
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.26330596241046
    - type: cos_sim_spearman
      value: 78.99008985666835
    - type: euclidean_pearson
      value: 78.51141445278363
    - type: euclidean_spearman
      value: 78.99010203692151
    - type: manhattan_pearson
      value: 78.06877144241578
    - type: manhattan_spearman
      value: 78.49232451344044
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 79.14106714330973
    - type: cos_sim_spearman
      value: 74.82820560037015
    - type: euclidean_pearson
      value: 77.62758758774916
    - type: euclidean_spearman
      value: 74.82819590900333
    - type: manhattan_pearson
      value: 77.48877257108047
    - type: manhattan_spearman
      value: 74.74789870583966
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 82.48914773660643
    - type: cos_sim_spearman
      value: 83.00065347429336
    - type: euclidean_pearson
      value: 82.64658342996727
    - type: euclidean_spearman
      value: 83.00065194339217
    - type: manhattan_pearson
      value: 82.55463149184536
    - type: manhattan_spearman
      value: 82.8911825343332
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.784876359328
    - type: cos_sim_spearman
      value: 78.360543979936
    - type: euclidean_pearson
      value: 77.73937696752135
    - type: euclidean_spearman
      value: 78.36053665222538
    - type: manhattan_pearson
      value: 77.56126269274264
    - type: manhattan_spearman
      value: 78.18717393504727
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 86.63171981287952
    - type: cos_sim_spearman
      value: 87.49687143000429
    - type: euclidean_pearson
      value: 86.37853734517222
    - type: euclidean_spearman
      value: 87.4977435828658
    - type: manhattan_pearson
      value: 86.40342805532555
    - type: manhattan_spearman
      value: 87.57812091712806
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 60.00736823914696
    - type: cos_sim_spearman
      value: 60.59580774316736
    - type: euclidean_pearson
      value: 61.893600849213094
    - type: euclidean_spearman
      value: 60.59580774316736
    - type: manhattan_pearson
      value: 61.43013801720455
    - type: manhattan_spearman
      value: 59.92526461879062
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 80.58292387813594
    - type: cos_sim_spearman
      value: 78.85975762418589
    - type: euclidean_pearson
      value: 80.28122335716425
    - type: euclidean_spearman
      value: 78.85977608876506
    - type: manhattan_pearson
      value: 80.20419882971093
    - type: manhattan_spearman
      value: 78.79811621332709
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 78.54383068715617
    - type: mrr
      value: 93.62365031482678
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 39.111000000000004
    - type: map_at_10
      value: 47.686
    - type: map_at_100
      value: 48.722
    - type: map_at_1000
      value: 48.776
    - type: map_at_3
      value: 44.625
    - type: map_at_5
      value: 46.289
    - type: mrr_at_1
      value: 41.667
    - type: mrr_at_10
      value: 49.619
    - type: mrr_at_100
      value: 50.434
    - type: mrr_at_1000
      value: 50.482000000000006
    - type: mrr_at_3
      value: 46.833000000000006
    - type: mrr_at_5
      value: 48.317
    - type: ndcg_at_1
      value: 41.667
    - type: ndcg_at_10
      value: 52.819
    - type: ndcg_at_100
      value: 57.69
    - type: ndcg_at_1000
      value: 58.965
    - type: ndcg_at_3
      value: 46.857
    - type: ndcg_at_5
      value: 49.697
    - type: precision_at_1
      value: 41.667
    - type: precision_at_10
      value: 7.367
    - type: precision_at_100
      value: 1.0070000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 18.333
    - type: precision_at_5
      value: 12.6
    - type: recall_at_1
      value: 39.111000000000004
    - type: recall_at_10
      value: 67.039
    - type: recall_at_100
      value: 89.767
    - type: recall_at_1000
      value: 99.467
    - type: recall_at_3
      value: 51.056000000000004
    - type: recall_at_5
      value: 57.99999999999999
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.72772277227723
    - type: cos_sim_ap
      value: 91.98542118937158
    - type: cos_sim_f1
      value: 85.91691995947316
    - type: cos_sim_precision
      value: 87.06365503080082
    - type: cos_sim_recall
      value: 84.8
    - type: dot_accuracy
      value: 99.72772277227723
    - type: dot_ap
      value: 91.98542118937158
    - type: dot_f1
      value: 85.91691995947316
    - type: dot_precision
      value: 87.06365503080082
    - type: dot_recall
      value: 84.8
    - type: euclidean_accuracy
      value: 99.72772277227723
    - type: euclidean_ap
      value: 91.98542118937158
    - type: euclidean_f1
      value: 85.91691995947316
    - type: euclidean_precision
      value: 87.06365503080082
    - type: euclidean_recall
      value: 84.8
    - type: manhattan_accuracy
      value: 99.72574257425742
    - type: manhattan_ap
      value: 91.96773898408213
    - type: manhattan_f1
