mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_500
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.80597014925372
    - type: ap
      value: 34.197330474755326
    - type: f1
      value: 65.6383323667309
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.1743
    - type: ap
      value: 60.20664078251553
    - type: f1
      value: 64.92146428468526
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.542
    - type: f1
      value: 34.03169070398656
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.407999999999998
    - type: map_at_10
      value: 35.25
    - type: map_at_100
      value: 36.434
    - type: map_at_1000
      value: 36.457
    - type: map_at_3
      value: 30.595
    - type: map_at_5
      value: 33.195
    - type: mrr_at_1
      value: 21.977
    - type: mrr_at_10
      value: 35.485
    - type: mrr_at_100
      value: 36.668
    - type: mrr_at_1000
      value: 36.691
    - type: mrr_at_3
      value: 30.797
    - type: mrr_at_5
      value: 33.442
    - type: ndcg_at_1
      value: 21.407999999999998
    - type: ndcg_at_10
      value: 43.329
    - type: ndcg_at_100
      value: 48.854
    - type: ndcg_at_1000
      value: 49.416
    - type: ndcg_at_3
      value: 33.639
    - type: ndcg_at_5
      value: 38.37
    - type: precision_at_1
      value: 21.407999999999998
    - type: precision_at_10
      value: 6.935
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.154
    - type: precision_at_5
      value: 10.811
    - type: recall_at_1
      value: 21.407999999999998
    - type: recall_at_10
      value: 69.346
    - type: recall_at_100
      value: 94.666
    - type: recall_at_1000
      value: 99.004
    - type: recall_at_3
      value: 42.461
    - type: recall_at_5
      value: 54.054
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 34.30039585122896
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.222077798266923
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.467946212899555
    - type: mrr
      value: 67.98498439080156
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.72978740558128
    - type: cos_sim_spearman
      value: 79.8415782806684
    - type: euclidean_pearson
      value: 81.0407016686661
    - type: euclidean_spearman
      value: 79.8415782806684
    - type: manhattan_pearson
      value: 81.08496262274785
    - type: manhattan_spearman
      value: 79.91206181439438
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.08116883116882
    - type: f1
      value: 72.32145914983063
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.09909290830503
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.168951685127244
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.884999999999998
    - type: map_at_10
      value: 30.014000000000003
    - type: map_at_100
      value: 31.081999999999997
    - type: map_at_1000
      value: 31.236000000000004
    - type: map_at_3
      value: 27.551
    - type: map_at_5
      value: 29.092000000000002
    - type: mrr_at_1
      value: 27.611
    - type: mrr_at_10
      value: 35.61
    - type: mrr_at_100
      value: 36.455
    - type: mrr_at_1000
      value: 36.528
    - type: mrr_at_3
      value: 33.763
    - type: mrr_at_5
      value: 34.949999999999996
    - type: ndcg_at_1
      value: 27.611
    - type: ndcg_at_10
      value: 35.055
    - type: ndcg_at_100
      value: 39.918
    - type: ndcg_at_1000
      value: 43.02
    - type: ndcg_at_3
      value: 31.679000000000002
    - type: ndcg_at_5
      value: 33.406000000000006
    - type: precision_at_1
      value: 27.611
    - type: precision_at_10
      value: 6.694999999999999
    - type: precision_at_100
      value: 1.127
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_3
      value: 15.546
    - type: precision_at_5
      value: 11.302
    - type: recall_at_1
      value: 21.884999999999998
    - type: recall_at_10
      value: 44.011
    - type: recall_at_100
      value: 65.778
    - type: recall_at_1000
      value: 86.833
    - type: recall_at_3
      value: 33.465
    - type: recall_at_5
      value: 38.573
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.336
    - type: map_at_10
      value: 22.978
    - type: map_at_100
      value: 23.945
    - type: map_at_1000
      value: 24.071
    - type: map_at_3
      value: 21.052
    - type: map_at_5
      value: 22.152
    - type: mrr_at_1
      value: 21.911
    - type: mrr_at_10
      value: 27.319
    - type: mrr_at_100
      value: 28.147
    - type: mrr_at_1000
      value: 28.225
    - type: mrr_at_3
      value: 25.372
    - type: mrr_at_5
      value: 26.499
    - type: ndcg_at_1
      value: 21.911
    - type: ndcg_at_10
      value: 26.828999999999997
    - type: ndcg_at_100
      value: 31.185000000000002
    - type: ndcg_at_1000
      value: 34.08
    - type: ndcg_at_3
      value: 23.555
    - type: ndcg_at_5
      value: 25.097
    - type: precision_at_1
      value: 21.911
    - type: precision_at_10
      value: 4.949
    - type: precision_at_100
      value: 0.89
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 11.168
    - type: precision_at_5
      value: 8.102
    - type: recall_at_1
      value: 17.336
    - type: recall_at_10
      value: 33.971000000000004
    - type: recall_at_100
      value: 53.03099999999999
    - type: recall_at_1000
      value: 72.611
    - type: recall_at_3
      value: 24.695
    - type: recall_at_5
      value: 28.705000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 26.566000000000003
    - type: map_at_10
      value: 34.985
    - type: map_at_100
      value: 36.131
    - type: map_at_1000
      value: 36.223
    - type: map_at_3
      value: 32.503
    - type: map_at_5
      value: 33.953
    - type: mrr_at_1
      value: 30.784
    - type: mrr_at_10
      value: 38.277
    - type: mrr_at_100
      value: 39.174
    - type: mrr_at_1000
      value: 39.232
    - type: mrr_at_3
      value: 35.946
    - type: mrr_at_5
      value: 37.309
    - type: ndcg_at_1
      value: 30.784
    - type: ndcg_at_10
