mteb model-index region:us
---
tags:
- mteb
model-index:
- name: model2vec_result_fixed
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.7910447761194
    - type: ap
      value: 33.038020188116036
    - type: f1
      value: 65.03799728338926
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 72.47644999999999
    - type: ap
      value: 66.91002822830875
    - type: f1
      value: 72.2600863044581
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 36.012
    - type: f1
      value: 35.38209336470206
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.124000000000002
    - type: map_at_10
      value: 34.329
    - type: map_at_100
      value: 35.612
    - type: map_at_1000
      value: 35.647
    - type: map_at_3
      value: 30.263
    - type: map_at_5
      value: 32.358
    - type: mrr_at_1
      value: 21.764
    - type: mrr_at_10
      value: 34.558
    - type: mrr_at_100
      value: 35.848
    - type: mrr_at_1000
      value: 35.882999999999996
    - type: mrr_at_3
      value: 30.441000000000003
    - type: mrr_at_5
      value: 32.621
    - type: ndcg_at_1
      value: 21.124000000000002
    - type: ndcg_at_10
      value: 41.961
    - type: ndcg_at_100
      value: 47.746
    - type: ndcg_at_1000
      value: 48.63
    - type: ndcg_at_3
      value: 33.469
    - type: ndcg_at_5
      value: 37.261
    - type: precision_at_1
      value: 21.124000000000002
    - type: precision_at_10
      value: 6.643000000000001
    - type: precision_at_100
      value: 0.9249999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.272000000000002
    - type: precision_at_5
      value: 10.413
    - type: recall_at_1
      value: 21.124000000000002
    - type: recall_at_10
      value: 66.43
    - type: recall_at_100
      value: 92.461
    - type: recall_at_1000
      value: 99.289
    - type: recall_at_3
      value: 42.817
    - type: recall_at_5
      value: 52.063
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.422522812555265
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 25.271555965391595
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.11180788298141
    - type: mrr
      value: 68.73587477465594
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 79.11612347924923
    - type: cos_sim_spearman
      value: 75.85775256673794
    - type: euclidean_pearson
      value: 77.46080567383865
    - type: euclidean_spearman
      value: 75.85775256673794
    - type: manhattan_pearson
      value: 77.7319143671074
    - type: manhattan_spearman
      value: 75.98908086034702
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.63636363636363
    - type: f1
      value: 71.69751597573539
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 30.861094091770546
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 20.222365644637257
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 19.939
    - type: map_at_10
      value: 26.924
    - type: map_at_100
      value: 28.16
    - type: map_at_1000
      value: 28.316999999999997
    - type: map_at_3
      value: 24.45
    - type: map_at_5
      value: 25.751
    - type: mrr_at_1
      value: 25.894000000000002
    - type: mrr_at_10
      value: 32.652
    - type: mrr_at_100
      value: 33.584
    - type: mrr_at_1000
      value: 33.664
    - type: mrr_at_3
      value: 30.520000000000003
    - type: mrr_at_5
      value: 31.671
    - type: ndcg_at_1
      value: 25.894000000000002
    - type: ndcg_at_10
      value: 31.835
    - type: ndcg_at_100
      value: 37.325
    - type: ndcg_at_1000
      value: 40.586
    - type: ndcg_at_3
      value: 28.143
    - type: ndcg_at_5
      value: 29.648999999999997
    - type: precision_at_1
      value: 25.894000000000002
    - type: precision_at_10
      value: 6.194999999999999
    - type: precision_at_100
      value: 1.126
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 13.543
    - type: precision_at_5
      value: 9.757
    - type: recall_at_1
      value: 19.939
    - type: recall_at_10
      value: 40.537
    - type: recall_at_100
      value: 64.717
    - type: recall_at_1000
      value: 87.01299999999999
    - type: recall_at_3
      value: 29.301
    - type: recall_at_5
      value: 33.918
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.601
    - type: map_at_10
      value: 22.07
    - type: map_at_100
      value: 22.958000000000002
    - type: map_at_1000
      value: 23.074
    - type: map_at_3
      value: 20.137
    - type: map_at_5
      value: 21.315
    - type: mrr_at_1
      value: 20.382
    - type: mrr_at_10
      value: 25.954
    - type: mrr_at_100
      value: 26.723000000000003
    - type: mrr_at_1000
      value: 26.791999999999998
    - type: mrr_at_3
      value: 24.098
    - type: mrr_at_5
      value: 25.27
    - type: ndcg_at_1
      value: 20.382
    - type: ndcg_at_10
      value: 25.734
    - type: ndcg_at_100
      value: 29.952
    - type: ndcg_at_1000
      value: 32.618
    - type: ndcg_at_3
      value: 22.445999999999998
    - type: ndcg_at_5
      value: 24.162
    - type: precision_at_1
      value: 20.382
    - type: precision_at_10
      value: 4.662
    - type: precision_at_100
      value: 0.8580000000000001
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 10.446
    - type: precision_at_5
      value: 7.682
    - type: recall_at_1
      value: 16.601
    - type: recall_at_10
      value: 32.882
    - type: recall_at_100
      value: 51.273
    - type: recall_at_1000
      value: 69.33200000000001
    - type: recall_at_3
      value: 23.54
    - type: recall_at_5
      value: 28.054000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.386999999999997
    - type: map_at_10
      value: 34.183
    - type: map_at_100
      value: 35.198
    - type: map_at_1000
      value: 35.292
    - type: map_at_3
      value: 31.466
    - type: map_at_5
      value: 33.037
    - type: mrr_at_1
      value: 29.404000000000003
    - type: mrr_at_10
      value: 37.519000000000005
    - type: mrr_at_100
      value: 38.305
    - type: mrr_at_1000
      value: 38.365
    - type: mrr_at_3
      value: 35.152
