mteb model-index region:us
---
tags:
- mteb
model-index:
- name: llama3_STSprompt_wordPCA
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.86567164179105
    - type: ap
      value: 35.44517238205241
    - type: f1
      value: 66.24481759245187
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 66.29775
    - type: ap
      value: 61.74437002242633
    - type: f1
      value: 65.67237033036794
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 33.742
    - type: f1
      value: 33.167768787949555
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 16.999
    - type: map_at_10
      value: 27.495000000000005
    - type: map_at_100
      value: 28.529
    - type: map_at_1000
      value: 28.593000000000004
    - type: map_at_3
      value: 24.169999999999998
    - type: map_at_5
      value: 26.005
    - type: mrr_at_1
      value: 17.639
    - type: mrr_at_10
      value: 27.712999999999997
    - type: mrr_at_100
      value: 28.754
    - type: mrr_at_1000
      value: 28.816999999999997
    - type: mrr_at_3
      value: 24.36
    - type: mrr_at_5
      value: 26.206000000000003
    - type: ndcg_at_1
      value: 16.999
    - type: ndcg_at_10
      value: 33.558
    - type: ndcg_at_100
      value: 38.917
    - type: ndcg_at_1000
      value: 40.755
    - type: ndcg_at_3
      value: 26.595999999999997
    - type: ndcg_at_5
      value: 29.935000000000002
    - type: precision_at_1
      value: 16.999
    - type: precision_at_10
      value: 5.306
    - type: precision_at_100
      value: 0.788
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 11.214
    - type: precision_at_5
      value: 8.364
    - type: recall_at_1
      value: 16.999
    - type: recall_at_10
      value: 53.05800000000001
    - type: recall_at_100
      value: 78.805
    - type: recall_at_1000
      value: 93.599
    - type: recall_at_3
      value: 33.642
    - type: recall_at_5
      value: 41.821000000000005
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 32.752423671997846
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.257964292209095
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 52.854790288659245
    - type: mrr
      value: 66.91795277667853
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 66.3620579957415
    - type: cos_sim_spearman
      value: 70.07810280120809
    - type: euclidean_pearson
      value: 67.02827963744735
    - type: euclidean_spearman
      value: 70.07810280120809
    - type: manhattan_pearson
      value: 67.75729071048507
    - type: manhattan_spearman
      value: 70.19617778078323
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 68.60714285714286
    - type: f1
      value: 67.64298065771641
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 31.698453903127977
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 21.36725660061154
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 20.275000000000002
    - type: map_at_10
      value: 27.144000000000002
    - type: map_at_100
      value: 28.281
    - type: map_at_1000
      value: 28.421999999999997
    - type: map_at_3
      value: 24.789
    - type: map_at_5
      value: 26.201
    - type: mrr_at_1
      value: 25.607999999999997
    - type: mrr_at_10
      value: 32.403999999999996
    - type: mrr_at_100
      value: 33.268
    - type: mrr_at_1000
      value: 33.337
    - type: mrr_at_3
      value: 30.329
    - type: mrr_at_5
      value: 31.637999999999998
    - type: ndcg_at_1
      value: 25.607999999999997
    - type: ndcg_at_10
      value: 31.81
    - type: ndcg_at_100
      value: 37.085
    - type: ndcg_at_1000
      value: 40.134
    - type: ndcg_at_3
      value: 28.421999999999997
    - type: ndcg_at_5
      value: 30.086000000000002
    - type: precision_at_1
      value: 25.607999999999997
    - type: precision_at_10
      value: 6.152
    - type: precision_at_100
      value: 1.114
    - type: precision_at_1000
      value: 0.169
    - type: precision_at_3
      value: 13.925
    - type: precision_at_5
      value: 9.986
    - type: recall_at_1
      value: 20.275000000000002
    - type: recall_at_10
      value: 39.7
    - type: recall_at_100
      value: 63.775999999999996
    - type: recall_at_1000
      value: 84.882
    - type: recall_at_3
      value: 29.265
    - type: recall_at_5
      value: 34.339999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.747
    - type: map_at_10
      value: 24.144
    - type: map_at_100
      value: 25.080999999999996
    - type: map_at_1000
      value: 25.186999999999998
    - type: map_at_3
      value: 22.038
    - type: map_at_5
      value: 23.205000000000002
    - type: mrr_at_1
      value: 22.803
    - type: mrr_at_10
      value: 28.814
    - type: mrr_at_100
      value: 29.599999999999998
    - type: mrr_at_1000
      value: 29.663
    - type: mrr_at_3
      value: 26.868
    - type: mrr_at_5
      value: 27.961000000000002
    - type: ndcg_at_1
      value: 22.803
    - type: ndcg_at_10
      value: 28.378999999999998
    - type: ndcg_at_100
      value: 32.64
    - type: ndcg_at_1000
      value: 35.169
    - type: ndcg_at_3
      value: 24.941
    - type: ndcg_at_5
      value: 26.471
    - type: precision_at_1
      value: 22.803
    - type: precision_at_10
      value: 5.427
    - type: precision_at_100
      value: 0.936
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 11.996
    - type: precision_at_5
      value: 8.599
    - type: recall_at_1
      value: 17.747
    - type: recall_at_10
      value: 36.197
    - type: recall_at_100
      value: 54.949000000000005
    - type: recall_at_1000
      value: 72.217
    - type: recall_at_3
      value: 26.383000000000003
    - type: recall_at_5
      value: 30.596
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.182
    - type: map_at_10
      value: 33.206
    - type: map_at_100
      value: 34.247
    - type: map_at_1000
      value: 34.342
    - type: map_at_3
      value: 31.070999999999998
    - type: map_at_5
      value: 32.223
    - type: mrr_at_1
      value: 29.592000000000002
    - type: mrr_at_10
      value: 36.665