      value: 39.690999999999995
    - type: ndcg_at_100
      value: 45.016
    - type: ndcg_at_1000
      value: 47.148
    - type: ndcg_at_3
      value: 35.091
    - type: ndcg_at_5
      value: 37.408
    - type: precision_at_1
      value: 30.784
    - type: precision_at_10
      value: 6.433
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 15.549
    - type: precision_at_5
      value: 10.884
    - type: recall_at_1
      value: 26.566000000000003
    - type: recall_at_10
      value: 50.70400000000001
    - type: recall_at_100
      value: 74.661
    - type: recall_at_1000
      value: 90.077
    - type: recall_at_3
      value: 38.284
    - type: recall_at_5
      value: 44.041999999999994
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.994
    - type: map_at_10
      value: 17.112
    - type: map_at_100
      value: 17.893
    - type: map_at_1000
      value: 18.004
    - type: map_at_3
      value: 15.662
    - type: map_at_5
      value: 16.483
    - type: mrr_at_1
      value: 14.237
    - type: mrr_at_10
      value: 18.378
    - type: mrr_at_100
      value: 19.161
    - type: mrr_at_1000
      value: 19.266
    - type: mrr_at_3
      value: 16.911
    - type: mrr_at_5
      value: 17.736
    - type: ndcg_at_1
      value: 14.237
    - type: ndcg_at_10
      value: 19.793
    - type: ndcg_at_100
      value: 24.13
    - type: ndcg_at_1000
      value: 27.450999999999997
    - type: ndcg_at_3
      value: 16.845
    - type: ndcg_at_5
      value: 18.291
    - type: precision_at_1
      value: 14.237
    - type: precision_at_10
      value: 3.04
    - type: precision_at_100
      value: 0.5539999999999999
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 7.005999999999999
    - type: precision_at_5
      value: 5.04
    - type: recall_at_1
      value: 12.994
    - type: recall_at_10
      value: 26.980999999999998
    - type: recall_at_100
      value: 47.827
    - type: recall_at_1000
      value: 73.694
    - type: recall_at_3
      value: 19.002
    - type: recall_at_5
      value: 22.429
  - 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: 9.829
    - type: map_at_100
      value: 10.552
    - type: map_at_1000
      value: 10.682
    - type: map_at_3
      value: 8.638
    - type: map_at_5
      value: 9.197
    - type: mrr_at_1
      value: 8.581999999999999
    - type: mrr_at_10
      value: 12.296
    - type: mrr_at_100
      value: 13.036
    - type: mrr_at_1000
      value: 13.138
    - type: mrr_at_3
      value: 10.821
    - type: mrr_at_5
      value: 11.524
    - type: ndcg_at_1
      value: 8.581999999999999
    - type: ndcg_at_10
      value: 12.422
    - type: ndcg_at_100
      value: 16.357
    - type: ndcg_at_1000
      value: 20.03
    - type: ndcg_at_3
      value: 9.956
    - type: ndcg_at_5
      value: 10.891
    - type: precision_at_1
      value: 8.581999999999999
    - type: precision_at_10
      value: 2.4250000000000003
    - type: precision_at_100
      value: 0.515
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_3
      value: 4.809
    - type: precision_at_5
      value: 3.557
    - type: recall_at_1
      value: 6.497999999999999
    - type: recall_at_10
      value: 18.165
    - type: recall_at_100
      value: 36.083
    - type: recall_at_1000
      value: 63.233
    - type: recall_at_3
      value: 11.204
    - type: recall_at_5
      value: 13.572000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.136000000000003
    - type: map_at_10
      value: 23.504
    - type: map_at_100
      value: 24.731
    - type: map_at_1000
      value: 24.866
    - type: map_at_3
      value: 21.485000000000003
    - type: map_at_5
      value: 22.591
    - type: mrr_at_1
      value: 21.654999999999998
    - type: mrr_at_10
      value: 28.249000000000002
    - type: mrr_at_100
      value: 29.243999999999996
    - type: mrr_at_1000
      value: 29.325000000000003
    - type: mrr_at_3
      value: 26.162999999999997
    - type: mrr_at_5
      value: 27.332
    - type: ndcg_at_1
      value: 21.654999999999998
    - type: ndcg_at_10
      value: 27.761000000000003
    - type: ndcg_at_100
      value: 33.535
    - type: ndcg_at_1000
      value: 36.606
    - type: ndcg_at_3
      value: 24.274
    - type: ndcg_at_5
      value: 25.884
    - type: precision_at_1
      value: 21.654999999999998
    - type: precision_at_10
      value: 5.043
    - type: precision_at_100
      value: 0.96
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.421000000000001
    - type: precision_at_5
      value: 8.296000000000001
    - type: recall_at_1
      value: 17.136000000000003
    - type: recall_at_10
      value: 36.083
    - type: recall_at_100
      value: 61.148
    - type: recall_at_1000
      value: 82.41199999999999
    - type: recall_at_3
      value: 26.149
    - type: recall_at_5
      value: 30.302
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.591
    - type: map_at_10
      value: 18.438
    - type: map_at_100
      value: 19.457
    - type: map_at_1000
      value: 19.6
    - type: map_at_3
      value: 16.506
    - type: map_at_5
      value: 17.604
    - type: mrr_at_1
      value: 15.867999999999999
    - type: mrr_at_10
      value: 21.933
    - type: mrr_at_100
      value: 22.829
    - type: mrr_at_1000
      value: 22.926
    - type: mrr_at_3
      value: 20.034
    - type: mrr_at_5
      value: 21.079
    - type: ndcg_at_1
      value: 15.867999999999999
    - type: ndcg_at_10
      value: 22.262999999999998
    - type: ndcg_at_100
      value: 27.183
    - type: ndcg_at_1000
      value: 30.736
    - type: ndcg_at_3
      value: 18.748
    - type: ndcg_at_5
      value: 20.349999999999998
    - type: precision_at_1
      value: 15.867999999999999
    - type: precision_at_10
      value: 4.247
    - type: precision_at_100
      value: 0.7969999999999999
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 9.132
    - type: precision_at_5
      value: 6.734999999999999
    - type: recall_at_1
      value: 12.591
    - type: recall_at_10
      value: 30.481
    - type: recall_at_100
