mteb model-index region:us
---
tags:
- mteb
model-index:
- name: llama3_STSprompt_noabtt_new
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.53731343283582
    - type: ap
      value: 35.09550935769008
    - type: f1
      value: 66.39064790565796
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 68.46487499999999
    - type: ap
      value: 63.194645384561895
    - type: f1
      value: 68.14318967696387
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 36.722
    - type: f1
      value: 36.0815270010246
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 17.994
    - type: map_at_10
      value: 29.559
    - type: map_at_100
      value: 30.679000000000002
    - type: map_at_1000
      value: 30.73
    - type: map_at_3
      value: 25.319999999999997
    - type: map_at_5
      value: 27.71
    - type: mrr_at_1
      value: 18.421000000000003
    - type: mrr_at_10
      value: 29.73
    - type: mrr_at_100
      value: 30.85
    - type: mrr_at_1000
      value: 30.901
    - type: mrr_at_3
      value: 25.45
    - type: mrr_at_5
      value: 27.883000000000003
    - type: ndcg_at_1
      value: 17.994
    - type: ndcg_at_10
      value: 36.642
    - type: ndcg_at_100
      value: 42.247
    - type: ndcg_at_1000
      value: 43.579
    - type: ndcg_at_3
      value: 27.865000000000002
    - type: ndcg_at_5
      value: 32.171
    - type: precision_at_1
      value: 17.994
    - type: precision_at_10
      value: 5.953
    - type: precision_at_100
      value: 0.861
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 11.759
    - type: precision_at_5
      value: 9.147
    - type: recall_at_1
      value: 17.994
    - type: recall_at_10
      value: 59.531
    - type: recall_at_100
      value: 86.06
    - type: recall_at_1000
      value: 96.515
    - type: recall_at_3
      value: 35.276999999999994
    - 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: 31.66949406382408
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.14545126769505
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.74601918537465
    - type: mrr
      value: 66.62885283383898
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 72.6753460041215
    - type: cos_sim_spearman
      value: 71.97935094171385
    - type: euclidean_pearson
      value: 72.35700410190371
    - type: euclidean_spearman
      value: 71.97935094171385
    - type: manhattan_pearson
      value: 73.65568445281664
    - type: manhattan_spearman
      value: 73.25166908897245
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 70.62337662337663
    - type: f1
      value: 69.8634895921265
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.04921398276571
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 22.3114828809719
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.685000000000002
    - type: map_at_10
      value: 28.016000000000002
    - type: map_at_100
      value: 29.028
    - type: map_at_1000
      value: 29.176999999999996
    - type: map_at_3
      value: 25.873
    - type: map_at_5
      value: 27.05
    - type: mrr_at_1
      value: 26.466
    - type: mrr_at_10
      value: 33.684999999999995
    - type: mrr_at_100
      value: 34.449999999999996
    - type: mrr_at_1000
      value: 34.522999999999996
    - type: mrr_at_3
      value: 31.879
    - type: mrr_at_5
      value: 32.836999999999996
    - type: ndcg_at_1
      value: 26.466
    - type: ndcg_at_10
      value: 32.897
    - type: ndcg_at_100
      value: 37.433
    - type: ndcg_at_1000
      value: 40.393
    - type: ndcg_at_3
      value: 29.793999999999997
    - type: ndcg_at_5
      value: 31.051000000000002
    - type: precision_at_1
      value: 26.466
    - type: precision_at_10
      value: 6.209
    - type: precision_at_100
      value: 1.057
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_3
      value: 14.591999999999999
    - type: precision_at_5
      value: 10.272
    - type: recall_at_1
      value: 20.685000000000002
    - type: recall_at_10
      value: 41.284
    - type: recall_at_100
      value: 61.91
    - type: recall_at_1000
      value: 81.846
    - type: recall_at_3
      value: 31.144
    - type: recall_at_5
      value: 35.33
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 18.683
    - type: map_at_10
      value: 24.818
    - type: map_at_100
      value: 25.702
    - type: map_at_1000
      value: 25.819
    - type: map_at_3
      value: 22.671
    - type: map_at_5
      value: 23.846
    - type: mrr_at_1
      value: 23.885
    - type: mrr_at_10
      value: 29.454
    - type: mrr_at_100
      value: 30.201
    - type: mrr_at_1000
      value: 30.270000000000003
    - type: mrr_at_3
      value: 27.537
    - type: mrr_at_5
      value: 28.594
    - type: ndcg_at_1
      value: 23.885
    - type: ndcg_at_10
      value: 28.961
    - type: ndcg_at_100
      value: 33.128
    - type: ndcg_at_1000
      value: 35.919000000000004
    - type: ndcg_at_3
      value: 25.455
    - type: ndcg_at_5
      value: 27.038
    - type: precision_at_1
      value: 23.885
    - type: precision_at_10
      value: 5.459
    - type: precision_at_100
      value: 0.9440000000000001
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_3
      value: 12.081
    - type: precision_at_5
      value: 8.738999999999999
    - type: recall_at_1
      value: 18.683
    - type: recall_at_10
      value: 36.616
    - type: recall_at_100
      value: 55.126
    - type: recall_at_1000
      value: 74.32600000000001
    - type: recall_at_3
      value: 26.540000000000003
    - type: recall_at_5
      value: 30.812
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.025
    - type: map_at_10
      value: 32.903999999999996
    - type: map_at_100
      value: 33.857
    - type: map_at_1000
      value: 33.945
    - type: map_at_3
      value: 30.711
    - type: map_at_5
      value: 31.972
    - type: mrr_at_1
      value: 29.279
    - type: mrr_at_10
      value: 36.281
    - type: mrr_at_100
      value: 37.119
    - type: mrr_at_1000
      value: 37.181999999999995
    - type: mrr_at_3
