mteb model-index region:us
---
tags:
- mteb
model-index:
- name: llama3_STSprompt_noPCA_new
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.22388059701493
    - type: ap
      value: 33.15280592815467
    - type: f1
      value: 64.30155266113444
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.195325
    - type: ap
      value: 62.918566799369444
    - type: f1
      value: 66.17251843397702
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 35.746
    - type: f1
      value: 34.42302777807612
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 14.580000000000002
    - type: map_at_10
      value: 23.768
    - type: map_at_100
      value: 24.869
    - type: map_at_1000
      value: 24.948
    - type: map_at_3
      value: 20.78
    - type: map_at_5
      value: 22.512
    - type: mrr_at_1
      value: 14.865
    - type: mrr_at_10
      value: 23.902
    - type: mrr_at_100
      value: 25.002000000000002
    - type: mrr_at_1000
      value: 25.081999999999997
    - type: mrr_at_3
      value: 20.827
    - type: mrr_at_5
      value: 22.634
    - type: ndcg_at_1
      value: 14.580000000000002
    - type: ndcg_at_10
      value: 29.103
    - type: ndcg_at_100
      value: 34.638999999999996
    - type: ndcg_at_1000
      value: 36.934
    - type: ndcg_at_3
      value: 22.923
    - type: ndcg_at_5
      value: 26.051000000000002
    - type: precision_at_1
      value: 14.580000000000002
    - type: precision_at_10
      value: 4.623
    - type: precision_at_100
      value: 0.726
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 9.719999999999999
    - type: precision_at_5
      value: 7.353999999999999
    - type: recall_at_1
      value: 14.580000000000002
    - type: recall_at_10
      value: 46.23
    - type: recall_at_100
      value: 72.617
    - type: recall_at_1000
      value: 91.11
    - type: recall_at_3
      value: 29.160999999999998
    - type: recall_at_5
      value: 36.771
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 29.494677683386687
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 20.537239830601045
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 49.64623075721122
    - type: mrr
      value: 64.14083454249659
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 37.6169823470911
    - type: cos_sim_spearman
      value: 50.74151762568413
    - type: euclidean_pearson
      value: 42.85893524170296
    - type: euclidean_spearman
      value: 50.74151762568413
    - type: manhattan_pearson
      value: 43.010352311091
    - type: manhattan_spearman
      value: 50.91200343802985
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 61.39935064935065
    - type: f1
      value: 59.87369729041336
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 28.980405842872102
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 19.65342041156845
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 18.481
    - type: map_at_10
      value: 25.494
    - type: map_at_100
      value: 26.483
    - type: map_at_1000
      value: 26.628
    - type: map_at_3
      value: 23.375
    - type: map_at_5
      value: 24.718999999999998
    - type: mrr_at_1
      value: 23.462
    - type: mrr_at_10
      value: 30.387999999999998
    - type: mrr_at_100
      value: 31.192999999999998
    - type: mrr_at_1000
      value: 31.275
    - type: mrr_at_3
      value: 28.469
    - type: mrr_at_5
      value: 29.799999999999997
    - type: ndcg_at_1
      value: 23.462
    - type: ndcg_at_10
      value: 29.945
    - type: ndcg_at_100
      value: 34.358
    - type: ndcg_at_1000
      value: 37.515
    - type: ndcg_at_3
      value: 26.918999999999997
    - type: ndcg_at_5
      value: 28.631
    - type: precision_at_1
      value: 23.462
    - type: precision_at_10
      value: 5.765
    - type: precision_at_100
      value: 0.987
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 13.114
    - type: precision_at_5
      value: 9.671000000000001
    - type: recall_at_1
      value: 18.481
    - type: recall_at_10
      value: 37.486999999999995
    - type: recall_at_100
      value: 57.34
    - type: recall_at_1000
      value: 79.196
    - type: recall_at_3
      value: 28.371000000000002
    - type: recall_at_5
      value: 33.379
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.904999999999998
    - type: map_at_10
      value: 24.077
    - type: map_at_100
      value: 24.935
    - type: map_at_1000
      value: 25.043
    - type: map_at_3
      value: 22.065
    - type: map_at_5
      value: 23.29
    - type: mrr_at_1
      value: 22.866
    - type: mrr_at_10
      value: 28.741
    - type: mrr_at_100
      value: 29.482999999999997
    - type: mrr_at_1000
      value: 29.544999999999998
    - type: mrr_at_3
      value: 26.932000000000002
    - type: mrr_at_5
      value: 28.021
    - type: ndcg_at_1
      value: 22.866
    - type: ndcg_at_10
      value: 28.069
    - type: ndcg_at_100
      value: 32.001000000000005
    - type: ndcg_at_1000
      value: 34.526
    - type: ndcg_at_3
      value: 24.945
    - type: ndcg_at_5
      value: 26.588
    - type: precision_at_1
      value: 22.866
    - type: precision_at_10
      value: 5.287
    - type: precision_at_100
      value: 0.885
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 11.975
    - type: precision_at_5
      value: 8.701
    - type: recall_at_1
      value: 17.904999999999998
    - type: recall_at_10
      value: 35.058
    - type: recall_at_100
      value: 52.445
    - type: recall_at_1000
      value: 69.759
    - type: recall_at_3
      value: 26.272000000000002
    - type: recall_at_5
      value: 30.667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 24.52
    - type: map_at_10
      value: 32.322
    - type: map_at_100
      value: 33.237
    - type: map_at_1000
      value: 33.321
    - type: map_at_3
      value: 30.051
    - type: map_at_5
      value: 31.308000000000003
    - type: mrr_at_1
      value: 28.527
    - type: mrr_at_10
      value: 35.577999999999996
    - type: mrr_at_100
      value: 36.406
    - type: mrr_at_1000
      value: 36.462