      value: 51.943
    - type: recall_at_1000
      value: 77.21900000000001
    - type: recall_at_3
      value: 20.633000000000003
    - type: recall_at_5
      value: 24.755
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.31925
    - type: map_at_10
      value: 19.728083333333334
    - type: map_at_100
      value: 20.634249999999998
    - type: map_at_1000
      value: 20.759749999999997
    - type: map_at_3
      value: 18.026916666666665
    - type: map_at_5
      value: 18.982000000000003
    - type: mrr_at_1
      value: 17.433916666666665
    - type: mrr_at_10
      value: 22.865083333333335
    - type: mrr_at_100
      value: 23.671333333333333
    - type: mrr_at_1000
      value: 23.758666666666667
    - type: mrr_at_3
      value: 21.17683333333333
    - type: mrr_at_5
      value: 22.126583333333333
    - type: ndcg_at_1
      value: 17.433916666666665
    - type: ndcg_at_10
      value: 23.24025
    - type: ndcg_at_100
      value: 27.731999999999996
    - type: ndcg_at_1000
      value: 30.89491666666666
    - type: ndcg_at_3
      value: 20.1805
    - type: ndcg_at_5
      value: 21.60258333333333
    - type: precision_at_1
      value: 17.433916666666665
    - type: precision_at_10
      value: 4.150666666666667
    - type: precision_at_100
      value: 0.7606666666666668
    - type: precision_at_1000
      value: 0.12116666666666667
    - type: precision_at_3
      value: 9.400833333333333
    - type: precision_at_5
      value: 6.769666666666666
    - type: recall_at_1
      value: 14.31925
    - type: recall_at_10
      value: 30.738583333333334
    - type: recall_at_100
      value: 51.23908333333333
    - type: recall_at_1000
      value: 74.19550000000001
    - type: recall_at_3
      value: 22.07891666666667
    - type: recall_at_5
      value: 25.751
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.459
    - type: map_at_10
      value: 14.745
    - type: map_at_100
      value: 15.365
    - type: map_at_1000
      value: 15.448999999999998
    - type: map_at_3
      value: 13.320000000000002
    - type: map_at_5
      value: 14.111
    - type: mrr_at_1
      value: 12.577
    - type: mrr_at_10
      value: 16.882
    - type: mrr_at_100
      value: 17.464
    - type: mrr_at_1000
      value: 17.541999999999998
    - type: mrr_at_3
      value: 15.389
    - type: mrr_at_5
      value: 16.178
    - type: ndcg_at_1
      value: 12.577
    - type: ndcg_at_10
      value: 17.718
    - type: ndcg_at_100
      value: 21.137
    - type: ndcg_at_1000
      value: 23.669
    - type: ndcg_at_3
      value: 14.91
    - type: ndcg_at_5
      value: 16.181
    - type: precision_at_1
      value: 12.577
    - type: precision_at_10
      value: 3.129
    - type: precision_at_100
      value: 0.532
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_3
      value: 6.902
    - type: precision_at_5
      value: 5.0
    - type: recall_at_1
      value: 10.459
    - type: recall_at_10
      value: 24.927
    - type: recall_at_100
      value: 41.27
    - type: recall_at_1000
      value: 60.644
    - type: recall_at_3
      value: 16.871
    - type: recall_at_5
      value: 20.151
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.815999999999999
    - type: map_at_10
      value: 11.289
    - type: map_at_100
      value: 11.919
    - type: map_at_1000
      value: 12.042
    - type: map_at_3
      value: 10.199
    - type: map_at_5
      value: 10.83
    - type: mrr_at_1
      value: 9.565999999999999
    - type: mrr_at_10
      value: 13.541
    - type: mrr_at_100
      value: 14.174000000000001
    - type: mrr_at_1000
      value: 14.277999999999999
    - type: mrr_at_3
      value: 12.308
    - type: mrr_at_5
      value: 13.003
    - type: ndcg_at_1
      value: 9.565999999999999
    - type: ndcg_at_10
      value: 13.66
    - type: ndcg_at_100
      value: 17.192
    - type: ndcg_at_1000
      value: 20.732
    - type: ndcg_at_3
      value: 11.599
    - type: ndcg_at_5
      value: 12.603
    - type: precision_at_1
      value: 9.565999999999999
    - type: precision_at_10
      value: 2.546
    - type: precision_at_100
      value: 0.518
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 5.552
    - type: precision_at_5
      value: 4.095
    - type: recall_at_1
      value: 7.815999999999999
    - type: recall_at_10
      value: 18.594
    - type: recall_at_100
      value: 35.154
    - type: recall_at_1000
      value: 61.454
    - type: recall_at_3
      value: 12.934999999999999
    - type: recall_at_5
      value: 15.440000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.396
    - type: map_at_10
      value: 17.274
    - type: map_at_100
      value: 18.17
    - type: map_at_1000
      value: 18.287
    - type: map_at_3
      value: 15.926000000000002
    - type: map_at_5
      value: 16.621
    - type: mrr_at_1
      value: 14.924999999999999
    - type: mrr_at_10
      value: 20.157
    - type: mrr_at_100
      value: 21.056
    - type: mrr_at_1000
      value: 21.149
    - type: mrr_at_3
      value: 18.719
    - type: mrr_at_5
      value: 19.433
    - type: ndcg_at_1
      value: 14.924999999999999
    - type: ndcg_at_10
      value: 20.468
    - type: ndcg_at_100
      value: 24.962
    - type: ndcg_at_1000
      value: 28.255999999999997
    - type: ndcg_at_3
      value: 17.836
    - type: ndcg_at_5
      value: 18.901
    - type: precision_at_1
      value: 14.924999999999999
    - type: precision_at_10
      value: 3.479
    - type: precision_at_100
      value: 0.626
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 8.333
    - type: precision_at_5
      value: 5.7090000000000005
    - type: recall_at_1
      value: 12.396
    - type: recall_at_10
      value: 27.554000000000002
    - type: recall_at_100
      value: 47.811
    - type: recall_at_1000
      value: 71.988
    - type: recall_at_3
      value: 20.054
    - type: recall_at_5
      value: 22.874
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.496999999999998
    - type: map_at_10
      value: 20.928
