mteb model-index region:us
---
tags:
- mteb
model-index:
- name: fasttext_main_lower
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 72.92537313432837
    - type: ap
      value: 35.92406337485786
    - type: f1
      value: 67.02887091461996
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 63.944849999999995
    - type: ap
      value: 59.63729279839117
    - type: f1
      value: 63.22827966847257
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.663999999999998
    - type: f1
      value: 31.01142901535539
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 14.651
    - type: map_at_10
      value: 24.84
    - type: map_at_100
      value: 25.907999999999998
    - type: map_at_1000
      value: 25.980999999999998
    - type: map_at_3
      value: 21.349
    - type: map_at_5
      value: 23.476
    - type: mrr_at_1
      value: 15.007000000000001
    - type: mrr_at_10
      value: 24.975
    - type: mrr_at_100
      value: 26.043
    - type: mrr_at_1000
      value: 26.116
    - type: mrr_at_3
      value: 21.55
    - type: mrr_at_5
      value: 23.624000000000002
    - type: ndcg_at_1
      value: 14.651
    - type: ndcg_at_10
      value: 30.675
    - type: ndcg_at_100
      value: 36.162
    - type: ndcg_at_1000
      value: 38.214
    - type: ndcg_at_3
      value: 23.571
    - type: ndcg_at_5
      value: 27.406000000000002
    - type: precision_at_1
      value: 14.651
    - type: precision_at_10
      value: 4.936
    - type: precision_at_100
      value: 0.757
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 10.005
    - type: precision_at_5
      value: 7.866
    - type: recall_at_1
      value: 14.651
    - type: recall_at_10
      value: 49.36
    - type: recall_at_100
      value: 75.676
    - type: recall_at_1000
      value: 92.105
    - type: recall_at_3
      value: 30.014000000000003
    - type: recall_at_5
      value: 39.330999999999996
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.330404041952
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 28.88645728041347
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 50.148759855706025
    - type: mrr
      value: 63.64430813876797
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 47.2456819755334
    - type: cos_sim_spearman
      value: 56.87539232993938
    - type: euclidean_pearson
      value: 51.27139431629815
    - type: euclidean_spearman
      value: 56.87539232993938
    - type: manhattan_pearson
      value: 54.61352629478075
    - type: manhattan_spearman
      value: 58.84230461724967
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 60.3474025974026
    - type: f1
      value: 58.61279983720927
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.53819524955979
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 26.93233785618298
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 16.328
    - type: map_at_10
      value: 22.020999999999997
    - type: map_at_100
      value: 23.037
    - type: map_at_1000
      value: 23.188
    - type: map_at_3
      value: 20.252
    - type: map_at_5
      value: 21.401
    - type: mrr_at_1
      value: 21.316
    - type: mrr_at_10
      value: 26.795
    - type: mrr_at_100
      value: 27.626
    - type: mrr_at_1000
      value: 27.721
    - type: mrr_at_3
      value: 25.155
    - type: mrr_at_5
      value: 26.299
    - type: ndcg_at_1
      value: 21.316
    - type: ndcg_at_10
      value: 25.846000000000004
    - type: ndcg_at_100
      value: 30.654999999999998
    - type: ndcg_at_1000
      value: 34.049
    - type: ndcg_at_3
      value: 23.247
    - type: ndcg_at_5
      value: 24.745
    - type: precision_at_1
      value: 21.316
    - type: precision_at_10
      value: 4.95
    - type: precision_at_100
      value: 0.9339999999999999
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 11.540000000000001
    - type: precision_at_5
      value: 8.469
    - type: recall_at_1
      value: 16.328
    - type: recall_at_10
      value: 32.345
    - type: recall_at_100
      value: 54.24099999999999
    - type: recall_at_1000
      value: 77.729
    - type: recall_at_3
      value: 24.11
    - type: recall_at_5
      value: 28.559
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 13.532
    - type: map_at_10
      value: 18.482000000000003
    - type: map_at_100
      value: 19.279
    - type: map_at_1000
      value: 19.39
    - type: map_at_3
      value: 16.875
    - type: map_at_5
      value: 17.83
    - type: mrr_at_1
      value: 17.516000000000002
    - type: mrr_at_10
      value: 22.781000000000002
    - type: mrr_at_100
      value: 23.439
    - type: mrr_at_1000
      value: 23.513
    - type: mrr_at_3
      value: 21.04
    - type: mrr_at_5
      value: 22.142
    - type: ndcg_at_1
      value: 17.516000000000002
    - type: ndcg_at_10
      value: 21.954
    - type: ndcg_at_100
      value: 25.662000000000003
    - type: ndcg_at_1000
      value: 28.519
    - type: ndcg_at_3
      value: 19.262999999999998
    - type: ndcg_at_5
      value: 20.676
    - type: precision_at_1
      value: 17.516000000000002
    - type: precision_at_10
      value: 4.274
    - type: precision_at_100
      value: 0.775
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 9.447999999999999
    - type: precision_at_5
      value: 7.031999999999999
    - type: recall_at_1
      value: 13.532
    - type: recall_at_10
      value: 27.967
    - type: recall_at_100
      value: 44.232
    - type: recall_at_1000
      value: 64.457
    - type: recall_at_3
      value: 20.454
    - type: recall_at_5
      value: 24.022
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 18.844
    - type: map_at_10
      value: 25.446
    - type: map_at_100
      value: 26.412999999999997
    - type: map_at_1000
      value: 26.508
    - type: map_at_3
      value: 23.354
    - type: map_at_5
      value: 24.531
    - type: mrr_at_1
      value: 21.755
    - type: mrr_at_10
      value: 28.182000000000002
    - type: mrr_at_100
      value: 29.096
    - type: mrr_at_1000
      value: 29.168
    - type: mrr_at_3
      value: 26.155
    - type: mrr_at_5
      value: 27.349