      value: 34.316
    - type: mrr_at_5
      value: 35.437999999999995
    - type: ndcg_at_1
      value: 29.279
    - type: ndcg_at_10
      value: 37.333
    - type: ndcg_at_100
      value: 41.948
    - type: ndcg_at_1000
      value: 44.249
    - type: ndcg_at_3
      value: 33.311
    - type: ndcg_at_5
      value: 35.251
    - type: precision_at_1
      value: 29.279
    - type: precision_at_10
      value: 5.956
    - type: precision_at_100
      value: 0.8959999999999999
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 14.774999999999999
    - type: precision_at_5
      value: 10.194
    - type: recall_at_1
      value: 25.025
    - type: recall_at_10
      value: 47.583
    - type: recall_at_100
      value: 68.42
    - type: recall_at_1000
      value: 85.47
    - type: recall_at_3
      value: 36.595
    - type: recall_at_5
      value: 41.461999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 11.356
    - type: map_at_10
      value: 15.417
    - type: map_at_100
      value: 15.988
    - type: map_at_1000
      value: 16.088
    - type: map_at_3
      value: 13.941999999999998
    - type: map_at_5
      value: 14.651
    - type: mrr_at_1
      value: 12.316
    - type: mrr_at_10
      value: 16.451999999999998
    - type: mrr_at_100
      value: 17.061999999999998
    - type: mrr_at_1000
      value: 17.158
    - type: mrr_at_3
      value: 14.953
    - type: mrr_at_5
      value: 15.733
    - type: ndcg_at_1
      value: 12.316
    - type: ndcg_at_10
      value: 18.109
    - type: ndcg_at_100
      value: 21.537
    - type: ndcg_at_1000
      value: 24.512999999999998
    - type: ndcg_at_3
      value: 15.058
    - type: ndcg_at_5
      value: 16.31
    - type: precision_at_1
      value: 12.316
    - type: precision_at_10
      value: 2.915
    - type: precision_at_100
      value: 0.494
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 6.29
    - type: precision_at_5
      value: 4.542
    - type: recall_at_1
      value: 11.356
    - type: recall_at_10
      value: 25.55
    - type: recall_at_100
      value: 42.369
    - type: recall_at_1000
      value: 65.642
    - type: recall_at_3
      value: 17.269000000000002
    - type: recall_at_5
      value: 20.139000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.926
    - type: map_at_10
      value: 9.023
    - type: map_at_100
      value: 9.705
    - type: map_at_1000
      value: 9.814
    - type: map_at_3
      value: 8.043
    - type: map_at_5
      value: 8.609
    - type: mrr_at_1
      value: 7.960000000000001
    - type: mrr_at_10
      value: 11.472999999999999
    - type: mrr_at_100
      value: 12.225
    - type: mrr_at_1000
      value: 12.316
    - type: mrr_at_3
      value: 10.365
    - type: mrr_at_5
      value: 11.049000000000001
    - type: ndcg_at_1
      value: 7.960000000000001
    - type: ndcg_at_10
      value: 11.266
    - type: ndcg_at_100
      value: 15.092
    - type: ndcg_at_1000
      value: 18.159
    - type: ndcg_at_3
      value: 9.343
    - type: ndcg_at_5
      value: 10.302
    - type: precision_at_1
      value: 7.960000000000001
    - type: precision_at_10
      value: 2.1270000000000002
    - type: precision_at_100
      value: 0.48
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 4.601999999999999
    - type: precision_at_5
      value: 3.383
    - type: recall_at_1
      value: 5.926
    - type: recall_at_10
      value: 15.873999999999999
    - type: recall_at_100
      value: 33.274
    - type: recall_at_1000
      value: 55.799
    - type: recall_at_3
      value: 10.571
    - type: recall_at_5
      value: 12.986
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.639
    - type: map_at_10
      value: 22.948
    - type: map_at_100
      value: 24.104
    - type: map_at_1000
      value: 24.226
    - type: map_at_3
      value: 21.128
    - type: map_at_5
      value: 22.218
    - type: mrr_at_1
      value: 21.559
    - type: mrr_at_10
      value: 27.443
    - type: mrr_at_100
      value: 28.363
    - type: mrr_at_1000
      value: 28.438000000000002
    - type: mrr_at_3
      value: 25.409
    - type: mrr_at_5
      value: 26.558999999999997
    - type: ndcg_at_1
      value: 21.559
    - type: ndcg_at_10
      value: 26.863999999999997
    - type: ndcg_at_100
      value: 32.417
    - type: ndcg_at_1000
      value: 35.3
    - type: ndcg_at_3
      value: 23.658
    - type: ndcg_at_5
      value: 25.240000000000002
    - type: precision_at_1
      value: 21.559
    - type: precision_at_10
      value: 4.859999999999999
    - type: precision_at_100
      value: 0.9159999999999999
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 11.004
    - type: precision_at_5
      value: 7.931000000000001
    - type: recall_at_1
      value: 17.639
    - type: recall_at_10
      value: 34.245
    - type: recall_at_100
      value: 58.754
    - type: recall_at_1000
      value: 79.14099999999999
    - type: recall_at_3
      value: 25.072
    - type: recall_at_5
      value: 29.334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.109
    - type: map_at_10
      value: 16.184
    - type: map_at_100
      value: 17.127
    - type: map_at_1000
      value: 17.247
    - type: map_at_3
      value: 14.389
    - type: map_at_5
      value: 15.323999999999998
    - type: mrr_at_1
      value: 13.699
    - type: mrr_at_10
      value: 19.358
    - type: mrr_at_100
      value: 20.233999999999998
    - type: mrr_at_1000
      value: 20.318
    - type: mrr_at_3
      value: 17.561
    - type: mrr_at_5
      value: 18.48
    - type: ndcg_at_1
      value: 13.699
    - type: ndcg_at_10
      value: 19.779
    - type: ndcg_at_100
      value: 24.352999999999998
    - type: ndcg_at_1000
      value: 27.633999999999997
    - type: ndcg_at_3
      value: 16.414
    - type: ndcg_at_5
      value: 17.802
    - type: precision_at_1
      value: 13.699
    - type: precision_at_10
      value: 3.8699999999999997
    - type: precision_at_100
      value: 0.729
    - type: precision_at_1000
      value: 0.117