    - type: mrr_at_3
      value: 33.595000000000006
    - type: mrr_at_5
      value: 34.717
    - type: ndcg_at_1
      value: 28.527
    - type: ndcg_at_10
      value: 36.773
    - type: ndcg_at_100
      value: 41.165
    - type: ndcg_at_1000
      value: 43.311
    - type: ndcg_at_3
      value: 32.584999999999994
    - type: ndcg_at_5
      value: 34.537
    - type: precision_at_1
      value: 28.527
    - type: precision_at_10
      value: 5.8999999999999995
    - type: precision_at_100
      value: 0.877
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 14.504
    - type: precision_at_5
      value: 9.994
    - type: recall_at_1
      value: 24.52
    - type: recall_at_10
      value: 47.237
    - type: recall_at_100
      value: 66.833
    - type: recall_at_1000
      value: 82.791
    - type: recall_at_3
      value: 35.803000000000004
    - type: recall_at_5
      value: 40.624
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 8.305
    - type: map_at_10
      value: 12.179
    - type: map_at_100
      value: 12.8
    - type: map_at_1000
      value: 12.888
    - type: map_at_3
      value: 10.822
    - type: map_at_5
      value: 11.533999999999999
    - type: mrr_at_1
      value: 9.153
    - type: mrr_at_10
      value: 13.062000000000001
    - type: mrr_at_100
      value: 13.718
    - type: mrr_at_1000
      value: 13.802
    - type: mrr_at_3
      value: 11.638
    - type: mrr_at_5
      value: 12.379
    - type: ndcg_at_1
      value: 9.153
    - type: ndcg_at_10
      value: 14.697
    - type: ndcg_at_100
      value: 18.369
    - type: ndcg_at_1000
      value: 21.122
    - type: ndcg_at_3
      value: 11.847000000000001
    - type: ndcg_at_5
      value: 13.11
    - type: precision_at_1
      value: 9.153
    - type: precision_at_10
      value: 2.486
    - type: precision_at_100
      value: 0.461
    - type: precision_at_1000
      value: 0.074
    - type: precision_at_3
      value: 5.122
    - type: precision_at_5
      value: 3.842
    - type: recall_at_1
      value: 8.305
    - type: recall_at_10
      value: 21.786
    - type: recall_at_100
      value: 39.835
    - type: recall_at_1000
      value: 61.517999999999994
    - type: recall_at_3
      value: 13.916999999999998
    - type: recall_at_5
      value: 16.956
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 5.864
    - type: map_at_10
      value: 8.607
    - type: map_at_100
      value: 9.251
    - type: map_at_1000
      value: 9.343
    - type: map_at_3
      value: 7.629
    - type: map_at_5
      value: 8.189
    - type: mrr_at_1
      value: 7.710999999999999
    - type: mrr_at_10
      value: 11.038
    - type: mrr_at_100
      value: 11.766
    - type: mrr_at_1000
      value: 11.841
    - type: mrr_at_3
      value: 9.908999999999999
    - type: mrr_at_5
      value: 10.562000000000001
    - type: ndcg_at_1
      value: 7.710999999999999
    - type: ndcg_at_10
      value: 10.747
    - type: ndcg_at_100
      value: 14.392
    - type: ndcg_at_1000
      value: 17.124
    - type: ndcg_at_3
      value: 8.841000000000001
    - type: ndcg_at_5
      value: 9.767000000000001
    - type: precision_at_1
      value: 7.710999999999999
    - type: precision_at_10
      value: 2.015
    - type: precision_at_100
      value: 0.453
    - type: precision_at_1000
      value: 0.078
    - type: precision_at_3
      value: 4.312
    - type: precision_at_5
      value: 3.234
    - type: recall_at_1
      value: 5.864
    - type: recall_at_10
      value: 15.097
    - type: recall_at_100
      value: 31.738
    - type: recall_at_1000
      value: 52.17
    - type: recall_at_3
      value: 9.799
    - type: recall_at_5
      value: 12.128
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 14.655000000000001
    - type: map_at_10
      value: 19.989
    - type: map_at_100
      value: 21.054000000000002
    - type: map_at_1000
      value: 21.175
    - type: map_at_3
      value: 18.11
    - type: map_at_5
      value: 19.198999999999998
    - type: mrr_at_1
      value: 18.383
    - type: mrr_at_10
      value: 24.104
    - type: mrr_at_100
      value: 25.029
    - type: mrr_at_1000
      value: 25.101000000000003
    - type: mrr_at_3
      value: 21.976000000000003
    - type: mrr_at_5
      value: 23.213
    - type: ndcg_at_1
      value: 18.383
    - type: ndcg_at_10
      value: 23.738999999999997
    - type: ndcg_at_100
      value: 29.076999999999998
    - type: ndcg_at_1000
      value: 31.897
    - type: ndcg_at_3
      value: 20.352999999999998
    - type: ndcg_at_5
      value: 22.006999999999998
    - type: precision_at_1
      value: 18.383
    - type: precision_at_10
      value: 4.475
    - type: precision_at_100
      value: 0.853
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 9.657
    - type: precision_at_5
      value: 7.122000000000001
    - type: recall_at_1
      value: 14.655000000000001
    - type: recall_at_10
      value: 31.079
    - type: recall_at_100
      value: 54.818
    - type: recall_at_1000
      value: 74.658
    - type: recall_at_3
      value: 21.541
    - type: recall_at_5
      value: 25.835
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 10.618
    - type: map_at_10
      value: 14.892
    - type: map_at_100
      value: 15.751000000000001
    - type: map_at_1000
      value: 15.876000000000001
    - type: map_at_3
      value: 13.239
    - type: map_at_5
      value: 14.149000000000001
    - type: mrr_at_1
      value: 13.356000000000002
    - type: mrr_at_10
      value: 17.955
    - type: mrr_at_100
      value: 18.759999999999998
    - type: mrr_at_1000
      value: 18.855
    - type: mrr_at_3
      value: 16.286
    - type: mrr_at_5
      value: 17.319000000000003
    - type: ndcg_at_1
      value: 13.356000000000002
    - type: ndcg_at_10
      value: 18.092
    - type: ndcg_at_100
      value: 22.497
    - type: ndcg_at_1000
      value: 25.897
    - type: ndcg_at_3
      value: 15.045
    - type: ndcg_at_5
      value: 16.483999999999998
    - type: precision_at_1
      value: 13.356000000000002
    - type: precision_at_10