    - type: ndcg_at_1
      value: 21.755
    - type: ndcg_at_10
      value: 29.421999999999997
    - type: ndcg_at_100
      value: 34.215
    - type: ndcg_at_1000
      value: 36.757
    - type: ndcg_at_3
      value: 25.374999999999996
    - type: ndcg_at_5
      value: 27.348
    - type: precision_at_1
      value: 21.755
    - type: precision_at_10
      value: 4.871
    - type: precision_at_100
      value: 0.788
    - type: precision_at_1000
      value: 0.108
    - type: precision_at_3
      value: 11.285
    - type: precision_at_5
      value: 8.025
    - type: recall_at_1
      value: 18.844
    - type: recall_at_10
      value: 38.932
    - type: recall_at_100
      value: 60.587
    - type: recall_at_1000
      value: 79.53099999999999
    - type: recall_at_3
      value: 28.072999999999997
    - type: recall_at_5
      value: 32.885
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 7.228999999999999
    - type: map_at_10
      value: 10.242999999999999
    - type: map_at_100
      value: 10.766
    - type: map_at_1000
      value: 10.864
    - type: map_at_3
      value: 9.231
    - type: map_at_5
      value: 9.782
    - type: mrr_at_1
      value: 7.91
    - type: mrr_at_10
      value: 11.044
    - type: mrr_at_100
      value: 11.600000000000001
    - type: mrr_at_1000
      value: 11.697000000000001
    - type: mrr_at_3
      value: 10.019
    - type: mrr_at_5
      value: 10.584
    - type: ndcg_at_1
      value: 7.91
    - type: ndcg_at_10
      value: 12.149000000000001
    - type: ndcg_at_100
      value: 15.177
    - type: ndcg_at_1000
      value: 18.240000000000002
    - type: ndcg_at_3
      value: 10.097000000000001
    - type: ndcg_at_5
      value: 11.058
    - type: precision_at_1
      value: 7.91
    - type: precision_at_10
      value: 1.966
    - type: precision_at_100
      value: 0.376
    - type: precision_at_1000
      value: 0.067
    - type: precision_at_3
      value: 4.331
    - type: precision_at_5
      value: 3.1189999999999998
    - type: recall_at_1
      value: 7.228999999999999
    - type: recall_at_10
      value: 17.360999999999997
    - type: recall_at_100
      value: 31.967000000000002
    - type: recall_at_1000
      value: 56.284
    - type: recall_at_3
      value: 11.692
    - type: recall_at_5
      value: 14.084
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 3.666
    - type: map_at_10
      value: 5.902
    - type: map_at_100
      value: 6.436
    - type: map_at_1000
      value: 6.529
    - type: map_at_3
      value: 5.0729999999999995
    - type: map_at_5
      value: 5.466
    - type: mrr_at_1
      value: 4.726
    - type: mrr_at_10
      value: 7.59
    - type: mrr_at_100
      value: 8.190999999999999
    - type: mrr_at_1000
      value: 8.275
    - type: mrr_at_3
      value: 6.426
    - type: mrr_at_5
      value: 6.973
    - type: ndcg_at_1
      value: 4.726
    - type: ndcg_at_10
      value: 7.707999999999999
    - type: ndcg_at_100
      value: 10.688
    - type: ndcg_at_1000
      value: 13.5
    - type: ndcg_at_3
      value: 5.865
    - type: ndcg_at_5
      value: 6.58
    - type: precision_at_1
      value: 4.726
    - type: precision_at_10
      value: 1.592
    - type: precision_at_100
      value: 0.356
    - type: precision_at_1000
      value: 0.06899999999999999
    - type: precision_at_3
      value: 2.861
    - type: precision_at_5
      value: 2.189
    - type: recall_at_1
      value: 3.666
    - type: recall_at_10
      value: 11.700000000000001
    - type: recall_at_100
      value: 25.474000000000004
    - type: recall_at_1000
      value: 46.483000000000004
    - type: recall_at_3
      value: 6.749
    - type: recall_at_5
      value: 8.461
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 12.57
    - type: map_at_10
      value: 16.923
    - type: map_at_100
      value: 17.78
    - type: map_at_1000
      value: 17.909
    - type: map_at_3
      value: 15.143
    - type: map_at_5
      value: 16.145
    - type: mrr_at_1
      value: 15.303
    - type: mrr_at_10
      value: 20.379
    - type: mrr_at_100
      value: 21.169
    - type: mrr_at_1000
      value: 21.257
    - type: mrr_at_3
      value: 18.479
    - type: mrr_at_5
      value: 19.548
    - type: ndcg_at_1
      value: 15.303
    - type: ndcg_at_10
      value: 20.308999999999997
    - type: ndcg_at_100
      value: 24.740000000000002
    - type: ndcg_at_1000
      value: 28.031
    - type: ndcg_at_3
      value: 17.03
    - type: ndcg_at_5
      value: 18.614
    - type: precision_at_1
      value: 15.303
    - type: precision_at_10
      value: 3.821
    - type: precision_at_100
      value: 0.741
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_3
      value: 7.988
    - type: precision_at_5
      value: 5.987
    - type: recall_at_1
      value: 12.57
    - type: recall_at_10
      value: 27.267000000000003
    - type: recall_at_100
      value: 46.995
    - type: recall_at_1000
      value: 70.743
    - type: recall_at_3
      value: 18.13
    - type: recall_at_5
      value: 22.16
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 8.965
    - type: map_at_10
      value: 11.955
    - type: map_at_100
      value: 12.82
    - type: map_at_1000
      value: 12.937999999999999
    - type: map_at_3
      value: 10.545
    - type: map_at_5
      value: 11.39
    - type: mrr_at_1
      value: 11.073
    - type: mrr_at_10
      value: 14.684
    - type: mrr_at_100
      value: 15.487
    - type: mrr_at_1000
      value: 15.583
    - type: mrr_at_3
      value: 12.995000000000001
    - type: mrr_at_5
      value: 14.022000000000002
    - type: ndcg_at_1
      value: 11.073
    - type: ndcg_at_10
      value: 14.511
    - type: ndcg_at_100
      value: 19.187
    - type: ndcg_at_1000
      value: 22.643
    - type: ndcg_at_3
      value: 11.736
    - type: ndcg_at_5
      value: 13.184000000000001
    - type: precision_at_1
      value: 11.073
    - type: precision_at_10
      value: 2.705
    - type: precision_at_100
      value: 0.614
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_3
      value: 5.4030000000000005
    - type: precision_at_5
