mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_prompt_domain_sample
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.53731343283583
    - type: ap
      value: 37.92571498384035
    - type: f1
      value: 68.77042705445326
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 66.16017500000001
    - type: ap
      value: 61.42247172783104
    - type: f1
      value: 65.38166709014324
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.396
    - type: f1
      value: 33.71300766345019
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.55
    - type: map_at_10
      value: 35.845
    - type: map_at_100
      value: 36.995
    - type: map_at_1000
      value: 37.018
    - type: map_at_3
      value: 30.856
    - type: map_at_5
      value: 33.605000000000004
    - type: mrr_at_1
      value: 22.048000000000002
    - type: mrr_at_10
      value: 36.039
    - type: mrr_at_100
      value: 37.181
    - type: mrr_at_1000
      value: 37.205
    - type: mrr_at_3
      value: 31.022
    - type: mrr_at_5
      value: 33.757
    - type: ndcg_at_1
      value: 21.55
    - type: ndcg_at_10
      value: 44.241
    - type: ndcg_at_100
      value: 49.457
    - type: ndcg_at_1000
      value: 50.024
    - type: ndcg_at_3
      value: 33.873999999999995
    - type: ndcg_at_5
      value: 38.826
    - type: precision_at_1
      value: 21.55
    - type: precision_at_10
      value: 7.134
    - type: precision_at_100
      value: 0.9490000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.201
    - type: precision_at_5
      value: 10.925
    - type: recall_at_1
      value: 21.55
    - type: recall_at_10
      value: 71.33699999999999
    - type: recall_at_100
      value: 94.879
    - type: recall_at_1000
      value: 99.21799999999999
    - type: recall_at_3
      value: 42.603
    - type: recall_at_5
      value: 54.623
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 34.77701037657294
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.616534607718528
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.39039727853101
    - type: mrr
      value: 68.89240645473332
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.96093442776794
    - type: cos_sim_spearman
      value: 79.80362560866212
    - type: euclidean_pearson
      value: 81.2337598243594
    - type: euclidean_spearman
      value: 79.80362560866212
    - type: manhattan_pearson
      value: 80.54695854084805
    - type: manhattan_spearman
      value: 79.70904514032895
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.1103896103896
    - type: f1
      value: 71.0424629611518
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.160979697519885
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.63609395107967
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.972
    - type: map_at_10
      value: 31.483
    - type: map_at_100
      value: 32.58
    - type: map_at_1000
      value: 32.732
    - type: map_at_3
      value: 28.822
    - type: map_at_5
      value: 30.412
    - type: mrr_at_1
      value: 28.754999999999995
    - type: mrr_at_10
      value: 37.302
    - type: mrr_at_100
      value: 38.065
    - type: mrr_at_1000
      value: 38.132
    - type: mrr_at_3
      value: 35.074
    - type: mrr_at_5
      value: 36.504999999999995
    - type: ndcg_at_1
      value: 28.754999999999995
    - type: ndcg_at_10
      value: 36.9
    - type: ndcg_at_100
      value: 41.785
    - type: ndcg_at_1000
      value: 44.861000000000004
    - type: ndcg_at_3
      value: 33.013999999999996
    - type: ndcg_at_5
      value: 34.966
    - type: precision_at_1
      value: 28.754999999999995
    - type: precision_at_10
      value: 7.053
    - type: precision_at_100
      value: 1.1860000000000002
    - type: precision_at_1000
      value: 0.17500000000000002
    - type: precision_at_3
      value: 16.023
    - type: precision_at_5
      value: 11.76
    - type: recall_at_1
      value: 22.972
    - type: recall_at_10
      value: 46.699
    - type: recall_at_100
      value: 68.476
    - type: recall_at_1000
      value: 89.461
    - type: recall_at_3
      value: 34.792
    - type: recall_at_5
      value: 40.453
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 18.001
    - type: map_at_10
      value: 24.213
    - type: map_at_100
      value: 25.184
    - type: map_at_1000
      value: 25.301000000000002
    - type: map_at_3
      value: 22.157
    - type: map_at_5
      value: 23.357
    - type: mrr_at_1
      value: 22.93
    - type: mrr_at_10
      value: 28.843000000000004
    - type: mrr_at_100
      value: 29.637999999999998
    - type: mrr_at_1000
      value: 29.706
    - type: mrr_at_3
      value: 26.868
    - type: mrr_at_5
      value: 28.021
    - type: ndcg_at_1
      value: 22.93
    - type: ndcg_at_10
      value: 28.337
    - type: ndcg_at_100
      value: 32.696
    - type: ndcg_at_1000
      value: 35.483
    - type: ndcg_at_3
      value: 24.909
    - type: ndcg_at_5
      value: 26.601999999999997
    - type: precision_at_1
      value: 22.93
    - type: precision_at_10
      value: 5.255
    - type: precision_at_100
      value: 0.9199999999999999
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 11.911
    - type: precision_at_5
      value: 8.599
    - type: recall_at_1
      value: 18.001
    - type: recall_at_10
      value: 36.047000000000004
    - type: recall_at_100
      value: 55.123999999999995
    - type: recall_at_1000
      value: 73.919
    - type: recall_at_3
      value: 26.230999999999998
    - type: recall_at_5
      value: 30.791
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 27.74
    - type: map_at_10
      value: 36.899
    - type: map_at_100
      value: 38.021
    - type: map_at_1000
      value: 38.115
    - type: map_at_3
      value: 34.226
    - type: map_at_5
      value: 35.791000000000004
    - type: mrr_at_1
      value: 32.038
    - type: mrr_at_10
      value: 40.196
    - type: mrr_at_100
      value: 41.099000000000004
    - type: mrr_at_1000