      value: 3.4819999999999998
    - type: precision_at_100
      value: 0.6839999999999999
    - type: precision_at_1000
      value: 0.11399999999999999
    - type: precision_at_3
      value: 7.23
    - type: precision_at_5
      value: 5.457
    - type: recall_at_1
      value: 10.618
    - type: recall_at_10
      value: 24.956999999999997
    - type: recall_at_100
      value: 44.483
    - type: recall_at_1000
      value: 69.353
    - type: recall_at_3
      value: 16.403000000000002
    - type: recall_at_5
      value: 20.044
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 12.472833333333332
    - type: map_at_10
      value: 17.009833333333336
    - type: map_at_100
      value: 17.794999999999998
    - type: map_at_1000
      value: 17.903333333333332
    - type: map_at_3
      value: 15.497916666666667
    - type: map_at_5
      value: 16.348333333333333
    - type: mrr_at_1
      value: 15.232916666666666
    - type: mrr_at_10
      value: 19.870083333333334
    - type: mrr_at_100
      value: 20.612499999999997
    - type: mrr_at_1000
      value: 20.69158333333333
    - type: mrr_at_3
      value: 18.33641666666667
    - type: mrr_at_5
      value: 19.213499999999996
    - type: ndcg_at_1
      value: 15.232916666666666
    - type: ndcg_at_10
      value: 20.074666666666662
    - type: ndcg_at_100
      value: 24.11125
    - type: ndcg_at_1000
      value: 26.968333333333327
    - type: ndcg_at_3
      value: 17.34958333333333
    - type: ndcg_at_5
      value: 18.63458333333334
    - type: precision_at_1
      value: 15.232916666666666
    - type: precision_at_10
      value: 3.610583333333333
    - type: precision_at_100
      value: 0.6667500000000001
    - type: precision_at_1000
      value: 0.10683333333333335
    - type: precision_at_3
      value: 8.048249999999998
    - type: precision_at_5
      value: 5.83975
    - type: recall_at_1
      value: 12.472833333333332
    - type: recall_at_10
      value: 26.479500000000005
    - type: recall_at_100
      value: 45.08208333333334
    - type: recall_at_1000
      value: 66.05941666666666
    - type: recall_at_3
      value: 18.786833333333334
    - type: recall_at_5
      value: 22.133000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 8.856
    - type: map_at_10
      value: 12.47
    - type: map_at_100
      value: 13.083
    - type: map_at_1000
      value: 13.166
    - type: map_at_3
      value: 11.115
    - type: map_at_5
      value: 11.878
    - type: mrr_at_1
      value: 10.428999999999998
    - type: mrr_at_10
      value: 14.341999999999999
    - type: mrr_at_100
      value: 14.918000000000001
    - type: mrr_at_1000
      value: 14.993
    - type: mrr_at_3
      value: 12.883
    - type: mrr_at_5
      value: 13.703999999999999
    - type: ndcg_at_1
      value: 10.428999999999998
    - type: ndcg_at_10
      value: 14.949000000000002
    - type: ndcg_at_100
      value: 18.205
    - type: ndcg_at_1000
      value: 20.666999999999998
    - type: ndcg_at_3
      value: 12.338000000000001
    - type: ndcg_at_5
      value: 13.56
    - type: precision_at_1
      value: 10.428999999999998
    - type: precision_at_10
      value: 2.6839999999999997
    - type: precision_at_100
      value: 0.477
    - type: precision_at_1000
      value: 0.074
    - type: precision_at_3
      value: 5.624
    - type: precision_at_5
      value: 4.172
    - type: recall_at_1
      value: 8.856
    - type: recall_at_10
      value: 20.75
    - type: recall_at_100
      value: 35.923
    - type: recall_at_1000
      value: 54.86600000000001
    - type: recall_at_3
      value: 13.572000000000001
    - type: recall_at_5
      value: 16.63
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 5.951
    - type: map_at_10
      value: 8.909
    - type: map_at_100
      value: 9.443
    - type: map_at_1000
      value: 9.54
    - type: map_at_3
      value: 7.870000000000001
    - type: map_at_5
      value: 8.431
    - type: mrr_at_1
      value: 7.707999999999999
    - type: mrr_at_10
      value: 11.004999999999999
    - type: mrr_at_100
      value: 11.587
    - type: mrr_at_1000
      value: 11.671
    - type: mrr_at_3
      value: 9.859
    - type: mrr_at_5
      value: 10.482
    - type: ndcg_at_1
      value: 7.707999999999999
    - type: ndcg_at_10
      value: 11.091
    - type: ndcg_at_100
      value: 14.145
    - type: ndcg_at_1000
      value: 17.075000000000003
    - type: ndcg_at_3
      value: 9.128
    - type: ndcg_at_5
      value: 9.991
    - type: precision_at_1
      value: 7.707999999999999
    - type: precision_at_10
      value: 2.1510000000000002
    - type: precision_at_100
      value: 0.443
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 4.428
    - type: precision_at_5
      value: 3.2969999999999997
    - type: recall_at_1
      value: 5.951
    - type: recall_at_10
      value: 15.747
    - type: recall_at_100
      value: 30.128
    - type: recall_at_1000
      value: 52.088
    - type: recall_at_3
      value: 10.137
    - type: recall_at_5
      value: 12.431000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.102
    - type: map_at_10
      value: 15.672
    - type: map_at_100
      value: 16.337
    - type: map_at_1000
      value: 16.436
    - type: map_at_3
      value: 14.548
    - type: map_at_5
      value: 15.154
    - type: mrr_at_1
      value: 14.738999999999999
    - type: mrr_at_10
      value: 18.633
    - type: mrr_at_100
      value: 19.317
    - type: mrr_at_1000
      value: 19.409000000000002
    - type: mrr_at_3
      value: 17.382
    - type: mrr_at_5
      value: 18.029999999999998
    - type: ndcg_at_1
      value: 14.738999999999999
    - type: ndcg_at_10
      value: 18.299000000000003
    - type: ndcg_at_100
      value: 22.06
    - type: ndcg_at_1000
      value: 24.898999999999997
    - type: ndcg_at_3
      value: 16.117
    - type: ndcg_at_5
      value: 17.041999999999998
    - type: precision_at_1
      value: 14.738999999999999
    - type: precision_at_10
      value: 2.976
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 7.152
