mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_300_correct
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.64179104477613
    - type: ap
      value: 34.159744260532136
    - type: f1
      value: 65.53100428249736
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.08860000000001
    - type: ap
      value: 60.14010028941874
    - type: f1
      value: 64.83351000800369
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.446
    - type: f1
      value: 33.94159065718346
  - 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: 34.697
    - type: map_at_100
      value: 35.941
    - type: map_at_1000
      value: 35.965
    - type: map_at_3
      value: 30.322
    - type: map_at_5
      value: 32.757999999999996
    - type: mrr_at_1
      value: 21.693
    - type: mrr_at_10
      value: 34.915
    - type: mrr_at_100
      value: 36.159
    - type: mrr_at_1000
      value: 36.184
    - type: mrr_at_3
      value: 30.464999999999996
    - type: mrr_at_5
      value: 32.965
    - type: ndcg_at_1
      value: 21.124000000000002
    - type: ndcg_at_10
      value: 42.515
    - type: ndcg_at_100
      value: 48.304
    - type: ndcg_at_1000
      value: 48.92
    - type: ndcg_at_3
      value: 33.397
    - type: ndcg_at_5
      value: 37.835
    - type: precision_at_1
      value: 21.124000000000002
    - type: precision_at_10
      value: 6.764
    - type: precision_at_100
      value: 0.942
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.106
    - type: precision_at_5
      value: 10.639999999999999
    - type: recall_at_1
      value: 21.124000000000002
    - type: recall_at_10
      value: 67.63900000000001
    - type: recall_at_100
      value: 94.16799999999999
    - type: recall_at_1000
      value: 98.933
    - type: recall_at_3
      value: 42.319
    - type: recall_at_5
      value: 53.201
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 33.518293831744074
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 23.84324528943955
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.14496107592509
    - type: mrr
      value: 67.71039440707031
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 80.81796255278779
    - type: cos_sim_spearman
      value: 79.26023973327042
    - type: euclidean_pearson
      value: 80.28015896874675
    - type: euclidean_spearman
      value: 79.26023973327042
    - type: manhattan_pearson
      value: 80.86598836117923
    - type: manhattan_spearman
      value: 79.52108905039304
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 72.09415584415585
    - type: f1
      value: 71.26661446466763
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.07186711903559
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.19051850098106
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.83
    - type: map_at_10
      value: 29.202
    - type: map_at_100
      value: 30.312
    - type: map_at_1000
      value: 30.473
    - type: map_at_3
      value: 26.756999999999998
    - type: map_at_5
      value: 28.249999999999996
    - type: mrr_at_1
      value: 27.611
    - type: mrr_at_10
      value: 34.859
    - type: mrr_at_100
      value: 35.711
    - type: mrr_at_1000
      value: 35.789
    - type: mrr_at_3
      value: 32.761
    - type: mrr_at_5
      value: 34.127
    - type: ndcg_at_1
      value: 27.611
    - type: ndcg_at_10
      value: 33.978
    - type: ndcg_at_100
      value: 38.931
    - type: ndcg_at_1000
      value: 42.204
    - type: ndcg_at_3
      value: 30.541
    - type: ndcg_at_5
      value: 32.272
    - type: precision_at_1
      value: 27.611
    - type: precision_at_10
      value: 6.366
    - type: precision_at_100
      value: 1.0959999999999999
    - type: precision_at_1000
      value: 0.168
    - type: precision_at_3
      value: 14.783
    - type: precision_at_5
      value: 10.786999999999999
    - type: recall_at_1
      value: 21.83
    - type: recall_at_10
      value: 42.213
    - type: recall_at_100
      value: 64.104
    - type: recall_at_1000
      value: 86.378
    - type: recall_at_3
      value: 31.624000000000002
    - type: recall_at_5
      value: 36.693999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.703000000000003
    - type: map_at_10
      value: 22.081999999999997
    - type: map_at_100
      value: 22.961000000000002
    - type: map_at_1000
      value: 23.087
    - type: map_at_3
      value: 20.185
    - type: map_at_5
      value: 21.199
    - type: mrr_at_1
      value: 21.019
    - type: mrr_at_10
      value: 26.307000000000002
    - type: mrr_at_100
      value: 27.053
    - type: mrr_at_1000
      value: 27.13
    - type: mrr_at_3
      value: 24.395
    - type: mrr_at_5
      value: 25.395
    - type: ndcg_at_1
      value: 21.019
    - type: ndcg_at_10
      value: 25.906000000000002
    - type: ndcg_at_100
      value: 30.051
    - type: ndcg_at_1000
      value: 32.974
    - type: ndcg_at_3
      value: 22.578
    - type: ndcg_at_5
      value: 23.964
    - type: precision_at_1
      value: 21.019
    - type: precision_at_10
      value: 4.828
    - type: precision_at_100
      value: 0.8630000000000001
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 10.722
    - type: precision_at_5
      value: 7.682
    - type: recall_at_1
      value: 16.703000000000003
    - type: recall_at_10
      value: 33.237
    - type: recall_at_100
      value: 51.71
    - type: recall_at_1000
      value: 71.625
    - type: recall_at_3
      value: 23.598
    - type: recall_at_5
      value: 27.339000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.507
    - type: map_at_10
      value: 33.812999999999995
    - type: map_at_100
      value: 34.899
    - type: map_at_1000
      value: 34.995
    - type: map_at_3
      value: 31.430999999999997
    - type: map_at_5
      value: 32.72
    - type: mrr_at_1
      value: 29.53
    - type: mrr_at_10
      value: 36.961
    - type: mrr_at_100
      value: 37.839
    - type: mrr_at_1000
      value: 37.9
    - type: mrr_at_3
      value: 34.775