      value: 41.159
    - type: mrr_at_3
      value: 37.858000000000004
    - type: mrr_at_5
      value: 39.262
    - type: ndcg_at_1
      value: 32.038
    - type: ndcg_at_10
      value: 41.835
    - type: ndcg_at_100
      value: 46.957
    - type: ndcg_at_1000
      value: 49.132
    - type: ndcg_at_3
      value: 37.03
    - type: ndcg_at_5
      value: 39.466
    - type: precision_at_1
      value: 32.038
    - type: precision_at_10
      value: 6.771000000000001
    - type: precision_at_100
      value: 1.027
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 16.405
    - type: precision_at_5
      value: 11.549
    - type: recall_at_1
      value: 27.74
    - type: recall_at_10
      value: 53.43599999999999
    - type: recall_at_100
      value: 76.239
    - type: recall_at_1000
      value: 92.038
    - type: recall_at_3
      value: 40.625
    - type: recall_at_5
      value: 46.483000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.71
    - type: map_at_10
      value: 18.269
    - type: map_at_100
      value: 19.095000000000002
    - type: map_at_1000
      value: 19.206
    - type: map_at_3
      value: 16.667
    - type: map_at_5
      value: 17.461
    - type: mrr_at_1
      value: 14.915000000000001
    - type: mrr_at_10
      value: 19.6
    - type: mrr_at_100
      value: 20.429
    - type: mrr_at_1000
      value: 20.527
    - type: mrr_at_3
      value: 18.041
    - type: mrr_at_5
      value: 18.826999999999998
    - type: ndcg_at_1
      value: 14.915000000000001
    - type: ndcg_at_10
      value: 21.197
    - type: ndcg_at_100
      value: 25.790999999999997
    - type: ndcg_at_1000
      value: 29.15
    - type: ndcg_at_3
      value: 17.947
    - type: ndcg_at_5
      value: 19.316
    - type: precision_at_1
      value: 14.915000000000001
    - type: precision_at_10
      value: 3.277
    - type: precision_at_100
      value: 0.601
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.495
    - type: precision_at_5
      value: 5.266
    - type: recall_at_1
      value: 13.71
    - type: recall_at_10
      value: 29.104999999999997
    - type: recall_at_100
      value: 51.283
    - type: recall_at_1000
      value: 77.706
    - type: recall_at_3
      value: 20.217
    - type: recall_at_5
      value: 23.465
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.8759999999999994
    - type: map_at_10
      value: 11.171000000000001
    - type: map_at_100
      value: 12.096
    - type: map_at_1000
      value: 12.224
    - type: map_at_3
      value: 10.148
    - type: map_at_5
      value: 10.529
    - type: mrr_at_1
      value: 10.199
    - type: mrr_at_10
      value: 13.789000000000001
    - type: mrr_at_100
      value: 14.789
    - type: mrr_at_1000
      value: 14.887
    - type: mrr_at_3
      value: 12.706999999999999
    - type: mrr_at_5
      value: 13.142999999999999
    - type: ndcg_at_1
      value: 10.199
    - type: ndcg_at_10
      value: 13.602
    - type: ndcg_at_100
      value: 18.54
    - type: ndcg_at_1000
      value: 22.141
    - type: ndcg_at_3
      value: 11.569
    - type: ndcg_at_5
      value: 12.151
    - type: precision_at_1
      value: 10.199
    - type: precision_at_10
      value: 2.488
    - type: precision_at_100
      value: 0.588
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 5.473
    - type: precision_at_5
      value: 3.781
    - type: recall_at_1
      value: 7.8759999999999994
    - type: recall_at_10
      value: 18.678
    - type: recall_at_100
      value: 40.818
    - type: recall_at_1000
      value: 67.49000000000001
    - type: recall_at_3
      value: 12.841
    - type: recall_at_5
      value: 14.366999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.293
    - type: map_at_10
      value: 24.626
    - type: map_at_100
      value: 25.828
    - type: map_at_1000
      value: 25.964
    - type: map_at_3
      value: 22.439
    - type: map_at_5
      value: 23.541
    - type: mrr_at_1
      value: 22.81
    - type: mrr_at_10
      value: 29.213
    - type: mrr_at_100
      value: 30.188
    - type: mrr_at_1000
      value: 30.258000000000003
    - type: mrr_at_3
      value: 26.933
    - type: mrr_at_5
      value: 28.069
    - type: ndcg_at_1
      value: 22.81
    - type: ndcg_at_10
      value: 29.107
    - type: ndcg_at_100
      value: 34.958
    - type: ndcg_at_1000
      value: 37.968
    - type: ndcg_at_3
      value: 25.144
    - type: ndcg_at_5
      value: 26.769
    - type: precision_at_1
      value: 22.81
    - type: precision_at_10
      value: 5.351
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 11.741999999999999
    - type: precision_at_5
      value: 8.431
    - type: recall_at_1
      value: 18.293
    - type: recall_at_10
      value: 38.315
    - type: recall_at_100
      value: 64.16199999999999
    - type: recall_at_1000
      value: 84.944
    - type: recall_at_3
      value: 27.006000000000004
    - type: recall_at_5
      value: 31.284
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.896
    - type: map_at_10
      value: 19.695999999999998
    - type: map_at_100
      value: 20.813000000000002
    - type: map_at_1000
      value: 20.953
    - type: map_at_3
      value: 17.657
    - type: map_at_5
      value: 18.752
    - type: mrr_at_1
      value: 17.122999999999998
    - type: mrr_at_10
      value: 23.345
    - type: mrr_at_100
      value: 24.294
    - type: mrr_at_1000
      value: 24.386
    - type: mrr_at_3
      value: 21.404
    - type: mrr_at_5
      value: 22.494
    - type: ndcg_at_1
      value: 17.122999999999998
    - type: ndcg_at_10
      value: 23.692
    - type: ndcg_at_100
      value: 29.012
    - type: ndcg_at_1000
      value: 32.45
    - type: ndcg_at_3
      value: 20.002
    - type: ndcg_at_5
      value: 21.62
    - type: precision_at_1
      value: 17.122999999999998
    - type: precision_at_10
      value: 4.543
    - type: precision_at_100
      value: 0.852
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 9.589
    - type: precision_at_5