      value: 4.224
    - type: recall_at_1
      value: 8.965
    - type: recall_at_10
      value: 19.739
    - type: recall_at_100
      value: 41.118
    - type: recall_at_1000
      value: 66.338
    - type: recall_at_3
      value: 12.456
    - type: recall_at_5
      value: 15.921
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 10.108083333333333
    - type: map_at_10
      value: 13.991999999999999
    - type: map_at_100
      value: 14.732333333333333
    - type: map_at_1000
      value: 14.844750000000001
    - type: map_at_3
      value: 12.643666666666666
    - type: map_at_5
      value: 13.403166666666666
    - type: mrr_at_1
      value: 12.410499999999999
    - type: mrr_at_10
      value: 16.612333333333332
    - type: mrr_at_100
      value: 17.314500000000002
    - type: mrr_at_1000
      value: 17.400916666666667
    - type: mrr_at_3
      value: 15.176250000000003
    - type: mrr_at_5
      value: 15.996083333333337
    - type: ndcg_at_1
      value: 12.410499999999999
    - type: ndcg_at_10
      value: 16.770000000000003
    - type: ndcg_at_100
      value: 20.619166666666665
    - type: ndcg_at_1000
      value: 23.642416666666666
    - type: ndcg_at_3
      value: 14.258999999999997
    - type: ndcg_at_5
      value: 15.456583333333333
    - type: precision_at_1
      value: 12.410499999999999
    - type: precision_at_10
      value: 3.072416666666667
    - type: precision_at_100
      value: 0.6025833333333332
    - type: precision_at_1000
      value: 0.10208333333333332
    - type: precision_at_3
      value: 6.697916666666666
    - type: precision_at_5
      value: 4.908416666666667
    - type: recall_at_1
      value: 10.108083333333333
    - type: recall_at_10
      value: 22.638333333333332
    - type: recall_at_100
      value: 40.4035
    - type: recall_at_1000
      value: 62.729666666666674
    - type: recall_at_3
      value: 15.552249999999997
    - type: recall_at_5
      value: 18.653
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 6.938999999999999
    - type: map_at_10
      value: 10.834000000000001
    - type: map_at_100
      value: 11.478
    - type: map_at_1000
      value: 11.552
    - type: map_at_3
      value: 9.661999999999999
    - type: map_at_5
      value: 10.316
    - type: mrr_at_1
      value: 8.436
    - type: mrr_at_10
      value: 12.531
    - type: mrr_at_100
      value: 13.165
    - type: mrr_at_1000
      value: 13.229
    - type: mrr_at_3
      value: 11.324
    - type: mrr_at_5
      value: 11.953
    - type: ndcg_at_1
      value: 8.436
    - type: ndcg_at_10
      value: 13.264999999999999
    - type: ndcg_at_100
      value: 16.637
    - type: ndcg_at_1000
      value: 18.681
    - type: ndcg_at_3
      value: 10.993
    - type: ndcg_at_5
      value: 12.033000000000001
    - type: precision_at_1
      value: 8.436
    - type: precision_at_10
      value: 2.408
    - type: precision_at_100
      value: 0.44600000000000006
    - type: precision_at_1000
      value: 0.067
    - type: precision_at_3
      value: 5.215
    - type: precision_at_5
      value: 3.804
    - type: recall_at_1
      value: 6.938999999999999
    - type: recall_at_10
      value: 19.154
    - type: recall_at_100
      value: 34.833
    - type: recall_at_1000
      value: 50.275999999999996
    - type: recall_at_3
      value: 12.740000000000002
    - type: recall_at_5
      value: 15.473999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 4.916
    - type: map_at_10
      value: 7.295
    - type: map_at_100
      value: 7.793
    - type: map_at_1000
      value: 7.886
    - type: map_at_3
      value: 6.462
    - type: map_at_5
      value: 6.927
    - type: mrr_at_1
      value: 6.607
    - type: mrr_at_10
      value: 9.322999999999999
    - type: mrr_at_100
      value: 9.847
    - type: mrr_at_1000
      value: 9.932
    - type: mrr_at_3
      value: 8.368
    - type: mrr_at_5
      value: 8.905000000000001
    - type: ndcg_at_1
      value: 6.607
    - type: ndcg_at_10
      value: 9.123000000000001
    - type: ndcg_at_100
      value: 11.846
    - type: ndcg_at_1000
      value: 14.732000000000001
    - type: ndcg_at_3
      value: 7.5520000000000005
    - type: ndcg_at_5
      value: 8.272
    - type: precision_at_1
      value: 6.607
    - type: precision_at_10
      value: 1.796
    - type: precision_at_100
      value: 0.379
    - type: precision_at_1000
      value: 0.074
    - type: precision_at_3
      value: 3.739
    - type: precision_at_5
      value: 2.815
    - type: recall_at_1
      value: 4.916
    - type: recall_at_10
      value: 12.773000000000001
    - type: recall_at_100
      value: 25.465
    - type: recall_at_1000
      value: 47.243
    - type: recall_at_3
      value: 8.272
    - type: recall_at_5
      value: 10.162
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 9.5
    - type: map_at_10
      value: 12.776000000000002
    - type: map_at_100
      value: 13.444
    - type: map_at_1000
      value: 13.547999999999998
    - type: map_at_3
      value: 11.858
    - type: map_at_5
      value: 12.231
    - type: mrr_at_1
      value: 11.66
    - type: mrr_at_10
      value: 15.454
    - type: mrr_at_100
      value: 16.137999999999998
    - type: mrr_at_1000
      value: 16.233
    - type: mrr_at_3
      value: 14.427999999999999
    - type: mrr_at_5
      value: 14.81
    - type: ndcg_at_1
      value: 11.66
    - type: ndcg_at_10
      value: 15.27
    - type: ndcg_at_100
      value: 18.965
    - type: ndcg_at_1000
      value: 22.177
    - type: ndcg_at_3
      value: 13.431000000000001
    - type: ndcg_at_5
      value: 13.944999999999999
    - type: precision_at_1
      value: 11.66
    - type: precision_at_10
      value: 2.603
    - type: precision_at_100
      value: 0.504
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.281000000000001
    - type: precision_at_5
      value: 4.179
    - type: recall_at_1
      value: 9.5
    - type: recall_at_10
      value: 20.514
    - type: recall_at_100
      value: 37.724000000000004
    - type: recall_at_1000
      value: 62.098
    - type: recall_at_3
      value: 15.034