    - type: mrr_at_5
      value: 36.531000000000006
    - type: ndcg_at_1
      value: 29.404000000000003
    - type: ndcg_at_10
      value: 39.235
    - type: ndcg_at_100
      value: 44.072
    - type: ndcg_at_1000
      value: 46.272999999999996
    - type: ndcg_at_3
      value: 34.292
    - type: ndcg_at_5
      value: 36.735
    - type: precision_at_1
      value: 29.404000000000003
    - type: precision_at_10
      value: 6.539000000000001
    - type: precision_at_100
      value: 0.984
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 15.423
    - type: precision_at_5
      value: 10.984
    - type: recall_at_1
      value: 25.386999999999997
    - type: recall_at_10
      value: 51.256
    - type: recall_at_100
      value: 73.53699999999999
    - type: recall_at_1000
      value: 89.522
    - type: recall_at_3
      value: 37.830999999999996
    - type: recall_at_5
      value: 43.811
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 10.832
    - type: map_at_10
      value: 16.154
    - type: map_at_100
      value: 16.863
    - type: map_at_1000
      value: 16.979
    - type: map_at_3
      value: 14.654
    - type: map_at_5
      value: 15.634
    - type: mrr_at_1
      value: 11.751000000000001
    - type: mrr_at_10
      value: 17.286
    - type: mrr_at_100
      value: 18.019
    - type: mrr_at_1000
      value: 18.122
    - type: mrr_at_3
      value: 15.706000000000001
    - type: mrr_at_5
      value: 16.774
    - type: ndcg_at_1
      value: 11.751000000000001
    - type: ndcg_at_10
      value: 19.197
    - type: ndcg_at_100
      value: 23.159
    - type: ndcg_at_1000
      value: 26.453
    - type: ndcg_at_3
      value: 16.186
    - type: ndcg_at_5
      value: 17.936
    - type: precision_at_1
      value: 11.751000000000001
    - type: precision_at_10
      value: 3.1189999999999998
    - type: precision_at_100
      value: 0.54
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 7.194000000000001
    - type: precision_at_5
      value: 5.311
    - type: recall_at_1
      value: 10.832
    - type: recall_at_10
      value: 27.472
    - type: recall_at_100
      value: 46.471000000000004
    - type: recall_at_1000
      value: 71.91199999999999
    - type: recall_at_3
      value: 19.417
    - type: recall_at_5
      value: 23.577
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.019
    - type: map_at_10
      value: 9.584
    - type: map_at_100
      value: 10.433
    - type: map_at_1000
      value: 10.562000000000001
    - type: map_at_3
      value: 8.351
    - type: map_at_5
      value: 9.005
    - type: mrr_at_1
      value: 7.2139999999999995
    - type: mrr_at_10
      value: 11.62
    - type: mrr_at_100
      value: 12.469
    - type: mrr_at_1000
      value: 12.577
    - type: mrr_at_3
      value: 10.158000000000001
    - type: mrr_at_5
      value: 10.898
    - type: ndcg_at_1
      value: 7.2139999999999995
    - type: ndcg_at_10
      value: 12.145
    - type: ndcg_at_100
      value: 16.672
    - type: ndcg_at_1000
      value: 20.342
    - type: ndcg_at_3
      value: 9.607000000000001
    - type: ndcg_at_5
      value: 10.712000000000002
    - type: precision_at_1
      value: 7.2139999999999995
    - type: precision_at_10
      value: 2.338
    - type: precision_at_100
      value: 0.5459999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 4.726
    - type: precision_at_5
      value: 3.5319999999999996
    - type: recall_at_1
      value: 6.019
    - type: recall_at_10
      value: 18.102999999999998
    - type: recall_at_100
      value: 38.482
    - type: recall_at_1000
      value: 65.436
    - type: recall_at_3
      value: 11.178
    - type: recall_at_5
      value: 13.877
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 16.822
    - type: map_at_10
      value: 22.476
    - type: map_at_100
      value: 23.69
    - type: map_at_1000
      value: 23.827
    - type: map_at_3
      value: 20.441000000000003
    - type: map_at_5
      value: 21.512
    - type: mrr_at_1
      value: 20.788999999999998
    - type: mrr_at_10
      value: 26.674
    - type: mrr_at_100
      value: 27.675
    - type: mrr_at_1000
      value: 27.753
    - type: mrr_at_3
      value: 24.495
    - type: mrr_at_5
      value: 25.629999999999995
    - type: ndcg_at_1
      value: 20.788999999999998
    - type: ndcg_at_10
      value: 26.667999999999996
    - type: ndcg_at_100
      value: 32.565
    - type: ndcg_at_1000
      value: 35.634
    - type: ndcg_at_3
      value: 22.942
    - type: ndcg_at_5
      value: 24.514
    - type: precision_at_1
      value: 20.788999999999998
    - type: precision_at_10
      value: 4.947
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 10.748000000000001
    - type: precision_at_5
      value: 7.68
    - type: recall_at_1
      value: 16.822
    - type: recall_at_10
      value: 35.237
    - type: recall_at_100
      value: 61.219
    - type: recall_at_1000
      value: 82.499
    - type: recall_at_3
      value: 24.524
    - type: recall_at_5
      value: 28.787000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.416
    - type: map_at_10
      value: 17.684
    - type: map_at_100
      value: 18.851000000000003
    - type: map_at_1000
      value: 18.991
    - type: map_at_3
      value: 15.770999999999999
    - type: map_at_5
      value: 16.606
    - type: mrr_at_1
      value: 15.068000000000001
    - type: mrr_at_10
      value: 21.288
    - type: mrr_at_100
      value: 22.306
    - type: mrr_at_1000
      value: 22.396
    - type: mrr_at_3
      value: 19.273
    - type: mrr_at_5
      value: 20.398
    - type: ndcg_at_1
      value: 15.068000000000001
    - type: ndcg_at_10
      value: 21.66
    - type: ndcg_at_100
      value: 27.245
    - type: ndcg_at_1000
      value: 30.591
    - type: ndcg_at_3
      value: 17.968999999999998
    - type: ndcg_at_5
      value: 19.352
    - type: precision_at_1
      value: 15.068000000000001
    - type: precision_at_10
      value: 4.326
    - type: precision_at_100
      value: 0.855
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 8.713999999999999