      value: 7.1
    - type: recall_at_1
      value: 13.896
    - type: recall_at_10
      value: 32.176
    - type: recall_at_100
      value: 55.382
    - type: recall_at_1000
      value: 79.725
    - type: recall_at_3
      value: 21.942
    - type: recall_at_5
      value: 26.068
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 15.481333333333335
    - type: map_at_10
      value: 21.042999999999996
    - type: map_at_100
      value: 22.0115
    - type: map_at_1000
      value: 22.138250000000003
    - type: map_at_3
      value: 19.255166666666664
    - type: map_at_5
      value: 20.23483333333333
    - type: mrr_at_1
      value: 18.692583333333335
    - type: mrr_at_10
      value: 24.281
    - type: mrr_at_100
      value: 25.134249999999998
    - type: mrr_at_1000
      value: 25.218833333333336
    - type: mrr_at_3
      value: 22.54816666666667
    - type: mrr_at_5
      value: 23.507916666666667
    - type: ndcg_at_1
      value: 18.692583333333335
    - type: ndcg_at_10
      value: 24.682166666666667
    - type: ndcg_at_100
      value: 29.43166666666666
    - type: ndcg_at_1000
      value: 32.59633333333334
    - type: ndcg_at_3
      value: 21.481749999999998
    - type: ndcg_at_5
      value: 22.93933333333333
    - type: precision_at_1
      value: 18.692583333333335
    - type: precision_at_10
      value: 4.370916666666667
    - type: precision_at_100
      value: 0.8024999999999999
    - type: precision_at_1000
      value: 0.12566666666666668
    - type: precision_at_3
      value: 9.923833333333334
    - type: precision_at_5
      value: 7.110416666666667
    - type: recall_at_1
      value: 15.481333333333335
    - type: recall_at_10
      value: 32.433166666666665
    - type: recall_at_100
      value: 54.03975
    - type: recall_at_1000
      value: 77.06675
    - type: recall_at_3
      value: 23.353916666666663
    - type: recall_at_5
      value: 27.16183333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 12.656999999999998
    - type: map_at_10
      value: 16.59
    - type: map_at_100
      value: 17.372
    - type: map_at_1000
      value: 17.465
    - type: map_at_3
      value: 15.075
    - type: map_at_5
      value: 16.016
    - type: mrr_at_1
      value: 14.877
    - type: mrr_at_10
      value: 18.726000000000003
    - type: mrr_at_100
      value: 19.488
    - type: mrr_at_1000
      value: 19.569
    - type: mrr_at_3
      value: 17.127
    - type: mrr_at_5
      value: 18.108
    - type: ndcg_at_1
      value: 14.877
    - type: ndcg_at_10
      value: 19.326
    - type: ndcg_at_100
      value: 23.426
    - type: ndcg_at_1000
      value: 26.168999999999997
    - type: ndcg_at_3
      value: 16.445
    - type: ndcg_at_5
      value: 18.037
    - type: precision_at_1
      value: 14.877
    - type: precision_at_10
      value: 3.206
    - type: precision_at_100
      value: 0.5740000000000001
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 7.26
    - type: precision_at_5
      value: 5.367999999999999
    - type: recall_at_1
      value: 12.656999999999998
    - type: recall_at_10
      value: 25.723000000000003
    - type: recall_at_100
      value: 44.9
    - type: recall_at_1000
      value: 65.923
    - type: recall_at_3
      value: 17.854
    - type: recall_at_5
      value: 21.912000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.997999999999999
    - type: map_at_10
      value: 11.765
    - type: map_at_100
      value: 12.453
    - type: map_at_1000
      value: 12.575
    - type: map_at_3
      value: 10.721
    - type: map_at_5
      value: 11.269
    - type: mrr_at_1
      value: 9.945
    - type: mrr_at_10
      value: 14.172
    - type: mrr_at_100
      value: 14.862
    - type: mrr_at_1000
      value: 14.965
    - type: mrr_at_3
      value: 13.048000000000002
    - type: mrr_at_5
      value: 13.638
    - type: ndcg_at_1
      value: 9.945
    - type: ndcg_at_10
      value: 14.238000000000001
    - type: ndcg_at_100
      value: 18.052
    - type: ndcg_at_1000
      value: 21.633
    - type: ndcg_at_3
      value: 12.301
    - type: ndcg_at_5
      value: 13.113
    - type: precision_at_1
      value: 9.945
    - type: precision_at_10
      value: 2.636
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 5.9990000000000006
    - type: precision_at_5
      value: 4.253
    - type: recall_at_1
      value: 7.997999999999999
    - type: recall_at_10
      value: 19.363
    - type: recall_at_100
      value: 37.203
    - type: recall_at_1000
      value: 63.9
    - type: recall_at_3
      value: 13.755999999999998
    - type: recall_at_5
      value: 15.966
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 14.132
    - type: map_at_10
      value: 19.032
    - type: map_at_100
      value: 19.942
    - type: map_at_1000
      value: 20.061999999999998
    - type: map_at_3
      value: 17.498
    - type: map_at_5
      value: 18.352
    - type: mrr_at_1
      value: 16.698
    - type: mrr_at_10
      value: 21.898
    - type: mrr_at_100
      value: 22.775000000000002
    - type: mrr_at_1000
      value: 22.869999999999997
    - type: mrr_at_3
      value: 20.196
    - type: mrr_at_5
      value: 21.143
    - type: ndcg_at_1
      value: 16.698
    - type: ndcg_at_10
      value: 22.303
    - type: ndcg_at_100
      value: 26.889000000000003
    - type: ndcg_at_1000
      value: 30.249
    - type: ndcg_at_3
      value: 19.28
    - type: ndcg_at_5
      value: 20.694000000000003
    - type: precision_at_1
      value: 16.698
    - type: precision_at_10
      value: 3.7409999999999997
    - type: precision_at_100
      value: 0.6649999999999999
    - type: precision_at_1000
      value: 0.107
    - type: precision_at_3
      value: 8.706
    - type: precision_at_5
      value: 6.119
    - type: recall_at_1
      value: 14.132
    - type: recall_at_10
      value: 29.572
    - type: recall_at_100
      value: 50.346999999999994
    - type: recall_at_1000
      value: 75.214
    - type: recall_at_3
      value: 21.197