    - type: precision_at_3
      value: 8.067
    - type: precision_at_5
      value: 5.913
    - type: recall_at_1
      value: 11.109
    - type: recall_at_10
      value: 27.606
    - type: recall_at_100
      value: 47.333999999999996
    - type: recall_at_1000
      value: 71.466
    - type: recall_at_3
      value: 18.209
    - type: recall_at_5
      value: 21.785
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.838916666666668
    - type: map_at_10
      value: 18.685583333333337
    - type: map_at_100
      value: 19.5005
    - type: map_at_1000
      value: 19.614833333333333
    - type: map_at_3
      value: 17.090333333333334
    - type: map_at_5
      value: 17.965833333333332
    - type: mrr_at_1
      value: 16.78108333333334
    - type: mrr_at_10
      value: 21.741
    - type: mrr_at_100
      value: 22.48608333333333
    - type: mrr_at_1000
      value: 22.568333333333335
    - type: mrr_at_3
      value: 20.163833333333333
    - type: mrr_at_5
      value: 21.01383333333333
    - type: ndcg_at_1
      value: 16.78108333333334
    - type: ndcg_at_10
      value: 21.979666666666667
    - type: ndcg_at_100
      value: 26.148500000000002
    - type: ndcg_at_1000
      value: 29.099749999999997
    - type: ndcg_at_3
      value: 19.107250000000004
    - type: ndcg_at_5
      value: 20.390916666666666
    - type: precision_at_1
      value: 16.78108333333334
    - type: precision_at_10
      value: 3.9185833333333338
    - type: precision_at_100
      value: 0.7166666666666665
    - type: precision_at_1000
      value: 0.11350000000000002
    - type: precision_at_3
      value: 8.856166666666667
    - type: precision_at_5
      value: 6.328749999999999
    - type: recall_at_1
      value: 13.838916666666668
    - type: recall_at_10
      value: 28.876583333333333
    - type: recall_at_100
      value: 48.09441666666666
    - type: recall_at_1000
      value: 69.68258333333333
    - type: recall_at_3
      value: 20.706999999999997
    - type: recall_at_5
      value: 24.09425
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.577
    - type: map_at_10
      value: 13.633999999999999
    - type: map_at_100
      value: 14.248
    - type: map_at_1000
      value: 14.322
    - type: map_at_3
      value: 12.423
    - type: map_at_5
      value: 13.083
    - type: mrr_at_1
      value: 11.503
    - type: mrr_at_10
      value: 15.67
    - type: mrr_at_100
      value: 16.292
    - type: mrr_at_1000
      value: 16.356
    - type: mrr_at_3
      value: 14.494000000000002
    - type: mrr_at_5
      value: 15.161
    - type: ndcg_at_1
      value: 11.503
    - type: ndcg_at_10
      value: 16.195999999999998
    - type: ndcg_at_100
      value: 19.733999999999998
    - type: ndcg_at_1000
      value: 21.956
    - type: ndcg_at_3
      value: 13.947000000000001
    - type: ndcg_at_5
      value: 14.976999999999999
    - type: precision_at_1
      value: 11.503
    - type: precision_at_10
      value: 2.868
    - type: precision_at_100
      value: 0.512
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_3
      value: 6.544
    - type: precision_at_5
      value: 4.601
    - type: recall_at_1
      value: 9.577
    - type: recall_at_10
      value: 22.055
    - type: recall_at_100
      value: 39.104
    - type: recall_at_1000
      value: 56.165
    - type: recall_at_3
      value: 15.719
    - type: recall_at_5
      value: 18.453
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.266
    - type: map_at_10
      value: 10.41
    - type: map_at_100
      value: 10.979
    - type: map_at_1000
      value: 11.084
    - type: map_at_3
      value: 9.379
    - type: map_at_5
      value: 9.937999999999999
    - type: mrr_at_1
      value: 9.188
    - type: mrr_at_10
      value: 12.662
    - type: mrr_at_100
      value: 13.257
    - type: mrr_at_1000
      value: 13.345
    - type: mrr_at_3
      value: 11.557
    - type: mrr_at_5
      value: 12.124
    - type: ndcg_at_1
      value: 9.188
    - type: ndcg_at_10
      value: 12.681999999999999
    - type: ndcg_at_100
      value: 15.937999999999999
    - type: ndcg_at_1000
      value: 19.088
    - type: ndcg_at_3
      value: 10.772
    - type: ndcg_at_5
      value: 11.591999999999999
    - type: precision_at_1
      value: 9.188
    - type: precision_at_10
      value: 2.3810000000000002
    - type: precision_at_100
      value: 0.481
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 5.196
    - type: precision_at_5
      value: 3.758
    - type: recall_at_1
      value: 7.266
    - type: recall_at_10
      value: 17.433
    - type: recall_at_100
      value: 32.822
    - type: recall_at_1000
      value: 56.45099999999999
    - type: recall_at_3
      value: 11.928999999999998
    - type: recall_at_5
      value: 14.152999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.674
    - type: map_at_10
      value: 17.061999999999998
    - type: map_at_100
      value: 17.845
    - type: map_at_1000
      value: 17.944
    - type: map_at_3
      value: 15.856
    - type: map_at_5
      value: 16.478
    - type: mrr_at_1
      value: 16.418
    - type: mrr_at_10
      value: 19.999
    - type: mrr_at_100
      value: 20.798
    - type: mrr_at_1000
      value: 20.884
    - type: mrr_at_3
      value: 18.657
    - type: mrr_at_5
      value: 19.31
    - type: ndcg_at_1
      value: 16.418
    - type: ndcg_at_10
      value: 19.64
    - type: ndcg_at_100
      value: 23.926
    - type: ndcg_at_1000
      value: 26.889999999999997
    - type: ndcg_at_3
      value: 17.283
    - type: ndcg_at_5
      value: 18.232
    - type: precision_at_1
      value: 16.418
    - type: precision_at_10
      value: 3.125
    - type: precision_at_100
      value: 0.59
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.494000000000001
    - type: precision_at_5
      value: 5.149
    - type: recall_at_1
      value: 13.674
    - type: recall_at_10
      value: 24.917
    - type: recall_at_100
      value: 44.851
    - type: recall_at_1000
      value: 67.123
    - type: recall_at_3