    - type: mrr_at_5
      value: 35.931999999999995
    - type: ndcg_at_1
      value: 29.53
    - type: ndcg_at_10
      value: 38.468999999999994
    - type: ndcg_at_100
      value: 43.652
    - type: ndcg_at_1000
      value: 45.873999999999995
    - type: ndcg_at_3
      value: 34.041
    - type: ndcg_at_5
      value: 36.042
    - type: precision_at_1
      value: 29.53
    - type: precision_at_10
      value: 6.263000000000001
    - type: precision_at_100
      value: 0.971
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 15.171999999999999
    - type: precision_at_5
      value: 10.458
    - type: recall_at_1
      value: 25.507
    - type: recall_at_10
      value: 49.464999999999996
    - type: recall_at_100
      value: 72.912
    - type: recall_at_1000
      value: 88.993
    - type: recall_at_3
      value: 37.492999999999995
    - type: recall_at_5
      value: 42.494
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 11.827
    - type: map_at_10
      value: 15.834999999999999
    - type: map_at_100
      value: 16.608999999999998
    - type: map_at_1000
      value: 16.718
    - type: map_at_3
      value: 14.510000000000002
    - type: map_at_5
      value: 15.213
    - type: mrr_at_1
      value: 12.994
    - type: mrr_at_10
      value: 17.09
    - type: mrr_at_100
      value: 17.868000000000002
    - type: mrr_at_1000
      value: 17.971
    - type: mrr_at_3
      value: 15.763
    - type: mrr_at_5
      value: 16.48
    - type: ndcg_at_1
      value: 12.994
    - type: ndcg_at_10
      value: 18.382
    - type: ndcg_at_100
      value: 22.656000000000002
    - type: ndcg_at_1000
      value: 26.017000000000003
    - type: ndcg_at_3
      value: 15.662
    - type: ndcg_at_5
      value: 16.902
    - type: precision_at_1
      value: 12.994
    - type: precision_at_10
      value: 2.836
    - type: precision_at_100
      value: 0.529
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.516
    - type: precision_at_5
      value: 4.655
    - type: recall_at_1
      value: 11.827
    - type: recall_at_10
      value: 25.179000000000002
    - type: recall_at_100
      value: 45.749
    - type: recall_at_1000
      value: 72.057
    - type: recall_at_3
      value: 17.740000000000002
    - type: recall_at_5
      value: 20.659
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.497999999999999
    - type: map_at_10
      value: 9.685
    - type: map_at_100
      value: 10.355
    - type: map_at_1000
      value: 10.481
    - type: map_at_3
      value: 8.545
    - type: map_at_5
      value: 9.135
    - type: mrr_at_1
      value: 8.458
    - type: mrr_at_10
      value: 11.968
    - type: mrr_at_100
      value: 12.681999999999999
    - type: mrr_at_1000
      value: 12.784
    - type: mrr_at_3
      value: 10.613999999999999
    - type: mrr_at_5
      value: 11.347
    - type: ndcg_at_1
      value: 8.458
    - type: ndcg_at_10
      value: 12.101
    - type: ndcg_at_100
      value: 15.809000000000001
    - type: ndcg_at_1000
      value: 19.514
    - type: ndcg_at_3
      value: 9.802
    - type: ndcg_at_5
      value: 10.796
    - type: precision_at_1
      value: 8.458
    - type: precision_at_10
      value: 2.313
    - type: precision_at_100
      value: 0.48900000000000005
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 4.726
    - type: precision_at_5
      value: 3.5319999999999996
    - type: recall_at_1
      value: 6.497999999999999
    - type: recall_at_10
      value: 17.455000000000002
    - type: recall_at_100
      value: 34.374
    - type: recall_at_1000
      value: 61.881
    - type: recall_at_3
      value: 10.955
    - type: recall_at_5
      value: 13.489
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 16.775000000000002
    - type: map_at_10
      value: 22.869999999999997
    - type: map_at_100
      value: 23.997
    - type: map_at_1000
      value: 24.136
    - type: map_at_3
      value: 20.956
    - type: map_at_5
      value: 21.936
    - type: mrr_at_1
      value: 20.885
    - type: mrr_at_10
      value: 27.388
    - type: mrr_at_100
      value: 28.314
    - type: mrr_at_1000
      value: 28.397
    - type: mrr_at_3
      value: 25.489
    - type: mrr_at_5
      value: 26.480999999999998
    - type: ndcg_at_1
      value: 20.885
    - type: ndcg_at_10
      value: 27.014
    - type: ndcg_at_100
      value: 32.499
    - type: ndcg_at_1000
      value: 35.64
    - type: ndcg_at_3
      value: 23.695
    - type: ndcg_at_5
      value: 25.061
    - type: precision_at_1
      value: 20.885
    - type: precision_at_10
      value: 4.928
    - type: precision_at_100
      value: 0.923
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_3
      value: 11.229
    - type: precision_at_5
      value: 7.988
    - type: recall_at_1
      value: 16.775000000000002
    - type: recall_at_10
      value: 35.189
    - type: recall_at_100
      value: 59.414
    - type: recall_at_1000
      value: 81.073
    - type: recall_at_3
      value: 25.621
    - type: recall_at_5
      value: 29.209000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 11.918
    - type: map_at_10
      value: 17.445
    - type: map_at_100
      value: 18.412
    - type: map_at_1000
      value: 18.556
    - type: map_at_3
      value: 15.715000000000002
    - type: map_at_5
      value: 16.622
    - type: mrr_at_1
      value: 15.068000000000001
    - type: mrr_at_10
      value: 20.82
    - type: mrr_at_100
      value: 21.7
    - type: mrr_at_1000
      value: 21.8
    - type: mrr_at_3
      value: 19.121
    - type: mrr_at_5
      value: 19.994
    - type: ndcg_at_1
      value: 15.068000000000001
    - type: ndcg_at_10
      value: 21.063000000000002
    - type: ndcg_at_100
      value: 25.81
    - type: ndcg_at_1000
      value: 29.446
    - type: ndcg_at_3
      value: 17.951
    - type: ndcg_at_5
      value: 19.246
    - type: precision_at_1
      value: 15.068000000000001
    - type: precision_at_10
      value: 3.995
    - type: precision_at_100
      value: 0.758