    - type: recall_at_5
      value: 24.887999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 16.474
    - type: map_at_10
      value: 22.362000000000002
    - type: map_at_100
      value: 23.533
    - type: map_at_1000
      value: 23.733999999999998
    - type: map_at_3
      value: 20.529
    - type: map_at_5
      value: 21.543
    - type: mrr_at_1
      value: 20.158
    - type: mrr_at_10
      value: 26.069
    - type: mrr_at_100
      value: 26.962999999999997
    - type: mrr_at_1000
      value: 27.049
    - type: mrr_at_3
      value: 24.44
    - type: mrr_at_5
      value: 25.3
    - type: ndcg_at_1
      value: 20.158
    - type: ndcg_at_10
      value: 26.447
    - type: ndcg_at_100
      value: 31.405
    - type: ndcg_at_1000
      value: 34.969
    - type: ndcg_at_3
      value: 23.639
    - type: ndcg_at_5
      value: 24.852
    - type: precision_at_1
      value: 20.158
    - type: precision_at_10
      value: 5.099
    - type: precision_at_100
      value: 1.113
    - type: precision_at_1000
      value: 0.196
    - type: precision_at_3
      value: 11.397
    - type: precision_at_5
      value: 8.182
    - type: recall_at_1
      value: 16.474
    - type: recall_at_10
      value: 33.812
    - type: recall_at_100
      value: 56.725
    - type: recall_at_1000
      value: 81.151
    - type: recall_at_3
      value: 25.043
    - type: recall_at_5
      value: 28.564
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.027000000000001
    - type: map_at_10
      value: 16.41
    - type: map_at_100
      value: 17.221
    - type: map_at_1000
      value: 17.328
    - type: map_at_3
      value: 15.123000000000001
    - type: map_at_5
      value: 15.795
    - type: mrr_at_1
      value: 13.863
    - type: mrr_at_10
      value: 18.218999999999998
    - type: mrr_at_100
      value: 19.021
    - type: mrr_at_1000
      value: 19.118
    - type: mrr_at_3
      value: 16.882
    - type: mrr_at_5
      value: 17.585
    - type: ndcg_at_1
      value: 13.863
    - type: ndcg_at_10
      value: 19.201999999999998
    - type: ndcg_at_100
      value: 23.669
    - type: ndcg_at_1000
      value: 26.951000000000004
    - type: ndcg_at_3
      value: 16.500999999999998
    - type: ndcg_at_5
      value: 17.686
    - type: precision_at_1
      value: 13.863
    - type: precision_at_10
      value: 3.031
    - type: precision_at_100
      value: 0.567
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 7.086
    - type: precision_at_5
      value: 4.917
    - type: recall_at_1
      value: 12.027000000000001
    - type: recall_at_10
      value: 26.272000000000002
    - type: recall_at_100
      value: 47.818
    - type: recall_at_1000
      value: 73.33
    - type: recall_at_3
      value: 18.743000000000002
    - type: recall_at_5
      value: 21.701
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.357
    - type: map_at_10
      value: 11.350999999999999
    - type: map_at_100
      value: 12.774
    - type: map_at_1000
      value: 12.962000000000002
    - type: map_at_3
      value: 9.142
    - type: map_at_5
      value: 10.219000000000001
    - type: mrr_at_1
      value: 14.593
    - type: mrr_at_10
      value: 23.003
    - type: mrr_at_100
      value: 24.15
    - type: mrr_at_1000
      value: 24.215999999999998
    - type: mrr_at_3
      value: 19.924
    - type: mrr_at_5
      value: 21.628
    - type: ndcg_at_1
      value: 14.593
    - type: ndcg_at_10
      value: 17.06
    - type: ndcg_at_100
      value: 23.674
    - type: ndcg_at_1000
      value: 27.57
    - type: ndcg_at_3
      value: 12.903
    - type: ndcg_at_5
      value: 14.399000000000001
    - type: precision_at_1
      value: 14.593
    - type: precision_at_10
      value: 5.6739999999999995
    - type: precision_at_100
      value: 1.279
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 9.794
    - type: precision_at_5
      value: 7.961
    - type: recall_at_1
      value: 6.357
    - type: recall_at_10
      value: 21.837
    - type: recall_at_100
      value: 45.317
    - type: recall_at_1000
      value: 67.868
    - type: recall_at_3
      value: 11.959999999999999
    - type: recall_at_5
      value: 15.744
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.972
    - type: map_at_10
      value: 9.464
    - type: map_at_100
      value: 13.014999999999999
    - type: map_at_1000
      value: 13.956
    - type: map_at_3
      value: 6.796
    - type: map_at_5
      value: 7.896
    - type: mrr_at_1
      value: 40.0
    - type: mrr_at_10
      value: 49.381
    - type: mrr_at_100
      value: 50.156
    - type: mrr_at_1000
      value: 50.17700000000001
    - type: mrr_at_3
      value: 46.208
    - type: mrr_at_5
      value: 47.958
    - type: ndcg_at_1
      value: 29.5
    - type: ndcg_at_10
      value: 23.438
    - type: ndcg_at_100
      value: 26.128
    - type: ndcg_at_1000
      value: 32.922000000000004
    - type: ndcg_at_3
      value: 26.436999999999998
    - type: ndcg_at_5
      value: 24.63
    - type: precision_at_1
      value: 40.0
    - type: precision_at_10
      value: 20.724999999999998
    - type: precision_at_100
      value: 6.353000000000001
    - type: precision_at_1000
      value: 1.329
    - type: precision_at_3
      value: 31.5
    - type: precision_at_5
      value: 26.400000000000002
    - type: recall_at_1
      value: 3.972
    - type: recall_at_10
      value: 14.173
    - type: recall_at_100
      value: 32.249
    - type: recall_at_1000
      value: 54.991
    - type: recall_at_3
      value: 8.177
    - type: recall_at_5
      value: 10.415000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.775
    - type: f1
      value: 40.9777201408297
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 15.373000000000001
    - type: map_at_10
      value: 23.247999999999998
    - type: map_at_100
      value: 24.16
    - type: map_at_1000
      value: 24.233
    - type: map_at_3
      value: 20.718
    - type: map_at_5
      value: 22.117
    - type: mrr_at_1