    - type: precision_at_5
      value: 6.3469999999999995
    - type: recall_at_1
      value: 12.416
    - type: recall_at_10
      value: 30.008000000000003
    - type: recall_at_100
      value: 54.498999999999995
    - type: recall_at_1000
      value: 78.32000000000001
    - type: recall_at_3
      value: 19.79
    - type: recall_at_5
      value: 23.376
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.36133333333333
    - type: map_at_10
      value: 18.6895
    - type: map_at_100
      value: 19.62275
    - type: map_at_1000
      value: 19.748833333333334
    - type: map_at_3
      value: 16.8815
    - type: map_at_5
      value: 17.84133333333334
    - type: mrr_at_1
      value: 16.093083333333336
    - type: mrr_at_10
      value: 21.63225
    - type: mrr_at_100
      value: 22.477333333333334
    - type: mrr_at_1000
      value: 22.563166666666664
    - type: mrr_at_3
      value: 19.83
    - type: mrr_at_5
      value: 20.799166666666668
    - type: ndcg_at_1
      value: 16.093083333333336
    - type: ndcg_at_10
      value: 22.30233333333333
    - type: ndcg_at_100
      value: 27.000333333333337
    - type: ndcg_at_1000
      value: 30.14883333333333
    - type: ndcg_at_3
      value: 18.966499999999996
    - type: ndcg_at_5
      value: 20.425916666666666
    - type: precision_at_1
      value: 16.093083333333336
    - type: precision_at_10
      value: 4.062916666666667
    - type: precision_at_100
      value: 0.7655833333333333
    - type: precision_at_1000
      value: 0.12208333333333334
    - type: precision_at_3
      value: 8.848666666666666
    - type: precision_at_5
      value: 6.400833333333333
    - type: recall_at_1
      value: 13.36133333333333
    - type: recall_at_10
      value: 30.32383333333334
    - type: recall_at_100
      value: 51.808
    - type: recall_at_1000
      value: 74.64483333333332
    - type: recall_at_3
      value: 20.884249999999994
    - type: recall_at_5
      value: 24.67641666666667
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.722999999999999
    - type: map_at_10
      value: 14.280999999999999
    - type: map_at_100
      value: 15.065000000000001
    - type: map_at_1000
      value: 15.154
    - type: map_at_3
      value: 13.004
    - type: map_at_5
      value: 13.626
    - type: mrr_at_1
      value: 11.81
    - type: mrr_at_10
      value: 16.384
    - type: mrr_at_100
      value: 17.189
    - type: mrr_at_1000
      value: 17.269000000000002
    - type: mrr_at_3
      value: 15.082
    - type: mrr_at_5
      value: 15.711
    - type: ndcg_at_1
      value: 11.81
    - type: ndcg_at_10
      value: 17.253
    - type: ndcg_at_100
      value: 21.404
    - type: ndcg_at_1000
      value: 24.09
    - type: ndcg_at_3
      value: 14.716999999999999
    - type: ndcg_at_5
      value: 15.706000000000001
    - type: precision_at_1
      value: 11.81
    - type: precision_at_10
      value: 2.9749999999999996
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.084
    - type: precision_at_3
      value: 6.902
    - type: precision_at_5
      value: 4.816
    - type: recall_at_1
      value: 9.722999999999999
    - type: recall_at_10
      value: 24.569
    - type: recall_at_100
      value: 43.997
    - type: recall_at_1000
      value: 64.44
    - type: recall_at_3
      value: 17.134
    - type: recall_at_5
      value: 19.72
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.497
    - type: map_at_10
      value: 10.846
    - type: map_at_100
      value: 11.498999999999999
    - type: map_at_1000
      value: 11.618
    - type: map_at_3
      value: 9.658999999999999
    - type: map_at_5
      value: 10.298
    - type: mrr_at_1
      value: 9.119
    - type: mrr_at_10
      value: 12.992999999999999
    - type: mrr_at_100
      value: 13.700999999999999
    - type: mrr_at_1000
      value: 13.797999999999998
    - type: mrr_at_3
      value: 11.666
    - type: mrr_at_5
      value: 12.362
    - type: ndcg_at_1
      value: 9.119
    - type: ndcg_at_10
      value: 13.308
    - type: ndcg_at_100
      value: 16.98
    - type: ndcg_at_1000
      value: 20.488
    - type: ndcg_at_3
      value: 10.982
    - type: ndcg_at_5
      value: 12.003
    - type: precision_at_1
      value: 9.119
    - type: precision_at_10
      value: 2.4979999999999998
    - type: precision_at_100
      value: 0.519
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 5.288
    - type: precision_at_5
      value: 3.8890000000000002
    - type: recall_at_1
      value: 7.497
    - type: recall_at_10
      value: 18.817999999999998
    - type: recall_at_100
      value: 35.893
    - type: recall_at_1000
      value: 61.966
    - type: recall_at_3
      value: 12.199
    - type: recall_at_5
      value: 14.87
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.856
    - type: map_at_10
      value: 16.685
    - type: map_at_100
      value: 17.433
    - type: map_at_1000
      value: 17.558
    - type: map_at_3
      value: 15.021
    - type: map_at_5
      value: 15.931999999999999
    - type: mrr_at_1
      value: 14.179
    - type: mrr_at_10
      value: 19.398
    - type: mrr_at_100
      value: 20.153
    - type: mrr_at_1000
      value: 20.251
    - type: mrr_at_3
      value: 17.631
    - type: mrr_at_5
      value: 18.517
    - type: ndcg_at_1
      value: 14.179
    - type: ndcg_at_10
      value: 20.061999999999998
    - type: ndcg_at_100
      value: 24.149
    - type: ndcg_at_1000
      value: 27.644999999999996
    - type: ndcg_at_3
      value: 16.794
    - type: ndcg_at_5
      value: 18.224
    - type: precision_at_1
      value: 14.179
    - type: precision_at_10
      value: 3.582
    - type: precision_at_100
      value: 0.623
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 7.774
    - type: precision_at_5
      value: 5.5969999999999995
    - type: recall_at_1
      value: 11.856
    - type: recall_at_10
      value: 27.778999999999996
    - type: recall_at_100
      value: 46.733000000000004
    - type: recall_at_1000
      value: 72.481
    - type: recall_at_3
      value: 18.859