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 8.828
    - type: precision_at_5
      value: 6.3469999999999995
    - type: recall_at_1
      value: 11.918
    - type: recall_at_10
      value: 28.693
    - type: recall_at_100
      value: 49.451
    - type: recall_at_1000
      value: 75.33999999999999
    - type: recall_at_3
      value: 20.044
    - type: recall_at_5
      value: 23.472
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 13.772666666666666
    - type: map_at_10
      value: 18.910083333333336
    - type: map_at_100
      value: 19.776333333333334
    - type: map_at_1000
      value: 19.9015
    - type: map_at_3
      value: 17.286333333333335
    - type: map_at_5
      value: 18.16575
    - type: mrr_at_1
      value: 16.76525
    - type: mrr_at_10
      value: 21.966250000000002
    - type: mrr_at_100
      value: 22.74941666666667
    - type: mrr_at_1000
      value: 22.837916666666665
    - type: mrr_at_3
      value: 20.33125
    - type: mrr_at_5
      value: 21.24025
    - type: ndcg_at_1
      value: 16.76525
    - type: ndcg_at_10
      value: 22.28141666666666
    - type: ndcg_at_100
      value: 26.642999999999994
    - type: ndcg_at_1000
      value: 29.849750000000004
    - type: ndcg_at_3
      value: 19.343999999999998
    - type: ndcg_at_5
      value: 20.661083333333334
    - type: precision_at_1
      value: 16.76525
    - type: precision_at_10
      value: 3.972666666666666
    - type: precision_at_100
      value: 0.7320833333333333
    - type: precision_at_1000
      value: 0.11858333333333335
    - type: precision_at_3
      value: 9.005583333333334
    - type: precision_at_5
      value: 6.460416666666667
    - type: recall_at_1
      value: 13.772666666666666
    - type: recall_at_10
      value: 29.464333333333332
    - type: recall_at_100
      value: 49.43716666666667
    - type: recall_at_1000
      value: 72.77666666666667
    - type: recall_at_3
      value: 21.147083333333335
    - type: recall_at_5
      value: 24.555500000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 9.792
    - type: map_at_10
      value: 13.836
    - type: map_at_100
      value: 14.435999999999998
    - type: map_at_1000
      value: 14.519000000000002
    - type: map_at_3
      value: 12.389999999999999
    - type: map_at_5
      value: 13.255
    - type: mrr_at_1
      value: 12.117
    - type: mrr_at_10
      value: 16.024
    - type: mrr_at_100
      value: 16.616
    - type: mrr_at_1000
      value: 16.694
    - type: mrr_at_3
      value: 14.519000000000002
    - type: mrr_at_5
      value: 15.409
    - type: ndcg_at_1
      value: 12.117
    - type: ndcg_at_10
      value: 16.607
    - type: ndcg_at_100
      value: 19.933999999999997
    - type: ndcg_at_1000
      value: 22.475
    - type: ndcg_at_3
      value: 13.875000000000002
    - type: ndcg_at_5
      value: 15.276
    - type: precision_at_1
      value: 12.117
    - type: precision_at_10
      value: 2.899
    - type: precision_at_100
      value: 0.509
    - type: precision_at_1000
      value: 0.079
    - type: precision_at_3
      value: 6.390999999999999
    - type: precision_at_5
      value: 4.755
    - type: recall_at_1
      value: 9.792
    - type: recall_at_10
      value: 23.230999999999998
    - type: recall_at_100
      value: 39.068999999999996
    - type: recall_at_1000
      value: 58.706
    - type: recall_at_3
      value: 15.414
    - type: recall_at_5
      value: 19.066
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.575
    - type: map_at_10
      value: 10.82
    - type: map_at_100
      value: 11.416
    - type: map_at_1000
      value: 11.537
    - type: map_at_3
      value: 9.758
    - type: map_at_5
      value: 10.362
    - type: mrr_at_1
      value: 9.36
    - type: mrr_at_10
      value: 13.007
    - type: mrr_at_100
      value: 13.621
    - type: mrr_at_1000
      value: 13.722999999999999
    - type: mrr_at_3
      value: 11.734
    - type: mrr_at_5
      value: 12.493
    - type: ndcg_at_1
      value: 9.36
    - type: ndcg_at_10
      value: 13.120000000000001
    - type: ndcg_at_100
      value: 16.486
    - type: ndcg_at_1000
      value: 20.01
    - type: ndcg_at_3
      value: 11.044
    - type: ndcg_at_5
      value: 12.064
    - type: precision_at_1
      value: 9.36
    - type: precision_at_10
      value: 2.4539999999999997
    - type: precision_at_100
      value: 0.498
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 5.231
    - type: precision_at_5
      value: 3.9570000000000003
    - type: recall_at_1
      value: 7.575
    - type: recall_at_10
      value: 17.968999999999998
    - type: recall_at_100
      value: 33.736
    - type: recall_at_1000
      value: 60.013000000000005
    - type: recall_at_3
      value: 12.293
    - type: recall_at_5
      value: 14.729999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 11.837
    - type: map_at_10
      value: 16.402
    - type: map_at_100
      value: 17.202
    - type: map_at_1000
      value: 17.314
    - type: map_at_3
      value: 14.908
    - type: map_at_5
      value: 15.717
    - type: mrr_at_1
      value: 14.366000000000001
    - type: mrr_at_10
      value: 19.252
    - type: mrr_at_100
      value: 20.078
    - type: mrr_at_1000
      value: 20.168
    - type: mrr_at_3
      value: 17.693
    - type: mrr_at_5
      value: 18.523
    - type: ndcg_at_1
      value: 14.366000000000001
    - type: ndcg_at_10
      value: 19.557
    - type: ndcg_at_100
      value: 23.821
    - type: ndcg_at_1000
      value: 27.095000000000002
    - type: ndcg_at_3
      value: 16.638
    - type: ndcg_at_5
      value: 17.927
    - type: precision_at_1
      value: 14.366000000000001
    - type: precision_at_10
      value: 3.3680000000000003
    - type: precision_at_100
      value: 0.605
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 7.649
    - type: precision_at_5
      value: 5.448
    - type: recall_at_1
      value: 11.837
    - type: recall_at_10
      value: 26.623
    - type: recall_at_100