      value: 16.381999999999998
    - type: mrr_at_10
      value: 24.654999999999998
    - type: mrr_at_100
      value: 25.56
    - type: mrr_at_1000
      value: 25.625999999999998
    - type: mrr_at_3
      value: 21.987000000000002
    - type: mrr_at_5
      value: 23.466
    - type: ndcg_at_1
      value: 16.381999999999998
    - type: ndcg_at_10
      value: 28.083000000000002
    - type: ndcg_at_100
      value: 32.939
    - type: ndcg_at_1000
      value: 35.025
    - type: ndcg_at_3
      value: 22.830000000000002
    - type: ndcg_at_5
      value: 25.351000000000003
    - type: precision_at_1
      value: 16.381999999999998
    - type: precision_at_10
      value: 4.5600000000000005
    - type: precision_at_100
      value: 0.722
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 9.921000000000001
    - type: precision_at_5
      value: 7.276000000000001
    - type: recall_at_1
      value: 15.373000000000001
    - type: recall_at_10
      value: 41.942
    - type: recall_at_100
      value: 65.051
    - type: recall_at_1000
      value: 81.208
    - type: recall_at_3
      value: 27.639999999999997
    - type: recall_at_5
      value: 33.708
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.894
    - type: map_at_10
      value: 11.912
    - type: map_at_100
      value: 13.096
    - type: map_at_1000
      value: 13.29
    - type: map_at_3
      value: 9.82
    - type: map_at_5
      value: 10.999
    - type: mrr_at_1
      value: 14.352
    - type: mrr_at_10
      value: 20.811
    - type: mrr_at_100
      value: 21.908
    - type: mrr_at_1000
      value: 22.001
    - type: mrr_at_3
      value: 18.441
    - type: mrr_at_5
      value: 19.961000000000002
    - type: ndcg_at_1
      value: 14.352
    - type: ndcg_at_10
      value: 16.636
    - type: ndcg_at_100
      value: 22.419
    - type: ndcg_at_1000
      value: 26.771
    - type: ndcg_at_3
      value: 13.436
    - type: ndcg_at_5
      value: 14.908
    - type: precision_at_1
      value: 14.352
    - type: precision_at_10
      value: 4.938
    - type: precision_at_100
      value: 1.076
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 9.156
    - type: precision_at_5
      value: 7.407
    - type: recall_at_1
      value: 6.894
    - type: recall_at_10
      value: 21.672
    - type: recall_at_100
      value: 44.193
    - type: recall_at_1000
      value: 71.604
    - type: recall_at_3
      value: 12.498
    - type: recall_at_5
      value: 16.704
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 18.555
    - type: map_at_10
      value: 25.963
    - type: map_at_100
      value: 26.932000000000002
    - type: map_at_1000
      value: 27.044
    - type: map_at_3
      value: 23.916
    - type: map_at_5
      value: 25.112000000000002
    - type: mrr_at_1
      value: 37.11
    - type: mrr_at_10
      value: 44.175
    - type: mrr_at_100
      value: 44.926
    - type: mrr_at_1000
      value: 44.978
    - type: mrr_at_3
      value: 42.254999999999995
    - type: mrr_at_5
      value: 43.427
    - type: ndcg_at_1
      value: 37.11
    - type: ndcg_at_10
      value: 32.991
    - type: ndcg_at_100
      value: 37.335
    - type: ndcg_at_1000
      value: 40.007
    - type: ndcg_at_3
      value: 29.206
    - type: ndcg_at_5
      value: 31.173000000000002
    - type: precision_at_1
      value: 37.11
    - type: precision_at_10
      value: 7.207
    - type: precision_at_100
      value: 1.065
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 18.375
    - type: precision_at_5
      value: 12.581000000000001
    - type: recall_at_1
      value: 18.555
    - type: recall_at_10
      value: 36.036
    - type: recall_at_100
      value: 53.248
    - type: recall_at_1000
      value: 71.128
    - type: recall_at_3
      value: 27.561999999999998
    - type: recall_at_5
      value: 31.452
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 67.5052
    - type: ap
      value: 62.39030828629721
    - type: f1
      value: 67.18333662684846
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 7.042
    - type: map_at_10
      value: 11.837
    - type: map_at_100
      value: 12.756
    - type: map_at_1000
      value: 12.863
    - type: map_at_3
      value: 10.131
    - type: map_at_5
      value: 11.05
    - type: mrr_at_1
      value: 7.2059999999999995
    - type: mrr_at_10
      value: 12.117
    - type: mrr_at_100
      value: 13.038
    - type: mrr_at_1000
      value: 13.141
    - type: mrr_at_3
      value: 10.392
    - type: mrr_at_5
      value: 11.323
    - type: ndcg_at_1
      value: 7.178
    - type: ndcg_at_10
      value: 14.806
    - type: ndcg_at_100
      value: 19.81
    - type: ndcg_at_1000
      value: 23.003999999999998
    - type: ndcg_at_3
      value: 11.236
    - type: ndcg_at_5
      value: 12.901000000000002
    - type: precision_at_1
      value: 7.178
    - type: precision_at_10
      value: 2.506
    - type: precision_at_100
      value: 0.51
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 4.89
    - type: precision_at_5
      value: 3.782
    - type: recall_at_1
      value: 7.042
    - type: recall_at_10
      value: 24.037
    - type: recall_at_100
      value: 48.415
    - type: recall_at_1000
      value: 74.039
    - type: recall_at_3
      value: 14.194999999999999
    - type: recall_at_5
      value: 18.209
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.73050615595074
    - type: f1
      value: 91.31113807339747
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 65.65435476516187
    - type: f1
      value: 45.186713172025684
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.97175521183591
    - type: f1
      value: 63.30094106953352
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.81775386684599
    - type: f1
      value: 71.5535406261331
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.530997915529994
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.711540056372872
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.199045062705064