    - type: recall_at_5
      value: 16.506999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 12.277000000000001
    - type: map_at_10
      value: 16.07
    - type: map_at_100
      value: 16.958000000000002
    - type: map_at_1000
      value: 17.142
    - type: map_at_3
      value: 14.457999999999998
    - type: map_at_5
      value: 15.283
    - type: mrr_at_1
      value: 15.415000000000001
    - type: mrr_at_10
      value: 19.624
    - type: mrr_at_100
      value: 20.434
    - type: mrr_at_1000
      value: 20.525
    - type: mrr_at_3
      value: 18.083
    - type: mrr_at_5
      value: 18.903
    - type: ndcg_at_1
      value: 15.415000000000001
    - type: ndcg_at_10
      value: 19.429
    - type: ndcg_at_100
      value: 23.767
    - type: ndcg_at_1000
      value: 27.415
    - type: ndcg_at_3
      value: 16.73
    - type: ndcg_at_5
      value: 17.882
    - type: precision_at_1
      value: 15.415000000000001
    - type: precision_at_10
      value: 3.794
    - type: precision_at_100
      value: 0.8869999999999999
    - type: precision_at_1000
      value: 0.173
    - type: precision_at_3
      value: 7.971
    - type: precision_at_5
      value: 5.731
    - type: recall_at_1
      value: 12.277000000000001
    - type: recall_at_10
      value: 25.441999999999997
    - type: recall_at_100
      value: 46.048
    - type: recall_at_1000
      value: 71.329
    - type: recall_at_3
      value: 17.055999999999997
    - type: recall_at_5
      value: 20.53
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 6.531000000000001
    - type: map_at_10
      value: 9.957
    - type: map_at_100
      value: 10.584
    - type: map_at_1000
      value: 10.683
    - type: map_at_3
      value: 8.811
    - type: map_at_5
      value: 9.536
    - type: mrr_at_1
      value: 7.2090000000000005
    - type: mrr_at_10
      value: 10.961
    - type: mrr_at_100
      value: 11.582
    - type: mrr_at_1000
      value: 11.677999999999999
    - type: mrr_at_3
      value: 9.643
    - type: mrr_at_5
      value: 10.465
    - type: ndcg_at_1
      value: 7.2090000000000005
    - type: ndcg_at_10
      value: 12.254
    - type: ndcg_at_100
      value: 15.891
    - type: ndcg_at_1000
      value: 18.965
    - type: ndcg_at_3
      value: 9.789
    - type: ndcg_at_5
      value: 11.142000000000001
    - type: precision_at_1
      value: 7.2090000000000005
    - type: precision_at_10
      value: 2.089
    - type: precision_at_100
      value: 0.43099999999999994
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.313000000000001
    - type: precision_at_5
      value: 3.327
    - type: recall_at_1
      value: 6.531000000000001
    - type: recall_at_10
      value: 18.465999999999998
    - type: recall_at_100
      value: 36.158
    - type: recall_at_1000
      value: 60.245000000000005
    - type: recall_at_3
      value: 11.860999999999999
    - type: recall_at_5
      value: 15.071000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 5.463
    - type: map_at_10
      value: 9.592
    - type: map_at_100
      value: 10.724
    - type: map_at_1000
      value: 10.892
    - type: map_at_3
      value: 7.866
    - type: map_at_5
      value: 8.658000000000001
    - type: mrr_at_1
      value: 12.899
    - type: mrr_at_10
      value: 20.073
    - type: mrr_at_100
      value: 21.05
    - type: mrr_at_1000
      value: 21.126
    - type: mrr_at_3
      value: 17.438000000000002
    - type: mrr_at_5
      value: 18.756999999999998
    - type: ndcg_at_1
      value: 12.899
    - type: ndcg_at_10
      value: 14.539
    - type: ndcg_at_100
      value: 19.903000000000002
    - type: ndcg_at_1000
      value: 23.485
    - type: ndcg_at_3
      value: 11.225999999999999
    - type: ndcg_at_5
      value: 12.232
    - type: precision_at_1
      value: 12.899
    - type: precision_at_10
      value: 4.8340000000000005
    - type: precision_at_100
      value: 1.053
    - type: precision_at_1000
      value: 0.16999999999999998
    - type: precision_at_3
      value: 8.512
    - type: precision_at_5
      value: 6.683999999999999
    - type: recall_at_1
      value: 5.463
    - type: recall_at_10
      value: 18.383
    - type: recall_at_100
      value: 37.592999999999996
    - type: recall_at_1000
      value: 58.12199999999999
    - type: recall_at_3
      value: 10.388
    - type: recall_at_5
      value: 13.197999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 2.386
    - type: map_at_10
      value: 5.118
    - type: map_at_100
      value: 6.997000000000001
    - type: map_at_1000
      value: 7.5520000000000005
    - type: map_at_3
      value: 3.8019999999999996
    - type: map_at_5
      value: 4.38
    - type: mrr_at_1
      value: 28.000000000000004
    - type: mrr_at_10
      value: 36.482
    - type: mrr_at_100
      value: 37.284
    - type: mrr_at_1000
      value: 37.338
    - type: mrr_at_3
      value: 33.875
    - type: mrr_at_5
      value: 35.3
    - type: ndcg_at_1
      value: 19.625
    - type: ndcg_at_10
      value: 14.543000000000001
    - type: ndcg_at_100
      value: 16.511
    - type: ndcg_at_1000
      value: 21.855
    - type: ndcg_at_3
      value: 16.842
    - type: ndcg_at_5
      value: 15.405
    - type: precision_at_1
      value: 28.000000000000004
    - type: precision_at_10
      value: 13.15
    - type: precision_at_100
      value: 4.192
    - type: precision_at_1000
      value: 0.918
    - type: precision_at_3
      value: 20.833
    - type: precision_at_5
      value: 16.950000000000003
    - type: recall_at_1
      value: 2.386
    - type: recall_at_10
      value: 8.482000000000001
    - type: recall_at_100
      value: 20.44
    - type: recall_at_1000
      value: 39.257
    - type: recall_at_3
      value: 4.739
    - type: recall_at_5
      value: 6.1370000000000005
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 32.865
    - type: f1
      value: 30.37449911679073
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 7.928
    - type: map_at_10
      value: 11.763
    - type: map_at_100
      value: 12.429
    - type: map_at_1000
      value: 12.499
    - type: map_at_3