    - type: mrr_at_100
      value: 37.543
    - type: mrr_at_1000
      value: 37.6
    - type: mrr_at_3
      value: 34.629
    - type: mrr_at_5
      value: 35.739
    - type: ndcg_at_1
      value: 29.592000000000002
    - type: ndcg_at_10
      value: 37.7
    - type: ndcg_at_100
      value: 42.585
    - type: ndcg_at_1000
      value: 44.738
    - type: ndcg_at_3
      value: 33.703
    - type: ndcg_at_5
      value: 35.510999999999996
    - type: precision_at_1
      value: 29.592000000000002
    - type: precision_at_10
      value: 6.038
    - type: precision_at_100
      value: 0.9249999999999999
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 15.046999999999999
    - type: precision_at_5
      value: 10.257
    - type: recall_at_1
      value: 25.182
    - type: recall_at_10
      value: 48.099
    - type: recall_at_100
      value: 69.95700000000001
    - type: recall_at_1000
      value: 85.47200000000001
    - type: recall_at_3
      value: 37.076
    - type: recall_at_5
      value: 41.660000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.226
    - type: map_at_10
      value: 14.316
    - type: map_at_100
      value: 15.119
    - type: map_at_1000
      value: 15.229999999999999
    - type: map_at_3
      value: 12.924
    - type: map_at_5
      value: 13.605999999999998
    - type: mrr_at_1
      value: 11.411999999999999
    - type: mrr_at_10
      value: 15.567
    - type: mrr_at_100
      value: 16.378999999999998
    - type: mrr_at_1000
      value: 16.479
    - type: mrr_at_3
      value: 14.181
    - type: mrr_at_5
      value: 14.847
    - type: ndcg_at_1
      value: 11.411999999999999
    - type: ndcg_at_10
      value: 16.952
    - type: ndcg_at_100
      value: 21.316
    - type: ndcg_at_1000
      value: 24.55
    - type: ndcg_at_3
      value: 14.099
    - type: ndcg_at_5
      value: 15.254000000000001
    - type: precision_at_1
      value: 11.411999999999999
    - type: precision_at_10
      value: 2.757
    - type: precision_at_100
      value: 0.52
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 6.064
    - type: precision_at_5
      value: 4.3389999999999995
    - type: recall_at_1
      value: 10.226
    - type: recall_at_10
      value: 24.05
    - type: recall_at_100
      value: 44.985
    - type: recall_at_1000
      value: 69.978
    - type: recall_at_3
      value: 16.224
    - type: recall_at_5
      value: 18.89
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.329999999999999
    - type: map_at_10
      value: 9.593
    - type: map_at_100
      value: 10.39
    - type: map_at_1000
      value: 10.498000000000001
    - type: map_at_3
      value: 8.276
    - type: map_at_5
      value: 8.892
    - type: mrr_at_1
      value: 8.085
    - type: mrr_at_10
      value: 12.049
    - type: mrr_at_100
      value: 12.881
    - type: mrr_at_1000
      value: 12.97
    - type: mrr_at_3
      value: 10.468
    - type: mrr_at_5
      value: 11.277
    - type: ndcg_at_1
      value: 8.085
    - type: ndcg_at_10
      value: 12.238
    - type: ndcg_at_100
      value: 16.543
    - type: ndcg_at_1000
      value: 19.584
    - type: ndcg_at_3
      value: 9.503
    - type: ndcg_at_5
      value: 10.57
    - type: precision_at_1
      value: 8.085
    - type: precision_at_10
      value: 2.4379999999999997
    - type: precision_at_100
      value: 0.5369999999999999
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 4.643
    - type: precision_at_5
      value: 3.557
    - type: recall_at_1
      value: 6.329999999999999
    - type: recall_at_10
      value: 18.126
    - type: recall_at_100
      value: 37.669000000000004
    - type: recall_at_1000
      value: 60.059
    - type: recall_at_3
      value: 10.613
    - type: recall_at_5
      value: 13.145999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 15.392
    - type: map_at_10
      value: 21.022
    - type: map_at_100
      value: 22.191
    - type: map_at_1000
      value: 22.325999999999997
    - type: map_at_3
      value: 18.916
    - type: map_at_5
      value: 20.207
    - type: mrr_at_1
      value: 19.442
    - type: mrr_at_10
      value: 25.308999999999997
    - type: mrr_at_100
      value: 26.301999999999996
    - type: mrr_at_1000
      value: 26.386
    - type: mrr_at_3
      value: 23.003
    - type: mrr_at_5
      value: 24.471
    - type: ndcg_at_1
      value: 19.442
    - type: ndcg_at_10
      value: 25.093
    - type: ndcg_at_100
      value: 30.796
    - type: ndcg_at_1000
      value: 34.001
    - type: ndcg_at_3
      value: 21.267
    - type: ndcg_at_5
      value: 23.296
    - type: precision_at_1
      value: 19.442
    - type: precision_at_10
      value: 4.755
    - type: precision_at_100
      value: 0.914
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 10.074
    - type: precision_at_5
      value: 7.5840000000000005
    - type: recall_at_1
      value: 15.392
    - type: recall_at_10
      value: 33.333
    - type: recall_at_100
      value: 58.333
    - type: recall_at_1000
      value: 80.989
    - type: recall_at_3
      value: 22.698
    - type: recall_at_5
      value: 27.877000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.144
    - type: map_at_10
      value: 17.264
    - type: map_at_100
      value: 18.368000000000002
    - type: map_at_1000
      value: 18.496000000000002
    - type: map_at_3
      value: 15.407000000000002
    - type: map_at_5
      value: 16.317
    - type: mrr_at_1
      value: 14.954
    - type: mrr_at_10
      value: 20.473
    - type: mrr_at_100
      value: 21.509
    - type: mrr_at_1000
      value: 21.595
    - type: mrr_at_3
      value: 18.721
    - type: mrr_at_5
      value: 19.622999999999998
    - type: ndcg_at_1
      value: 14.954
    - type: ndcg_at_10
      value: 20.825
    - type: ndcg_at_100
      value: 26.346000000000004
    - type: ndcg_at_1000
      value: 29.696
    - type: ndcg_at_3
      value: 17.455000000000002
    - type: ndcg_at_5
      value: 18.788
    - type: precision_at_1
      value: 14.954
    - type: precision_at_10
      value: 3.95
    - type: precision_at_100