    - type: mrr
      value: 31.1642426854302
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.9730000000000003
    - type: map_at_10
      value: 8.282
    - type: map_at_100
      value: 10.331
    - type: map_at_1000
      value: 11.613
    - type: map_at_3
      value: 6.106
    - type: map_at_5
      value: 7.258000000000001
    - type: mrr_at_1
      value: 35.604
    - type: mrr_at_10
      value: 44.241
    - type: mrr_at_100
      value: 45.023
    - type: mrr_at_1000
      value: 45.079
    - type: mrr_at_3
      value: 42.002
    - type: mrr_at_5
      value: 43.751
    - type: ndcg_at_1
      value: 32.663
    - type: ndcg_at_10
      value: 25.419999999999998
    - type: ndcg_at_100
      value: 23.454
    - type: ndcg_at_1000
      value: 32.726
    - type: ndcg_at_3
      value: 28.892
    - type: ndcg_at_5
      value: 27.982000000000003
    - type: precision_at_1
      value: 35.604
    - type: precision_at_10
      value: 18.7
    - type: precision_at_100
      value: 6.353000000000001
    - type: precision_at_1000
      value: 1.9429999999999998
    - type: precision_at_3
      value: 27.554000000000002
    - type: precision_at_5
      value: 24.396
    - type: recall_at_1
      value: 3.9730000000000003
    - type: recall_at_10
      value: 12.606
    - type: recall_at_100
      value: 24.915000000000003
    - type: recall_at_1000
      value: 57.75900000000001
    - type: recall_at_3
      value: 7.207
    - type: recall_at_5
      value: 10.017
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.543
    - type: map_at_10
      value: 16.445999999999998
    - type: map_at_100
      value: 17.682000000000002
    - type: map_at_1000
      value: 17.78
    - type: map_at_3
      value: 13.895
    - type: map_at_5
      value: 15.282000000000002
    - type: mrr_at_1
      value: 10.863
    - type: mrr_at_10
      value: 18.137
    - type: mrr_at_100
      value: 19.291
    - type: mrr_at_1000
      value: 19.371
    - type: mrr_at_3
      value: 15.556000000000001
    - type: mrr_at_5
      value: 16.98
    - type: ndcg_at_1
      value: 10.834000000000001
    - type: ndcg_at_10
      value: 20.96
    - type: ndcg_at_100
      value: 27.336
    - type: ndcg_at_1000
      value: 30.001
    - type: ndcg_at_3
      value: 15.719
    - type: ndcg_at_5
      value: 18.212999999999997
    - type: precision_at_1
      value: 10.834000000000001
    - type: precision_at_10
      value: 3.911
    - type: precision_at_100
      value: 0.756
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 7.455
    - type: precision_at_5
      value: 5.846
    - type: recall_at_1
      value: 9.543
    - type: recall_at_10
      value: 33.35
    - type: recall_at_100
      value: 63.141999999999996
    - type: recall_at_1000
      value: 83.57
    - type: recall_at_3
      value: 19.38
    - type: recall_at_5
      value: 25.266
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.660000000000004
    - type: map_at_10
      value: 76.48
    - type: map_at_100
      value: 77.24
    - type: map_at_1000
      value: 77.275
    - type: map_at_3
      value: 73.52199999999999
    - type: map_at_5
      value: 75.323
    - type: mrr_at_1
      value: 73.3
    - type: mrr_at_10
      value: 80.741
    - type: mrr_at_100
      value: 80.975
    - type: mrr_at_1000
      value: 80.979
    - type: mrr_at_3
      value: 79.282
    - type: mrr_at_5
      value: 80.24900000000001
    - type: ndcg_at_1
      value: 73.32
    - type: ndcg_at_10
      value: 81.172
    - type: ndcg_at_100
      value: 83.22800000000001
    - type: ndcg_at_1000
      value: 83.576
    - type: ndcg_at_3
      value: 77.586
    - type: ndcg_at_5
      value: 79.46600000000001
    - type: precision_at_1
      value: 73.32
    - type: precision_at_10
      value: 12.246
    - type: precision_at_100
      value: 1.459
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.607
    - type: precision_at_5
      value: 22.214
    - type: recall_at_1
      value: 63.660000000000004
    - type: recall_at_10
      value: 90.147
    - type: recall_at_100
      value: 97.882
    - type: recall_at_1000
      value: 99.705
    - type: recall_at_3
      value: 79.948
    - type: recall_at_5
      value: 85.15
    - type: map_at_1
      value: 3.003
    - type: map_at_10
      value: 7.0169999999999995
    - type: map_at_100
      value: 8.436
    - type: map_at_1000
      value: 8.693
    - type: map_at_3
      value: 5.143
    - type: map_at_5
      value: 6.165
    - type: mrr_at_1
      value: 14.7
    - type: mrr_at_10
      value: 22.664
    - type: mrr_at_100
      value: 23.880000000000003
    - type: mrr_at_1000
      value: 23.964
    - type: mrr_at_3
      value: 19.650000000000002
    - type: mrr_at_5
      value: 21.295
    - type: ndcg_at_1
      value: 14.7
    - type: ndcg_at_10
      value: 12.509999999999998
    - type: ndcg_at_100
      value: 18.848000000000003
    - type: ndcg_at_1000
      value: 23.97
    - type: ndcg_at_3
      value: 11.673
    - type: ndcg_at_5
      value: 10.397
    - type: precision_at_1
      value: 14.7
    - type: precision_at_10
      value: 6.49
    - type: precision_at_100
      value: 1.562
    - type: precision_at_1000
      value: 0.27899999999999997
    - type: precision_at_3
      value: 10.767
    - type: precision_at_5
      value: 9.139999999999999
    - type: recall_at_1
      value: 3.003
    - type: recall_at_10
      value: 13.161999999999999
    - type: recall_at_100
      value: 31.747999999999998
    - type: recall_at_1000
      value: 56.752
    - type: recall_at_3
      value: 6.563
    - type: recall_at_5
      value: 9.263
    - type: map_at_1
      value: 0.125
    - type: map_at_10
      value: 0.683
    - type: map_at_100
      value: 3.88
    - type: map_at_1000
      value: 10.776
    - type: map_at_3
      value: 0.28200000000000003
    - type: map_at_5
      value: 0.416
    - type: mrr_at_1
      value: 56.00000000000001
    - type: mrr_at_10
      value: 67.144