    - type: map_at_100
      value: 21.991
    - type: map_at_1000
      value: 22.171
    - type: map_at_3
      value: 19.159000000000002
    - type: map_at_5
      value: 20.121
    - type: mrr_at_1
      value: 18.182000000000002
    - type: mrr_at_10
      value: 24.456
    - type: mrr_at_100
      value: 25.308000000000003
    - type: mrr_at_1000
      value: 25.387999999999998
    - type: mrr_at_3
      value: 22.892000000000003
    - type: mrr_at_5
      value: 23.831
    - type: ndcg_at_1
      value: 18.182000000000002
    - type: ndcg_at_10
      value: 24.923000000000002
    - type: ndcg_at_100
      value: 29.720000000000002
    - type: ndcg_at_1000
      value: 33.265
    - type: ndcg_at_3
      value: 22.137999999999998
    - type: ndcg_at_5
      value: 23.422
    - type: precision_at_1
      value: 18.182000000000002
    - type: precision_at_10
      value: 4.901
    - type: precision_at_100
      value: 1.079
    - type: precision_at_1000
      value: 0.19
    - type: precision_at_3
      value: 10.738
    - type: precision_at_5
      value: 7.747
    - type: recall_at_1
      value: 14.496999999999998
    - type: recall_at_10
      value: 32.266
    - type: recall_at_100
      value: 54.874
    - type: recall_at_1000
      value: 79.469
    - type: recall_at_3
      value: 24.083
    - type: recall_at_5
      value: 27.602
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.657
    - type: map_at_10
      value: 15.641
    - type: map_at_100
      value: 16.375
    - type: map_at_1000
      value: 16.486
    - type: map_at_3
      value: 14.322
    - type: map_at_5
      value: 15.029
    - type: mrr_at_1
      value: 13.309000000000001
    - type: mrr_at_10
      value: 17.283
    - type: mrr_at_100
      value: 18.008
    - type: mrr_at_1000
      value: 18.107
    - type: mrr_at_3
      value: 15.804000000000002
    - type: mrr_at_5
      value: 16.645
    - type: ndcg_at_1
      value: 13.309000000000001
    - type: ndcg_at_10
      value: 18.3
    - type: ndcg_at_100
      value: 22.448999999999998
    - type: ndcg_at_1000
      value: 25.746000000000002
    - type: ndcg_at_3
      value: 15.534999999999998
    - type: ndcg_at_5
      value: 16.797
    - type: precision_at_1
      value: 13.309000000000001
    - type: precision_at_10
      value: 2.921
    - type: precision_at_100
      value: 0.536
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.654
    - type: precision_at_5
      value: 4.769
    - type: recall_at_1
      value: 11.657
    - type: recall_at_10
      value: 25.125999999999998
    - type: recall_at_100
      value: 45.289
    - type: recall_at_1000
      value: 70.712
    - type: recall_at_3
      value: 17.572
    - type: recall_at_5
      value: 20.567
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.065
    - type: map_at_10
      value: 10.929
    - type: map_at_100
      value: 12.303
    - type: map_at_1000
      value: 12.496
    - type: map_at_3
      value: 8.85
    - type: map_at_5
      value: 9.801
    - type: mrr_at_1
      value: 13.028999999999998
    - type: mrr_at_10
      value: 21.607000000000003
    - type: mrr_at_100
      value: 22.767
    - type: mrr_at_1000
      value: 22.835
    - type: mrr_at_3
      value: 18.675
    - type: mrr_at_5
      value: 20.193
    - type: ndcg_at_1
      value: 13.028999999999998
    - type: ndcg_at_10
      value: 16.444
    - type: ndcg_at_100
      value: 22.966
    - type: ndcg_at_1000
      value: 27.016000000000002
    - type: ndcg_at_3
      value: 12.45
    - type: ndcg_at_5
      value: 13.736
    - type: precision_at_1
      value: 13.028999999999998
    - type: precision_at_10
      value: 5.57
    - type: precision_at_100
      value: 1.261
    - type: precision_at_1000
      value: 0.199
    - type: precision_at_3
      value: 9.597999999999999
    - type: precision_at_5
      value: 7.596
    - type: recall_at_1
      value: 6.065
    - type: recall_at_10
      value: 21.267
    - type: recall_at_100
      value: 44.603
    - type: recall_at_1000
      value: 68.116
    - type: recall_at_3
      value: 11.855
    - type: recall_at_5
      value: 15.145
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.109
    - type: map_at_10
      value: 9.25
    - type: map_at_100
      value: 12.601999999999999
    - type: map_at_1000
      value: 13.52
    - type: map_at_3
      value: 6.708
    - type: map_at_5
      value: 7.908999999999999
    - type: mrr_at_1
      value: 38.5
    - type: mrr_at_10
      value: 48.581
    - type: mrr_at_100
      value: 49.366
    - type: mrr_at_1000
      value: 49.396
    - type: mrr_at_3
      value: 45.917
    - type: mrr_at_5
      value: 47.342
    - type: ndcg_at_1
      value: 27.875
    - type: ndcg_at_10
      value: 22.938
    - type: ndcg_at_100
      value: 25.574
    - type: ndcg_at_1000
      value: 32.25
    - type: ndcg_at_3
      value: 25.624000000000002
    - type: ndcg_at_5
      value: 24.2
    - type: precision_at_1
      value: 38.5
    - type: precision_at_10
      value: 20.05
    - type: precision_at_100
      value: 6.245
    - type: precision_at_1000
      value: 1.341
    - type: precision_at_3
      value: 30.166999999999998
    - type: precision_at_5
      value: 25.75
    - type: recall_at_1
      value: 4.109
    - type: recall_at_10
      value: 13.535
    - type: recall_at_100
      value: 31.313999999999997
    - type: recall_at_1000
      value: 53.547999999999995
    - type: recall_at_3
      value: 8.042
    - type: recall_at_5
      value: 10.446
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 44.93000000000001
    - type: f1
      value: 40.86871174296382
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.285999999999998
    - type: map_at_10
      value: 21.746
    - type: map_at_100
      value: 22.659000000000002
    - type: map_at_1000
      value: 22.736
    - type: map_at_3
      value: 19.366
    - type: map_at_5
      value: 20.632
    - type: mrr_at_1
      value: 15.257000000000001
    - type: mrr_at_10
      value: 23.133