      value: 18.275
    - type: recall_at_5
      value: 20.757
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.392
    - type: map_at_10
      value: 20.598
    - type: map_at_100
      value: 21.512
    - type: map_at_1000
      value: 21.698999999999998
    - type: map_at_3
      value: 18.884
    - type: map_at_5
      value: 19.911
    - type: mrr_at_1
      value: 18.379
    - type: mrr_at_10
      value: 23.854
    - type: mrr_at_100
      value: 24.581
    - type: mrr_at_1000
      value: 24.685000000000002
    - type: mrr_at_3
      value: 22.299
    - type: mrr_at_5
      value: 23.119
    - type: ndcg_at_1
      value: 18.379
    - type: ndcg_at_10
      value: 24.285999999999998
    - type: ndcg_at_100
      value: 28.53
    - type: ndcg_at_1000
      value: 32.124
    - type: ndcg_at_3
      value: 21.504
    - type: ndcg_at_5
      value: 22.853
    - type: precision_at_1
      value: 18.379
    - type: precision_at_10
      value: 4.684
    - type: precision_at_100
      value: 1.002
    - type: precision_at_1000
      value: 0.181
    - type: precision_at_3
      value: 10.145
    - type: precision_at_5
      value: 7.470000000000001
    - type: recall_at_1
      value: 15.392
    - type: recall_at_10
      value: 30.941000000000003
    - type: recall_at_100
      value: 51.361000000000004
    - type: recall_at_1000
      value: 75.82900000000001
    - type: recall_at_3
      value: 22.823
    - type: recall_at_5
      value: 26.495
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 9.735000000000001
    - type: map_at_10
      value: 13.213
    - type: map_at_100
      value: 13.911000000000001
    - type: map_at_1000
      value: 14.013
    - type: map_at_3
      value: 11.785
    - type: map_at_5
      value: 12.509999999999998
    - type: mrr_at_1
      value: 10.721
    - type: mrr_at_10
      value: 14.560999999999998
    - type: mrr_at_100
      value: 15.251000000000001
    - type: mrr_at_1000
      value: 15.345
    - type: mrr_at_3
      value: 12.939
    - type: mrr_at_5
      value: 13.761999999999999
    - type: ndcg_at_1
      value: 10.721
    - type: ndcg_at_10
      value: 15.742999999999999
    - type: ndcg_at_100
      value: 19.746
    - type: ndcg_at_1000
      value: 22.972
    - type: ndcg_at_3
      value: 12.748000000000001
    - type: ndcg_at_5
      value: 14.043
    - type: precision_at_1
      value: 10.721
    - type: precision_at_10
      value: 2.569
    - type: precision_at_100
      value: 0.49899999999999994
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 5.484
    - type: precision_at_5
      value: 3.993
    - type: recall_at_1
      value: 9.735000000000001
    - type: recall_at_10
      value: 22.415
    - type: recall_at_100
      value: 41.808
    - type: recall_at_1000
      value: 66.93299999999999
    - type: recall_at_3
      value: 14.338000000000001
    - type: recall_at_5
      value: 17.424999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.368
    - type: map_at_10
      value: 11.819
    - type: map_at_100
      value: 13.311
    - type: map_at_1000
      value: 13.517000000000001
    - type: map_at_3
      value: 9.451
    - type: map_at_5
      value: 10.68
    - type: mrr_at_1
      value: 14.463000000000001
    - type: mrr_at_10
      value: 23.502000000000002
    - type: mrr_at_100
      value: 24.635
    - type: mrr_at_1000
      value: 24.693
    - type: mrr_at_3
      value: 20.25
    - type: mrr_at_5
      value: 22.015
    - type: ndcg_at_1
      value: 14.463000000000001
    - type: ndcg_at_10
      value: 17.832
    - type: ndcg_at_100
      value: 24.514
    - type: ndcg_at_1000
      value: 28.395
    - type: ndcg_at_3
      value: 13.378
    - type: ndcg_at_5
      value: 15.078
    - type: precision_at_1
      value: 14.463000000000001
    - type: precision_at_10
      value: 6.065
    - type: precision_at_100
      value: 1.319
    - type: precision_at_1000
      value: 0.202
    - type: precision_at_3
      value: 10.25
    - type: precision_at_5
      value: 8.534
    - type: recall_at_1
      value: 6.368
    - type: recall_at_10
      value: 23.093
    - type: recall_at_100
      value: 46.664
    - type: recall_at_1000
      value: 68.657
    - type: recall_at_3
      value: 12.711
    - type: recall_at_5
      value: 16.858
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.75
    - type: map_at_10
      value: 8.94
    - type: map_at_100
      value: 12.631999999999998
    - type: map_at_1000
      value: 13.541
    - type: map_at_3
      value: 6.140000000000001
    - type: map_at_5
      value: 7.432999999999999
    - type: mrr_at_1
      value: 39.5
    - type: mrr_at_10
      value: 48.983
    - type: mrr_at_100
      value: 49.75
    - type: mrr_at_1000
      value: 49.782
    - type: mrr_at_3
      value: 46.125
    - type: mrr_at_5
      value: 47.825
    - type: ndcg_at_1
      value: 28.249999999999996
    - type: ndcg_at_10
      value: 22.241
    - type: ndcg_at_100
      value: 25.387999999999998
    - type: ndcg_at_1000
      value: 32.11
    - type: ndcg_at_3
      value: 24.495
    - type: ndcg_at_5
      value: 23.402
    - type: precision_at_1
      value: 39.5
    - type: precision_at_10
      value: 19.675
    - type: precision_at_100
      value: 6.3
    - type: precision_at_1000
      value: 1.3259999999999998
    - type: precision_at_3
      value: 29.666999999999998
    - type: precision_at_5
      value: 25.45
    - type: recall_at_1
      value: 3.75
    - type: recall_at_10
      value: 13.766
    - type: recall_at_100
      value: 31.915
    - type: recall_at_1000
      value: 54.85
    - type: recall_at_3
      value: 7.167
    - type: recall_at_5
      value: 9.728
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.135000000000005
    - type: f1
      value: 40.132852463847094
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.445999999999998
    - type: map_at_10
      value: 24.275
    - type: map_at_100
      value: 25.205
    - type: map_at_1000
      value: 25.278
    - type: map_at_3
      value: 21.813