    - type: mrr_at_100
      value: 67.674
    - type: mrr_at_1000
      value: 67.674
    - type: mrr_at_3
      value: 63.333
    - type: mrr_at_5
      value: 66.033
    - type: ndcg_at_1
      value: 48.0
    - type: ndcg_at_10
      value: 40.453
    - type: ndcg_at_100
      value: 32.356
    - type: ndcg_at_1000
      value: 30.54
    - type: ndcg_at_3
      value: 45.531
    - type: ndcg_at_5
      value: 43.791999999999994
    - type: precision_at_1
      value: 54.0
    - type: precision_at_10
      value: 43.2
    - type: precision_at_100
      value: 34.12
    - type: precision_at_1000
      value: 15.192
    - type: precision_at_3
      value: 48.667
    - type: precision_at_5
      value: 47.199999999999996
    - type: recall_at_1
      value: 0.125
    - type: recall_at_10
      value: 0.9490000000000001
    - type: recall_at_100
      value: 7.066
    - type: recall_at_1000
      value: 29.948000000000004
    - type: recall_at_3
      value: 0.313
    - type: recall_at_5
      value: 0.526
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 37.24530383149719
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 47.10522668186171
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.5160077089625
    - type: cos_sim_spearman
      value: 67.28825297023138
    - type: euclidean_pearson
      value: 72.39938443269206
    - type: euclidean_spearman
      value: 67.28835245540397
    - type: manhattan_pearson
      value: 69.46413862678756
    - type: manhattan_spearman
      value: 65.04853993701172
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 70.89271048242642
    - type: cos_sim_spearman
      value: 66.18310956468201
    - type: euclidean_pearson
      value: 68.35445603238207
    - type: euclidean_spearman
      value: 66.18456540329906
    - type: manhattan_pearson
      value: 67.8411114817822
    - type: manhattan_spearman
      value: 66.416716585612
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.2216356861313
    - type: cos_sim_spearman
      value: 79.37038668590753
    - type: euclidean_pearson
      value: 79.01512518225226
    - type: euclidean_spearman
      value: 79.37042448746669
    - type: manhattan_pearson
      value: 78.96268955680836
    - type: manhattan_spearman
      value: 79.54073298193023
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.3544215128133
    - type: cos_sim_spearman
      value: 75.07229525913817
    - type: euclidean_pearson
      value: 77.35598390483041
    - type: euclidean_spearman
      value: 75.07228556747974
    - type: manhattan_pearson
      value: 76.27348311336605
    - type: manhattan_spearman
      value: 74.50258040498937
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.86410111924121
    - type: cos_sim_spearman
      value: 81.79657437718866
    - type: euclidean_pearson
      value: 81.77144036632458
    - type: euclidean_spearman
      value: 81.79657286849607
    - type: manhattan_pearson
      value: 81.87491956950679
    - type: manhattan_spearman
      value: 82.16993847726854
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.43507688364112
    - type: cos_sim_spearman
      value: 77.63882301316933
    - type: euclidean_pearson
      value: 77.25501398026381
    - type: euclidean_spearman
      value: 77.63965196736244
    - type: manhattan_pearson
      value: 77.67118978923139
    - type: manhattan_spearman
      value: 78.01084214592416
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.39964672680482
    - type: cos_sim_spearman
      value: 85.4075592513342
    - type: euclidean_pearson
      value: 85.111606756296
    - type: euclidean_spearman
      value: 85.40843260765956
    - type: manhattan_pearson
      value: 84.8842901249278
    - type: manhattan_spearman
      value: 85.63868618596224
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.75456403534724
    - type: cos_sim_spearman
      value: 60.22663871632273
    - type: euclidean_pearson
      value: 62.65086137572171
    - type: euclidean_spearman
      value: 60.22663871632273
    - type: manhattan_pearson
      value: 62.250953520717104
    - type: manhattan_spearman
      value: 60.3533574497436
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.7231724327084
    - type: cos_sim_spearman
      value: 76.94587277885458
    - type: euclidean_pearson
      value: 78.13987744447253
    - type: euclidean_spearman
      value: 76.94589124562322
    - type: manhattan_pearson
      value: 77.01673792666305
    - type: manhattan_spearman
      value: 75.80700280973542
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.367197197921
    - type: mrr
      value: 91.09422258932064
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 37.583
    - type: map_at_10
      value: 45.412
    - type: map_at_100
      value: 46.504
    - type: map_at_1000
      value: 46.558
    - type: map_at_3
      value: 42.552
    - type: map_at_5
      value: 44.635000000000005
    - type: mrr_at_1
      value: 40.0
    - type: mrr_at_10
      value: 47.33
    - type: mrr_at_100
      value: 48.285
    - type: mrr_at_1000
      value: 48.329
    - type: mrr_at_3
      value: 44.944
    - type: mrr_at_5
      value: 46.711000000000006
    - type: ndcg_at_1
      value: 40.0
    - type: ndcg_at_10
      value: 49.818
    - type: ndcg_at_100
      value: 55.226
    - type: ndcg_at_1000
      value: 56.599999999999994
    - type: ndcg_at_3
      value: 44.659
    - type: ndcg_at_5
      value: 48.107
    - type: precision_at_1
      value: 40.0
    - type: precision_at_10
      value: 6.833
    - type: precision_at_100
      value: 0.98
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 17.444000000000003
    - type: precision_at_5
      value: 12.333
    - type: recall_at_1
      value: 37.583
    - type: recall_at_10
      value: 61.622
    - type: recall_at_100
      value: 87.1
    - type: recall_at_1000
      value: 97.8
    - type: recall_at_3
      value: 47.983
    - type: recall_at_5
      value: 56.65
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.70990099009902