      value: 46.274
    - type: recall_at_1000
      value: 70.49499999999999
    - type: recall_at_3
      value: 18.429000000000002
    - type: recall_at_5
      value: 21.711
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.091999999999999
    - type: map_at_10
      value: 20.265
    - type: map_at_100
      value: 21.262
    - type: map_at_1000
      value: 21.433
    - type: map_at_3
      value: 18.755
    - type: map_at_5
      value: 19.55
    - type: mrr_at_1
      value: 17.391000000000002
    - type: mrr_at_10
      value: 23.730999999999998
    - type: mrr_at_100
      value: 24.534
    - type: mrr_at_1000
      value: 24.616
    - type: mrr_at_3
      value: 22.2
    - type: mrr_at_5
      value: 23.218
    - type: ndcg_at_1
      value: 17.391000000000002
    - type: ndcg_at_10
      value: 24.095
    - type: ndcg_at_100
      value: 28.762
    - type: ndcg_at_1000
      value: 32.279
    - type: ndcg_at_3
      value: 21.617
    - type: ndcg_at_5
      value: 22.829
    - type: precision_at_1
      value: 17.391000000000002
    - type: precision_at_10
      value: 4.723
    - type: precision_at_100
      value: 1.028
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 10.474
    - type: precision_at_5
      value: 7.628
    - type: recall_at_1
      value: 14.091999999999999
    - type: recall_at_10
      value: 31.102
    - type: recall_at_100
      value: 53.197
    - type: recall_at_1000
      value: 77.602
    - type: recall_at_3
      value: 23.937
    - type: recall_at_5
      value: 27.060000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 10.918
    - type: map_at_10
      value: 14.666
    - type: map_at_100
      value: 15.455
    - type: map_at_1000
      value: 15.568999999999999
    - type: map_at_3
      value: 13.526
    - type: map_at_5
      value: 14.030000000000001
    - type: mrr_at_1
      value: 12.384
    - type: mrr_at_10
      value: 16.188
    - type: mrr_at_100
      value: 16.977
    - type: mrr_at_1000
      value: 17.083000000000002
    - type: mrr_at_3
      value: 14.911
    - type: mrr_at_5
      value: 15.484
    - type: ndcg_at_1
      value: 12.384
    - type: ndcg_at_10
      value: 17.085
    - type: ndcg_at_100
      value: 21.305
    - type: ndcg_at_1000
      value: 24.669
    - type: ndcg_at_3
      value: 14.684
    - type: ndcg_at_5
      value: 15.554000000000002
    - type: precision_at_1
      value: 12.384
    - type: precision_at_10
      value: 2.699
    - type: precision_at_100
      value: 0.516
    - type: precision_at_1000
      value: 0.08800000000000001
    - type: precision_at_3
      value: 6.346
    - type: precision_at_5
      value: 4.288
    - type: recall_at_1
      value: 10.918
    - type: recall_at_10
      value: 23.216
    - type: recall_at_100
      value: 43.256
    - type: recall_at_1000
      value: 69.157
    - type: recall_at_3
      value: 16.617
    - type: recall_at_5
      value: 18.743000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.3629999999999995
    - type: map_at_10
      value: 9.915000000000001
    - type: map_at_100
      value: 11.212
    - type: map_at_1000
      value: 11.405
    - type: map_at_3
      value: 7.9479999999999995
    - type: map_at_5
      value: 8.862
    - type: mrr_at_1
      value: 11.661000000000001
    - type: mrr_at_10
      value: 19.907
    - type: mrr_at_100
      value: 21.046
    - type: mrr_at_1000
      value: 21.124000000000002
    - type: mrr_at_3
      value: 17.09
    - type: mrr_at_5
      value: 18.582
    - type: ndcg_at_1
      value: 11.661000000000001
    - type: ndcg_at_10
      value: 15.129999999999999
    - type: ndcg_at_100
      value: 21.393
    - type: ndcg_at_1000
      value: 25.506
    - type: ndcg_at_3
      value: 11.325000000000001
    - type: ndcg_at_5
      value: 12.604000000000001
    - type: precision_at_1
      value: 11.661000000000001
    - type: precision_at_10
      value: 5.186
    - type: precision_at_100
      value: 1.197
    - type: precision_at_1000
      value: 0.194
    - type: precision_at_3
      value: 8.817
    - type: precision_at_5
      value: 7.101
    - type: recall_at_1
      value: 5.3629999999999995
    - type: recall_at_10
      value: 19.82
    - type: recall_at_100
      value: 42.22
    - type: recall_at_1000
      value: 66.17
    - type: recall_at_3
      value: 10.904
    - type: recall_at_5
      value: 14.088000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 3.385
    - type: map_at_10
      value: 7.8149999999999995
    - type: map_at_100
      value: 10.774000000000001
    - type: map_at_1000
      value: 11.568000000000001
    - type: map_at_3
      value: 5.539000000000001
    - type: map_at_5
      value: 6.603000000000001
    - type: mrr_at_1
      value: 34.5
    - type: mrr_at_10
      value: 44.3
    - type: mrr_at_100
      value: 45.218
    - type: mrr_at_1000
      value: 45.261
    - type: mrr_at_3
      value: 41.75
    - type: mrr_at_5
      value: 43.3
    - type: ndcg_at_1
      value: 25.25
    - type: ndcg_at_10
      value: 20.493
    - type: ndcg_at_100
      value: 22.833000000000002
    - type: ndcg_at_1000
      value: 29.278
    - type: ndcg_at_3
      value: 22.862
    - type: ndcg_at_5
      value: 21.636
    - type: precision_at_1
      value: 34.5
    - type: precision_at_10
      value: 18.275
    - type: precision_at_100
      value: 5.685
    - type: precision_at_1000
      value: 1.206
    - type: precision_at_3
      value: 26.917
    - type: precision_at_5
      value: 23.45
    - type: recall_at_1
      value: 3.385
    - type: recall_at_10
      value: 12.22
    - type: recall_at_100
      value: 28.225
    - type: recall_at_1000
      value: 50.20099999999999
    - type: recall_at_3
      value: 6.603000000000001
    - type: recall_at_5
      value: 8.872
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.30500000000001
    - type: f1
      value: 40.23633979795541
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 12.283
    - type: map_at_10