    - type: mrr_at_100
      value: 24.038
    - type: mrr_at_1000
      value: 24.105999999999998
    - type: mrr_at_3
      value: 20.622
    - type: mrr_at_5
      value: 21.968
    - type: ndcg_at_1
      value: 15.257000000000001
    - type: ndcg_at_10
      value: 26.381
    - type: ndcg_at_100
      value: 31.14
    - type: ndcg_at_1000
      value: 33.291
    - type: ndcg_at_3
      value: 21.409
    - type: ndcg_at_5
      value: 23.692
    - type: precision_at_1
      value: 15.257000000000001
    - type: precision_at_10
      value: 4.311
    - type: precision_at_100
      value: 0.688
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 9.361
    - type: precision_at_5
      value: 6.8229999999999995
    - type: recall_at_1
      value: 14.285999999999998
    - type: recall_at_10
      value: 39.660000000000004
    - type: recall_at_100
      value: 62.107
    - type: recall_at_1000
      value: 78.771
    - type: recall_at_3
      value: 26.054
    - type: recall_at_5
      value: 31.532
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.04
    - type: map_at_10
      value: 10.43
    - type: map_at_100
      value: 11.541
    - type: map_at_1000
      value: 11.745999999999999
    - type: map_at_3
      value: 8.863
    - type: map_at_5
      value: 9.76
    - type: mrr_at_1
      value: 12.346
    - type: mrr_at_10
      value: 18.407
    - type: mrr_at_100
      value: 19.395
    - type: mrr_at_1000
      value: 19.500999999999998
    - type: mrr_at_3
      value: 16.281000000000002
    - type: mrr_at_5
      value: 17.438000000000002
    - type: ndcg_at_1
      value: 12.346
    - type: ndcg_at_10
      value: 14.597999999999999
    - type: ndcg_at_100
      value: 19.942999999999998
    - type: ndcg_at_1000
      value: 24.65
    - type: ndcg_at_3
      value: 12.209
    - type: ndcg_at_5
      value: 13.135
    - type: precision_at_1
      value: 12.346
    - type: precision_at_10
      value: 4.306
    - type: precision_at_100
      value: 0.9610000000000001
    - type: precision_at_1000
      value: 0.17500000000000002
    - type: precision_at_3
      value: 8.385
    - type: precision_at_5
      value: 6.451
    - type: recall_at_1
      value: 6.04
    - type: recall_at_10
      value: 19.039
    - type: recall_at_100
      value: 39.897
    - type: recall_at_1000
      value: 69.652
    - type: recall_at_3
      value: 11.376999999999999
    - type: recall_at_5
      value: 14.597999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 17.097
    - type: map_at_10
      value: 23.765
    - type: map_at_100
      value: 24.673000000000002
    - type: map_at_1000
      value: 24.784
    - type: map_at_3
      value: 21.881999999999998
    - type: map_at_5
      value: 22.947
    - type: mrr_at_1
      value: 34.193
    - type: mrr_at_10
      value: 40.818
    - type: mrr_at_100
      value: 41.571999999999996
    - type: mrr_at_1000
      value: 41.631
    - type: mrr_at_3
      value: 38.924
    - type: mrr_at_5
      value: 40.017
    - type: ndcg_at_1
      value: 34.193
    - type: ndcg_at_10
      value: 30.343999999999998
    - type: ndcg_at_100
      value: 34.587
    - type: ndcg_at_1000
      value: 37.275000000000006
    - type: ndcg_at_3
      value: 26.754
    - type: ndcg_at_5
      value: 28.538000000000004
    - type: precision_at_1
      value: 34.193
    - type: precision_at_10
      value: 6.641
    - type: precision_at_100
      value: 1.004
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 16.75
    - type: precision_at_5
      value: 11.465
    - type: recall_at_1
      value: 17.097
    - type: recall_at_10
      value: 33.207
    - type: recall_at_100
      value: 50.18899999999999
    - type: recall_at_1000
      value: 68.143
    - type: recall_at_3
      value: 25.124999999999996
    - type: recall_at_5
      value: 28.663
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.3804
    - type: ap
      value: 59.49035666846163
    - type: f1
      value: 64.24322259403525
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.232
    - type: map_at_10
      value: 10.822
    - type: map_at_100
      value: 11.688
    - type: map_at_1000
      value: 11.790000000000001
    - type: map_at_3
      value: 9.118
    - type: map_at_5
      value: 10.042
    - type: mrr_at_1
      value: 6.418
    - type: mrr_at_10
      value: 11.115
    - type: mrr_at_100
      value: 11.985999999999999
    - type: mrr_at_1000
      value: 12.084
    - type: mrr_at_3
      value: 9.384
    - type: mrr_at_5
      value: 10.32
    - type: ndcg_at_1
      value: 6.404
    - type: ndcg_at_10
      value: 13.719000000000001
    - type: ndcg_at_100
      value: 18.491
    - type: ndcg_at_1000
      value: 21.58
    - type: ndcg_at_3
      value: 10.141
    - type: ndcg_at_5
      value: 11.818
    - type: precision_at_1
      value: 6.404
    - type: precision_at_10
      value: 2.37
    - type: precision_at_100
      value: 0.485
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.441
    - type: precision_at_5
      value: 3.5130000000000003
    - type: recall_at_1
      value: 6.232
    - type: recall_at_10
      value: 22.747
    - type: recall_at_100
      value: 46.085
    - type: recall_at_1000
      value: 70.949
    - type: recall_at_3
      value: 12.851
    - type: recall_at_5
      value: 16.915
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.578203374373
    - type: f1
      value: 88.85225302664156
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.606475148198825
    - type: f1
      value: 41.71354863184995
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.07330195023536
    - type: f1
      value: 61.05376930007893
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.82515131136516
    - type: f1
      value: 68.60461212305022
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.95405092796609
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.228351073417375
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.15684785427689
    - type: mrr
      value: 30.08928599398446