    - type: map_at_5
      value: 23.254
    - type: mrr_at_1
      value: 17.567
    - type: mrr_at_10
      value: 25.733
    - type: mrr_at_100
      value: 26.663999999999998
    - type: mrr_at_1000
      value: 26.727
    - type: mrr_at_3
      value: 23.169999999999998
    - type: mrr_at_5
      value: 24.666
    - type: ndcg_at_1
      value: 17.567
    - type: ndcg_at_10
      value: 28.937
    - type: ndcg_at_100
      value: 33.757
    - type: ndcg_at_1000
      value: 35.792
    - type: ndcg_at_3
      value: 23.91
    - type: ndcg_at_5
      value: 26.485999999999997
    - type: precision_at_1
      value: 17.567
    - type: precision_at_10
      value: 4.58
    - type: precision_at_100
      value: 0.718
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 10.241
    - type: precision_at_5
      value: 7.521999999999999
    - type: recall_at_1
      value: 16.445999999999998
    - type: recall_at_10
      value: 42.152
    - type: recall_at_100
      value: 64.795
    - type: recall_at_1000
      value: 80.54
    - type: recall_at_3
      value: 28.608
    - type: recall_at_5
      value: 34.771
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.658
    - type: map_at_10
      value: 10.437000000000001
    - type: map_at_100
      value: 11.411
    - type: map_at_1000
      value: 11.581
    - type: map_at_3
      value: 8.876000000000001
    - type: map_at_5
      value: 9.806
    - type: mrr_at_1
      value: 13.117
    - type: mrr_at_10
      value: 18.447
    - type: mrr_at_100
      value: 19.363
    - type: mrr_at_1000
      value: 19.461000000000002
    - type: mrr_at_3
      value: 16.512
    - type: mrr_at_5
      value: 17.607999999999997
    - type: ndcg_at_1
      value: 13.117
    - type: ndcg_at_10
      value: 14.277999999999999
    - type: ndcg_at_100
      value: 19.259999999999998
    - type: ndcg_at_1000
      value: 23.27
    - type: ndcg_at_3
      value: 11.965
    - type: ndcg_at_5
      value: 13.020000000000001
    - type: precision_at_1
      value: 13.117
    - type: precision_at_10
      value: 3.92
    - type: precision_at_100
      value: 0.8920000000000001
    - type: precision_at_1000
      value: 0.158
    - type: precision_at_3
      value: 7.819
    - type: precision_at_5
      value: 6.019
    - type: recall_at_1
      value: 6.658
    - type: recall_at_10
      value: 17.913999999999998
    - type: recall_at_100
      value: 37.687
    - type: recall_at_1000
      value: 62.647
    - type: recall_at_3
      value: 10.908
    - type: recall_at_5
      value: 14.381
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 18.15
    - type: map_at_10
      value: 25.289
    - type: map_at_100
      value: 26.174999999999997
    - type: map_at_1000
      value: 26.282
    - type: map_at_3
      value: 23.31
    - type: map_at_5
      value: 24.367
    - type: mrr_at_1
      value: 36.3
    - type: mrr_at_10
      value: 43.134
    - type: mrr_at_100
      value: 43.854
    - type: mrr_at_1000
      value: 43.908
    - type: mrr_at_3
      value: 41.276
    - type: mrr_at_5
      value: 42.315000000000005
    - type: ndcg_at_1
      value: 36.3
    - type: ndcg_at_10
      value: 32.193
    - type: ndcg_at_100
      value: 36.301
    - type: ndcg_at_1000
      value: 38.853
    - type: ndcg_at_3
      value: 28.477000000000004
    - type: ndcg_at_5
      value: 30.223
    - type: precision_at_1
      value: 36.3
    - type: precision_at_10
      value: 7.051
    - type: precision_at_100
      value: 1.0330000000000001
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 17.889
    - type: precision_at_5
      value: 12.119
    - type: recall_at_1
      value: 18.15
    - type: recall_at_10
      value: 35.253
    - type: recall_at_100
      value: 51.668000000000006
    - type: recall_at_1000
      value: 68.717
    - type: recall_at_3
      value: 26.833000000000002
    - type: recall_at_5
      value: 30.297
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 66.5428
    - type: ap
      value: 61.12502572883321
    - type: f1
      value: 66.3624123025287
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.946
    - type: map_at_10
      value: 10.17
    - type: map_at_100
      value: 11.058
    - type: map_at_1000
      value: 11.164
    - type: map_at_3
      value: 8.414000000000001
    - type: map_at_5
      value: 9.316
    - type: mrr_at_1
      value: 6.132
    - type: mrr_at_10
      value: 10.459999999999999
    - type: mrr_at_100
      value: 11.354000000000001
    - type: mrr_at_1000
      value: 11.456
    - type: mrr_at_3
      value: 8.674999999999999
    - type: mrr_at_5
      value: 9.592
    - type: ndcg_at_1
      value: 6.089
    - type: ndcg_at_10
      value: 13.027
    - type: ndcg_at_100
      value: 17.9
    - type: ndcg_at_1000
      value: 21.053
    - type: ndcg_at_3
      value: 9.314
    - type: ndcg_at_5
      value: 10.943999999999999
    - type: precision_at_1
      value: 6.089
    - type: precision_at_10
      value: 2.291
    - type: precision_at_100
      value: 0.482
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.031
    - type: precision_at_5
      value: 3.235
    - type: recall_at_1
      value: 5.946
    - type: recall_at_10
      value: 22.017999999999997
    - type: recall_at_100
      value: 45.811
    - type: recall_at_1000
      value: 71.039
    - type: recall_at_3
      value: 11.691
    - type: recall_at_5
      value: 15.618000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 90.25763793889648
    - type: f1
      value: 89.49997029740435
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 63.0095759233926
    - type: f1
      value: 44.42212537420128
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.641560188298584
    - type: f1
      value: 60.99041094723092
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.90450571620714
    - type: f1
      value: 69.64935741375153
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 26.23206350160216
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.265258673517774