    - type: precision_at_5
      value: 4.963
    - type: recall_at_1
      value: 12.102
    - type: recall_at_10
      value: 23.709
    - type: recall_at_100
      value: 41.448
    - type: recall_at_1000
      value: 62.572
    - type: recall_at_3
      value: 17.352
    - type: recall_at_5
      value: 19.892000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.315
    - type: map_at_10
      value: 18.662
    - type: map_at_100
      value: 19.573999999999998
    - type: map_at_1000
      value: 19.737
    - type: map_at_3
      value: 17.291
    - type: map_at_5
      value: 18.027
    - type: mrr_at_1
      value: 17.589
    - type: mrr_at_10
      value: 21.727
    - type: mrr_at_100
      value: 22.525000000000002
    - type: mrr_at_1000
      value: 22.614
    - type: mrr_at_3
      value: 20.355999999999998
    - type: mrr_at_5
      value: 21.057000000000002
    - type: ndcg_at_1
      value: 17.589
    - type: ndcg_at_10
      value: 21.775
    - type: ndcg_at_100
      value: 26.104
    - type: ndcg_at_1000
      value: 29.637
    - type: ndcg_at_3
      value: 19.448
    - type: ndcg_at_5
      value: 20.435
    - type: precision_at_1
      value: 17.589
    - type: precision_at_10
      value: 4.091
    - type: precision_at_100
      value: 0.881
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 9.025
    - type: precision_at_5
      value: 6.482
    - type: recall_at_1
      value: 14.315
    - type: recall_at_10
      value: 27.305
    - type: recall_at_100
      value: 48.016
    - type: recall_at_1000
      value: 72.404
    - type: recall_at_3
      value: 20.316000000000003
    - type: recall_at_5
      value: 23.048
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.102
    - type: map_at_10
      value: 10.845
    - type: map_at_100
      value: 11.591999999999999
    - type: map_at_1000
      value: 11.687
    - type: map_at_3
      value: 9.86
    - type: map_at_5
      value: 10.302
    - type: mrr_at_1
      value: 8.872
    - type: mrr_at_10
      value: 11.867999999999999
    - type: mrr_at_100
      value: 12.648000000000001
    - type: mrr_at_1000
      value: 12.731
    - type: mrr_at_3
      value: 10.752
    - type: mrr_at_5
      value: 11.278
    - type: ndcg_at_1
      value: 8.872
    - type: ndcg_at_10
      value: 12.72
    - type: ndcg_at_100
      value: 16.962
    - type: ndcg_at_1000
      value: 19.950000000000003
    - type: ndcg_at_3
      value: 10.629
    - type: ndcg_at_5
      value: 11.463
    - type: precision_at_1
      value: 8.872
    - type: precision_at_10
      value: 2.015
    - type: precision_at_100
      value: 0.457
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 4.436
    - type: precision_at_5
      value: 3.1419999999999995
    - type: recall_at_1
      value: 8.102
    - type: recall_at_10
      value: 17.541999999999998
    - type: recall_at_100
      value: 37.978
    - type: recall_at_1000
      value: 61.338
    - type: recall_at_3
      value: 11.959
    - type: recall_at_5
      value: 13.962
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.5489999999999995
    - type: map_at_10
      value: 10.225
    - type: map_at_100
      value: 11.385000000000002
    - type: map_at_1000
      value: 11.544
    - type: map_at_3
      value: 8.364
    - type: map_at_5
      value: 9.225
    - type: mrr_at_1
      value: 12.638
    - type: mrr_at_10
      value: 20.867
    - type: mrr_at_100
      value: 21.768
    - type: mrr_at_1000
      value: 21.841
    - type: mrr_at_3
      value: 18.241
    - type: mrr_at_5
      value: 19.528000000000002
    - type: ndcg_at_1
      value: 12.638
    - type: ndcg_at_10
      value: 15.501999999999999
    - type: ndcg_at_100
      value: 20.892
    - type: ndcg_at_1000
      value: 24.137
    - type: ndcg_at_3
      value: 11.99
    - type: ndcg_at_5
      value: 13.048000000000002
    - type: precision_at_1
      value: 12.638
    - type: precision_at_10
      value: 5.231
    - type: precision_at_100
      value: 1.0999999999999999
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 9.425
    - type: precision_at_5
      value: 7.309
    - type: recall_at_1
      value: 5.5489999999999995
    - type: recall_at_10
      value: 19.945
    - type: recall_at_100
      value: 39.34
    - type: recall_at_1000
      value: 57.811
    - type: recall_at_3
      value: 11.317
    - type: recall_at_5
      value: 14.302000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.527
    - type: map_at_10
      value: 6.274
    - type: map_at_100
      value: 8.793
    - type: map_at_1000
      value: 9.54
    - type: map_at_3
      value: 4.222
    - type: map_at_5
      value: 5.277
    - type: mrr_at_1
      value: 29.5
    - type: mrr_at_10
      value: 39.761
    - type: mrr_at_100
      value: 40.482
    - type: mrr_at_1000
      value: 40.528
    - type: mrr_at_3
      value: 36.542
    - type: mrr_at_5
      value: 38.592
    - type: ndcg_at_1
      value: 20.875
    - type: ndcg_at_10
      value: 16.846
    - type: ndcg_at_100
      value: 19.827
    - type: ndcg_at_1000
      value: 26.445
    - type: ndcg_at_3
      value: 17.956
    - type: ndcg_at_5
      value: 17.694
    - type: precision_at_1
      value: 29.5
    - type: precision_at_10
      value: 15.325
    - type: precision_at_100
      value: 5.06
    - type: precision_at_1000
      value: 1.1360000000000001
    - type: precision_at_3
      value: 22.167
    - type: precision_at_5
      value: 20.05
    - type: recall_at_1
      value: 2.527
    - type: recall_at_10
      value: 10.761999999999999
    - type: recall_at_100
      value: 26.184
    - type: recall_at_1000
      value: 49.284
    - type: recall_at_3
      value: 5.329
    - type: recall_at_5
      value: 7.936999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 38.519999999999996
    - type: f1
      value: 34.756439478470746
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.831
    - type: map_at_10
      value: 21.414
    - type: map_at_100
      value: 22.274
    - type: map_at_1000
      value: 22.359