      value: 10.452
    - type: map_at_5
      value: 11.162999999999998
    - type: mrr_at_1
      value: 8.371
    - type: mrr_at_10
      value: 12.357
    - type: mrr_at_100
      value: 13.061
    - type: mrr_at_1000
      value: 13.129
    - type: mrr_at_3
      value: 11.016
    - type: mrr_at_5
      value: 11.729000000000001
    - type: ndcg_at_1
      value: 8.371
    - type: ndcg_at_10
      value: 14.182
    - type: ndcg_at_100
      value: 17.771
    - type: ndcg_at_1000
      value: 19.872
    - type: ndcg_at_3
      value: 11.434999999999999
    - type: ndcg_at_5
      value: 12.708
    - type: precision_at_1
      value: 8.371
    - type: precision_at_10
      value: 2.283
    - type: precision_at_100
      value: 0.42100000000000004
    - type: precision_at_1000
      value: 0.062
    - type: precision_at_3
      value: 4.8500000000000005
    - type: precision_at_5
      value: 3.5700000000000003
    - type: recall_at_1
      value: 7.928
    - type: recall_at_10
      value: 21.287
    - type: recall_at_100
      value: 38.393
    - type: recall_at_1000
      value: 54.925000000000004
    - type: recall_at_3
      value: 13.725000000000001
    - type: recall_at_5
      value: 16.798
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 4.37
    - type: map_at_10
      value: 7.382
    - type: map_at_100
      value: 8.193
    - type: map_at_1000
      value: 8.349
    - type: map_at_3
      value: 6.361
    - type: map_at_5
      value: 6.814000000000001
    - type: mrr_at_1
      value: 8.642
    - type: mrr_at_10
      value: 13.352
    - type: mrr_at_100
      value: 14.288
    - type: mrr_at_1000
      value: 14.394000000000002
    - type: mrr_at_3
      value: 11.728
    - type: mrr_at_5
      value: 12.592999999999998
    - type: ndcg_at_1
      value: 8.642
    - type: ndcg_at_10
      value: 10.464
    - type: ndcg_at_100
      value: 14.921000000000001
    - type: ndcg_at_1000
      value: 19.106
    - type: ndcg_at_3
      value: 8.564
    - type: ndcg_at_5
      value: 9.186
    - type: precision_at_1
      value: 8.642
    - type: precision_at_10
      value: 2.978
    - type: precision_at_100
      value: 0.738
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 5.71
    - type: precision_at_5
      value: 4.352
    - type: recall_at_1
      value: 4.37
    - type: recall_at_10
      value: 13.794
    - type: recall_at_100
      value: 31.596000000000004
    - type: recall_at_1000
      value: 58.724
    - type: recall_at_3
      value: 8.401
    - type: recall_at_5
      value: 10.266
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 8.596
    - type: map_at_10
      value: 11.951
    - type: map_at_100
      value: 12.478
    - type: map_at_1000
      value: 12.558
    - type: map_at_3
      value: 10.870000000000001
    - type: map_at_5
      value: 11.476
    - type: mrr_at_1
      value: 17.191000000000003
    - type: mrr_at_10
      value: 21.662
    - type: mrr_at_100
      value: 22.249
    - type: mrr_at_1000
      value: 22.319
    - type: mrr_at_3
      value: 20.227
    - type: mrr_at_5
      value: 21.047
    - type: ndcg_at_1
      value: 17.191000000000003
    - type: ndcg_at_10
      value: 15.939
    - type: ndcg_at_100
      value: 18.711
    - type: ndcg_at_1000
      value: 20.942
    - type: ndcg_at_3
      value: 13.642999999999999
    - type: ndcg_at_5
      value: 14.767
    - type: precision_at_1
      value: 17.191000000000003
    - type: precision_at_10
      value: 3.633
    - type: precision_at_100
      value: 0.587
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 8.643
    - type: precision_at_5
      value: 6.077
    - type: recall_at_1
      value: 8.596
    - type: recall_at_10
      value: 18.163
    - type: recall_at_100
      value: 29.359
    - type: recall_at_1000
      value: 44.348
    - type: recall_at_3
      value: 12.964
    - type: recall_at_5
      value: 15.192
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 63.91439999999999
    - type: ap
      value: 59.096879955371705
    - type: f1
      value: 63.65122028830217
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 4.728000000000001
    - type: map_at_10
      value: 7.846
    - type: map_at_100
      value: 8.577
    - type: map_at_1000
      value: 8.669
    - type: map_at_3
      value: 6.601
    - type: map_at_5
      value: 7.239
    - type: mrr_at_1
      value: 4.857
    - type: mrr_at_10
      value: 8.056000000000001
    - type: mrr_at_100
      value: 8.792
    - type: mrr_at_1000
      value: 8.882
    - type: mrr_at_3
      value: 6.776999999999999
    - type: mrr_at_5
      value: 7.430000000000001
    - type: ndcg_at_1
      value: 4.842
    - type: ndcg_at_10
      value: 9.908999999999999
    - type: ndcg_at_100
      value: 14.008999999999999
    - type: ndcg_at_1000
      value: 16.833000000000002
    - type: ndcg_at_3
      value: 7.276000000000001
    - type: ndcg_at_5
      value: 8.434
    - type: precision_at_1
      value: 4.842
    - type: precision_at_10
      value: 1.699
    - type: precision_at_100
      value: 0.384
    - type: precision_at_1000
      value: 0.063
    - type: precision_at_3
      value: 3.114
    - type: precision_at_5
      value: 2.45
    - type: recall_at_1
      value: 4.728000000000001
    - type: recall_at_10
      value: 16.375
    - type: recall_at_100
      value: 36.644
    - type: recall_at_1000
      value: 59.394999999999996
    - type: recall_at_3
      value: 9.062000000000001
    - type: recall_at_5
      value: 11.866999999999999
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.20291837665299
    - type: f1
      value: 84.70904496376967
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.529867761057915
    - type: f1
      value: 37.68950362422533
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 56.38870208473436
    - type: f1
      value: 53.66913773017876
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.53597848016139
    - type: f1
      value: 62.79623963098659
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 27.17951777550973
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.59311527698471