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.796475009504274
    - type: mrr
      value: 29.653223337884594
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.811
    - type: map_at_10
      value: 8.58
    - type: map_at_100
      value: 10.663
    - type: map_at_1000
      value: 11.855
    - type: map_at_3
      value: 6.842
    - type: map_at_5
      value: 7.643
    - type: mrr_at_1
      value: 34.985
    - type: mrr_at_10
      value: 44.877
    - type: mrr_at_100
      value: 45.622
    - type: mrr_at_1000
      value: 45.684000000000005
    - type: mrr_at_3
      value: 42.466
    - type: mrr_at_5
      value: 43.782
    - type: ndcg_at_1
      value: 33.282000000000004
    - type: ndcg_at_10
      value: 25.583
    - type: ndcg_at_100
      value: 23.957
    - type: ndcg_at_1000
      value: 33.216
    - type: ndcg_at_3
      value: 29.86
    - type: ndcg_at_5
      value: 27.883000000000003
    - type: precision_at_1
      value: 34.985
    - type: precision_at_10
      value: 18.142
    - type: precision_at_100
      value: 6.245
    - type: precision_at_1000
      value: 1.894
    - type: precision_at_3
      value: 27.554000000000002
    - type: precision_at_5
      value: 23.034
    - type: recall_at_1
      value: 4.811
    - type: recall_at_10
      value: 12.264999999999999
    - type: recall_at_100
      value: 25.483
    - type: recall_at_1000
      value: 58.396
    - type: recall_at_3
      value: 7.888000000000001
    - type: recall_at_5
      value: 9.607000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.876000000000001
    - type: map_at_10
      value: 14.799999999999999
    - type: map_at_100
      value: 15.967999999999998
    - type: map_at_1000
      value: 16.070999999999998
    - type: map_at_3
      value: 12.422
    - type: map_at_5
      value: 13.628000000000002
    - type: mrr_at_1
      value: 9.994
    - type: mrr_at_10
      value: 16.250999999999998
    - type: mrr_at_100
      value: 17.341
    - type: mrr_at_1000
      value: 17.43
    - type: mrr_at_3
      value: 13.808000000000002
    - type: mrr_at_5
      value: 15.057
    - type: ndcg_at_1
      value: 9.994
    - type: ndcg_at_10
      value: 18.887
    - type: ndcg_at_100
      value: 24.878
    - type: ndcg_at_1000
      value: 27.744000000000003
    - type: ndcg_at_3
      value: 13.921
    - type: ndcg_at_5
      value: 16.083
    - type: precision_at_1
      value: 9.994
    - type: precision_at_10
      value: 3.54
    - type: precision_at_100
      value: 0.698
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 6.489000000000001
    - type: precision_at_5
      value: 5.116
    - type: recall_at_1
      value: 8.876000000000001
    - type: recall_at_10
      value: 30.272
    - type: recall_at_100
      value: 58.097
    - type: recall_at_1000
      value: 80.207
    - type: recall_at_3
      value: 16.903000000000002
    - type: recall_at_5
      value: 21.948999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 61.650000000000006
    - type: map_at_10
      value: 73.951
    - type: map_at_100
      value: 74.725
    - type: map_at_1000
      value: 74.76
    - type: map_at_3
      value: 71.13199999999999
    - type: map_at_5
      value: 72.785
    - type: mrr_at_1
      value: 71.07
    - type: mrr_at_10
      value: 78.533
    - type: mrr_at_100
      value: 78.805
    - type: mrr_at_1000
      value: 78.81099999999999
    - type: mrr_at_3
      value: 77.108
    - type: mrr_at_5
      value: 77.986
    - type: ndcg_at_1
      value: 71.09
    - type: ndcg_at_10
      value: 78.717
    - type: ndcg_at_100
      value: 81.01
    - type: ndcg_at_1000
      value: 81.448
    - type: ndcg_at_3
      value: 75.223
    - type: ndcg_at_5
      value: 76.913
    - type: precision_at_1
      value: 71.09
    - type: precision_at_10
      value: 11.873000000000001
    - type: precision_at_100
      value: 1.43
    - type: precision_at_1000
      value: 0.153
    - type: precision_at_3
      value: 32.6
    - type: precision_at_5
      value: 21.46
    - type: recall_at_1
      value: 61.650000000000006
    - type: recall_at_10
      value: 87.759
    - type: recall_at_100
      value: 96.697
    - type: recall_at_1000
      value: 99.213
    - type: recall_at_3
      value: 77.627
    - type: recall_at_5
      value: 82.433
    - type: map_at_1
      value: 2.973
    - type: map_at_10
      value: 6.963
    - type: map_at_100
      value: 8.179
    - type: map_at_1000
      value: 8.391
    - type: map_at_3
      value: 5.1209999999999996
    - type: map_at_5
      value: 6.1
    - type: mrr_at_1
      value: 14.6
    - type: mrr_at_10
      value: 22.519
    - type: mrr_at_100
      value: 23.656
    - type: mrr_at_1000
      value: 23.752000000000002
    - type: mrr_at_3
      value: 19.933
    - type: mrr_at_5
      value: 21.418
    - type: ndcg_at_1
      value: 14.6
    - type: ndcg_at_10
      value: 12.357999999999999
    - type: ndcg_at_100
      value: 18.071
    - type: ndcg_at_1000
      value: 22.658
    - type: ndcg_at_3
      value: 11.78
    - type: ndcg_at_5
      value: 10.377
    - type: precision_at_1
      value: 14.6
    - type: precision_at_10
      value: 6.34
    - type: precision_at_100
      value: 1.462
    - type: precision_at_1000
      value: 0.257
    - type: precision_at_3
      value: 10.9
    - type: precision_at_5
      value: 9.08
    - type: recall_at_1
      value: 2.973
    - type: recall_at_10
      value: 12.876999999999999
    - type: recall_at_100
      value: 29.732999999999997
    - type: recall_at_1000
      value: 52.25300000000001
    - type: recall_at_3
      value: 6.638
    - type: recall_at_5
      value: 9.223
    - type: map_at_1
      value: 0.149
    - type: map_at_10
      value: 0.808
    - type: map_at_100
      value: 4.284000000000001
    - type: map_at_1000
      value: 11.209
    - type: map_at_3
      value: 0.334
    - type: map_at_5
      value: 0.461
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 67.533
    - type: mrr_at_100