    - type: recall_at_5
      value: 22.435
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 13.164000000000001
    - type: map_at_10
      value: 19.317999999999998
    - type: map_at_100
      value: 20.463
    - type: map_at_1000
      value: 20.646
    - type: map_at_3
      value: 17.126
    - type: map_at_5
      value: 18.056
    - type: mrr_at_1
      value: 16.601
    - type: mrr_at_10
      value: 22.62
    - type: mrr_at_100
      value: 23.601
    - type: mrr_at_1000
      value: 23.676
    - type: mrr_at_3
      value: 20.685000000000002
    - type: mrr_at_5
      value: 21.465999999999998
    - type: ndcg_at_1
      value: 16.601
    - type: ndcg_at_10
      value: 23.735999999999997
    - type: ndcg_at_100
      value: 29.047
    - type: ndcg_at_1000
      value: 32.323
    - type: ndcg_at_3
      value: 20.013
    - type: ndcg_at_5
      value: 21.165
    - type: precision_at_1
      value: 16.601
    - type: precision_at_10
      value: 4.7829999999999995
    - type: precision_at_100
      value: 1.077
    - type: precision_at_1000
      value: 0.197
    - type: precision_at_3
      value: 9.881
    - type: precision_at_5
      value: 7.074999999999999
    - type: recall_at_1
      value: 13.164000000000001
    - type: recall_at_10
      value: 33.041
    - type: recall_at_100
      value: 57.907
    - type: recall_at_1000
      value: 79.887
    - type: recall_at_3
      value: 21.397
    - type: recall_at_5
      value: 24.863
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.08
    - type: map_at_10
      value: 14.069
    - type: map_at_100
      value: 14.860000000000001
    - type: map_at_1000
      value: 14.968
    - type: map_at_3
      value: 12.498
    - type: map_at_5
      value: 13.324
    - type: mrr_at_1
      value: 10.906
    - type: mrr_at_10
      value: 15.198999999999998
    - type: mrr_at_100
      value: 16.003
    - type: mrr_at_1000
      value: 16.095000000000002
    - type: mrr_at_3
      value: 13.494
    - type: mrr_at_5
      value: 14.362
    - type: ndcg_at_1
      value: 10.906
    - type: ndcg_at_10
      value: 16.794999999999998
    - type: ndcg_at_100
      value: 21.434
    - type: ndcg_at_1000
      value: 24.743000000000002
    - type: ndcg_at_3
      value: 13.507
    - type: ndcg_at_5
      value: 14.953
    - type: precision_at_1
      value: 10.906
    - type: precision_at_10
      value: 2.791
    - type: precision_at_100
      value: 0.5559999999999999
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 5.545
    - type: precision_at_5
      value: 4.14
    - type: recall_at_1
      value: 10.08
    - type: recall_at_10
      value: 24.184
    - type: recall_at_100
      value: 46.967999999999996
    - type: recall_at_1000
      value: 72.92999999999999
    - type: recall_at_3
      value: 15.440999999999999
    - type: recall_at_5
      value: 18.829
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.537
    - type: map_at_10
      value: 11.465
    - type: map_at_100
      value: 12.851
    - type: map_at_1000
      value: 13.045000000000002
    - type: map_at_3
      value: 9.369
    - type: map_at_5
      value: 10.331
    - type: mrr_at_1
      value: 15.244
    - type: mrr_at_10
      value: 23.593
    - type: mrr_at_100
      value: 24.772
    - type: mrr_at_1000
      value: 24.839
    - type: mrr_at_3
      value: 20.467
    - type: mrr_at_5
      value: 22.027
    - type: ndcg_at_1
      value: 15.244
    - type: ndcg_at_10
      value: 17.288999999999998
    - type: ndcg_at_100
      value: 23.757
    - type: ndcg_at_1000
      value: 27.725
    - type: ndcg_at_3
      value: 13.245000000000001
    - type: ndcg_at_5
      value: 14.485000000000001
    - type: precision_at_1
      value: 15.244
    - type: precision_at_10
      value: 5.733
    - type: precision_at_100
      value: 1.264
    - type: precision_at_1000
      value: 0.199
    - type: precision_at_3
      value: 10.054
    - type: precision_at_5
      value: 7.9350000000000005
    - type: recall_at_1
      value: 6.537
    - type: recall_at_10
      value: 22.046
    - type: recall_at_100
      value: 44.818000000000005
    - type: recall_at_1000
      value: 67.676
    - type: recall_at_3
      value: 12.232
    - type: recall_at_5
      value: 15.540999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.304
    - type: map_at_10
      value: 9.944
    - type: map_at_100
      value: 14.113000000000001
    - type: map_at_1000
      value: 15.085
    - type: map_at_3
      value: 7.228999999999999
    - type: map_at_5
      value: 8.368
    - type: mrr_at_1
      value: 43.0
    - type: mrr_at_10
      value: 53.303999999999995
    - type: mrr_at_100
      value: 53.979
    - type: mrr_at_1000
      value: 54.005
    - type: mrr_at_3
      value: 50.542
    - type: mrr_at_5
      value: 52.154
    - type: ndcg_at_1
      value: 31.5
    - type: ndcg_at_10
      value: 24.235
    - type: ndcg_at_100
      value: 28.01
    - type: ndcg_at_1000
      value: 34.724
    - type: ndcg_at_3
      value: 26.682
    - type: ndcg_at_5
      value: 25.249
    - type: precision_at_1
      value: 43.0
    - type: precision_at_10
      value: 21.65
    - type: precision_at_100
      value: 6.97
    - type: precision_at_1000
      value: 1.4449999999999998
    - type: precision_at_3
      value: 32.25
    - type: precision_at_5
      value: 27.250000000000004
    - type: recall_at_1
      value: 4.304
    - type: recall_at_10
      value: 15.014
    - type: recall_at_100
      value: 35.115
    - type: recall_at_1000
      value: 58.52
    - type: recall_at_3
      value: 8.698
    - type: recall_at_5
      value: 11.052
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 45.09
    - type: f1
      value: 41.3731018097549
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.349
    - type: map_at_10
      value: 24.917
    - type: map_at_100
      value: 26.003
    - type: map_at_1000
      value: 26.072
    - type: map_at_3
      value: 22.067999999999998
    - type: map_at_5
      value: 23.610999999999997
    - type: mrr_at_1