      value: 0.8049999999999999
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 8.408999999999999
    - type: precision_at_5
      value: 6.096
    - type: recall_at_1
      value: 12.144
    - type: recall_at_10
      value: 28.572999999999997
    - type: recall_at_100
      value: 52.85300000000001
    - type: recall_at_1000
      value: 76.93100000000001
    - type: recall_at_3
      value: 18.948
    - type: recall_at_5
      value: 22.521
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.331416666666668
    - type: map_at_10
      value: 18.174333333333333
    - type: map_at_100
      value: 19.092833333333335
    - type: map_at_1000
      value: 19.213083333333334
    - type: map_at_3
      value: 16.5355
    - type: map_at_5
      value: 17.383166666666668
    - type: mrr_at_1
      value: 16.21033333333333
    - type: mrr_at_10
      value: 21.16625
    - type: mrr_at_100
      value: 22.005083333333335
    - type: mrr_at_1000
      value: 22.091249999999995
    - type: mrr_at_3
      value: 19.51425
    - type: mrr_at_5
      value: 20.373916666666663
    - type: ndcg_at_1
      value: 16.21033333333333
    - type: ndcg_at_10
      value: 21.50541666666667
    - type: ndcg_at_100
      value: 26.111666666666665
    - type: ndcg_at_1000
      value: 29.20516666666666
    - type: ndcg_at_3
      value: 18.499333333333333
    - type: ndcg_at_5
      value: 19.757749999999998
    - type: precision_at_1
      value: 16.21033333333333
    - type: precision_at_10
      value: 3.890333333333333
    - type: precision_at_100
      value: 0.7356666666666667
    - type: precision_at_1000
      value: 0.11758333333333335
    - type: precision_at_3
      value: 8.611083333333335
    - type: precision_at_5
      value: 6.1665833333333335
    - type: recall_at_1
      value: 13.331416666666668
    - type: recall_at_10
      value: 28.629749999999998
    - type: recall_at_100
      value: 49.690250000000006
    - type: recall_at_1000
      value: 72.24116666666667
    - type: recall_at_3
      value: 20.055999999999997
    - type: recall_at_5
      value: 23.340416666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.521
    - type: map_at_10
      value: 13.597999999999999
    - type: map_at_100
      value: 14.347999999999999
    - type: map_at_1000
      value: 14.441
    - type: map_at_3
      value: 12.036
    - type: map_at_5
      value: 12.831999999999999
    - type: mrr_at_1
      value: 11.196
    - type: mrr_at_10
      value: 15.598999999999998
    - type: mrr_at_100
      value: 16.331
    - type: mrr_at_1000
      value: 16.413
    - type: mrr_at_3
      value: 13.983
    - type: mrr_at_5
      value: 14.757000000000001
    - type: ndcg_at_1
      value: 11.196
    - type: ndcg_at_10
      value: 16.532
    - type: ndcg_at_100
      value: 20.524
    - type: ndcg_at_1000
      value: 23.299
    - type: ndcg_at_3
      value: 13.459
    - type: ndcg_at_5
      value: 14.731
    - type: precision_at_1
      value: 11.196
    - type: precision_at_10
      value: 2.991
    - type: precision_at_100
      value: 0.5479999999999999
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.237
    - type: precision_at_5
      value: 4.601
    - type: recall_at_1
      value: 9.521
    - type: recall_at_10
      value: 23.776
    - type: recall_at_100
      value: 42.483
    - type: recall_at_1000
      value: 63.724000000000004
    - type: recall_at_3
      value: 15.040000000000001
    - type: recall_at_5
      value: 18.259
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 6.464
    - type: map_at_10
      value: 9.512
    - type: map_at_100
      value: 10.120999999999999
    - type: map_at_1000
      value: 10.237
    - type: map_at_3
      value: 8.465
    - type: map_at_5
      value: 9.001000000000001
    - type: mrr_at_1
      value: 8.259
    - type: mrr_at_10
      value: 11.695
    - type: mrr_at_100
      value: 12.315
    - type: mrr_at_1000
      value: 12.416
    - type: mrr_at_3
      value: 10.530000000000001
    - type: mrr_at_5
      value: 11.111
    - type: ndcg_at_1
      value: 8.259
    - type: ndcg_at_10
      value: 11.782
    - type: ndcg_at_100
      value: 15.139
    - type: ndcg_at_1000
      value: 18.512999999999998
    - type: ndcg_at_3
      value: 9.772
    - type: ndcg_at_5
      value: 10.607999999999999
    - type: precision_at_1
      value: 8.259
    - type: precision_at_10
      value: 2.257
    - type: precision_at_100
      value: 0.47000000000000003
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 4.714
    - type: precision_at_5
      value: 3.5029999999999997
    - type: recall_at_1
      value: 6.464
    - type: recall_at_10
      value: 16.604
    - type: recall_at_100
      value: 32.39
    - type: recall_at_1000
      value: 57.458
    - type: recall_at_3
      value: 10.883
    - type: recall_at_5
      value: 13.044
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.754999999999999
    - type: map_at_10
      value: 16.646
    - type: map_at_100
      value: 17.521
    - type: map_at_1000
      value: 17.630000000000003
    - type: map_at_3
      value: 15.598
    - type: map_at_5
      value: 16.125
    - type: mrr_at_1
      value: 15.392
    - type: mrr_at_10
      value: 19.578
    - type: mrr_at_100
      value: 20.413
    - type: mrr_at_1000
      value: 20.512
    - type: mrr_at_3
      value: 18.377
    - type: mrr_at_5
      value: 18.945999999999998
    - type: ndcg_at_1
      value: 15.392
    - type: ndcg_at_10
      value: 19.326
    - type: ndcg_at_100
      value: 23.862
    - type: ndcg_at_1000
      value: 26.980999999999998
    - type: ndcg_at_3
      value: 17.286
    - type: ndcg_at_5
      value: 18.058
    - type: precision_at_1
      value: 15.392
    - type: precision_at_10
      value: 3.1530000000000005
    - type: precision_at_100
      value: 0.599
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 7.743
    - type: precision_at_5
      value: 5.242999999999999
    - type: recall_at_1
      value: 12.754999999999999
    - type: recall_at_10
      value: 24.809