      value: 68.00699999999999
    - type: mrr_at_1000
      value: 68.00699999999999
    - type: mrr_at_3
      value: 66.0
    - type: mrr_at_5
      value: 67.2
    - type: ndcg_at_1
      value: 50.0
    - type: ndcg_at_10
      value: 44.132
    - type: ndcg_at_100
      value: 33.656000000000006
    - type: ndcg_at_1000
      value: 31.062
    - type: ndcg_at_3
      value: 46.939
    - type: ndcg_at_5
      value: 44.299
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 47.0
    - type: precision_at_100
      value: 35.56
    - type: precision_at_1000
      value: 15.160000000000002
    - type: precision_at_3
      value: 51.333
    - type: precision_at_5
      value: 46.800000000000004
    - type: recall_at_1
      value: 0.149
    - type: recall_at_10
      value: 1.081
    - type: recall_at_100
      value: 7.614999999999999
    - type: recall_at_1000
      value: 30.381999999999998
    - type: recall_at_3
      value: 0.384
    - type: recall_at_5
      value: 0.5519999999999999
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 31.5539671147009
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 39.054096619731716
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 74.16263342018726
    - type: cos_sim_spearman
      value: 65.47896874175562
    - type: euclidean_pearson
      value: 69.85793726549834
    - type: euclidean_spearman
      value: 65.4790013428057
    - type: manhattan_pearson
      value: 64.55568963713883
    - type: manhattan_spearman
      value: 61.568825078510024
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 66.8016903690634
    - type: cos_sim_spearman
      value: 59.14548944908871
    - type: euclidean_pearson
      value: 63.51433073183812
    - type: euclidean_spearman
      value: 59.1468815981049
    - type: manhattan_pearson
      value: 66.7777786631213
    - type: manhattan_spearman
      value: 62.983103811799964
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 72.28649661642542
    - type: cos_sim_spearman
      value: 74.15608835313905
    - type: euclidean_pearson
      value: 73.82320584523798
    - type: euclidean_spearman
      value: 74.15612619641261
    - type: manhattan_pearson
      value: 75.8258411016566
    - type: manhattan_spearman
      value: 76.30803708387923
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 73.43505716930555
    - type: cos_sim_spearman
      value: 70.62852856991695
    - type: euclidean_pearson
      value: 72.89910614146251
    - type: euclidean_spearman
      value: 70.62851888356735
    - type: manhattan_pearson
      value: 71.9214204068933
    - type: manhattan_spearman
      value: 70.57115043790483
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 76.28414453948841
    - type: cos_sim_spearman
      value: 77.64236034865235
    - type: euclidean_pearson
      value: 77.82436104070885
    - type: euclidean_spearman
      value: 77.64235891658193
    - type: manhattan_pearson
      value: 78.02479262236683
    - type: manhattan_spearman
      value: 78.41394470741825
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 74.80262034437214
    - type: cos_sim_spearman
      value: 75.61749265386518
    - type: euclidean_pearson
      value: 75.24995074046139
    - type: euclidean_spearman
      value: 75.61748558266487
    - type: manhattan_pearson
      value: 72.8680664793595
    - type: manhattan_spearman
      value: 72.64465541572571
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 82.77228924820331
    - type: cos_sim_spearman
      value: 84.45133365648942
    - type: euclidean_pearson
      value: 83.65508313764323
    - type: euclidean_spearman
      value: 84.45220756360993
    - type: manhattan_pearson
      value: 79.31968289045513
    - type: manhattan_spearman
      value: 79.95192251749855
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 52.345708620762984
    - type: cos_sim_spearman
      value: 57.64880367305184
    - type: euclidean_pearson
      value: 56.52639850051479
    - type: euclidean_spearman
      value: 57.64880367305184
    - type: manhattan_pearson
      value: 59.969265121930434
    - type: manhattan_spearman
      value: 59.099517496575984
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 75.5029813815189
    - type: cos_sim_spearman
      value: 73.8791301142112
    - type: euclidean_pearson
      value: 75.44794524705392
    - type: euclidean_spearman
      value: 73.87914858448825
    - type: manhattan_pearson
      value: 71.2741911732711
    - type: manhattan_spearman
      value: 69.5920899359239
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 69.98974452315024
    - type: mrr
      value: 90.37764250999545
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 32.667
    - type: map_at_10
      value: 41.303
    - type: map_at_100
      value: 42.292
    - type: map_at_1000
      value: 42.372
    - type: map_at_3
      value: 39.013999999999996
    - type: map_at_5
      value: 40.469
    - type: mrr_at_1
      value: 34.666999999999994
    - type: mrr_at_10
      value: 43.187
    - type: mrr_at_100
      value: 44.028
    - type: mrr_at_1000
      value: 44.092
    - type: mrr_at_3
      value: 41.111
    - type: mrr_at_5
      value: 42.428
    - type: ndcg_at_1
      value: 34.666999999999994
    - type: ndcg_at_10
      value: 45.94
    - type: ndcg_at_100
      value: 50.67
    - type: ndcg_at_1000
      value: 52.654999999999994
    - type: ndcg_at_3
      value: 41.571999999999996
    - type: ndcg_at_5
      value: 43.998
    - type: precision_at_1
      value: 34.666999999999994
    - type: precision_at_10
      value: 6.367000000000001
    - type: precision_at_100
      value: 0.907
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 16.889000000000003
    - type: precision_at_5
      value: 11.4
    - type: recall_at_1
      value: 32.667
    - type: recall_at_10
      value: 58.556
    - type: recall_at_100
      value: 80.122
    - type: recall_at_1000
      value: 95.517
    - type: recall_at_3
      value: 46.778
    - type: recall_at_5
      value: 52.722