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 28.965933039410707
    - type: mrr
      value: 29.71860627679794
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.497
    - type: map_at_10
      value: 7.195
    - type: map_at_100
      value: 8.738999999999999
    - type: map_at_1000
      value: 9.934999999999999
    - type: map_at_3
      value: 5.572
    - type: map_at_5
      value: 6.311
    - type: mrr_at_1
      value: 26.935
    - type: mrr_at_10
      value: 38.634
    - type: mrr_at_100
      value: 39.236
    - type: mrr_at_1000
      value: 39.308
    - type: mrr_at_3
      value: 35.759
    - type: mrr_at_5
      value: 37.183
    - type: ndcg_at_1
      value: 25.697
    - type: ndcg_at_10
      value: 21.618000000000002
    - type: ndcg_at_100
      value: 20.832
    - type: ndcg_at_1000
      value: 30.742000000000004
    - type: ndcg_at_3
      value: 23.904
    - type: ndcg_at_5
      value: 22.922
    - type: precision_at_1
      value: 26.935
    - type: precision_at_10
      value: 15.851
    - type: precision_at_100
      value: 5.5329999999999995
    - type: precision_at_1000
      value: 1.886
    - type: precision_at_3
      value: 22.497
    - type: precision_at_5
      value: 19.752
    - type: recall_at_1
      value: 3.497
    - type: recall_at_10
      value: 11.411999999999999
    - type: recall_at_100
      value: 23.757
    - type: recall_at_1000
      value: 58.314
    - type: recall_at_3
      value: 6.814000000000001
    - type: recall_at_5
      value: 8.36
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 6.4430000000000005
    - type: map_at_10
      value: 10.884
    - type: map_at_100
      value: 11.689
    - type: map_at_1000
      value: 11.772
    - type: map_at_3
      value: 9.109
    - type: map_at_5
      value: 10.075000000000001
    - type: mrr_at_1
      value: 7.445
    - type: mrr_at_10
      value: 12.103
    - type: mrr_at_100
      value: 12.882
    - type: mrr_at_1000
      value: 12.956999999999999
    - type: mrr_at_3
      value: 10.294
    - type: mrr_at_5
      value: 11.292
    - type: ndcg_at_1
      value: 7.445
    - type: ndcg_at_10
      value: 13.949
    - type: ndcg_at_100
      value: 18.285999999999998
    - type: ndcg_at_1000
      value: 20.738
    - type: ndcg_at_3
      value: 10.302999999999999
    - type: ndcg_at_5
      value: 12.052
    - type: precision_at_1
      value: 7.445
    - type: precision_at_10
      value: 2.648
    - type: precision_at_100
      value: 0.516
    - type: precision_at_1000
      value: 0.075
    - type: precision_at_3
      value: 4.896
    - type: precision_at_5
      value: 3.9170000000000003
    - type: recall_at_1
      value: 6.4430000000000005
    - type: recall_at_10
      value: 22.296
    - type: recall_at_100
      value: 42.903000000000006
    - type: recall_at_1000
      value: 61.988
    - type: recall_at_3
      value: 12.617999999999999
    - type: recall_at_5
      value: 16.77
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 54.93599999999999
    - type: map_at_10
      value: 66.461
    - type: map_at_100
      value: 67.274
    - type: map_at_1000
      value: 67.31899999999999
    - type: map_at_3
      value: 63.742
    - type: map_at_5
      value: 65.347
    - type: mrr_at_1
      value: 63.28
    - type: mrr_at_10
      value: 71.163
    - type: mrr_at_100
      value: 71.53
    - type: mrr_at_1000
      value: 71.54599999999999
    - type: mrr_at_3
      value: 69.50699999999999
    - type: mrr_at_5
      value: 70.52000000000001
    - type: ndcg_at_1
      value: 63.33
    - type: ndcg_at_10
      value: 71.439
    - type: ndcg_at_100
      value: 74.154
    - type: ndcg_at_1000
      value: 74.90400000000001
    - type: ndcg_at_3
      value: 67.723
    - type: ndcg_at_5
      value: 69.549
    - type: precision_at_1
      value: 63.33
    - type: precision_at_10
      value: 10.81
    - type: precision_at_100
      value: 1.3390000000000002
    - type: precision_at_1000
      value: 0.147
    - type: precision_at_3
      value: 29.38
    - type: precision_at_5
      value: 19.432
    - type: recall_at_1
      value: 54.93599999999999
    - type: recall_at_10
      value: 81.259
    - type: recall_at_100
      value: 92.15100000000001
    - type: recall_at_1000
      value: 96.994
    - type: recall_at_3
      value: 70.499
    - type: recall_at_5
      value: 75.575
    - type: map_at_1
      value: 2.078
    - type: map_at_10
      value: 5.050000000000001
    - type: map_at_100
      value: 6.0440000000000005
    - type: map_at_1000
      value: 6.261
    - type: map_at_3
      value: 3.763
    - type: map_at_5
      value: 4.376
    - type: mrr_at_1
      value: 10.2
    - type: mrr_at_10
      value: 17.36
    - type: mrr_at_100
      value: 18.403
    - type: mrr_at_1000
      value: 18.52
    - type: mrr_at_3
      value: 14.899999999999999
    - type: mrr_at_5
      value: 16.13
    - type: ndcg_at_1
      value: 10.2
    - type: ndcg_at_10
      value: 9.398
    - type: ndcg_at_100
      value: 14.48
    - type: ndcg_at_1000
      value: 19.551
    - type: ndcg_at_3
      value: 8.790000000000001
    - type: ndcg_at_5
      value: 7.669
    - type: precision_at_1
      value: 10.2
    - type: precision_at_10
      value: 4.9399999999999995
    - type: precision_at_100
      value: 1.25
    - type: precision_at_1000
      value: 0.248
    - type: precision_at_3
      value: 8.267
    - type: precision_at_5
      value: 6.74
    - type: recall_at_1
      value: 2.078
    - type: recall_at_10
      value: 10.025
    - type: recall_at_100
      value: 25.346999999999998
    - type: recall_at_1000
      value: 50.393
    - type: recall_at_3
      value: 5.038
    - type: recall_at_5
      value: 6.851999999999999
    - type: map_at_1
      value: 0.127
    - type: map_at_10
      value: 0.79
    - type: map_at_100
      value: 3.549
    - type: map_at_1000
      value: 8.137
    - type: map_at_3
      value: 0.32299999999999995
    - type: map_at_5
      value: 0.44200000000000006
    - type: mrr_at_1
      value: 56.00000000000001
    - type: mrr_at_10