    - type: recall_at_100
      value: 45.554
    - type: recall_at_1000
      value: 68.655
    - type: recall_at_3
      value: 18.872
    - type: recall_at_5
      value: 21.027
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.007000000000001
    - type: map_at_10
      value: 19.471
    - type: map_at_100
      value: 20.557
    - type: map_at_1000
      value: 20.748
    - type: map_at_3
      value: 18.055
    - type: map_at_5
      value: 18.603
    - type: mrr_at_1
      value: 17.984
    - type: mrr_at_10
      value: 22.578
    - type: mrr_at_100
      value: 23.549
    - type: mrr_at_1000
      value: 23.648
    - type: mrr_at_3
      value: 21.343999999999998
    - type: mrr_at_5
      value: 21.779
    - type: ndcg_at_1
      value: 17.984
    - type: ndcg_at_10
      value: 22.803
    - type: ndcg_at_100
      value: 27.868
    - type: ndcg_at_1000
      value: 31.713
    - type: ndcg_at_3
      value: 20.437
    - type: ndcg_at_5
      value: 21.113
    - type: precision_at_1
      value: 17.984
    - type: precision_at_10
      value: 4.289
    - type: precision_at_100
      value: 0.972
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 9.552
    - type: precision_at_5
      value: 6.7589999999999995
    - type: recall_at_1
      value: 15.007000000000001
    - type: recall_at_10
      value: 28.953
    - type: recall_at_100
      value: 52.691
    - type: recall_at_1000
      value: 79.045
    - type: recall_at_3
      value: 21.632
    - type: recall_at_5
      value: 23.432
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.934000000000001
    - type: map_at_10
      value: 12.176
    - type: map_at_100
      value: 12.889999999999999
    - type: map_at_1000
      value: 13.0
    - type: map_at_3
      value: 10.850999999999999
    - type: map_at_5
      value: 11.386000000000001
    - type: mrr_at_1
      value: 9.797
    - type: mrr_at_10
      value: 13.264000000000001
    - type: mrr_at_100
      value: 13.971
    - type: mrr_at_1000
      value: 14.076
    - type: mrr_at_3
      value: 11.738
    - type: mrr_at_5
      value: 12.338000000000001
    - type: ndcg_at_1
      value: 9.797
    - type: ndcg_at_10
      value: 14.625
    - type: ndcg_at_100
      value: 18.636
    - type: ndcg_at_1000
      value: 22.084
    - type: ndcg_at_3
      value: 11.648
    - type: ndcg_at_5
      value: 12.607
    - type: precision_at_1
      value: 9.797
    - type: precision_at_10
      value: 2.477
    - type: precision_at_100
      value: 0.488
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 4.929
    - type: precision_at_5
      value: 3.4750000000000005
    - type: recall_at_1
      value: 8.934000000000001
    - type: recall_at_10
      value: 21.337
    - type: recall_at_100
      value: 40.643
    - type: recall_at_1000
      value: 67.484
    - type: recall_at_3
      value: 13.038
    - type: recall_at_5
      value: 15.293000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.619999999999999
    - type: map_at_10
      value: 12.036
    - type: map_at_100
      value: 13.524
    - type: map_at_1000
      value: 13.706
    - type: map_at_3
      value: 9.885
    - type: map_at_5
      value: 11.044
    - type: mrr_at_1
      value: 15.440000000000001
    - type: mrr_at_10
      value: 24.657999999999998
    - type: mrr_at_100
      value: 25.714
    - type: mrr_at_1000
      value: 25.775
    - type: mrr_at_3
      value: 21.477
    - type: mrr_at_5
      value: 23.193
    - type: ndcg_at_1
      value: 15.440000000000001
    - type: ndcg_at_10
      value: 18.071
    - type: ndcg_at_100
      value: 24.747
    - type: ndcg_at_1000
      value: 28.285
    - type: ndcg_at_3
      value: 14.129
    - type: ndcg_at_5
      value: 15.620000000000001
    - type: precision_at_1
      value: 15.440000000000001
    - type: precision_at_10
      value: 5.961
    - type: precision_at_100
      value: 1.304
    - type: precision_at_1000
      value: 0.19499999999999998
    - type: precision_at_3
      value: 10.879
    - type: precision_at_5
      value: 8.704
    - type: recall_at_1
      value: 6.619999999999999
    - type: recall_at_10
      value: 22.797
    - type: recall_at_100
      value: 46.646
    - type: recall_at_1000
      value: 66.61500000000001
    - type: recall_at_3
      value: 13.358
    - type: recall_at_5
      value: 17.336
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.258
    - type: map_at_10
      value: 7.720000000000001
    - type: map_at_100
      value: 10.972
    - type: map_at_1000
      value: 11.849
    - type: map_at_3
      value: 5.305
    - type: map_at_5
      value: 6.401999999999999
    - type: mrr_at_1
      value: 37.0
    - type: mrr_at_10
      value: 45.73
    - type: mrr_at_100
      value: 46.472
    - type: mrr_at_1000
      value: 46.516000000000005
    - type: mrr_at_3
      value: 42.5
    - type: mrr_at_5
      value: 44.462
    - type: ndcg_at_1
      value: 25.374999999999996
    - type: ndcg_at_10
      value: 19.869999999999997
    - type: ndcg_at_100
      value: 23.191
    - type: ndcg_at_1000
      value: 30.17
    - type: ndcg_at_3
      value: 21.565
    - type: ndcg_at_5
      value: 20.622
    - type: precision_at_1
      value: 37.0
    - type: precision_at_10
      value: 18.05
    - type: precision_at_100
      value: 5.865
    - type: precision_at_1000
      value: 1.256
    - type: precision_at_3
      value: 26.417
    - type: precision_at_5
      value: 22.6
    - type: recall_at_1
      value: 3.258
    - type: recall_at_10
      value: 12.098
    - type: recall_at_100
      value: 30.075000000000003
    - type: recall_at_1000
      value: 54.348
    - type: recall_at_3
      value: 6.3740000000000006
    - type: recall_at_5
      value: 8.75
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 39.775
    - type: f1
      value: 37.253467952273716
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 15.539
    - type: map_at_10
      value: 23.506
    - type: map_at_100
      value: 24.433
    - type: map_at_1000
      value: 24.512999999999998
    - type: map_at_3