    - type: map_at_3
      value: 19.275000000000002
    - type: map_at_5
      value: 20.402
    - type: mrr_at_1
      value: 15.781999999999998
    - type: mrr_at_10
      value: 22.639
    - type: mrr_at_100
      value: 23.522000000000002
    - type: mrr_at_1000
      value: 23.599999999999998
    - type: mrr_at_3
      value: 20.43
    - type: mrr_at_5
      value: 21.597
    - type: ndcg_at_1
      value: 15.781999999999998
    - type: ndcg_at_10
      value: 25.482
    - type: ndcg_at_100
      value: 30.089
    - type: ndcg_at_1000
      value: 32.511
    - type: ndcg_at_3
      value: 21.026
    - type: ndcg_at_5
      value: 23.042
    - type: precision_at_1
      value: 15.781999999999998
    - type: precision_at_10
      value: 4.0169999999999995
    - type: precision_at_100
      value: 0.653
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 8.921
    - type: precision_at_5
      value: 6.421
    - type: recall_at_1
      value: 14.831
    - type: recall_at_10
      value: 37.169999999999995
    - type: recall_at_100
      value: 59.079
    - type: recall_at_1000
      value: 77.89
    - type: recall_at_3
      value: 24.927
    - type: recall_at_5
      value: 29.759999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.762
    - type: map_at_10
      value: 9.483
    - type: map_at_100
      value: 10.302
    - type: map_at_1000
      value: 10.466000000000001
    - type: map_at_3
      value: 8.168000000000001
    - type: map_at_5
      value: 8.777
    - type: mrr_at_1
      value: 11.111
    - type: mrr_at_10
      value: 16.742
    - type: mrr_at_100
      value: 17.627000000000002
    - type: mrr_at_1000
      value: 17.727
    - type: mrr_at_3
      value: 15.251999999999999
    - type: mrr_at_5
      value: 16.024
    - type: ndcg_at_1
      value: 11.111
    - type: ndcg_at_10
      value: 13.157
    - type: ndcg_at_100
      value: 17.679000000000002
    - type: ndcg_at_1000
      value: 21.802
    - type: ndcg_at_3
      value: 11.185
    - type: ndcg_at_5
      value: 11.777
    - type: precision_at_1
      value: 11.111
    - type: precision_at_10
      value: 3.7190000000000003
    - type: precision_at_100
      value: 0.843
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 7.562
    - type: precision_at_5
      value: 5.494000000000001
    - type: recall_at_1
      value: 5.762
    - type: recall_at_10
      value: 16.824
    - type: recall_at_100
      value: 34.918
    - type: recall_at_1000
      value: 61.316
    - type: recall_at_3
      value: 10.731
    - type: recall_at_5
      value: 13.047
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 14.288
    - type: map_at_10
      value: 19.54
    - type: map_at_100
      value: 20.230999999999998
    - type: map_at_1000
      value: 20.315
    - type: map_at_3
      value: 18.106
    - type: map_at_5
      value: 18.883
    - type: mrr_at_1
      value: 28.589
    - type: mrr_at_10
      value: 34.375
    - type: mrr_at_100
      value: 35.006
    - type: mrr_at_1000
      value: 35.064
    - type: mrr_at_3
      value: 32.793
    - type: mrr_at_5
      value: 33.648
    - type: ndcg_at_1
      value: 28.575
    - type: ndcg_at_10
      value: 25.182
    - type: ndcg_at_100
      value: 28.483999999999998
    - type: ndcg_at_1000
      value: 30.646
    - type: ndcg_at_3
      value: 22.342000000000002
    - type: ndcg_at_5
      value: 23.669
    - type: precision_at_1
      value: 28.575
    - type: precision_at_10
      value: 5.491
    - type: precision_at_100
      value: 0.8130000000000001
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 14.018
    - type: precision_at_5
      value: 9.458
    - type: recall_at_1
      value: 14.288
    - type: recall_at_10
      value: 27.454
    - type: recall_at_100
      value: 40.628
    - type: recall_at_1000
      value: 55.098
    - type: recall_at_3
      value: 21.026
    - type: recall_at_5
      value: 23.646
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.6432
    - type: ap
      value: 59.8892267461648
    - type: f1
      value: 64.099708033942
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.122
    - type: map_at_10
      value: 8.932
    - type: map_at_100
      value: 9.774
    - type: map_at_1000
      value: 9.873
    - type: map_at_3
      value: 7.388999999999999
    - type: map_at_5
      value: 8.173
    - type: mrr_at_1
      value: 5.287
    - type: mrr_at_10
      value: 9.188
    - type: mrr_at_100
      value: 10.038
    - type: mrr_at_1000
      value: 10.135
    - type: mrr_at_3
      value: 7.61
    - type: mrr_at_5
      value: 8.422
    - type: ndcg_at_1
      value: 5.287
    - type: ndcg_at_10
      value: 11.487
    - type: ndcg_at_100
      value: 16.175
    - type: ndcg_at_1000
      value: 19.177
    - type: ndcg_at_3
      value: 8.214
    - type: ndcg_at_5
      value: 9.644
    - type: precision_at_1
      value: 5.287
    - type: precision_at_10
      value: 2.026
    - type: precision_at_100
      value: 0.447
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 3.5770000000000004
    - type: precision_at_5
      value: 2.871
    - type: recall_at_1
      value: 5.122
    - type: recall_at_10
      value: 19.503
    - type: recall_at_100
      value: 42.561
    - type: recall_at_1000
      value: 66.654
    - type: recall_at_3
      value: 10.394
    - type: recall_at_5
      value: 13.844000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.67669858641132
    - type: f1
      value: 86.84850678526456
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 48.59325125398997
    - type: f1
      value: 34.2362361780031
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 55.82380632145261
    - type: f1
      value: 52.24960851587166
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.2104909213181
    - type: f1
      value: 64.36855821264822
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 25.623942924515813
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 22.428987103227033
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 27.00863745669677