      value: 66.777
    - type: mrr_at_100
      value: 67.09
    - type: mrr_at_1000
      value: 67.09
    - type: mrr_at_3
      value: 65.0
    - type: mrr_at_5
      value: 65.4
    - type: ndcg_at_1
      value: 48.0
    - type: ndcg_at_10
      value: 41.178
    - type: ndcg_at_100
      value: 28.372000000000003
    - type: ndcg_at_1000
      value: 24.953
    - type: ndcg_at_3
      value: 44.285000000000004
    - type: ndcg_at_5
      value: 42.074
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 45.4
    - type: precision_at_100
      value: 29.34
    - type: precision_at_1000
      value: 12.112
    - type: precision_at_3
      value: 49.333
    - type: precision_at_5
      value: 45.2
    - type: recall_at_1
      value: 0.127
    - type: recall_at_10
      value: 1.0739999999999998
    - type: recall_at_100
      value: 6.36
    - type: recall_at_1000
      value: 24.374000000000002
    - type: recall_at_3
      value: 0.372
    - type: recall_at_5
      value: 0.528
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 28.528725482087307
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 39.02529299655054
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 70.69485438461535
    - type: cos_sim_spearman
      value: 60.7079462281202
    - type: euclidean_pearson
      value: 66.34648734074841
    - type: euclidean_spearman
      value: 60.70819668068561
    - type: manhattan_pearson
      value: 67.08589891209486
    - type: manhattan_spearman
      value: 61.037259945651165
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 62.63440086574824
    - type: cos_sim_spearman
      value: 57.22862459567004
    - type: euclidean_pearson
      value: 61.33135391980671
    - type: euclidean_spearman
      value: 57.2287396395971
    - type: manhattan_pearson
      value: 63.538353299276665
    - type: manhattan_spearman
      value: 59.31604272847601
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 66.99729287299299
    - type: cos_sim_spearman
      value: 69.20264774948375
    - type: euclidean_pearson
      value: 68.83879433164682
    - type: euclidean_spearman
      value: 69.20257380705361
    - type: manhattan_pearson
      value: 68.82235273988779
    - type: manhattan_spearman
      value: 69.12895594376502
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 63.43542239265359
    - type: cos_sim_spearman
      value: 62.75650954855537
    - type: euclidean_pearson
      value: 63.87500752354951
    - type: euclidean_spearman
      value: 62.75647357698498
    - type: manhattan_pearson
      value: 64.30854220561612
    - type: manhattan_spearman
      value: 63.221533112975756
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 70.3113558570832
    - type: cos_sim_spearman
      value: 72.99345938388264
    - type: euclidean_pearson
      value: 72.46131589134022
    - type: euclidean_spearman
      value: 72.99345776180552
    - type: manhattan_pearson
      value: 72.98365443642383
    - type: manhattan_spearman
      value: 73.52773752441843
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 59.508816955942734
    - type: cos_sim_spearman
      value: 64.16476610475141
    - type: euclidean_pearson
      value: 63.49096301327081
    - type: euclidean_spearman
      value: 64.16559631894077
    - type: manhattan_pearson
      value: 63.756149631030304
    - type: manhattan_spearman
      value: 64.26840399223137
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 67.68609826979123
    - type: cos_sim_spearman
      value: 71.8432324170499
    - type: euclidean_pearson
      value: 70.78716630279412
    - type: euclidean_spearman
      value: 71.84411358655781
    - type: manhattan_pearson
      value: 71.1878199213668
    - type: manhattan_spearman
      value: 71.86475568531382
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 37.9433386647078
    - type: cos_sim_spearman
      value: 52.54985995593481
    - type: euclidean_pearson
      value: 46.11105905665655
    - type: euclidean_spearman
      value: 52.54985995593481
    - type: manhattan_pearson
      value: 46.41925532506553
    - type: manhattan_spearman
      value: 52.88777657839048
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 60.69914968545304
    - type: cos_sim_spearman
      value: 60.16961331310221
    - type: euclidean_pearson
      value: 62.24558593778339
    - type: euclidean_spearman
      value: 60.16965021618944
    - type: manhattan_pearson
      value: 62.75643658834279
    - type: manhattan_spearman
      value: 60.537294014043894
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 67.86284091295416
    - type: mrr
      value: 88.32576192870312
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 24.778
    - type: map_at_10
      value: 32.706
    - type: map_at_100
      value: 33.571
    - type: map_at_1000
      value: 33.678000000000004
    - type: map_at_3
      value: 29.976999999999997
    - type: map_at_5
      value: 31.594
    - type: mrr_at_1
      value: 25.667
    - type: mrr_at_10
      value: 33.932
    - type: mrr_at_100
      value: 34.698
    - type: mrr_at_1000
      value: 34.788000000000004
    - type: mrr_at_3
      value: 31.278
    - type: mrr_at_5
      value: 32.861000000000004
    - type: ndcg_at_1
      value: 25.667
    - type: ndcg_at_10
      value: 37.522
    - type: ndcg_at_100
      value: 42.132
    - type: ndcg_at_1000
      value: 44.702999999999996
    - type: ndcg_at_3
      value: 31.948
    - type: ndcg_at_5
      value: 34.867
    - type: precision_at_1
      value: 25.667
    - type: precision_at_10
      value: 5.567
    - type: precision_at_100
      value: 0.827
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_3
      value: 13.0
    - type: precision_at_5
      value: 9.4
    - type: recall_at_1
      value: 24.778
    - type: recall_at_10
      value: 51.471999999999994
    - type: recall_at_100
      value: 73.47200000000001
    - type: recall_at_1000
      value: 93.01700000000001
    - type: recall_at_3
      value: 36.222
    - type: recall_at_5
      value: 43.389
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.48514851485149