      value: 17.416999999999998
    - type: mrr_at_10
      value: 26.44
    - type: mrr_at_100
      value: 27.509
    - type: mrr_at_1000
      value: 27.57
    - type: mrr_at_3
      value: 23.422
    - type: mrr_at_5
      value: 25.063999999999997
    - type: ndcg_at_1
      value: 17.416999999999998
    - type: ndcg_at_10
      value: 30.267
    - type: ndcg_at_100
      value: 35.650999999999996
    - type: ndcg_at_1000
      value: 37.57
    - type: ndcg_at_3
      value: 24.303
    - type: ndcg_at_5
      value: 27.099
    - type: precision_at_1
      value: 17.416999999999998
    - type: precision_at_10
      value: 4.9590000000000005
    - type: precision_at_100
      value: 0.7799999999999999
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 10.536
    - type: precision_at_5
      value: 7.807
    - type: recall_at_1
      value: 16.349
    - type: recall_at_10
      value: 45.678999999999995
    - type: recall_at_100
      value: 70.541
    - type: recall_at_1000
      value: 85.36500000000001
    - type: recall_at_3
      value: 29.42
    - type: recall_at_5
      value: 36.112
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.478999999999999
    - type: map_at_10
      value: 11.933
    - type: map_at_100
      value: 13.078000000000001
    - type: map_at_1000
      value: 13.267999999999999
    - type: map_at_3
      value: 9.975000000000001
    - type: map_at_5
      value: 10.928
    - type: mrr_at_1
      value: 14.66
    - type: mrr_at_10
      value: 20.737
    - type: mrr_at_100
      value: 21.719
    - type: mrr_at_1000
      value: 21.809
    - type: mrr_at_3
      value: 18.57
    - type: mrr_at_5
      value: 19.558
    - type: ndcg_at_1
      value: 14.66
    - type: ndcg_at_10
      value: 16.619
    - type: ndcg_at_100
      value: 22.467000000000002
    - type: ndcg_at_1000
      value: 26.745
    - type: ndcg_at_3
      value: 13.547
    - type: ndcg_at_5
      value: 14.466999999999999
    - type: precision_at_1
      value: 14.66
    - type: precision_at_10
      value: 4.8149999999999995
    - type: precision_at_100
      value: 1.0619999999999998
    - type: precision_at_1000
      value: 0.182
    - type: precision_at_3
      value: 9.002
    - type: precision_at_5
      value: 6.79
    - type: recall_at_1
      value: 7.478999999999999
    - type: recall_at_10
      value: 21.884
    - type: recall_at_100
      value: 45.545
    - type: recall_at_1000
      value: 71.887
    - type: recall_at_3
      value: 12.485
    - type: recall_at_5
      value: 15.862000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 20.628
    - type: map_at_10
      value: 28.559
    - type: map_at_100
      value: 29.5
    - type: map_at_1000
      value: 29.601
    - type: map_at_3
      value: 26.429000000000002
    - type: map_at_5
      value: 27.589000000000002
    - type: mrr_at_1
      value: 41.256
    - type: mrr_at_10
      value: 48.842999999999996
    - type: mrr_at_100
      value: 49.523
    - type: mrr_at_1000
      value: 49.57
    - type: mrr_at_3
      value: 46.894000000000005
    - type: mrr_at_5
      value: 48.024
    - type: ndcg_at_1
      value: 41.256
    - type: ndcg_at_10
      value: 36.217
    - type: ndcg_at_100
      value: 40.422000000000004
    - type: ndcg_at_1000
      value: 42.762
    - type: ndcg_at_3
      value: 32.275999999999996
    - type: ndcg_at_5
      value: 34.184
    - type: precision_at_1
      value: 41.256
    - type: precision_at_10
      value: 7.838000000000001
    - type: precision_at_100
      value: 1.119
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 20.207
    - type: precision_at_5
      value: 13.636999999999999
    - type: recall_at_1
      value: 20.628
    - type: recall_at_10
      value: 39.190000000000005
    - type: recall_at_100
      value: 55.962
    - type: recall_at_1000
      value: 71.56700000000001
    - type: recall_at_3
      value: 30.311
    - type: recall_at_5
      value: 34.092
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 70.78
    - type: ap
      value: 65.09281598781793
    - type: f1
      value: 70.56498155979408
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 7.149
    - type: map_at_10
      value: 12.494
    - type: map_at_100
      value: 13.438
    - type: map_at_1000
      value: 13.544
    - type: map_at_3
      value: 10.58
    - type: map_at_5
      value: 11.623
    - type: mrr_at_1
      value: 7.364
    - type: mrr_at_10
      value: 12.817
    - type: mrr_at_100
      value: 13.758000000000001
    - type: mrr_at_1000
      value: 13.861
    - type: mrr_at_3
      value: 10.879
    - type: mrr_at_5
      value: 11.942
    - type: ndcg_at_1
      value: 7.364
    - type: ndcg_at_10
      value: 15.787999999999998
    - type: ndcg_at_100
      value: 20.973
    - type: ndcg_at_1000
      value: 24.156
    - type: ndcg_at_3
      value: 11.782
    - type: ndcg_at_5
      value: 13.675
    - type: precision_at_1
      value: 7.364
    - type: precision_at_10
      value: 2.702
    - type: precision_at_100
      value: 0.539
    - type: precision_at_1000
      value: 0.08099999999999999
    - type: precision_at_3
      value: 5.148
    - type: precision_at_5
      value: 4.043
    - type: recall_at_1
      value: 7.149
    - type: recall_at_10
      value: 26.039
    - type: recall_at_100
      value: 51.405
    - type: recall_at_1000
      value: 76.97500000000001
    - type: recall_at_3
      value: 14.979000000000001
    - type: recall_at_5
      value: 19.553
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.95576835385319
    - type: f1
      value: 88.06364678376042
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.99726402188783
    - type: f1
      value: 38.19916053247397
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.79287155346336
    - type: f1
      value: 61.634629394462934
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.30934767989241
    - type: f1
      value: 68.77914761769519
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.617349409076375
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 23.802943866708315
