mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.86567164179104
    - type: ap
      value: 34.245594561996064
    - type: f1
      value: 65.69023935040455
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 65.190925
    - type: ap
      value: 60.21626939955754
    - type: f1
      value: 64.943414550771
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 34.529999999999994
    - type: f1
      value: 34.01639094527221
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.55
    - type: map_at_10
      value: 35.416
    - type: map_at_100
      value: 36.602000000000004
    - type: map_at_1000
      value: 36.625
    - type: map_at_3
      value: 30.725
    - type: map_at_5
      value: 33.35
    - type: mrr_at_1
      value: 21.906
    - type: mrr_at_10
      value: 35.553000000000004
    - type: mrr_at_100
      value: 36.746
    - type: mrr_at_1000
      value: 36.769
    - type: mrr_at_3
      value: 30.819999999999997
    - type: mrr_at_5
      value: 33.495000000000005
    - type: ndcg_at_1
      value: 21.55
    - type: ndcg_at_10
      value: 43.527
    - type: ndcg_at_100
      value: 49.025
    - type: ndcg_at_1000
      value: 49.586999999999996
    - type: ndcg_at_3
      value: 33.772000000000006
    - type: ndcg_at_5
      value: 38.57
    - type: precision_at_1
      value: 21.55
    - type: precision_at_10
      value: 6.963
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.201
    - type: precision_at_5
      value: 10.882
    - type: recall_at_1
      value: 21.55
    - type: recall_at_10
      value: 69.63000000000001
    - type: recall_at_100
      value: 94.73700000000001
    - type: recall_at_1000
      value: 99.075
    - type: recall_at_3
      value: 42.603
    - type: recall_at_5
      value: 54.410000000000004
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 34.411339757911335
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.489247458031933
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.582468551652696
    - type: mrr
      value: 68.10425185771446
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 81.96093442776794
    - type: cos_sim_spearman
      value: 79.80362560866212
    - type: euclidean_pearson
      value: 81.2337598243594
    - type: euclidean_spearman
      value: 79.80362560866212
    - type: manhattan_pearson
      value: 80.54695854084805
    - type: manhattan_spearman
      value: 79.70904514032895
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.23051948051948
    - type: f1
      value: 72.48430722973309
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.40784337223032
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.628387342867686
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.909
    - type: map_at_10
      value: 30.186
    - type: map_at_100
      value: 31.301000000000002
    - type: map_at_1000
      value: 31.457
    - type: map_at_3
      value: 27.752
    - type: map_at_5
      value: 29.255
    - type: mrr_at_1
      value: 27.467999999999996
    - type: mrr_at_10
      value: 35.655
    - type: mrr_at_100
      value: 36.535000000000004
    - type: mrr_at_1000
      value: 36.608000000000004
    - type: mrr_at_3
      value: 33.882
    - type: mrr_at_5
      value: 34.961999999999996
    - type: ndcg_at_1
      value: 27.467999999999996
    - type: ndcg_at_10
      value: 35.17
    - type: ndcg_at_100
      value: 40.136
    - type: ndcg_at_1000
      value: 43.254999999999995
    - type: ndcg_at_3
      value: 31.884
    - type: ndcg_at_5
      value: 33.532000000000004
    - type: precision_at_1
      value: 27.467999999999996
    - type: precision_at_10
      value: 6.694999999999999
    - type: precision_at_100
      value: 1.133
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 15.689
    - type: precision_at_5
      value: 11.302
    - type: recall_at_1
      value: 21.909
    - type: recall_at_10
      value: 44.008
    - type: recall_at_100
      value: 65.989
    - type: recall_at_1000
      value: 87.046
    - type: recall_at_3
      value: 33.733000000000004
    - type: recall_at_5
      value: 38.626
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.623
    - type: map_at_10
      value: 23.324
    - type: map_at_100
      value: 24.287
    - type: map_at_1000
      value: 24.410999999999998
    - type: map_at_3
      value: 21.392
    - type: map_at_5
      value: 22.477
    - type: mrr_at_1
      value: 22.229
    - type: mrr_at_10
      value: 27.71
    - type: mrr_at_100
      value: 28.523
    - type: mrr_at_1000
      value: 28.596
    - type: mrr_at_3
      value: 25.775
    - type: mrr_at_5
      value: 26.895999999999997
    - type: ndcg_at_1
      value: 22.229
    - type: ndcg_at_10
      value: 27.252
    - type: ndcg_at_100
      value: 31.616
    - type: ndcg_at_1000
      value: 34.488
    - type: ndcg_at_3
      value: 23.926
    - type: ndcg_at_5
      value: 25.467000000000002
    - type: precision_at_1
      value: 22.229
    - type: precision_at_10
      value: 5.032
    - type: precision_at_100
      value: 0.903
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 11.359
    - type: precision_at_5
      value: 8.229000000000001
    - type: recall_at_1
      value: 17.623
    - type: recall_at_10
      value: 34.613
    - type: recall_at_100
      value: 53.784
    - type: recall_at_1000
      value: 73.289
    - type: recall_at_3
      value: 25.121
    - type: recall_at_5
      value: 29.132
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 26.368000000000002
    - type: map_at_10
      value: 35.022
    - type: map_at_100
      value: 36.187999999999995