    - type: cos_sim_ap
      value: 75.38722575287751
    - type: cos_sim_f1
      value: 70.21505376344086
    - type: cos_sim_precision
      value: 75.93023255813954
    - type: cos_sim_recall
      value: 65.3
    - type: dot_accuracy
      value: 99.48514851485149
    - type: dot_ap
      value: 75.38722575287751
    - type: dot_f1
      value: 70.21505376344086
    - type: dot_precision
      value: 75.93023255813954
    - type: dot_recall
      value: 65.3
    - type: euclidean_accuracy
      value: 99.48514851485149
    - type: euclidean_ap
      value: 75.38722575287751
    - type: euclidean_f1
      value: 70.21505376344086
    - type: euclidean_precision
      value: 75.93023255813954
    - type: euclidean_recall
      value: 65.3
    - type: manhattan_accuracy
      value: 99.51782178217822
    - type: manhattan_ap
      value: 78.5581368006355
    - type: manhattan_f1
      value: 72.85333333333335
    - type: manhattan_precision
      value: 78.05714285714286
    - type: manhattan_recall
      value: 68.30000000000001
    - type: max_accuracy
      value: 99.51782178217822
    - type: max_ap
      value: 78.5581368006355
    - type: max_f1
      value: 72.85333333333335
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 41.454786971313716
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 27.982742328787946
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 39.80307350579408
    - type: mrr
      value: 39.984641583906296
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.508810779370265
    - type: cos_sim_spearman
      value: 31.41267324195085
    - type: dot_pearson
      value: 30.50881077275705
    - type: dot_spearman
      value: 31.409127482666634
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.353
    - type: map_at_10
      value: 3.871
    - type: map_at_100
      value: 6.507000000000001
    - type: map_at_1000
      value: 7.982
    - type: map_at_3
      value: 2.249
    - type: map_at_5
      value: 3.0140000000000002
    - type: mrr_at_1
      value: 18.367
    - type: mrr_at_10
      value: 27.947
    - type: mrr_at_100
      value: 30.349999999999998
    - type: mrr_at_1000
      value: 30.372
    - type: mrr_at_3
      value: 23.469
    - type: mrr_at_5
      value: 26.429000000000002
    - type: ndcg_at_1
      value: 16.326999999999998
    - type: ndcg_at_10
      value: 11.886
    - type: ndcg_at_100
      value: 20.929000000000002
    - type: ndcg_at_1000
      value: 34.422999999999995
    - type: ndcg_at_3
      value: 12.806999999999999
    - type: ndcg_at_5
      value: 12.879999999999999
    - type: precision_at_1
      value: 18.367
    - type: precision_at_10
      value: 11.224
    - type: precision_at_100
      value: 5.061
    - type: precision_at_1000
      value: 1.341
    - type: precision_at_3
      value: 13.605
    - type: precision_at_5
      value: 13.877999999999998
    - type: recall_at_1
      value: 1.353
    - type: recall_at_10
      value: 7.654
    - type: recall_at_100
      value: 31.558000000000003
    - type: recall_at_1000
      value: 72.898
    - type: recall_at_3
      value: 2.964
    - type: recall_at_5
      value: 4.874
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.8528
    - type: ap
      value: 13.242246154786407
    - type: f1
      value: 53.36206582019686
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.292020373514426
    - type: f1
      value: 52.43359560180576
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 31.730793809823094
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.0826131012696
    - type: cos_sim_ap
      value: 58.927117152392015
    - type: cos_sim_f1
      value: 57.50386797318205
    - type: cos_sim_precision
      value: 56.227937468482104
    - type: cos_sim_recall
      value: 58.839050131926115
    - type: dot_accuracy
      value: 82.0826131012696
    - type: dot_ap
      value: 58.927117152392015
    - type: dot_f1
      value: 57.50386797318205
    - type: dot_precision
      value: 56.227937468482104
    - type: dot_recall
      value: 58.839050131926115
    - type: euclidean_accuracy
      value: 82.0826131012696
    - type: euclidean_ap
      value: 58.927117152392015
    - type: euclidean_f1
      value: 57.50386797318205
    - type: euclidean_precision
      value: 56.227937468482104
    - type: euclidean_recall
      value: 58.839050131926115
    - type: manhattan_accuracy
      value: 82.02300768909816
    - type: manhattan_ap
      value: 58.522165728999134
    - type: manhattan_f1
      value: 57.4462890625
    - type: manhattan_precision
      value: 53.45297592003635
    - type: manhattan_recall
      value: 62.0844327176781
    - type: max_accuracy
      value: 82.0826131012696
    - type: max_ap
      value: 58.927117152392015
    - type: max_f1
      value: 57.50386797318205
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.2459735320371
    - type: cos_sim_ap
      value: 78.90275828118249
    - type: cos_sim_f1
      value: 71.35335558027438
    - type: cos_sim_precision
      value: 68.81705049349162
    - type: cos_sim_recall
      value: 74.08376963350786
    - type: dot_accuracy
      value: 86.2459735320371
    - type: dot_ap
      value: 78.90275960892674
    - type: dot_f1
      value: 71.35335558027438
    - type: dot_precision
      value: 68.81705049349162
    - type: dot_recall
      value: 74.08376963350786
    - type: euclidean_accuracy
      value: 86.2459735320371
    - type: euclidean_ap
      value: 78.90275805900576
    - type: euclidean_f1
      value: 71.35335558027438
    - type: euclidean_precision
      value: 68.81705049349162
    - type: euclidean_recall
      value: 74.08376963350786
    - type: manhattan_accuracy
      value: 86.16835487251136
    - type: manhattan_ap
      value: 78.84683659402509
    - type: manhattan_f1
      value: 71.18720602069612
    - type: manhattan_precision
      value: 69.61801722234489
    - type: manhattan_recall
      value: 72.82876501385894
    - type: max_accuracy
      value: 86.2459735320371
    - type: max_ap
      value: 78.90275960892674
    - type: max_f1
      value: 71.35335558027438
---