      value: 20.944
    - type: map_at_5
      value: 22.427
    - type: mrr_at_1
      value: 16.607
    - type: mrr_at_10
      value: 24.911
    - type: mrr_at_100
      value: 25.835
    - type: mrr_at_1000
      value: 25.903
    - type: mrr_at_3
      value: 22.235
    - type: mrr_at_5
      value: 23.782
    - type: ndcg_at_1
      value: 16.607
    - type: ndcg_at_10
      value: 28.327999999999996
    - type: ndcg_at_100
      value: 33.239000000000004
    - type: ndcg_at_1000
      value: 35.447
    - type: ndcg_at_3
      value: 23.044
    - type: ndcg_at_5
      value: 25.711000000000002
    - type: precision_at_1
      value: 16.607
    - type: precision_at_10
      value: 4.584
    - type: precision_at_100
      value: 0.729
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 9.981
    - type: precision_at_5
      value: 7.396
    - type: recall_at_1
      value: 15.539
    - type: recall_at_10
      value: 42.138999999999996
    - type: recall_at_100
      value: 65.42999999999999
    - type: recall_at_1000
      value: 82.536
    - type: recall_at_3
      value: 27.809
    - type: recall_at_5
      value: 34.217999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.7860000000000005
    - type: map_at_10
      value: 9.501
    - type: map_at_100
      value: 10.509
    - type: map_at_1000
      value: 10.685
    - type: map_at_3
      value: 7.879
    - type: map_at_5
      value: 8.703
    - type: mrr_at_1
      value: 11.728
    - type: mrr_at_10
      value: 17.121
    - type: mrr_at_100
      value: 18.062
    - type: mrr_at_1000
      value: 18.15
    - type: mrr_at_3
      value: 14.969
    - type: mrr_at_5
      value: 16.219
    - type: ndcg_at_1
      value: 11.728
    - type: ndcg_at_10
      value: 13.520999999999999
    - type: ndcg_at_100
      value: 18.794
    - type: ndcg_at_1000
      value: 23.032
    - type: ndcg_at_3
      value: 10.814
    - type: ndcg_at_5
      value: 11.884
    - type: precision_at_1
      value: 11.728
    - type: precision_at_10
      value: 4.074
    - type: precision_at_100
      value: 0.9289999999999999
    - type: precision_at_1000
      value: 0.165
    - type: precision_at_3
      value: 7.305000000000001
    - type: precision_at_5
      value: 5.8020000000000005
    - type: recall_at_1
      value: 5.7860000000000005
    - type: recall_at_10
      value: 17.765
    - type: recall_at_100
      value: 39.159
    - type: recall_at_1000
      value: 66.101
    - type: recall_at_3
      value: 10.113
    - type: recall_at_5
      value: 13.379
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 16.232
    - type: map_at_10
      value: 22.717000000000002
    - type: map_at_100
      value: 23.508000000000003
    - type: map_at_1000
      value: 23.604
    - type: map_at_3
      value: 21.029999999999998
    - type: map_at_5
      value: 21.938
    - type: mrr_at_1
      value: 32.478
    - type: mrr_at_10
      value: 39.043
    - type: mrr_at_100
      value: 39.711999999999996
    - type: mrr_at_1000
      value: 39.765
    - type: mrr_at_3
      value: 37.317
    - type: mrr_at_5
      value: 38.257999999999996
    - type: ndcg_at_1
      value: 32.464999999999996
    - type: ndcg_at_10
      value: 29.037000000000003
    - type: ndcg_at_100
      value: 32.756
    - type: ndcg_at_1000
      value: 35.086
    - type: ndcg_at_3
      value: 25.779000000000003
    - type: ndcg_at_5
      value: 27.303
    - type: precision_at_1
      value: 32.464999999999996
    - type: precision_at_10
      value: 6.363
    - type: precision_at_100
      value: 0.9339999999999999
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 16.291
    - type: precision_at_5
      value: 10.982
    - type: recall_at_1
      value: 16.232
    - type: recall_at_10
      value: 31.816
    - type: recall_at_100
      value: 46.691
    - type: recall_at_1000
      value: 62.235
    - type: recall_at_3
      value: 24.436
    - type: recall_at_5
      value: 27.454
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.2676
    - type: ap
      value: 58.73564850695608
    - type: f1
      value: 62.72506969821588
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.532
    - type: map_at_10
      value: 9.656
    - type: map_at_100
      value: 10.525
    - type: map_at_1000
      value: 10.625
    - type: map_at_3
      value: 8.062999999999999
    - type: map_at_5
      value: 8.892999999999999
    - type: mrr_at_1
      value: 5.659
    - type: mrr_at_10
      value: 9.881
    - type: mrr_at_100
      value: 10.764
    - type: mrr_at_1000
      value: 10.86
    - type: mrr_at_3
      value: 8.25
    - type: mrr_at_5
      value: 9.102
    - type: ndcg_at_1
      value: 5.659
    - type: ndcg_at_10
      value: 12.341000000000001
    - type: ndcg_at_100
      value: 17.154
    - type: ndcg_at_1000
      value: 20.154
    - type: ndcg_at_3
      value: 8.968
    - type: ndcg_at_5
      value: 10.469000000000001
    - type: precision_at_1
      value: 5.659
    - type: precision_at_10
      value: 2.153
    - type: precision_at_100
      value: 0.466
    - type: precision_at_1000
      value: 0.073
    - type: precision_at_3
      value: 3.916
    - type: precision_at_5
      value: 3.1029999999999998
    - type: recall_at_1
      value: 5.532
    - type: recall_at_10
      value: 20.788
    - type: recall_at_100
      value: 44.419
    - type: recall_at_1000
      value: 68.47999999999999
    - type: recall_at_3
      value: 11.405999999999999
    - type: recall_at_5
      value: 15.014
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.68536251709985
    - type: f1
      value: 88.79185391392097
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.47423620611034
    - type: f1
      value: 42.681111996933936
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.62743779421655
    - type: f1
      value: 59.44525066841824
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.18964357767317
    - type: f1
      value: 67.75095808014
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.261678947620393
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 24.12573884860151