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.6130000000000004
    - type: map_at_10
      value: 7.698
    - type: map_at_100
      value: 9.657
    - type: map_at_1000
      value: 10.942
    - type: map_at_3
      value: 5.8950000000000005
    - type: map_at_5
      value: 6.816
    - type: mrr_at_1
      value: 32.817
    - type: mrr_at_10
      value: 42.766999999999996
    - type: mrr_at_100
      value: 43.506
    - type: mrr_at_1000
      value: 43.565
    - type: mrr_at_3
      value: 40.454
    - type: mrr_at_5
      value: 42.064
    - type: ndcg_at_1
      value: 30.341
    - type: ndcg_at_10
      value: 24.366
    - type: ndcg_at_100
      value: 22.671
    - type: ndcg_at_1000
      value: 32.309
    - type: ndcg_at_3
      value: 27.862
    - type: ndcg_at_5
      value: 26.849
    - type: precision_at_1
      value: 32.817
    - type: precision_at_10
      value: 18.05
    - type: precision_at_100
      value: 6.257
    - type: precision_at_1000
      value: 1.947
    - type: precision_at_3
      value: 26.729000000000003
    - type: precision_at_5
      value: 23.529
    - type: recall_at_1
      value: 3.6130000000000004
    - type: recall_at_10
      value: 11.92
    - type: recall_at_100
      value: 24.817
    - type: recall_at_1000
      value: 59.638000000000005
    - type: recall_at_3
      value: 7.536
    - type: recall_at_5
      value: 9.574
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.078999999999999
    - type: map_at_10
      value: 15.555
    - type: map_at_100
      value: 16.656000000000002
    - type: map_at_1000
      value: 16.76
    - type: map_at_3
      value: 13.053
    - type: map_at_5
      value: 14.352
    - type: mrr_at_1
      value: 10.342
    - type: mrr_at_10
      value: 17.169999999999998
    - type: mrr_at_100
      value: 18.194
    - type: mrr_at_1000
      value: 18.279999999999998
    - type: mrr_at_3
      value: 14.536999999999999
    - type: mrr_at_5
      value: 15.916
    - type: ndcg_at_1
      value: 10.342
    - type: ndcg_at_10
      value: 19.961000000000002
    - type: ndcg_at_100
      value: 25.730999999999998
    - type: ndcg_at_1000
      value: 28.538999999999998
    - type: ndcg_at_3
      value: 14.712
    - type: ndcg_at_5
      value: 17.069000000000003
    - type: precision_at_1
      value: 10.342
    - type: precision_at_10
      value: 3.7830000000000004
    - type: precision_at_100
      value: 0.709
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.904000000000001
    - type: precision_at_5
      value: 5.457999999999999
    - type: recall_at_1
      value: 9.078999999999999
    - type: recall_at_10
      value: 32.135999999999996
    - type: recall_at_100
      value: 59.275
    - type: recall_at_1000
      value: 80.73599999999999
    - type: recall_at_3
      value: 18.086
    - type: recall_at_5
      value: 23.634
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 62.601
    - type: map_at_10
      value: 75.139
    - type: map_at_100
      value: 75.909
    - type: map_at_1000
      value: 75.945
    - type: map_at_3
      value: 72.221
    - type: map_at_5
      value: 73.97200000000001
    - type: mrr_at_1
      value: 72.2
    - type: mrr_at_10
      value: 79.56299999999999
    - type: mrr_at_100
      value: 79.81899999999999
    - type: mrr_at_1000
      value: 79.825
    - type: mrr_at_3
      value: 78.102
    - type: mrr_at_5
      value: 79.035
    - type: ndcg_at_1
      value: 72.24000000000001
    - type: ndcg_at_10
      value: 79.865
    - type: ndcg_at_100
      value: 82.047
    - type: ndcg_at_1000
      value: 82.462
    - type: ndcg_at_3
      value: 76.268
    - type: ndcg_at_5
      value: 78.105
    - type: precision_at_1
      value: 72.24000000000001
    - type: precision_at_10
      value: 12.056000000000001
    - type: precision_at_100
      value: 1.448
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 33.019999999999996
    - type: precision_at_5
      value: 21.814
    - type: recall_at_1
      value: 62.601
    - type: recall_at_10
      value: 88.9
    - type: recall_at_100
      value: 97.21300000000001
    - type: recall_at_1000
      value: 99.564
    - type: recall_at_3
      value: 78.578
    - type: recall_at_5
      value: 83.712
    - type: map_at_1
      value: 3.093
    - type: map_at_10
      value: 6.7589999999999995
    - type: map_at_100
      value: 8.079
    - type: map_at_1000
      value: 8.324
    - type: map_at_3
      value: 4.989
    - type: map_at_5
      value: 5.8340000000000005
    - type: mrr_at_1
      value: 15.2
    - type: mrr_at_10
      value: 22.102
    - type: mrr_at_100
      value: 23.41
    - type: mrr_at_1000
      value: 23.494999999999997
    - type: mrr_at_3
      value: 19.35
    - type: mrr_at_5
      value: 20.915
    - type: ndcg_at_1
      value: 15.2
    - type: ndcg_at_10
      value: 12.041
    - type: ndcg_at_100
      value: 18.262999999999998
    - type: ndcg_at_1000
      value: 23.319000000000003
    - type: ndcg_at_3
      value: 11.361
    - type: ndcg_at_5
      value: 9.922
    - type: precision_at_1
      value: 15.2
    - type: precision_at_10
      value: 6.2
    - type: precision_at_100
      value: 1.524
    - type: precision_at_1000
      value: 0.27499999999999997
    - type: precision_at_3
      value: 10.366999999999999
    - type: precision_at_5
      value: 8.559999999999999
    - type: recall_at_1
      value: 3.093
    - type: recall_at_10
      value: 12.558
    - type: recall_at_100
      value: 30.968
    - type: recall_at_1000
      value: 55.822
    - type: recall_at_3
      value: 6.313000000000001
    - type: recall_at_5
      value: 8.663
    - type: map_at_1
      value: 0.10300000000000001
    - type: map_at_10
      value: 0.6709999999999999
    - type: map_at_100
      value: 3.6519999999999997
    - type: map_at_1000
      value: 9.259
    - type: map_at_3
      value: 0.272
    - type: map_at_5
      value: 0.40099999999999997
    - type: mrr_at_1
      value: 44.0
    - type: mrr_at_10