      value: 18.655
    - type: map_at_100
      value: 19.587
    - type: map_at_1000
      value: 19.666
    - type: map_at_3
      value: 16.592000000000002
    - type: map_at_5
      value: 17.655
    - type: mrr_at_1
      value: 13.126
    - type: mrr_at_10
      value: 19.869999999999997
    - type: mrr_at_100
      value: 20.809
    - type: mrr_at_1000
      value: 20.883
    - type: mrr_at_3
      value: 17.697
    - type: mrr_at_5
      value: 18.829
    - type: ndcg_at_1
      value: 13.126
    - type: ndcg_at_10
      value: 22.631999999999998
    - type: ndcg_at_100
      value: 27.476
    - type: ndcg_at_1000
      value: 29.788999999999998
    - type: ndcg_at_3
      value: 18.295
    - type: ndcg_at_5
      value: 20.224
    - type: precision_at_1
      value: 13.126
    - type: precision_at_10
      value: 3.705
    - type: precision_at_100
      value: 0.629
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 7.951
    - type: precision_at_5
      value: 5.800000000000001
    - type: recall_at_1
      value: 12.283
    - type: recall_at_10
      value: 34.016999999999996
    - type: recall_at_100
      value: 56.83200000000001
    - type: recall_at_1000
      value: 74.942
    - type: recall_at_3
      value: 22.104
    - type: recall_at_5
      value: 26.75
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 5.615
    - type: map_at_10
      value: 9.742
    - type: map_at_100
      value: 10.782
    - type: map_at_1000
      value: 10.981
    - type: map_at_3
      value: 8.324
    - type: map_at_5
      value: 9.097
    - type: mrr_at_1
      value: 11.574
    - type: mrr_at_10
      value: 17.386
    - type: mrr_at_100
      value: 18.349
    - type: mrr_at_1000
      value: 18.451
    - type: mrr_at_3
      value: 15.406
    - type: mrr_at_5
      value: 16.448
    - type: ndcg_at_1
      value: 11.574
    - type: ndcg_at_10
      value: 13.623
    - type: ndcg_at_100
      value: 18.82
    - type: ndcg_at_1000
      value: 23.534
    - type: ndcg_at_3
      value: 11.521
    - type: ndcg_at_5
      value: 12.3
    - type: precision_at_1
      value: 11.574
    - type: precision_at_10
      value: 3.997
    - type: precision_at_100
      value: 0.918
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 7.973
    - type: precision_at_5
      value: 6.049
    - type: recall_at_1
      value: 5.615
    - type: recall_at_10
      value: 17.588
    - type: recall_at_100
      value: 38.091
    - type: recall_at_1000
      value: 68.12
    - type: recall_at_3
      value: 10.763
    - type: recall_at_5
      value: 13.65
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 14.868
    - type: map_at_10
      value: 20.803
    - type: map_at_100
      value: 21.625
    - type: map_at_1000
      value: 21.739
    - type: map_at_3
      value: 19.075
    - type: map_at_5
      value: 20.072000000000003
    - type: mrr_at_1
      value: 29.737000000000002
    - type: mrr_at_10
      value: 36.177
    - type: mrr_at_100
      value: 36.923
    - type: mrr_at_1000
      value: 36.992999999999995
    - type: mrr_at_3
      value: 34.414
    - type: mrr_at_5
      value: 35.417
    - type: ndcg_at_1
      value: 29.737000000000002
    - type: ndcg_at_10
      value: 26.884000000000004
    - type: ndcg_at_100
      value: 30.873
    - type: ndcg_at_1000
      value: 33.727000000000004
    - type: ndcg_at_3
      value: 23.557
    - type: ndcg_at_5
      value: 25.215
    - type: precision_at_1
      value: 29.737000000000002
    - type: precision_at_10
      value: 5.966
    - type: precision_at_100
      value: 0.9169999999999999
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 14.868
    - type: precision_at_5
      value: 10.236
    - type: recall_at_1
      value: 14.868
    - type: recall_at_10
      value: 29.831000000000003
    - type: recall_at_100
      value: 45.861000000000004
    - type: recall_at_1000
      value: 64.956
    - type: recall_at_3
      value: 22.302
    - type: recall_at_5
      value: 25.591
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.77400000000002
    - type: ap
      value: 59.8271641498241
    - type: f1
      value: 64.63116569862132
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 5.795
    - type: map_at_10
      value: 9.893
    - type: map_at_100
      value: 10.7
    - type: map_at_1000
      value: 10.801
    - type: map_at_3
      value: 8.402
    - type: map_at_5
      value: 9.168
    - type: mrr_at_1
      value: 5.974
    - type: mrr_at_10
      value: 10.168000000000001
    - type: mrr_at_100
      value: 10.983
    - type: mrr_at_1000
      value: 11.081000000000001
    - type: mrr_at_3
      value: 8.656
    - type: mrr_at_5
      value: 9.434
    - type: ndcg_at_1
      value: 5.946
    - type: ndcg_at_10
      value: 12.485
    - type: ndcg_at_100
      value: 16.982
    - type: ndcg_at_1000
      value: 20.038
    - type: ndcg_at_3
      value: 9.34
    - type: ndcg_at_5
      value: 10.725999999999999
    - type: precision_at_1
      value: 5.946
    - type: precision_at_10
      value: 2.1399999999999997
    - type: precision_at_100
      value: 0.44799999999999995
    - type: precision_at_1000
      value: 0.07100000000000001
    - type: precision_at_3
      value: 4.093
    - type: precision_at_5
      value: 3.16
    - type: recall_at_1
      value: 5.795
    - type: recall_at_10
      value: 20.558
    - type: recall_at_100
      value: 42.65
    - type: recall_at_1000
      value: 67.243
    - type: recall_at_3
      value: 11.812000000000001
    - type: recall_at_5
      value: 15.162
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.16324669402644
    - type: f1
      value: 88.43597223143398
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.58595531235751
    - type: f1
      value: 41.403903752740575
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.076664425016816
    - type: f1
      value: 61.059741194179736
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.74781439139205
    - type: f1