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.38819156715654
    - type: mrr
      value: 28.876813734506364
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 5.303
    - type: map_at_10
      value: 9.311
    - type: map_at_100
      value: 11.889
    - type: map_at_1000
      value: 13.279
    - type: map_at_3
      value: 7.4270000000000005
    - type: map_at_5
      value: 8.299
    - type: mrr_at_1
      value: 35.913000000000004
    - type: mrr_at_10
      value: 46.418
    - type: mrr_at_100
      value: 47.024
    - type: mrr_at_1000
      value: 47.073
    - type: mrr_at_3
      value: 44.013999999999996
    - type: mrr_at_5
      value: 45.083
    - type: ndcg_at_1
      value: 34.52
    - type: ndcg_at_10
      value: 26.689
    - type: ndcg_at_100
      value: 26.064999999999998
    - type: ndcg_at_1000
      value: 35.589
    - type: ndcg_at_3
      value: 31.080999999999996
    - type: ndcg_at_5
      value: 28.872999999999998
    - type: precision_at_1
      value: 35.913000000000004
    - type: precision_at_10
      value: 19.040000000000003
    - type: precision_at_100
      value: 6.954000000000001
    - type: precision_at_1000
      value: 2.031
    - type: precision_at_3
      value: 28.688999999999997
    - type: precision_at_5
      value: 23.901
    - type: recall_at_1
      value: 5.303
    - type: recall_at_10
      value: 12.974
    - type: recall_at_100
      value: 28.157
    - type: recall_at_1000
      value: 62.261
    - type: recall_at_3
      value: 8.459999999999999
    - type: recall_at_5
      value: 10.128
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.881
    - type: map_at_10
      value: 16.489
    - type: map_at_100
      value: 17.548
    - type: map_at_1000
      value: 17.645
    - type: map_at_3
      value: 14.044
    - type: map_at_5
      value: 15.368
    - type: mrr_at_1
      value: 11.211
    - type: mrr_at_10
      value: 18.099
    - type: mrr_at_100
      value: 19.096
    - type: mrr_at_1000
      value: 19.179
    - type: mrr_at_3
      value: 15.648000000000001
    - type: mrr_at_5
      value: 17.02
    - type: ndcg_at_1
      value: 11.211
    - type: ndcg_at_10
      value: 20.747
    - type: ndcg_at_100
      value: 26.075
    - type: ndcg_at_1000
      value: 28.662
    - type: ndcg_at_3
      value: 15.756999999999998
    - type: ndcg_at_5
      value: 18.133
    - type: precision_at_1
      value: 11.211
    - type: precision_at_10
      value: 3.83
    - type: precision_at_100
      value: 0.6859999999999999
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_3
      value: 7.367999999999999
    - type: precision_at_5
      value: 5.771
    - type: recall_at_1
      value: 9.881
    - type: recall_at_10
      value: 32.363
    - type: recall_at_100
      value: 56.948
    - type: recall_at_1000
      value: 76.753
    - type: recall_at_3
      value: 19.131
    - type: recall_at_5
      value: 24.684
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.333999999999996
    - type: map_at_10
      value: 72.433
    - type: map_at_100
      value: 73.179
    - type: map_at_1000
      value: 73.217
    - type: map_at_3
      value: 69.56
    - type: map_at_5
      value: 71.321
    - type: mrr_at_1
      value: 69.5
    - type: mrr_at_10
      value: 77.039
    - type: mrr_at_100
      value: 77.31400000000001
    - type: mrr_at_1000
      value: 77.323
    - type: mrr_at_3
      value: 75.5
    - type: mrr_at_5
      value: 76.493
    - type: ndcg_at_1
      value: 69.58
    - type: ndcg_at_10
      value: 77.208
    - type: ndcg_at_100
      value: 79.445
    - type: ndcg_at_1000
      value: 79.98100000000001
    - type: ndcg_at_3
      value: 73.585
    - type: ndcg_at_5
      value: 75.48
    - type: precision_at_1
      value: 69.58
    - type: precision_at_10
      value: 11.616999999999999
    - type: precision_at_100
      value: 1.397
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 31.817
    - type: precision_at_5
      value: 21.074
    - type: recall_at_1
      value: 60.333999999999996
    - type: recall_at_10
      value: 86.349
    - type: recall_at_100
      value: 95.025
    - type: recall_at_1000
      value: 98.29
    - type: recall_at_3
      value: 75.91499999999999
    - type: recall_at_5
      value: 81.182
    - type: map_at_1
      value: 2.4379999999999997
    - type: map_at_10
      value: 6.553000000000001
    - type: map_at_100
      value: 7.898
    - type: map_at_1000
      value: 8.142000000000001
    - type: map_at_3
      value: 4.682
    - type: map_at_5
      value: 5.62
    - type: mrr_at_1
      value: 12.0
    - type: mrr_at_10
      value: 20.631
    - type: mrr_at_100
      value: 21.834
    - type: mrr_at_1000
      value: 21.935
    - type: mrr_at_3
      value: 17.817
    - type: mrr_at_5
      value: 19.477
    - type: ndcg_at_1
      value: 12.0
    - type: ndcg_at_10
      value: 11.854000000000001
    - type: ndcg_at_100
      value: 18.048000000000002
    - type: ndcg_at_1000
      value: 23.244999999999997
    - type: ndcg_at_3
      value: 10.865
    - type: ndcg_at_5
      value: 9.699
    - type: precision_at_1
      value: 12.0
    - type: precision_at_10
      value: 6.35
    - type: precision_at_100
      value: 1.537
    - type: precision_at_1000
      value: 0.27999999999999997
    - type: precision_at_3
      value: 10.467
    - type: precision_at_5
      value: 8.82
    - type: recall_at_1
      value: 2.4379999999999997
    - type: recall_at_10
      value: 12.889999999999999
    - type: recall_at_100
      value: 31.272
    - type: recall_at_1000
      value: 56.83200000000001
    - type: recall_at_3
      value: 6.372999999999999
    - type: recall_at_5
      value: 8.943
    - type: map_at_1
      value: 0.151
    - type: map_at_10
      value: 1.11
    - type: map_at_100
      value: 5.493
    - type: map_at_1000
      value: 12.9
    - type: map_at_3
      value: 0.42300000000000004
    - type: map_at_5
      value: 0.652
    - type: mrr_at_1
      value: 66.0
    - type: mrr_at_10