      value: 58.408
    - type: mrr_at_100
      value: 58.884
    - type: mrr_at_1000
      value: 58.884
    - type: mrr_at_3
      value: 54.0
    - type: mrr_at_5
      value: 56.699999999999996
    - type: ndcg_at_1
      value: 38.0
    - type: ndcg_at_10
      value: 38.509
    - type: ndcg_at_100
      value: 29.579
    - type: ndcg_at_1000
      value: 26.949
    - type: ndcg_at_3
      value: 41.307
    - type: ndcg_at_5
      value: 40.125
    - type: precision_at_1
      value: 44.0
    - type: precision_at_10
      value: 42.0
    - type: precision_at_100
      value: 31.019999999999996
    - type: precision_at_1000
      value: 13.370000000000001
    - type: precision_at_3
      value: 46.666999999999994
    - type: precision_at_5
      value: 44.800000000000004
    - type: recall_at_1
      value: 0.10300000000000001
    - type: recall_at_10
      value: 0.9299999999999999
    - type: recall_at_100
      value: 6.471
    - type: recall_at_1000
      value: 26.168999999999997
    - type: recall_at_3
      value: 0.31
    - type: recall_at_5
      value: 0.496
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.70907132721693
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 44.64376174681288
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.59936883090633
    - type: cos_sim_spearman
      value: 67.449780263824
    - type: euclidean_pearson
      value: 72.60428215386752
    - type: euclidean_spearman
      value: 67.44984967322037
    - type: manhattan_pearson
      value: 70.45191579421203
    - type: manhattan_spearman
      value: 65.69863566501837
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.50923047867227
    - type: cos_sim_spearman
      value: 67.38818934089512
    - type: euclidean_pearson
      value: 70.59764726174319
    - type: euclidean_spearman
      value: 67.3895124414073
    - type: manhattan_pearson
      value: 70.93710455066322
    - type: manhattan_spearman
      value: 68.47333448128255
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.19112365575151
    - type: cos_sim_spearman
      value: 79.38112417768889
    - type: euclidean_pearson
      value: 79.02004199857001
    - type: euclidean_spearman
      value: 79.38116197916214
    - type: manhattan_pearson
      value: 79.33062720702922
    - type: manhattan_spearman
      value: 79.86274598216346
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.27661661577554
    - type: cos_sim_spearman
      value: 75.02645051253974
    - type: euclidean_pearson
      value: 77.31963861590447
    - type: euclidean_spearman
      value: 75.02644082093607
    - type: manhattan_pearson
      value: 76.88075387757338
    - type: manhattan_spearman
      value: 75.03620772365731
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.73501459044348
    - type: cos_sim_spearman
      value: 81.7087832439833
    - type: euclidean_pearson
      value: 81.70375595238252
    - type: euclidean_spearman
      value: 81.70879349429642
    - type: manhattan_pearson
      value: 82.21073460122751
    - type: manhattan_spearman
      value: 82.45344973434487
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.24869898679407
    - type: cos_sim_spearman
      value: 77.47191941649987
    - type: euclidean_pearson
      value: 77.14620105063327
    - type: euclidean_spearman
      value: 77.47219091002489
    - type: manhattan_pearson
      value: 77.88837129949594
    - type: manhattan_spearman
      value: 78.26164627132523
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.15270089083396
    - type: cos_sim_spearman
      value: 85.24857271570637
    - type: euclidean_pearson
      value: 84.98738655400811
    - type: euclidean_spearman
      value: 85.24944616360952
    - type: manhattan_pearson
      value: 85.04472988712456
    - type: manhattan_spearman
      value: 85.48535037229792
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.77663686460365
    - type: cos_sim_spearman
      value: 60.285236974552035
    - type: euclidean_pearson
      value: 62.70838876789665
    - type: euclidean_spearman
      value: 60.285236974552035
    - type: manhattan_pearson
      value: 62.679276682561145
    - type: manhattan_spearman
      value: 60.92428353513052
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.52806201186114
    - type: cos_sim_spearman
      value: 77.38921404464156
    - type: euclidean_pearson
      value: 78.55234100248828
    - type: euclidean_spearman
      value: 77.3892624307418
    - type: manhattan_pearson
      value: 78.40272170392453
    - type: manhattan_spearman
      value: 77.3848057032632
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.17674803973841
    - type: mrr
      value: 90.82954264326813
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.306000000000004
    - type: map_at_10
      value: 41.47
    - type: map_at_100
      value: 42.742000000000004
    - type: map_at_1000
      value: 42.819
    - type: map_at_3
      value: 39.189
    - type: map_at_5
      value: 40.806
    - type: mrr_at_1
      value: 35.333
    - type: mrr_at_10
      value: 43.263
    - type: mrr_at_100
      value: 44.336999999999996
    - type: mrr_at_1000
      value: 44.395
    - type: mrr_at_3
      value: 41.278
    - type: mrr_at_5
      value: 42.628
    - type: ndcg_at_1
      value: 35.333
    - type: ndcg_at_10
      value: 45.786
    - type: ndcg_at_100
      value: 51.669
    - type: ndcg_at_1000
      value: 53.381
    - type: ndcg_at_3
      value: 41.576
    - type: ndcg_at_5
      value: 44.22
    - type: precision_at_1
      value: 35.333
    - type: precision_at_10
      value: 6.3
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 16.778000000000002
    - type: precision_at_5
      value: 11.533
    - type: recall_at_1
      value: 33.306000000000004
    - type: recall_at_10
      value: 57.343999999999994
    - type: recall_at_100
      value: 84.18299999999999
    - type: recall_at_1000
      value: 97.13300000000001
    - type: recall_at_3
      value: 46.067
    - type: recall_at_5
      value: 52.65