    - type: cos_sim_ap
      value: 91.32913696282823
    - type: cos_sim_f1
      value: 85.01006036217304
    - type: cos_sim_precision
      value: 85.52631578947368
    - type: cos_sim_recall
      value: 84.5
    - type: dot_accuracy
      value: 99.70990099009902
    - type: dot_ap
      value: 91.32913696282823
    - type: dot_f1
      value: 85.01006036217304
    - type: dot_precision
      value: 85.52631578947368
    - type: dot_recall
      value: 84.5
    - type: euclidean_accuracy
      value: 99.70990099009902
    - type: euclidean_ap
      value: 91.32913696282823
    - type: euclidean_f1
      value: 85.01006036217304
    - type: euclidean_precision
      value: 85.52631578947368
    - type: euclidean_recall
      value: 84.5
    - type: manhattan_accuracy
      value: 99.76138613861386
    - type: manhattan_ap
      value: 93.79556639749748
    - type: manhattan_f1
      value: 87.80246913580247
    - type: manhattan_precision
      value: 86.73170731707317
    - type: manhattan_recall
      value: 88.9
    - type: max_accuracy
      value: 99.76138613861386
    - type: max_ap
      value: 93.79556639749748
    - type: max_f1
      value: 87.80246913580247
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 43.31369355223715
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.601772320922777
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 45.58773371195953
    - type: mrr
      value: 46.30187112723877
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.0154193888818
    - type: cos_sim_spearman
      value: 30.147164982667924
    - type: dot_pearson
      value: 30.015419367262712
    - type: dot_spearman
      value: 30.1547894792066
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.494
    - type: map_at_10
      value: 8.271
    - type: map_at_100
      value: 13.59
    - type: map_at_1000
      value: 15.18
    - type: map_at_3
      value: 4.232
    - type: map_at_5
      value: 5.656
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 42.504999999999995
    - type: mrr_at_100
      value: 43.318
    - type: mrr_at_1000
      value: 43.318
    - type: mrr_at_3
      value: 39.456
    - type: mrr_at_5
      value: 39.966
    - type: ndcg_at_1
      value: 24.490000000000002
    - type: ndcg_at_10
      value: 22.358
    - type: ndcg_at_100
      value: 33.625
    - type: ndcg_at_1000
      value: 45.211
    - type: ndcg_at_3
      value: 26.345000000000002
    - type: ndcg_at_5
      value: 22.743
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 20.612
    - type: precision_at_100
      value: 7.5920000000000005
    - type: precision_at_1000
      value: 1.494
    - type: precision_at_3
      value: 28.571
    - type: precision_at_5
      value: 22.857
    - type: recall_at_1
      value: 1.494
    - type: recall_at_10
      value: 14.657
    - type: recall_at_100
      value: 45.273
    - type: recall_at_1000
      value: 80.66
    - type: recall_at_3
      value: 5.904
    - type: recall_at_5
      value: 8.053
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 68.7092
    - type: ap
      value: 13.166630913914243
    - type: f1
      value: 52.79567185490722
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.9660441426146
    - type: f1
      value: 55.17567905972333
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 37.58792693202503
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.88269654884664
    - type: cos_sim_ap
      value: 66.09276985843528
    - type: cos_sim_f1
      value: 63.225649744959924
    - type: cos_sim_precision
      value: 58.573357335733576
    - type: cos_sim_recall
      value: 68.68073878627968
    - type: dot_accuracy
      value: 83.88269654884664
    - type: dot_ap
      value: 66.09276747019544
    - type: dot_f1
      value: 63.225649744959924
    - type: dot_precision
      value: 58.573357335733576
    - type: dot_recall
      value: 68.68073878627968
    - type: euclidean_accuracy
      value: 83.88269654884664
    - type: euclidean_ap
      value: 66.09276985843528
    - type: euclidean_f1
      value: 63.225649744959924
    - type: euclidean_precision
      value: 58.573357335733576
    - type: euclidean_recall
      value: 68.68073878627968
    - type: manhattan_accuracy
      value: 82.69058830541813
    - type: manhattan_ap
      value: 62.74574997540533
    - type: manhattan_f1
      value: 59.96326905417815
    - type: manhattan_precision
      value: 53.06785859406745
    - type: manhattan_recall
      value: 68.91820580474935
    - type: max_accuracy
      value: 83.88269654884664
    - type: max_ap
      value: 66.09276985843528
    - type: max_f1
      value: 63.225649744959924
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.57519307641557
    - type: cos_sim_ap
      value: 83.25474211186804
    - type: cos_sim_f1
      value: 75.56529680365297
    - type: cos_sim_precision
      value: 71.89129074859248
    - type: cos_sim_recall
      value: 79.63504773637203
    - type: dot_accuracy
      value: 87.57519307641557
    - type: dot_ap
      value: 83.25474240805171
    - type: dot_f1
      value: 75.56529680365297
    - type: dot_precision
      value: 71.89129074859248
    - type: dot_recall
      value: 79.63504773637203
    - type: euclidean_accuracy
      value: 87.57519307641557
    - type: euclidean_ap
      value: 83.25474211186805
    - type: euclidean_f1
      value: 75.56529680365297
    - type: euclidean_precision
      value: 71.89129074859248
    - type: euclidean_recall
      value: 79.63504773637203
    - type: manhattan_accuracy
      value: 87.60041914076145
    - type: manhattan_ap
      value: 83.11911507311108
    - type: manhattan_f1
      value: 75.27478546649627
    - type: manhattan_precision
      value: 71.59130374383552
    - type: manhattan_recall
      value: 79.35786880197105
    - type: max_accuracy
      value: 87.60041914076145
    - type: max_ap
      value: 83.25474240805171
    - type: max_f1
      value: 75.56529680365297
---