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.431263837648547
    - type: mrr
      value: 30.205900793315156
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.479
    - type: map_at_10
      value: 7.603
    - type: map_at_100
      value: 9.725999999999999
    - type: map_at_1000
      value: 10.84
    - type: map_at_3
      value: 5.844
    - type: map_at_5
      value: 6.732
    - type: mrr_at_1
      value: 33.745999999999995
    - type: mrr_at_10
      value: 43.516
    - type: mrr_at_100
      value: 44.190000000000005
    - type: mrr_at_1000
      value: 44.248
    - type: mrr_at_3
      value: 41.744
    - type: mrr_at_5
      value: 42.828
    - type: ndcg_at_1
      value: 31.424000000000003
    - type: ndcg_at_10
      value: 24.267
    - type: ndcg_at_100
      value: 22.416
    - type: ndcg_at_1000
      value: 31.165
    - type: ndcg_at_3
      value: 28.349999999999998
    - type: ndcg_at_5
      value: 26.596999999999998
    - type: precision_at_1
      value: 33.745999999999995
    - type: precision_at_10
      value: 18.173000000000002
    - type: precision_at_100
      value: 6.142
    - type: precision_at_1000
      value: 1.856
    - type: precision_at_3
      value: 27.141
    - type: precision_at_5
      value: 22.91
    - type: recall_at_1
      value: 3.479
    - type: recall_at_10
      value: 10.838000000000001
    - type: recall_at_100
      value: 23.817
    - type: recall_at_1000
      value: 54.910000000000004
    - type: recall_at_3
      value: 7.236
    - type: recall_at_5
      value: 9.003
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.413
    - type: map_at_10
      value: 15.137
    - type: map_at_100
      value: 16.393
    - type: map_at_1000
      value: 16.492
    - type: map_at_3
      value: 12.584999999999999
    - type: map_at_5
      value: 13.963000000000001
    - type: mrr_at_1
      value: 9.762
    - type: mrr_at_10
      value: 16.813
    - type: mrr_at_100
      value: 17.98
    - type: mrr_at_1000
      value: 18.064
    - type: mrr_at_3
      value: 14.257
    - type: mrr_at_5
      value: 15.651000000000002
    - type: ndcg_at_1
      value: 9.733
    - type: ndcg_at_10
      value: 19.543
    - type: ndcg_at_100
      value: 25.965
    - type: ndcg_at_1000
      value: 28.663
    - type: ndcg_at_3
      value: 14.308000000000002
    - type: ndcg_at_5
      value: 16.771
    - type: precision_at_1
      value: 9.733
    - type: precision_at_10
      value: 3.7249999999999996
    - type: precision_at_100
      value: 0.739
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 6.856
    - type: precision_at_5
      value: 5.475
    - type: recall_at_1
      value: 8.413
    - type: recall_at_10
      value: 31.668000000000003
    - type: recall_at_100
      value: 61.551
    - type: recall_at_1000
      value: 82.228
    - type: recall_at_3
      value: 17.669
    - type: recall_at_5
      value: 23.488999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.522
    - type: map_at_10
      value: 76.068
    - type: map_at_100
      value: 76.858
    - type: map_at_1000
      value: 76.89099999999999
    - type: map_at_3
      value: 73.07000000000001
    - type: map_at_5
      value: 74.883
    - type: mrr_at_1
      value: 73.11
    - type: mrr_at_10
      value: 80.134
    - type: mrr_at_100
      value: 80.403
    - type: mrr_at_1000
      value: 80.411
    - type: mrr_at_3
      value: 78.728
    - type: mrr_at_5
      value: 79.60000000000001
    - type: ndcg_at_1
      value: 73.1
    - type: ndcg_at_10
      value: 80.595
    - type: ndcg_at_100
      value: 82.749
    - type: ndcg_at_1000
      value: 83.14099999999999
    - type: ndcg_at_3
      value: 77.021
    - type: ndcg_at_5
      value: 78.846
    - type: precision_at_1
      value: 73.1
    - type: precision_at_10
      value: 12.206999999999999
    - type: precision_at_100
      value: 1.459
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.36
    - type: precision_at_5
      value: 22.09
    - type: recall_at_1
      value: 63.522
    - type: recall_at_10
      value: 89.32600000000001
    - type: recall_at_100
      value: 97.35000000000001
    - type: recall_at_1000
      value: 99.613
    - type: recall_at_3
      value: 79.074
    - type: recall_at_5
      value: 84.143
    - type: map_at_1
      value: 3.053
    - type: map_at_10
      value: 6.912999999999999
    - type: map_at_100
      value: 8.261000000000001
    - type: map_at_1000
      value: 8.530999999999999
    - type: map_at_3
      value: 5.094
    - type: map_at_5
      value: 5.997
    - type: mrr_at_1
      value: 15.0
    - type: mrr_at_10
      value: 22.795
    - type: mrr_at_100
      value: 24.008
    - type: mrr_at_1000
      value: 24.099999999999998
    - type: mrr_at_3
      value: 20.1
    - type: mrr_at_5
      value: 21.685
    - type: ndcg_at_1
      value: 15.0
    - type: ndcg_at_10
      value: 12.386999999999999
    - type: ndcg_at_100
      value: 18.533
    - type: ndcg_at_1000
      value: 23.955000000000002
    - type: ndcg_at_3
      value: 11.75
    - type: ndcg_at_5
      value: 10.285
    - type: precision_at_1
      value: 15.0
    - type: precision_at_10
      value: 6.36
    - type: precision_at_100
      value: 1.528
    - type: precision_at_1000
      value: 0.28300000000000003
    - type: precision_at_3
      value: 10.767
    - type: precision_at_5
      value: 8.9
    - type: recall_at_1
      value: 3.053
    - type: recall_at_10
      value: 12.873000000000001
    - type: recall_at_100
      value: 30.982
    - type: recall_at_1000
      value: 57.489999999999995
    - type: recall_at_3
      value: 6.553000000000001
    - type: recall_at_5
      value: 9.013
    - type: map_at_1
      value: 0.148
    - type: map_at_10
      value: 0.971
    - type: map_at_100
      value: 4.65
    - type: map_at_1000
      value: 11.509
    - type: map_at_3
      value: 0.366
    - type: map_at_5
      value: 0.5599999999999999
    - type: mrr_at_1
      value: 62.0
    - type: mrr_at_10
      value: 70.069
    - type: mrr_at_100