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.64455445544554
    - type: cos_sim_ap
      value: 87.59975053126642
    - type: cos_sim_f1
      value: 81.30325814536342
    - type: cos_sim_precision
      value: 81.50753768844221
    - type: cos_sim_recall
      value: 81.10000000000001
    - type: dot_accuracy
      value: 99.64455445544554
    - type: dot_ap
      value: 87.59975053126642
    - type: dot_f1
      value: 81.30325814536342
    - type: dot_precision
      value: 81.50753768844221
    - type: dot_recall
      value: 81.10000000000001
    - type: euclidean_accuracy
      value: 99.64455445544554
    - type: euclidean_ap
      value: 87.59975053126642
    - type: euclidean_f1
      value: 81.30325814536342
    - type: euclidean_precision
      value: 81.50753768844221
    - type: euclidean_recall
      value: 81.10000000000001
    - type: manhattan_accuracy
      value: 99.75544554455446
    - type: manhattan_ap
      value: 92.79867201777404
    - type: manhattan_f1
      value: 87.35279057859702
    - type: manhattan_precision
      value: 89.50682056663169
    - type: manhattan_recall
      value: 85.3
    - type: max_accuracy
      value: 99.75544554455446
    - type: max_ap
      value: 92.79867201777404
    - type: max_f1
      value: 87.35279057859702
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 38.67507463066139
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.940405218037796
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.17856950522057
    - type: mrr
      value: 42.73857270180799
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.824946271899556
    - type: cos_sim_spearman
      value: 30.19370307268101
    - type: dot_pearson
      value: 30.824946248457795
    - type: dot_spearman
      value: 30.239461621041393
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.138
    - type: map_at_10
      value: 6.84
    - type: map_at_100
      value: 11.829
    - type: map_at_1000
      value: 13.431999999999999
    - type: map_at_3
      value: 3.4299999999999997
    - type: map_at_5
      value: 5.1450000000000005
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 40.96
    - type: mrr_at_100
      value: 42.259
    - type: mrr_at_1000
      value: 42.262
    - type: mrr_at_3
      value: 37.075
    - type: mrr_at_5
      value: 39.728
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 19.358
    - type: ndcg_at_100
      value: 32.036
    - type: ndcg_at_1000
      value: 43.552
    - type: ndcg_at_3
      value: 20.689
    - type: ndcg_at_5
      value: 21.308
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 17.755000000000003
    - type: precision_at_100
      value: 7.449
    - type: precision_at_1000
      value: 1.478
    - type: precision_at_3
      value: 21.088
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 2.138
    - type: recall_at_10
      value: 11.958
    - type: recall_at_100
      value: 44.659
    - type: recall_at_1000
      value: 80.16499999999999
    - type: recall_at_3
      value: 4.295
    - type: recall_at_5
      value: 7.701
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.4548
    - type: ap
      value: 14.903569291537838
    - type: f1
      value: 54.76990636936144
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 58.678551216751565
    - type: f1
      value: 58.927198725369465
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.90243227502835
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.88269654884664
    - type: cos_sim_ap
      value: 65.74743802769225
    - type: cos_sim_f1
      value: 63.409891845910806
    - type: cos_sim_precision
      value: 58.774498760982205
    - type: cos_sim_recall
      value: 68.83905013192611
    - type: dot_accuracy
      value: 83.88269654884664
    - type: dot_ap
      value: 65.74743802769225
    - type: dot_f1
      value: 63.409891845910806
    - type: dot_precision
      value: 58.774498760982205
    - type: dot_recall
      value: 68.83905013192611
    - type: euclidean_accuracy
      value: 83.88269654884664
    - type: euclidean_ap
      value: 65.74743802769225
    - type: euclidean_f1
      value: 63.409891845910806
    - type: euclidean_precision
      value: 58.774498760982205
    - type: euclidean_recall
      value: 68.83905013192611
    - type: manhattan_accuracy
      value: 81.29582166060678
    - type: manhattan_ap
      value: 57.475373048925846
    - type: manhattan_f1
      value: 55.90868397493285
    - type: manhattan_precision
      value: 48.54255732607851
    - type: manhattan_recall
      value: 65.91029023746702
    - type: max_accuracy
      value: 83.88269654884664
    - type: max_ap
      value: 65.74743802769225
    - type: max_f1
      value: 63.409891845910806
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.36174176271976
    - type: cos_sim_ap
      value: 82.35619973560178
    - type: cos_sim_f1
      value: 75.05234819024828
    - type: cos_sim_precision
      value: 72.95725501599301
    - type: cos_sim_recall
      value: 77.27132737911919
    - type: dot_accuracy
      value: 87.36174176271976
    - type: dot_ap
      value: 82.35619970731375
    - type: dot_f1
      value: 75.05234819024828
    - type: dot_precision
      value: 72.95725501599301
    - type: dot_recall
      value: 77.27132737911919
    - type: euclidean_accuracy
      value: 87.36174176271976
    - type: euclidean_ap
      value: 82.35619955418572
    - type: euclidean_f1
      value: 75.05234819024828
    - type: euclidean_precision
      value: 72.95725501599301
    - type: euclidean_recall
      value: 77.27132737911919
    - type: manhattan_accuracy
      value: 87.25889703884813
    - type: manhattan_ap
      value: 81.85878727777866
    - type: manhattan_f1
      value: 74.52758333031083
    - type: manhattan_precision
      value: 70.45189604333814
    - type: manhattan_recall
      value: 79.10378811210347
    - type: max_accuracy
      value: 87.36174176271976
    - type: max_ap
      value: 82.35619973560178
    - type: max_f1
      value: 75.05234819024828
---