    - type: mrr
      value: 27.355047242237458
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.5089999999999995
    - type: map_at_10
      value: 7.672
    - type: map_at_100
      value: 9.436
    - type: map_at_1000
      value: 10.607
    - type: map_at_3
      value: 6.177
    - type: map_at_5
      value: 6.918
    - type: mrr_at_1
      value: 31.889
    - type: mrr_at_10
      value: 42.291000000000004
    - type: mrr_at_100
      value: 43.017
    - type: mrr_at_1000
      value: 43.08
    - type: mrr_at_3
      value: 39.628
    - type: mrr_at_5
      value: 41.223
    - type: ndcg_at_1
      value: 30.186
    - type: ndcg_at_10
      value: 22.867
    - type: ndcg_at_100
      value: 22.124
    - type: ndcg_at_1000
      value: 31.602000000000004
    - type: ndcg_at_3
      value: 26.106
    - type: ndcg_at_5
      value: 24.534
    - type: precision_at_1
      value: 31.889
    - type: precision_at_10
      value: 16.099
    - type: precision_at_100
      value: 5.864
    - type: precision_at_1000
      value: 1.8769999999999998
    - type: precision_at_3
      value: 23.529
    - type: precision_at_5
      value: 19.814
    - type: recall_at_1
      value: 4.5089999999999995
    - type: recall_at_10
      value: 11.227
    - type: recall_at_100
      value: 24.526999999999997
    - type: recall_at_1000
      value: 57.764
    - type: recall_at_3
      value: 6.993
    - type: recall_at_5
      value: 8.973
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.345
    - type: map_at_10
      value: 15.14
    - type: map_at_100
      value: 16.115
    - type: map_at_1000
      value: 16.204
    - type: map_at_3
      value: 12.903
    - type: map_at_5
      value: 14.05
    - type: mrr_at_1
      value: 10.603
    - type: mrr_at_10
      value: 16.669
    - type: mrr_at_100
      value: 17.602
    - type: mrr_at_1000
      value: 17.678
    - type: mrr_at_3
      value: 14.368
    - type: mrr_at_5
      value: 15.568000000000001
    - type: ndcg_at_1
      value: 10.603
    - type: ndcg_at_10
      value: 19.039
    - type: ndcg_at_100
      value: 24.05
    - type: ndcg_at_1000
      value: 26.454
    - type: ndcg_at_3
      value: 14.396999999999998
    - type: ndcg_at_5
      value: 16.459
    - type: precision_at_1
      value: 10.603
    - type: precision_at_10
      value: 3.485
    - type: precision_at_100
      value: 0.635
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 6.6339999999999995
    - type: precision_at_5
      value: 5.11
    - type: recall_at_1
      value: 9.345
    - type: recall_at_10
      value: 29.703000000000003
    - type: recall_at_100
      value: 52.961999999999996
    - type: recall_at_1000
      value: 71.34
    - type: recall_at_3
      value: 17.294
    - type: recall_at_5
      value: 22.131999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.341
    - type: map_at_10
      value: 69.675
    - type: map_at_100
      value: 70.392
    - type: map_at_1000
      value: 70.42699999999999
    - type: map_at_3
      value: 67.092
    - type: map_at_5
      value: 68.638
    - type: mrr_at_1
      value: 67.29
    - type: mrr_at_10
      value: 74.378
    - type: mrr_at_100
      value: 74.677
    - type: mrr_at_1000
      value: 74.688
    - type: mrr_at_3
      value: 73.01299999999999
    - type: mrr_at_5
      value: 73.85300000000001
    - type: ndcg_at_1
      value: 67.32000000000001
    - type: ndcg_at_10
      value: 74.23100000000001
    - type: ndcg_at_100
      value: 76.481
    - type: ndcg_at_1000
      value: 77.067
    - type: ndcg_at_3
      value: 71.007
    - type: ndcg_at_5
      value: 72.595
    - type: precision_at_1
      value: 67.32000000000001
    - type: precision_at_10
      value: 11.086
    - type: precision_at_100
      value: 1.332
    - type: precision_at_1000
      value: 0.14400000000000002
    - type: precision_at_3
      value: 30.623
    - type: precision_at_5
      value: 20.136000000000003
    - type: recall_at_1
      value: 58.341
    - type: recall_at_10
      value: 82.712
    - type: recall_at_100
      value: 91.658
    - type: recall_at_1000
      value: 95.381
    - type: recall_at_3
      value: 73.21
    - type: recall_at_5
      value: 77.757
    - type: map_at_1
      value: 2.27
    - type: map_at_10
      value: 5.769
    - type: map_at_100
      value: 6.877999999999999
    - type: map_at_1000
      value: 7.087000000000001
    - type: map_at_3
      value: 4.218
    - type: map_at_5
      value: 4.97
    - type: mrr_at_1
      value: 11.200000000000001
    - type: mrr_at_10
      value: 19.136
    - type: mrr_at_100
      value: 20.259
    - type: mrr_at_1000
      value: 20.362
    - type: mrr_at_3
      value: 16.5
    - type: mrr_at_5
      value: 18.125
    - type: ndcg_at_1
      value: 11.200000000000001
    - type: ndcg_at_10
      value: 10.620000000000001
    - type: ndcg_at_100
      value: 15.97
    - type: ndcg_at_1000
      value: 20.663999999999998
    - type: ndcg_at_3
      value: 9.907
    - type: ndcg_at_5
      value: 8.746
    - type: precision_at_1
      value: 11.200000000000001
    - type: precision_at_10
      value: 5.62
    - type: precision_at_100
      value: 1.343
    - type: precision_at_1000
      value: 0.248
    - type: precision_at_3
      value: 9.433
    - type: precision_at_5
      value: 7.84
    - type: recall_at_1
      value: 2.27
    - type: recall_at_10
      value: 11.425
    - type: recall_at_100
      value: 27.287
    - type: recall_at_1000
      value: 50.428
    - type: recall_at_3
      value: 5.7250000000000005
    - type: recall_at_5
      value: 7.945
    - type: map_at_1
      value: 0.16999999999999998
    - type: map_at_10
      value: 1.1280000000000001
    - type: map_at_100
      value: 5.016
    - type: map_at_1000
      value: 11.338
    - type: map_at_3
      value: 0.432
    - type: map_at_5
      value: 0.6479999999999999
    - type: mrr_at_1
      value: 70.0
    - type: mrr_at_10
      value: 78.319
    - type: mrr_at_100
      value: 78.52
    - type: mrr_at_1000
      value: 78.52
    - type: mrr_at_3