      value: 70.455
    - type: mrr_at_1000
      value: 70.455
    - type: mrr_at_3
      value: 68.0
    - type: mrr_at_5
      value: 69.19999999999999
    - type: ndcg_at_1
      value: 56.00000000000001
    - type: ndcg_at_10
      value: 45.729
    - type: ndcg_at_100
      value: 32.757
    - type: ndcg_at_1000
      value: 29.631999999999998
    - type: ndcg_at_3
      value: 50.407999999999994
    - type: ndcg_at_5
      value: 48.208
    - type: precision_at_1
      value: 62.0
    - type: precision_at_10
      value: 47.8
    - type: precision_at_100
      value: 33.72
    - type: precision_at_1000
      value: 14.238000000000001
    - type: precision_at_3
      value: 53.333
    - type: precision_at_5
      value: 50.8
    - type: recall_at_1
      value: 0.148
    - type: recall_at_10
      value: 1.143
    - type: recall_at_100
      value: 7.219
    - type: recall_at_1000
      value: 28.294999999999998
    - type: recall_at_3
      value: 0.392
    - type: recall_at_5
      value: 0.628
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.546512756347916
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 47.07923662495948
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.6733681207629
    - type: cos_sim_spearman
      value: 64.67529822790183
    - type: euclidean_pearson
      value: 69.13481548437119
    - type: euclidean_spearman
      value: 64.67521597440148
    - type: manhattan_pearson
      value: 69.01619022585454
    - type: manhattan_spearman
      value: 64.8728374071917
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 72.06681953798454
    - type: cos_sim_spearman
      value: 62.247506425866405
    - type: euclidean_pearson
      value: 68.05816014766324
    - type: euclidean_spearman
      value: 62.24902354181767
    - type: manhattan_pearson
      value: 66.68543187933726
    - type: manhattan_spearman
      value: 61.438544148098664
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.53983672284885
    - type: cos_sim_spearman
      value: 77.2760080817994
    - type: euclidean_pearson
      value: 76.7796065728204
    - type: euclidean_spearman
      value: 77.27600787572996
    - type: manhattan_pearson
      value: 76.37651419577129
    - type: manhattan_spearman
      value: 76.85568457177312
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.2085441120845
    - type: cos_sim_spearman
      value: 71.91409062241355
    - type: euclidean_pearson
      value: 74.52730472762947
    - type: euclidean_spearman
      value: 71.91409512725335
    - type: manhattan_pearson
      value: 74.53275469819042
    - type: manhattan_spearman
      value: 71.9720930787841
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 79.2427339046162
    - type: cos_sim_spearman
      value: 79.75345017876988
    - type: euclidean_pearson
      value: 79.31395774152486
    - type: euclidean_spearman
      value: 79.75345672749796
    - type: manhattan_pearson
      value: 79.24199253925532
    - type: manhattan_spearman
      value: 79.64057053536243
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.64452384480809
    - type: cos_sim_spearman
      value: 76.26343905510407
    - type: euclidean_pearson
      value: 75.64112078051633
    - type: euclidean_spearman
      value: 76.26343823222666
    - type: manhattan_pearson
      value: 75.32718790811802
    - type: manhattan_spearman
      value: 75.9420892784719
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.67406953406964
    - type: cos_sim_spearman
      value: 85.96709815630739
    - type: euclidean_pearson
      value: 84.71863724469544
    - type: euclidean_spearman
      value: 85.96709815630739
    - type: manhattan_pearson
      value: 85.07894738833434
    - type: manhattan_spearman
      value: 86.57110045700985
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 59.318066667301615
    - type: cos_sim_spearman
      value: 63.07956002739231
    - type: euclidean_pearson
      value: 62.464248268498814
    - type: euclidean_spearman
      value: 63.07956002739231
    - type: manhattan_pearson
      value: 62.04813588964373
    - type: manhattan_spearman
      value: 61.83898606879604
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.25982574948274
    - type: cos_sim_spearman
      value: 75.4051305973876
    - type: euclidean_pearson
      value: 77.1987828515963
    - type: euclidean_spearman
      value: 75.40516069202422
    - type: manhattan_pearson
      value: 77.04099633595793
    - type: manhattan_spearman
      value: 75.32222510947251
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.10127087089839
    - type: mrr
      value: 90.62288020621355
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 35.5
    - type: map_at_10
      value: 45.238
    - type: map_at_100
      value: 46.135999999999996
    - type: map_at_1000
      value: 46.181
    - type: map_at_3
      value: 42.329
    - type: map_at_5
      value: 44.054
    - type: mrr_at_1
      value: 37.667
    - type: mrr_at_10
      value: 46.661
    - type: mrr_at_100
      value: 47.378
    - type: mrr_at_1000
      value: 47.418
    - type: mrr_at_3
      value: 43.944
    - type: mrr_at_5
      value: 45.528
    - type: ndcg_at_1
      value: 37.667
    - type: ndcg_at_10
      value: 50.63999999999999
    - type: ndcg_at_100
      value: 54.885
    - type: ndcg_at_1000
      value: 56.274
    - type: ndcg_at_3
      value: 44.891999999999996
    - type: ndcg_at_5
      value: 47.788000000000004
    - type: precision_at_1
      value: 37.667
    - type: precision_at_10
      value: 7.3
    - type: precision_at_100
      value: 0.97
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 18.333
    - type: precision_at_5
      value: 12.6
    - type: recall_at_1
      value: 35.5
    - type: recall_at_10
      value: 66.178
    - type: recall_at_100
      value: 85.9
    - type: recall_at_1000
      value: 97.1
    - type: recall_at_3
      value: 50.306
    - type: recall_at_5
      value: 57.443999999999996
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.71386138613862
    - type: cos_sim_ap