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.69504950495049
    - type: cos_sim_ap
      value: 90.79424558972948
    - type: cos_sim_f1
      value: 84.48448448448448
    - type: cos_sim_precision
      value: 84.5691382765531
    - type: cos_sim_recall
      value: 84.39999999999999
    - type: dot_accuracy
      value: 99.69504950495049
    - type: dot_ap
      value: 90.79424558972948
    - type: dot_f1
      value: 84.48448448448448
    - type: dot_precision
      value: 84.5691382765531
    - type: dot_recall
      value: 84.39999999999999
    - type: euclidean_accuracy
      value: 99.69504950495049
    - type: euclidean_ap
      value: 90.79424558972948
    - type: euclidean_f1
      value: 84.48448448448448
    - type: euclidean_precision
      value: 84.5691382765531
    - type: euclidean_recall
      value: 84.39999999999999
    - type: manhattan_accuracy
      value: 99.75643564356436
    - type: manhattan_ap
      value: 93.41396654747622
    - type: manhattan_f1
      value: 87.5882946518668
    - type: manhattan_precision
      value: 88.39103869653768
    - type: manhattan_recall
      value: 86.8
    - type: max_accuracy
      value: 99.75643564356436
    - type: max_ap
      value: 93.41396654747622
    - type: max_f1
      value: 87.5882946518668
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 43.00307928573676
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.337614632610055
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.61569502307688
    - type: mrr
      value: 44.13243517103811
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.006930304818425
    - type: cos_sim_spearman
      value: 30.418908411172975
    - type: dot_pearson
      value: 30.006930280987586
    - type: dot_spearman
      value: 30.38081230487529
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.16
    - type: map_at_10
      value: 8.18
    - type: map_at_100
      value: 13.54
    - type: map_at_1000
      value: 15.123000000000001
    - type: map_at_3
      value: 4.556
    - type: map_at_5
      value: 5.808
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 41.914
    - type: mrr_at_100
      value: 42.746
    - type: mrr_at_1000
      value: 42.748999999999995
    - type: mrr_at_3
      value: 37.415
    - type: mrr_at_5
      value: 39.354
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 21.407
    - type: ndcg_at_100
      value: 33.811
    - type: ndcg_at_1000
      value: 45.165
    - type: ndcg_at_3
      value: 24.823999999999998
    - type: ndcg_at_5
      value: 22.439
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 19.387999999999998
    - type: precision_at_100
      value: 7.611999999999999
    - type: precision_at_1000
      value: 1.486
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 22.041
    - type: recall_at_1
      value: 2.16
    - type: recall_at_10
      value: 13.299
    - type: recall_at_100
      value: 45.473
    - type: recall_at_1000
      value: 80.25
    - type: recall_at_3
      value: 5.418
    - type: recall_at_5
      value: 7.582
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.2412
    - type: ap
      value: 13.838035383851436
    - type: f1
      value: 53.98636348585877
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.31239388794567
    - type: f1
      value: 54.51029711856694
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 36.200252800690315
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.91845979614949
    - type: cos_sim_ap
      value: 66.31917886451025
    - type: cos_sim_f1
      value: 63.34641805691855
    - type: cos_sim_precision
      value: 59.193030719853276
    - type: cos_sim_recall
      value: 68.12664907651715
    - type: dot_accuracy
      value: 83.91845979614949
    - type: dot_ap
      value: 66.31917886451025
    - type: dot_f1
      value: 63.34641805691855
    - type: dot_precision
      value: 59.193030719853276
    - type: dot_recall
      value: 68.12664907651715
    - type: euclidean_accuracy
      value: 83.91845979614949
    - type: euclidean_ap
      value: 66.31917886451025
    - type: euclidean_f1
      value: 63.34641805691855
    - type: euclidean_precision
      value: 59.193030719853276
    - type: euclidean_recall
      value: 68.12664907651715
    - type: manhattan_accuracy
      value: 83.07206294331525
    - type: manhattan_ap
      value: 64.02709472190338
    - type: manhattan_f1
      value: 60.95680900526123
    - type: manhattan_precision
      value: 56.833219256217205
    - type: manhattan_recall
      value: 65.72559366754618
    - type: max_accuracy
      value: 83.91845979614949
    - type: max_ap
      value: 66.31917886451025
    - type: max_f1
      value: 63.34641805691855
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.52086001474754
    - type: cos_sim_ap
      value: 83.16118544055554
    - type: cos_sim_f1
      value: 75.42429906542057
    - type: cos_sim_precision
      value: 73.30329893910769
    - type: cos_sim_recall
      value: 77.67169695103172
    - type: dot_accuracy
      value: 87.52086001474754
    - type: dot_ap
      value: 83.16118403036499
    - type: dot_f1
      value: 75.42429906542057
    - type: dot_precision
      value: 73.30329893910769
    - type: dot_recall
      value: 77.67169695103172
    - type: euclidean_accuracy
      value: 87.52086001474754
    - type: euclidean_ap
      value: 83.16117609787312
    - type: euclidean_f1
      value: 75.42429906542057
    - type: euclidean_precision
      value: 73.30329893910769
    - type: euclidean_recall
      value: 77.67169695103172
    - type: manhattan_accuracy
      value: 87.56549074397485
    - type: manhattan_ap
      value: 83.15926973242618
    - type: manhattan_f1
      value: 75.27466550636353
    - type: manhattan_precision
      value: 71.13974367760949
    - type: manhattan_recall
      value: 79.91992608561749
    - type: max_accuracy
      value: 87.56549074397485
    - type: max_ap
      value: 83.16118544055554
    - type: max_f1
      value: 75.42429906542057
---