      value: 77.986
    - type: mrr_at_100
      value: 78.086
    - type: mrr_at_1000
      value: 78.086
    - type: mrr_at_3
      value: 76.0
    - type: mrr_at_5
      value: 77.5
    - type: ndcg_at_1
      value: 60.0
    - type: ndcg_at_10
      value: 54.611
    - type: ndcg_at_100
      value: 38.848
    - type: ndcg_at_1000
      value: 32.887
    - type: ndcg_at_3
      value: 60.123000000000005
    - type: ndcg_at_5
      value: 59.477000000000004
    - type: precision_at_1
      value: 66.0
    - type: precision_at_10
      value: 58.4
    - type: precision_at_100
      value: 40.52
    - type: precision_at_1000
      value: 15.518
    - type: precision_at_3
      value: 65.333
    - type: precision_at_5
      value: 64.0
    - type: recall_at_1
      value: 0.151
    - type: recall_at_10
      value: 1.365
    - type: recall_at_100
      value: 8.67
    - type: recall_at_1000
      value: 31.286
    - type: recall_at_3
      value: 0.479
    - type: recall_at_5
      value: 0.771
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 25.89330417520166
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 35.47472439634197
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 74.60915562909248
    - type: cos_sim_spearman
      value: 65.49000650957157
    - type: euclidean_pearson
      value: 70.1700684443695
    - type: euclidean_spearman
      value: 65.4899957190204
    - type: manhattan_pearson
      value: 67.85541431977921
    - type: manhattan_spearman
      value: 64.7047707491316
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 72.60466030817162
    - type: cos_sim_spearman
      value: 66.56226716201341
    - type: euclidean_pearson
      value: 69.45460734110853
    - type: euclidean_spearman
      value: 66.56350168932688
    - type: manhattan_pearson
      value: 64.58382463812974
    - type: manhattan_spearman
      value: 63.34159521108897
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 71.13568380319647
    - type: cos_sim_spearman
      value: 72.07503695778388
    - type: euclidean_pearson
      value: 72.35421536816658
    - type: euclidean_spearman
      value: 72.07507481770585
    - type: manhattan_pearson
      value: 70.41274758896546
    - type: manhattan_spearman
      value: 69.91549531015315
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 68.81125447529332
    - type: cos_sim_spearman
      value: 67.99712816171936
    - type: euclidean_pearson
      value: 68.66215488899678
    - type: euclidean_spearman
      value: 67.9971184785134
    - type: manhattan_pearson
      value: 67.53466035323753
    - type: manhattan_spearman
      value: 67.18583918058982
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 76.28182368707374
    - type: cos_sim_spearman
      value: 77.69940987577804
    - type: euclidean_pearson
      value: 77.53646310718189
    - type: euclidean_spearman
      value: 77.69940643216601
    - type: manhattan_pearson
      value: 76.78213156277387
    - type: manhattan_spearman
      value: 76.86316540517423
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 62.0726077717635
    - type: cos_sim_spearman
      value: 65.98319186337503
    - type: euclidean_pearson
      value: 65.67598389197177
    - type: euclidean_spearman
      value: 65.9837431693805
    - type: manhattan_pearson
      value: 65.48878961096061
    - type: manhattan_spearman
      value: 65.66497181372006
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 77.12393911158544
    - type: cos_sim_spearman
      value: 79.41807979078037
    - type: euclidean_pearson
      value: 78.99684302370609
    - type: euclidean_spearman
      value: 79.41895659710345
    - type: manhattan_pearson
      value: 78.12406378720547
    - type: manhattan_spearman
      value: 78.40030554117344
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 38.27620893980747
    - type: cos_sim_spearman
      value: 52.39237713694356
    - type: euclidean_pearson
      value: 45.92209181781139
    - type: euclidean_spearman
      value: 52.39237713694356
    - type: manhattan_pearson
      value: 43.04874873424595
    - type: manhattan_spearman
      value: 49.321502859848856
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 68.63138120529958
    - type: cos_sim_spearman
      value: 67.5933878528282
    - type: euclidean_pearson
      value: 69.44664795794799
    - type: euclidean_spearman
      value: 67.59340633029616
    - type: manhattan_pearson
      value: 68.36628416501331
    - type: manhattan_spearman
      value: 66.87881145545586
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 70.55175992915854
    - type: mrr
      value: 90.46667384902678
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 35.75
    - type: map_at_10
      value: 45.054
    - type: map_at_100
      value: 46.208
    - type: map_at_1000
      value: 46.265
    - type: map_at_3
      value: 42.625
    - type: map_at_5
      value: 44.185
    - type: mrr_at_1
      value: 37.667
    - type: mrr_at_10
      value: 46.555
    - type: mrr_at_100
      value: 47.521
    - type: mrr_at_1000
      value: 47.571000000000005
    - type: mrr_at_3
      value: 44.278
    - type: mrr_at_5
      value: 45.778
    - type: ndcg_at_1
      value: 37.667
    - type: ndcg_at_10
      value: 49.854
    - type: ndcg_at_100
      value: 54.986999999999995
    - type: ndcg_at_1000
      value: 56.455999999999996
    - type: ndcg_at_3
      value: 45.084
    - type: ndcg_at_5
      value: 47.782000000000004
    - type: precision_at_1
      value: 37.667
    - type: precision_at_10
      value: 6.9
    - type: precision_at_100
      value: 0.98
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 18.0
    - type: precision_at_5
      value: 12.333
    - type: recall_at_1
      value: 35.75
    - type: recall_at_10
      value: 63.306
    - type: recall_at_100
      value: 86.13300000000001
    - type: recall_at_1000
      value: 97.6
    - type: recall_at_3
      value: 50.556
    - type: recall_at_5
      value: 57.028
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.54554455445545