      value: 90.20131932554314
    - type: cos_sim_f1
      value: 84.7749114820435
    - type: cos_sim_precision
      value: 85.7727737973388
    - type: cos_sim_recall
      value: 83.8
    - type: dot_accuracy
      value: 99.71386138613862
    - type: dot_ap
      value: 90.20131927652947
    - type: dot_f1
      value: 84.7749114820435
    - type: dot_precision
      value: 85.7727737973388
    - type: dot_recall
      value: 83.8
    - type: euclidean_accuracy
      value: 99.71386138613862
    - type: euclidean_ap
      value: 90.20131927652946
    - type: euclidean_f1
      value: 84.7749114820435
    - type: euclidean_precision
      value: 85.7727737973388
    - type: euclidean_recall
      value: 83.8
    - type: manhattan_accuracy
      value: 99.7059405940594
    - type: manhattan_ap
      value: 90.00682250828238
    - type: manhattan_f1
      value: 84.44211629125196
    - type: manhattan_precision
      value: 88.66886688668868
    - type: manhattan_recall
      value: 80.60000000000001
    - type: max_accuracy
      value: 99.71386138613862
    - type: max_ap
      value: 90.20131932554314
    - type: max_f1
      value: 84.7749114820435
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 48.18939518021159
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 30.748387331082416
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.24644967679195
    - type: mrr
      value: 43.66944126135303
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.88359913790285
    - type: cos_sim_spearman
      value: 29.20319307230353
    - type: dot_pearson
      value: 29.883592420103206
    - type: dot_spearman
      value: 29.228231500970136
  - 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: 6.635000000000001
    - type: map_at_100
      value: 10.873
    - type: map_at_1000
      value: 12.415
    - type: map_at_3
      value: 2.8240000000000003
    - type: map_at_5
      value: 4.111
    - type: mrr_at_1
      value: 14.285999999999998
    - type: mrr_at_10
      value: 31.857999999999997
    - type: mrr_at_100
      value: 33.049
    - type: mrr_at_1000
      value: 33.049
    - type: mrr_at_3
      value: 25.85
    - type: mrr_at_5
      value: 29.218
    - type: ndcg_at_1
      value: 12.245000000000001
    - type: ndcg_at_10
      value: 18.618000000000002
    - type: ndcg_at_100
      value: 28.488000000000003
    - type: ndcg_at_1000
      value: 41.208
    - type: ndcg_at_3
      value: 15.045
    - type: ndcg_at_5
      value: 16.359
    - type: precision_at_1
      value: 14.285999999999998
    - type: precision_at_10
      value: 19.796
    - type: precision_at_100
      value: 6.5920000000000005
    - type: precision_at_1000
      value: 1.471
    - type: precision_at_3
      value: 18.367
    - type: precision_at_5
      value: 18.776
    - type: recall_at_1
      value: 1.22
    - type: recall_at_10
      value: 13.763
    - type: recall_at_100
      value: 40.107
    - type: recall_at_1000
      value: 79.06800000000001
    - type: recall_at_3
      value: 4.2540000000000004
    - type: recall_at_5
      value: 7.142999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 71.82600000000001
    - type: ap
      value: 14.59656193783295
    - type: f1
      value: 55.237720537754875
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 55.387662705149964
    - type: f1
      value: 55.62292803889264
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.53590896395144
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 81.57000655659535
    - type: cos_sim_ap
      value: 57.187256107173354
    - type: cos_sim_f1
      value: 54.94480738905159
    - type: cos_sim_precision
      value: 47.93632075471698
    - type: cos_sim_recall
      value: 64.35356200527704
    - type: dot_accuracy
      value: 81.57000655659535
    - type: dot_ap
      value: 57.187234074371496
    - type: dot_f1
      value: 54.94480738905159
    - type: dot_precision
      value: 47.93632075471698
    - type: dot_recall
      value: 64.35356200527704
    - type: euclidean_accuracy
      value: 81.57000655659535
    - type: euclidean_ap
      value: 57.18724422350816
    - type: euclidean_f1
      value: 54.94480738905159
    - type: euclidean_precision
      value: 47.93632075471698
    - type: euclidean_recall
      value: 64.35356200527704
    - type: manhattan_accuracy
      value: 81.71902008702389
    - type: manhattan_ap
      value: 57.51605309414705
    - type: manhattan_f1
      value: 55.16339869281046
    - type: manhattan_precision
      value: 50.18378378378379
    - type: manhattan_recall
      value: 61.24010554089709
    - type: max_accuracy
      value: 81.71902008702389
    - type: max_ap
      value: 57.51605309414705
    - type: max_f1
      value: 55.16339869281046
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.09977878682035
    - type: cos_sim_ap
      value: 81.948747937846
    - type: cos_sim_f1
      value: 74.04089724292375
    - type: cos_sim_precision
      value: 70.7599466704091
    - type: cos_sim_recall
      value: 77.64089929165382
    - type: dot_accuracy
      value: 87.09977878682035
    - type: dot_ap
      value: 81.94874861792225
    - type: dot_f1
      value: 74.04089724292375
    - type: dot_precision
      value: 70.7599466704091
    - type: dot_recall
      value: 77.64089929165382
    - type: euclidean_accuracy
      value: 87.09977878682035
    - type: euclidean_ap
      value: 81.94875280390386
    - type: euclidean_f1
      value: 74.04089724292375
    - type: euclidean_precision
      value: 70.7599466704091
    - type: euclidean_recall
      value: 77.64089929165382
    - type: manhattan_accuracy
      value: 87.19292117825125
    - type: manhattan_ap
      value: 82.13752985145429
    - type: manhattan_f1
      value: 74.36426623424485
    - type: manhattan_precision
      value: 71.32051463311183
    - type: manhattan_recall
      value: 77.6793963658762
    - type: max_accuracy
      value: 87.19292117825125
    - type: max_ap
      value: 82.13752985145429
    - type: max_f1
      value: 74.36426623424485
---