      value: 85.8601327207759
    - type: manhattan_precision
      value: 87.69551616266945
    - type: manhattan_recall
      value: 84.1
    - type: max_accuracy
      value: 99.72772277227723
    - type: max_ap
      value: 91.98542118937158
    - type: max_f1
      value: 85.91691995947316
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 50.974351388709024
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.94724711190474
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.618618519378074
    - type: mrr
      value: 44.19061942959002
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.75942900919329
    - type: cos_sim_spearman
      value: 30.265779375382486
    - type: dot_pearson
      value: 29.759429009193283
    - type: dot_spearman
      value: 30.216316271647514
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.144
    - type: map_at_10
      value: 8.38
    - type: map_at_100
      value: 14.482000000000001
    - type: map_at_1000
      value: 16.179
    - type: map_at_3
      value: 3.821
    - type: map_at_5
      value: 5.96
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 41.501
    - type: mrr_at_100
      value: 42.575
    - type: mrr_at_1000
      value: 42.575
    - type: mrr_at_3
      value: 36.054
    - type: mrr_at_5
      value: 40.238
    - type: ndcg_at_1
      value: 21.429000000000002
    - type: ndcg_at_10
      value: 21.644
    - type: ndcg_at_100
      value: 35.427
    - type: ndcg_at_1000
      value: 47.116
    - type: ndcg_at_3
      value: 20.814
    - type: ndcg_at_5
      value: 22.783
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 21.224
    - type: precision_at_100
      value: 8.265
    - type: precision_at_1000
      value: 1.5959999999999999
    - type: precision_at_3
      value: 23.810000000000002
    - type: precision_at_5
      value: 26.122
    - type: recall_at_1
      value: 2.144
    - type: recall_at_10
      value: 15.278
    - type: recall_at_100
      value: 50.541000000000004
    - type: recall_at_1000
      value: 86.144
    - type: recall_at_3
      value: 5.056
    - type: recall_at_5
      value: 9.203
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 75.88100000000001
    - type: ap
      value: 17.210410808772743
    - type: f1
      value: 58.7851360197636
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 59.68024900962084
    - type: f1
      value: 59.95386992880734
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 41.55446050017461
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.32699529117244
    - type: cos_sim_ap
      value: 61.49148139881723
    - type: cos_sim_f1
      value: 59.31940298507462
    - type: cos_sim_precision
      value: 54.17666303162486
    - type: cos_sim_recall
      value: 65.54089709762533
    - type: dot_accuracy
      value: 82.32699529117244
    - type: dot_ap
      value: 61.49148139881723
    - type: dot_f1
      value: 59.31940298507462
    - type: dot_precision
      value: 54.17666303162486
    - type: dot_recall
      value: 65.54089709762533
    - type: euclidean_accuracy
      value: 82.32699529117244
    - type: euclidean_ap
      value: 61.49148139881723
    - type: euclidean_f1
      value: 59.31940298507462
    - type: euclidean_precision
      value: 54.17666303162486
    - type: euclidean_recall
      value: 65.54089709762533
    - type: manhattan_accuracy
      value: 82.44024557429815
    - type: manhattan_ap
      value: 61.57050440663527
    - type: manhattan_f1
      value: 59.36456916800594
    - type: manhattan_precision
      value: 55.8501977204001
    - type: manhattan_recall
      value: 63.35092348284961
    - type: max_accuracy
      value: 82.44024557429815
    - type: max_ap
      value: 61.57050440663527
    - type: max_f1
      value: 59.36456916800594
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.70714479760935
    - type: cos_sim_ap
      value: 83.52059059692118
    - type: cos_sim_f1
      value: 75.8043805261034
    - type: cos_sim_precision
      value: 72.40171000070083
    - type: cos_sim_recall
      value: 79.54265475823837
    - type: dot_accuracy
      value: 87.70714479760935
    - type: dot_ap
      value: 83.52059016767844
    - type: dot_f1
      value: 75.8043805261034
    - type: dot_precision
      value: 72.40171000070083
    - type: dot_recall
      value: 79.54265475823837
    - type: euclidean_accuracy
      value: 87.70714479760935
    - type: euclidean_ap
      value: 83.52059046795347
    - type: euclidean_f1
      value: 75.8043805261034
    - type: euclidean_precision
      value: 72.40171000070083
    - type: euclidean_recall
      value: 79.54265475823837
    - type: manhattan_accuracy
      value: 87.7187875965382
    - type: manhattan_ap
      value: 83.5377383098018
    - type: manhattan_f1
      value: 75.87021520062012
    - type: manhattan_precision
      value: 72.87102035028008
    - type: manhattan_recall
      value: 79.12688635663689
    - type: max_accuracy
      value: 87.7187875965382
    - type: max_ap
      value: 83.5377383098018
    - type: max_f1
      value: 75.87021520062012
---