    - type: cos_sim_ap
      value: 81.03057853356
    - type: cos_sim_f1
      value: 74.78813559322035
    - type: cos_sim_precision
      value: 79.5045045045045
    - type: cos_sim_recall
      value: 70.6
    - type: dot_accuracy
      value: 99.54554455445545
    - type: dot_ap
      value: 81.03057853356
    - type: dot_f1
      value: 74.78813559322035
    - type: dot_precision
      value: 79.5045045045045
    - type: dot_recall
      value: 70.6
    - type: euclidean_accuracy
      value: 99.54554455445545
    - type: euclidean_ap
      value: 81.03057853356
    - type: euclidean_f1
      value: 74.78813559322035
    - type: euclidean_precision
      value: 79.5045045045045
    - type: euclidean_recall
      value: 70.6
    - type: manhattan_accuracy
      value: 99.53861386138614
    - type: manhattan_ap
      value: 81.55735590238187
    - type: manhattan_f1
      value: 74.7789911596464
    - type: manhattan_precision
      value: 77.89815817984832
    - type: manhattan_recall
      value: 71.89999999999999
    - type: max_accuracy
      value: 99.54554455445545
    - type: max_ap
      value: 81.55735590238187
    - type: max_f1
      value: 74.78813559322035
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 32.85426529220047
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 25.801245404544826
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.73333062572138
    - type: mrr
      value: 42.17854755538579
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.401104847347938
    - type: cos_sim_spearman
      value: 30.63067494754781
    - type: dot_pearson
      value: 30.401104842345617
    - type: dot_spearman
      value: 30.619796987282573
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.22
    - type: map_at_10
      value: 4.533
    - type: map_at_100
      value: 8.429
    - type: map_at_1000
      value: 9.981
    - type: map_at_3
      value: 2.606
    - type: map_at_5
      value: 3.5159999999999996
    - type: mrr_at_1
      value: 22.448999999999998
    - type: mrr_at_10
      value: 32.958999999999996
    - type: mrr_at_100
      value: 34.754000000000005
    - type: mrr_at_1000
      value: 34.79
    - type: mrr_at_3
      value: 29.932
    - type: mrr_at_5
      value: 31.871
    - type: ndcg_at_1
      value: 20.408
    - type: ndcg_at_10
      value: 13.79
    - type: ndcg_at_100
      value: 25.476
    - type: ndcg_at_1000
      value: 38.714999999999996
    - type: ndcg_at_3
      value: 17.061999999999998
    - type: ndcg_at_5
      value: 15.52
    - type: precision_at_1
      value: 22.448999999999998
    - type: precision_at_10
      value: 12.653
    - type: precision_at_100
      value: 6.265
    - type: precision_at_1000
      value: 1.455
    - type: precision_at_3
      value: 17.687
    - type: precision_at_5
      value: 15.509999999999998
    - type: recall_at_1
      value: 1.22
    - type: recall_at_10
      value: 8.862
    - type: recall_at_100
      value: 38.118
    - type: recall_at_1000
      value: 79.078
    - type: recall_at_3
      value: 3.621
    - type: recall_at_5
      value: 5.6610000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.85280000000002
    - type: ap
      value: 12.628576580480205
    - type: f1
      value: 52.846767656927774
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.85738539898133
    - type: f1
      value: 56.08638204262546
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 29.18350429483415
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.88728616558384
    - type: cos_sim_ap
      value: 62.5610472971754
    - type: cos_sim_f1
      value: 59.31407094197792
    - type: cos_sim_precision
      value: 53.45046570702794
    - type: cos_sim_recall
      value: 66.62269129287598
    - type: dot_accuracy
      value: 82.88728616558384
    - type: dot_ap
      value: 62.5610472971754
    - type: dot_f1
      value: 59.31407094197792
    - type: dot_precision
      value: 53.45046570702794
    - type: dot_recall
      value: 66.62269129287598
    - type: euclidean_accuracy
      value: 82.88728616558384
    - type: euclidean_ap
      value: 62.5610472971754
    - type: euclidean_f1
      value: 59.31407094197792
    - type: euclidean_precision
      value: 53.45046570702794
    - type: euclidean_recall
      value: 66.62269129287598
    - type: manhattan_accuracy
      value: 83.26876080348096
    - type: manhattan_ap
      value: 63.94957813634585
    - type: manhattan_f1
      value: 60.783125227300296
    - type: manhattan_precision
      value: 56.22336846826643
    - type: manhattan_recall
      value: 66.14775725593668
    - type: max_accuracy
      value: 83.26876080348096
    - type: max_ap
      value: 63.94957813634585
    - type: max_f1
      value: 60.783125227300296
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.36822292079016
    - type: cos_sim_ap
      value: 79.73424609471161
    - type: cos_sim_f1
      value: 71.86706497386109
    - type: cos_sim_precision
      value: 69.77233178654292
    - type: cos_sim_recall
      value: 74.09146904835232
    - type: dot_accuracy
      value: 86.36822292079016
    - type: dot_ap
      value: 79.73424618447234
    - type: dot_f1
      value: 71.86706497386109
    - type: dot_precision
      value: 69.77233178654292
    - type: dot_recall
      value: 74.09146904835232
    - type: euclidean_accuracy
      value: 86.36822292079016
    - type: euclidean_ap
      value: 79.73424609471161
    - type: euclidean_f1
      value: 71.86706497386109
    - type: euclidean_precision
      value: 69.77233178654292
    - type: euclidean_recall
      value: 74.09146904835232
    - type: manhattan_accuracy
      value: 86.72138782163232
    - type: manhattan_ap
      value: 80.19743850847341
    - type: manhattan_f1
      value: 72.42654064560388
    - type: manhattan_precision
      value: 71.70779563806505
    - type: manhattan_recall
      value: 73.15983985217123
    - type: max_accuracy
      value: 86.72138782163232
    - type: max_ap
      value: 80.19743850847341
    - type: max_f1
      value: 72.42654064560388
---