      value: 77.0
    - type: mrr_at_5
      value: 77.5
    - type: ndcg_at_1
      value: 65.0
    - type: ndcg_at_10
      value: 54.847
    - type: ndcg_at_100
      value: 36.88
    - type: ndcg_at_1000
      value: 30.770999999999997
    - type: ndcg_at_3
      value: 60.162000000000006
    - type: ndcg_at_5
      value: 58.629
    - type: precision_at_1
      value: 70.0
    - type: precision_at_10
      value: 59.4
    - type: precision_at_100
      value: 38.080000000000005
    - type: precision_at_1000
      value: 14.533999999999999
    - type: precision_at_3
      value: 63.333
    - type: precision_at_5
      value: 63.2
    - type: recall_at_1
      value: 0.16999999999999998
    - type: recall_at_10
      value: 1.39
    - type: recall_at_100
      value: 8.053
    - type: recall_at_1000
      value: 29.154999999999998
    - type: recall_at_3
      value: 0.468
    - type: recall_at_5
      value: 0.735
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 24.63161493660249
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 36.40184260295017
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 70.03175710063232
    - type: cos_sim_spearman
      value: 61.52765747564237
    - type: euclidean_pearson
      value: 67.46569139533412
    - type: euclidean_spearman
      value: 61.52769788330812
    - type: manhattan_pearson
      value: 67.48506956368522
    - type: manhattan_spearman
      value: 61.53988743724379
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 59.96512611891871
    - type: cos_sim_spearman
      value: 60.190775841740404
    - type: euclidean_pearson
      value: 63.81983299921028
    - type: euclidean_spearman
      value: 60.192120842165195
    - type: manhattan_pearson
      value: 64.09272092040531
    - type: manhattan_spearman
      value: 60.41619118181485
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 50.90910815277711
    - type: cos_sim_spearman
      value: 54.40201788920689
    - type: euclidean_pearson
      value: 55.17123526569839
    - type: euclidean_spearman
      value: 54.402055890513104
    - type: manhattan_pearson
      value: 55.042791447635395
    - type: manhattan_spearman
      value: 54.32155877962158
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 53.44497097947539
    - type: cos_sim_spearman
      value: 58.07199334661257
    - type: euclidean_pearson
      value: 56.9869825577771
    - type: euclidean_spearman
      value: 58.07198367526384
    - type: manhattan_pearson
      value: 56.92875462947201
    - type: manhattan_spearman
      value: 58.023905268548106
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 54.74302028582996
    - type: cos_sim_spearman
      value: 63.26482649498452
    - type: euclidean_pearson
      value: 61.60335106539482
    - type: euclidean_spearman
      value: 63.264823319214244
    - type: manhattan_pearson
      value: 61.474580453771125
    - type: manhattan_spearman
      value: 63.13879158312673
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 41.511796087191456
    - type: cos_sim_spearman
      value: 53.4050428298679
    - type: euclidean_pearson
      value: 50.878533021587366
    - type: euclidean_spearman
      value: 53.40559531209078
    - type: manhattan_pearson
      value: 50.89050381405268
    - type: manhattan_spearman
      value: 53.472976973356324
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 51.939695238146065
    - type: cos_sim_spearman
      value: 63.42974644375647
    - type: euclidean_pearson
      value: 61.79883335166281
    - type: euclidean_spearman
      value: 63.43063245951309
    - type: manhattan_pearson
      value: 61.86138676420604
    - type: manhattan_spearman
      value: 63.62817388503853
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 28.369126325904677
    - type: cos_sim_spearman
      value: 50.74283616778858
    - type: euclidean_pearson
      value: 40.19775205927606
    - type: euclidean_spearman
      value: 50.74283616778858
    - type: manhattan_pearson
      value: 40.174729898784605
    - type: manhattan_spearman
      value: 50.78930784202322
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 54.634624869142954
    - type: cos_sim_spearman
      value: 56.846676048599754
    - type: euclidean_pearson
      value: 57.97668466036474
    - type: euclidean_spearman
      value: 56.846694538362044
    - type: manhattan_pearson
      value: 57.967753152499476
    - type: manhattan_spearman
      value: 56.80745274984118
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 58.35497783651584
    - type: mrr
      value: 83.44287430071743
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 29.610999999999997
    - type: map_at_10
      value: 37.937
    - type: map_at_100
      value: 38.911
    - type: map_at_1000
      value: 38.983000000000004
    - type: map_at_3
      value: 35.324
    - type: map_at_5
      value: 36.657000000000004
    - type: mrr_at_1
      value: 31.0
    - type: mrr_at_10
      value: 39.415
    - type: mrr_at_100
      value: 40.255
    - type: mrr_at_1000
      value: 40.309
    - type: mrr_at_3
      value: 36.944
    - type: mrr_at_5
      value: 38.194
    - type: ndcg_at_1
      value: 31.0
    - type: ndcg_at_10
      value: 42.989
    - type: ndcg_at_100
      value: 47.88
    - type: ndcg_at_1000
      value: 49.797999999999995
    - type: ndcg_at_3
      value: 37.638
    - type: ndcg_at_5
      value: 39.96
    - type: precision_at_1
      value: 31.0
    - type: precision_at_10
      value: 6.267
    - type: precision_at_100
      value: 0.903
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 15.222
    - type: precision_at_5
      value: 10.4
    - type: recall_at_1
      value: 29.610999999999997
    - type: recall_at_10
      value: 57.416999999999994
    - type: recall_at_100
      value: 80.472
    - type: recall_at_1000
      value: 95.517
    - type: recall_at_3
      value: 42.667
    - type: recall_at_5
      value: 48.388999999999996
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.27128712871287
    - type: cos_sim_ap