      value: 68.49712942816453
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.87584903553076
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.076231171218932
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.963878084019868
    - type: mrr
      value: 29.861285643130348
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.319
    - type: map_at_10
      value: 6.807
    - type: map_at_100
      value: 8.634
    - type: map_at_1000
      value: 9.887
    - type: map_at_3
      value: 5.153
    - type: map_at_5
      value: 5.863
    - type: mrr_at_1
      value: 31.269000000000002
    - type: mrr_at_10
      value: 40.787
    - type: mrr_at_100
      value: 41.498000000000005
    - type: mrr_at_1000
      value: 41.563
    - type: mrr_at_3
      value: 38.287
    - type: mrr_at_5
      value: 39.772999999999996
    - type: ndcg_at_1
      value: 28.947
    - type: ndcg_at_10
      value: 22.505
    - type: ndcg_at_100
      value: 21.15
    - type: ndcg_at_1000
      value: 30.887999999999998
    - type: ndcg_at_3
      value: 25.357000000000003
    - type: ndcg_at_5
      value: 24.492
    - type: precision_at_1
      value: 31.269000000000002
    - type: precision_at_10
      value: 16.594
    - type: precision_at_100
      value: 6.031000000000001
    - type: precision_at_1000
      value: 1.9300000000000002
    - type: precision_at_3
      value: 23.942
    - type: precision_at_5
      value: 21.424000000000003
    - type: recall_at_1
      value: 3.319
    - type: recall_at_10
      value: 11.189
    - type: recall_at_100
      value: 23.278
    - type: recall_at_1000
      value: 58.019
    - type: recall_at_3
      value: 6.6129999999999995
    - type: recall_at_5
      value: 8.093
  - 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: 14.465
    - type: map_at_100
      value: 15.564
    - type: map_at_1000
      value: 15.667
    - type: map_at_3
      value: 12.258
    - type: map_at_5
      value: 13.377
    - type: mrr_at_1
      value: 9.647
    - type: mrr_at_10
      value: 16.003
    - type: mrr_at_100
      value: 17.052999999999997
    - type: mrr_at_1000
      value: 17.14
    - type: mrr_at_3
      value: 13.688
    - type: mrr_at_5
      value: 14.868
    - type: ndcg_at_1
      value: 9.647
    - type: ndcg_at_10
      value: 18.519
    - type: ndcg_at_100
      value: 24.247
    - type: ndcg_at_1000
      value: 27.113
    - type: ndcg_at_3
      value: 13.88
    - type: ndcg_at_5
      value: 15.913
    - type: precision_at_1
      value: 9.647
    - type: precision_at_10
      value: 3.476
    - type: precision_at_100
      value: 0.676
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 6.566
    - type: precision_at_5
      value: 5.075
    - type: recall_at_1
      value: 8.413
    - type: recall_at_10
      value: 29.664
    - type: recall_at_100
      value: 56.508
    - type: recall_at_1000
      value: 78.58699999999999
    - type: recall_at_3
      value: 17.207
    - type: recall_at_5
      value: 22.006999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 60.949
    - type: map_at_10
      value: 73.328
    - type: map_at_100
      value: 74.127
    - type: map_at_1000
      value: 74.166
    - type: map_at_3
      value: 70.415
    - type: map_at_5
      value: 72.138
    - type: mrr_at_1
      value: 70.3
    - type: mrr_at_10
      value: 77.842
    - type: mrr_at_100
      value: 78.133
    - type: mrr_at_1000
      value: 78.14
    - type: mrr_at_3
      value: 76.28200000000001
    - type: mrr_at_5
      value: 77.268
    - type: ndcg_at_1
      value: 70.35
    - type: ndcg_at_10
      value: 78.159
    - type: ndcg_at_100
      value: 80.508
    - type: ndcg_at_1000
      value: 81.0
    - type: ndcg_at_3
      value: 74.42999999999999
    - type: ndcg_at_5
      value: 76.292
    - type: precision_at_1
      value: 70.35
    - type: precision_at_10
      value: 11.823
    - type: precision_at_100
      value: 1.432
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 32.196999999999996
    - type: precision_at_5
      value: 21.310000000000002
    - type: recall_at_1
      value: 60.949
    - type: recall_at_10
      value: 87.467
    - type: recall_at_100
      value: 96.538
    - type: recall_at_1000
      value: 99.392
    - type: recall_at_3
      value: 76.785
    - type: recall_at_5
      value: 81.96900000000001
    - type: map_at_1
      value: 2.713
    - type: map_at_10
      value: 6.231
    - type: map_at_100
      value: 7.498
    - type: map_at_1000
      value: 7.739
    - type: map_at_3
      value: 4.605
    - type: map_at_5
      value: 5.425
    - type: mrr_at_1
      value: 13.3
    - type: mrr_at_10
      value: 20.465
    - type: mrr_at_100
      value: 21.77
    - type: mrr_at_1000
      value: 21.86
    - type: mrr_at_3
      value: 17.9
    - type: mrr_at_5
      value: 19.43
    - type: ndcg_at_1
      value: 13.3
    - type: ndcg_at_10
      value: 11.212
    - type: ndcg_at_100
      value: 17.29
    - type: ndcg_at_1000
      value: 22.394
    - type: ndcg_at_3
      value: 10.612
    - type: ndcg_at_5
      value: 9.347
    - type: precision_at_1
      value: 13.3
    - type: precision_at_10
      value: 5.81
    - type: precision_at_100
      value: 1.466
    - type: precision_at_1000
      value: 0.27
    - type: precision_at_3
      value: 9.9
    - type: precision_at_5
      value: 8.24
    - type: recall_at_1
      value: 2.713
    - type: recall_at_10
      value: 11.782
    - type: recall_at_100
      value: 29.782999999999998
    - type: recall_at_1000
      value: 54.893
    - type: recall_at_3
      value: 6.033
    - type: recall_at_5
      value: 8.347999999999999
    - type: map_at_1
      value: 0.087
    - type: map_at_10
      value: 0.623
    - type: map_at_100
      value: 3.476
    - type: map_at_1000
      value: 8.825
    - type: map_at_3
      value: 0.23800000000000002
    - type: map_at_5
      value: 0.35500000000000004
    - type: mrr_at_1
      value: 40.0
    - type: mrr_at_10
      value: 52.532000000000004
    - type: mrr_at_100
      value: 53.517
    - type: mrr_at_1000
      value: 53.517
    - type: mrr_at_3
      value: 48.667
    - type: mrr_at_5
      value: 50.166999999999994
    - type: ndcg_at_1
      value: 35.0
    - type: ndcg_at_10
      value: 35.978
    - type: ndcg_at_100
      value: 28.303
    - type: ndcg_at_1000
      value: 26.102999999999998
    - type: ndcg_at_3
      value: 37.653999999999996
    - type: ndcg_at_5
      value: 36.553999999999995
    - type: precision_at_1
      value: 40.0
    - type: precision_at_10
      value: 39.800000000000004
    - type: precision_at_100
      value: 29.92
    - type: precision_at_1000
      value: 12.994
    - type: precision_at_3
      value: 43.333
    - type: precision_at_5
      value: 40.8
    - type: recall_at_1
      value: 0.087
    - type: recall_at_10
      value: 0.881
    - type: recall_at_100
      value: 6.22
    - type: recall_at_1000
      value: 25.499
    - type: recall_at_3
      value: 0.272
    - type: recall_at_5
      value: 0.438
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 35.43953690940825
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 44.61896168883127
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.63214304205766
    - type: cos_sim_spearman
      value: 67.71499664891415
    - type: euclidean_pearson
      value: 72.96053690788013
    - type: euclidean_spearman
      value: 67.7150505294685
    - type: manhattan_pearson
      value: 71.49242466797857
    - type: manhattan_spearman
      value: 66.30592132651962
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 73.98202042588984
    - type: cos_sim_spearman
      value: 66.78936320389309
    - type: euclidean_pearson
      value: 70.21512206492227
    - type: euclidean_spearman
      value: 66.79063000258616
    - type: manhattan_pearson
      value: 71.20537398006118
    - type: manhattan_spearman
      value: 68.24653806879788
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.0171307532766
    - type: cos_sim_spearman
      value: 79.27543352695267
    - type: euclidean_pearson
      value: 78.89714107587923
    - type: euclidean_spearman
      value: 79.27547132927144
    - type: manhattan_pearson
      value: 79.42523987308677
    - type: manhattan_spearman
      value: 79.87737374819056
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.85725187643486
    - type: cos_sim_spearman
      value: 74.68123464950044
    - type: euclidean_pearson
      value: 76.98841747589384
    - type: euclidean_spearman
      value: 74.68122495830917
    - type: manhattan_pearson
      value: 77.08757593726176
    - type: manhattan_spearman
      value: 75.11390045739613
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.2129330424808
    - type: cos_sim_spearman
      value: 81.28472593405756
    - type: euclidean_pearson
      value: 81.33066572648997
    - type: euclidean_spearman
      value: 81.28473217949549
    - type: manhattan_pearson
      value: 82.06012406739636
    - type: manhattan_spearman
      value: 82.19433208543246
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.55753675792221
    - type: cos_sim_spearman
      value: 76.89378362885061
    - type: euclidean_pearson
      value: 76.6218145917796
    - type: euclidean_spearman
      value: 76.89461265271441
    - type: manhattan_pearson
      value: 77.4558040757338
    - type: manhattan_spearman
      value: 77.8288305199812
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 83.3112412907745
    - type: cos_sim_spearman
      value: 84.57510944099658
    - type: euclidean_pearson
      value: 84.50205420480455
    - type: euclidean_spearman
      value: 84.57598327682105
    - type: manhattan_pearson
      value: 84.74804769582275
    - type: manhattan_spearman
      value: 84.99120851101564
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.794108283023945
    - type: cos_sim_spearman
      value: 60.54176712724478
    - type: euclidean_pearson
      value: 62.85277340145373
    - type: euclidean_spearman
      value: 60.54176712724478
    - type: manhattan_pearson
      value: 63.363680183757786
    - type: manhattan_spearman
      value: 61.435797497590514
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.86730952817506
    - type: cos_sim_spearman
      value: 76.76096493974984
    - type: euclidean_pearson
      value: 78.03353994564065
    - type: euclidean_spearman
      value: 76.76098340673005
    - type: manhattan_pearson
      value: 78.37579820301903
    - type: manhattan_spearman
      value: 77.16141833792992
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 71.57871845338573
    - type: mrr
      value: 90.27109419266283
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 30.416999999999998
    - type: map_at_10
      value: 38.872
    - type: map_at_100
      value: 40.050000000000004
    - type: map_at_1000
      value: 40.128
    - type: map_at_3
      value: 36.754
    - type: map_at_5
      value: 37.979
    - type: mrr_at_1
      value: 32.667
    - type: mrr_at_10
      value: 40.801
    - type: mrr_at_100
      value: 41.765
    - type: mrr_at_1000
      value: 41.824
    - type: mrr_at_3
      value: 38.944
    - type: mrr_at_5
      value: 39.944
    - type: ndcg_at_1
      value: 32.667
    - type: ndcg_at_10
      value: 43.383
    - type: ndcg_at_100
      value: 49.155
    - type: ndcg_at_1000
      value: 51.065000000000005
    - type: ndcg_at_3
      value: 39.344
    - type: ndcg_at_5
      value: 41.272999999999996
    - type: precision_at_1
      value: 32.667
    - type: precision_at_10
      value: 6.1
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 16.111
    - type: precision_at_5
      value: 10.8
    - type: recall_at_1
      value: 30.416999999999998
    - type: recall_at_10
      value: 55.510999999999996
    - type: recall_at_100
      value: 82.68299999999999
    - type: recall_at_1000
      value: 97.467
    - type: recall_at_3
      value: 44.4
    - type: recall_at_5
      value: 49.15