      value: 52.46495032507127
    - type: cos_sim_f1
      value: 53.895410885805774
    - type: cos_sim_precision
      value: 57.78032036613272
    - type: cos_sim_recall
      value: 50.5
    - type: dot_accuracy
      value: 99.27128712871287
    - type: dot_ap
      value: 52.46495032507127
    - type: dot_f1
      value: 53.895410885805774
    - type: dot_precision
      value: 57.78032036613272
    - type: dot_recall
      value: 50.5
    - type: euclidean_accuracy
      value: 99.27128712871287
    - type: euclidean_ap
      value: 52.46495032507127
    - type: euclidean_f1
      value: 53.895410885805774
    - type: euclidean_precision
      value: 57.78032036613272
    - type: euclidean_recall
      value: 50.5
    - type: manhattan_accuracy
      value: 99.27227722772277
    - type: manhattan_ap
      value: 52.801209747879376
    - type: manhattan_f1
      value: 53.80053908355795
    - type: manhattan_precision
      value: 58.36257309941521
    - type: manhattan_recall
      value: 49.9
    - type: max_accuracy
      value: 99.27227722772277
    - type: max_ap
      value: 52.801209747879376
    - type: max_f1
      value: 53.895410885805774
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 34.968177094227855
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 26.1149146180284
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 39.83297002642528
    - type: mrr
      value: 40.044046027501906
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.935051707944027
    - type: cos_sim_spearman
      value: 30.26700625495751
    - type: dot_pearson
      value: 29.935051705877093
    - type: dot_spearman
      value: 30.221993011054217
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.8319999999999999
    - type: map_at_10
      value: 4.5920000000000005
    - type: map_at_100
      value: 8.299
    - type: map_at_1000
      value: 9.689
    - type: map_at_3
      value: 2.621
    - type: map_at_5
      value: 3.727
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 34.016000000000005
    - type: mrr_at_100
      value: 35.798
    - type: mrr_at_1000
      value: 35.827999999999996
    - type: mrr_at_3
      value: 30.612000000000002
    - type: mrr_at_5
      value: 32.755
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 13.833
    - type: ndcg_at_100
      value: 25.037
    - type: ndcg_at_1000
      value: 37.330000000000005
    - type: ndcg_at_3
      value: 16.064999999999998
    - type: ndcg_at_5
      value: 15.878999999999998
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 12.653
    - type: precision_at_100
      value: 5.9799999999999995
    - type: precision_at_1000
      value: 1.376
    - type: precision_at_3
      value: 15.645999999999999
    - type: precision_at_5
      value: 16.326999999999998
    - type: recall_at_1
      value: 1.8319999999999999
    - type: recall_at_10
      value: 8.932
    - type: recall_at_100
      value: 37.151
    - type: recall_at_1000
      value: 75.446
    - type: recall_at_3
      value: 3.292
    - type: recall_at_5
      value: 5.938000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 72.10000000000001
    - type: ap
      value: 14.115196181547034
    - type: f1
      value: 54.93552377149315
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 56.33559705715903
    - type: f1
      value: 56.339239183143484
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 24.677900542724814
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 80.78917565714967
    - type: cos_sim_ap
      value: 54.826509003050006
    - type: cos_sim_f1
      value: 52.78737049827331
    - type: cos_sim_precision
      value: 49.55998147290413
    - type: cos_sim_recall
      value: 56.464379947229546
    - type: dot_accuracy
      value: 80.78917565714967
    - type: dot_ap
      value: 54.826509003050006
    - type: dot_f1
      value: 52.78737049827331
    - type: dot_precision
      value: 49.55998147290413
    - type: dot_recall
      value: 56.464379947229546
    - type: euclidean_accuracy
      value: 80.78917565714967
    - type: euclidean_ap
      value: 54.826509003050006
    - type: euclidean_f1
      value: 52.78737049827331
    - type: euclidean_precision
      value: 49.55998147290413
    - type: euclidean_recall
      value: 56.464379947229546
    - type: manhattan_accuracy
      value: 80.80109673958395
    - type: manhattan_ap
      value: 54.66844954191278
    - type: manhattan_f1
      value: 52.620396600566586
    - type: manhattan_precision
      value: 47.60785988893635
    - type: manhattan_recall
      value: 58.812664907651715
    - type: max_accuracy
      value: 80.80109673958395
    - type: max_ap
      value: 54.826509003050006
    - type: max_f1
      value: 52.78737049827331
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 83.59141537625645
    - type: cos_sim_ap
      value: 71.5726566487385
    - type: cos_sim_f1
      value: 63.98524281188595
    - type: cos_sim_precision
      value: 66.76709348062599
    - type: cos_sim_recall
      value: 61.425931629196185
    - type: dot_accuracy
      value: 83.59141537625645
    - type: dot_ap
      value: 71.57265636287138
    - type: dot_f1
      value: 63.98524281188595
    - type: dot_precision
      value: 66.76709348062599
    - type: dot_recall
      value: 61.425931629196185
    - type: euclidean_accuracy
      value: 83.59141537625645
    - type: euclidean_ap
      value: 71.57265651040298
    - type: euclidean_f1
      value: 63.98524281188595
    - type: euclidean_precision
      value: 66.76709348062599
    - type: euclidean_recall
      value: 61.425931629196185
    - type: manhattan_accuracy
      value: 83.57977257732759
    - type: manhattan_ap
      value: 71.47338269623076
    - type: manhattan_f1
      value: 63.99874573746717
    - type: manhattan_precision
      value: 65.18163672654691
    - type: manhattan_recall
      value: 62.858022790267945
    - type: max_accuracy
      value: 83.59141537625645
    - type: max_ap
      value: 71.5726566487385
    - type: max_f1
      value: 63.99874573746717
---