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.65841584158416
    - type: cos_sim_ap
      value: 88.83936843897057
    - type: cos_sim_f1
      value: 82.16902784562775
    - type: cos_sim_precision
      value: 80.32473734479466
    - type: cos_sim_recall
      value: 84.1
    - type: dot_accuracy
      value: 99.65841584158416
    - type: dot_ap
      value: 88.83936843897057
    - type: dot_f1
      value: 82.16902784562775
    - type: dot_precision
      value: 80.32473734479466
    - type: dot_recall
      value: 84.1
    - type: euclidean_accuracy
      value: 99.65841584158416
    - type: euclidean_ap
      value: 88.83936843897057
    - type: euclidean_f1
      value: 82.16902784562775
    - type: euclidean_precision
      value: 80.32473734479466
    - type: euclidean_recall
      value: 84.1
    - type: manhattan_accuracy
      value: 99.71485148514851
    - type: manhattan_ap
      value: 91.63698188533668
    - type: manhattan_f1
      value: 85.08508508508508
    - type: manhattan_precision
      value: 85.17034068136272
    - type: manhattan_recall
      value: 85.0
    - type: max_accuracy
      value: 99.71485148514851
    - type: max_ap
      value: 91.63698188533668
    - type: max_f1
      value: 85.08508508508508
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 42.666748560286464
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.343481229719927
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.39912629341728
    - type: mrr
      value: 43.935388549359125
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.05640966068664
    - type: cos_sim_spearman
      value: 30.256551014432674
    - type: dot_pearson
      value: 30.056409657847823
    - type: dot_spearman
      value: 30.25071937079099
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.046
    - type: map_at_10
      value: 8.117
    - type: map_at_100
      value: 13.159
    - type: map_at_1000
      value: 14.748
    - type: map_at_3
      value: 4.562
    - type: map_at_5
      value: 6.215
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 41.349000000000004
    - type: mrr_at_100
      value: 41.982
    - type: mrr_at_1000
      value: 41.984
    - type: mrr_at_3
      value: 36.735
    - type: mrr_at_5
      value: 38.673
    - type: ndcg_at_1
      value: 27.551
    - type: ndcg_at_10
      value: 20.86
    - type: ndcg_at_100
      value: 33.036
    - type: ndcg_at_1000
      value: 44.36
    - type: ndcg_at_3
      value: 24.487000000000002
    - type: ndcg_at_5
      value: 22.817999999999998
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 18.776
    - type: precision_at_100
      value: 7.388
    - type: precision_at_1000
      value: 1.4569999999999999
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 22.857
    - type: recall_at_1
      value: 2.046
    - type: recall_at_10
      value: 12.764000000000001
    - type: recall_at_100
      value: 43.954
    - type: recall_at_1000
      value: 78.73599999999999
    - type: recall_at_3
      value: 5.418
    - type: recall_at_5
      value: 8.019
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.994
    - type: ap
      value: 13.68746964334237
    - type: f1
      value: 53.767802041499934
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.131295981890204
    - type: f1
      value: 54.32672197643019
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 36.172642558951175
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.0734338677952
    - type: cos_sim_ap
      value: 66.76083954282574
    - type: cos_sim_f1
      value: 63.71746303311744
    - type: cos_sim_precision
      value: 59.34441156385159
    - type: cos_sim_recall
      value: 68.7862796833773
    - type: dot_accuracy
      value: 84.0734338677952
    - type: dot_ap
      value: 66.76083954282574
    - type: dot_f1
      value: 63.71746303311744
    - type: dot_precision
      value: 59.34441156385159
    - type: dot_recall
      value: 68.7862796833773
    - type: euclidean_accuracy
      value: 84.0734338677952
    - type: euclidean_ap
      value: 66.76083954282574
    - type: euclidean_f1
      value: 63.71746303311744
    - type: euclidean_precision
      value: 59.34441156385159
    - type: euclidean_recall
      value: 68.7862796833773
    - type: manhattan_accuracy
      value: 83.65023544137807
    - type: manhattan_ap
      value: 65.52713910437838
    - type: manhattan_f1
      value: 62.558898151504174
    - type: manhattan_precision
      value: 57.700022286605744
    - type: manhattan_recall
      value: 68.311345646438
    - type: max_accuracy
      value: 84.0734338677952
    - type: max_ap
      value: 66.76083954282574
    - type: max_f1
      value: 63.71746303311744
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.4917530174254
    - type: cos_sim_ap
      value: 82.8306139255757
    - type: cos_sim_f1
      value: 75.05183137525916
    - type: cos_sim_precision
      value: 71.1271975180972
    - type: cos_sim_recall
      value: 79.43486295041576
    - type: dot_accuracy
      value: 87.4917530174254
    - type: dot_ap
      value: 82.83061488150707
    - type: dot_f1
      value: 75.05183137525916
    - type: dot_precision
      value: 71.1271975180972
    - type: dot_recall
      value: 79.43486295041576
    - type: euclidean_accuracy
      value: 87.4917530174254
    - type: euclidean_ap
      value: 82.83061361460264
    - type: euclidean_f1
      value: 75.05183137525916
    - type: euclidean_precision
      value: 71.1271975180972
    - type: euclidean_recall
      value: 79.43486295041576
    - type: manhattan_accuracy
      value: 87.4607055536151
    - type: manhattan_ap
      value: 82.89483623981917
    - type: manhattan_f1
      value: 75.04707388717331
    - type: manhattan_precision
      value: 73.44832669910069
    - type: manhattan_recall
      value: 76.71696951031721
    - type: max_accuracy
      value: 87.4917530174254
    - type: max_ap
      value: 82.89483623981917
    - type: max_f1
      value: 75.05183137525916
---