    - type: map_at_1000
      value: 36.278
    - type: map_at_3
      value: 32.594
    - type: map_at_5
      value: 33.910000000000004
    - type: mrr_at_1
      value: 30.596
    - type: mrr_at_10
      value: 38.29
    - type: mrr_at_100
      value: 39.225
    - type: mrr_at_1000
      value: 39.28
    - type: mrr_at_3
      value: 36.019
    - type: mrr_at_5
      value: 37.285000000000004
    - type: ndcg_at_1
      value: 30.596
    - type: ndcg_at_10
      value: 39.788000000000004
    - type: ndcg_at_100
      value: 45.214
    - type: ndcg_at_1000
      value: 47.301
    - type: ndcg_at_3
      value: 35.28
    - type: ndcg_at_5
      value: 37.368
    - type: precision_at_1
      value: 30.596
    - type: precision_at_10
      value: 6.476
    - type: precision_at_100
      value: 1.004
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 15.758
    - type: precision_at_5
      value: 10.871
    - type: recall_at_1
      value: 26.368000000000002
    - type: recall_at_10
      value: 50.973
    - type: recall_at_100
      value: 75.357
    - type: recall_at_1000
      value: 90.476
    - type: recall_at_3
      value: 38.754
    - type: recall_at_5
      value: 43.958000000000006
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.277
    - type: map_at_10
      value: 17.374000000000002
    - type: map_at_100
      value: 18.182000000000002
    - type: map_at_1000
      value: 18.291
    - type: map_at_3
      value: 15.982
    - type: map_at_5
      value: 16.750999999999998
    - type: mrr_at_1
      value: 14.463000000000001
    - type: mrr_at_10
      value: 18.637
    - type: mrr_at_100
      value: 19.448999999999998
    - type: mrr_at_1000
      value: 19.552
    - type: mrr_at_3
      value: 17.232
    - type: mrr_at_5
      value: 18.006
    - type: ndcg_at_1
      value: 14.463000000000001
    - type: ndcg_at_10
      value: 20.063
    - type: ndcg_at_100
      value: 24.509
    - type: ndcg_at_1000
      value: 27.875
    - type: ndcg_at_3
      value: 17.238
    - type: ndcg_at_5
      value: 18.594
    - type: precision_at_1
      value: 14.463000000000001
    - type: precision_at_10
      value: 3.0620000000000003
    - type: precision_at_100
      value: 0.563
    - type: precision_at_1000
      value: 0.09
    - type: precision_at_3
      value: 7.269
    - type: precision_at_5
      value: 5.106999999999999
    - type: recall_at_1
      value: 13.277
    - type: recall_at_10
      value: 27.250000000000004
    - type: recall_at_100
      value: 48.553000000000004
    - type: recall_at_1000
      value: 74.937
    - type: recall_at_3
      value: 19.586000000000002
    - type: recall_at_5
      value: 22.853
  - 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: 9.888
    - type: map_at_100
      value: 10.645
    - type: map_at_1000
      value: 10.775
    - type: map_at_3
      value: 8.673
    - type: map_at_5
      value: 9.275
    - type: mrr_at_1
      value: 8.581999999999999
    - type: mrr_at_10
      value: 12.365
    - type: mrr_at_100
      value: 13.156
    - type: mrr_at_1000
      value: 13.257
    - type: mrr_at_3
      value: 10.883
    - type: mrr_at_5
      value: 11.616999999999999
    - type: ndcg_at_1
      value: 8.581999999999999
    - type: ndcg_at_10
      value: 12.469
    - type: ndcg_at_100
      value: 16.564
    - type: ndcg_at_1000
      value: 20.263
    - type: ndcg_at_3
      value: 10.001999999999999
    - type: ndcg_at_5
      value: 11.008
    - type: precision_at_1
      value: 8.581999999999999
    - type: precision_at_10
      value: 2.413
    - type: precision_at_100
      value: 0.525
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 4.851
    - type: precision_at_5
      value: 3.6069999999999998
    - type: recall_at_1
      value: 6.497999999999999
    - type: recall_at_10
      value: 18.14
    - type: recall_at_100
      value: 36.699
    - type: recall_at_1000
      value: 64.044
    - type: recall_at_3
      value: 11.245
    - type: recall_at_5
      value: 13.8
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.617
    - type: map_at_10
      value: 23.912
    - type: map_at_100
      value: 25.165
    - type: map_at_1000
      value: 25.298
    - type: map_at_3
      value: 21.953
    - type: map_at_5
      value: 23.114
    - type: mrr_at_1
      value: 22.137
    - type: mrr_at_10
      value: 28.62
    - type: mrr_at_100
      value: 29.653000000000002
    - type: mrr_at_1000
      value: 29.73
    - type: mrr_at_3
      value: 26.58
    - type: mrr_at_5
      value: 27.836
    - type: ndcg_at_1
      value: 22.137
    - type: ndcg_at_10
      value: 28.138
    - type: ndcg_at_100
      value: 34.032000000000004
    - type: ndcg_at_1000
      value: 37.022
    - type: ndcg_at_3
      value: 24.783
    - type: ndcg_at_5
      value: 26.512
    - type: precision_at_1
      value: 22.137
    - type: precision_at_10
      value: 5.101
    - type: precision_at_100
      value: 0.971
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.709999999999999
    - type: precision_at_5
      value: 8.488999999999999
    - type: recall_at_1
      value: 17.617
    - type: recall_at_10
      value: 36.367
    - type: recall_at_100
      value: 61.939
    - type: recall_at_1000
      value: 82.565
    - type: recall_at_3
      value: 26.651000000000003
    - type: recall_at_5
      value: 31.312
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 12.742999999999999
    - type: map_at_10
      value: 18.634999999999998
    - type: map_at_100
      value: 19.686
    - type: map_at_1000
      value: 19.825
    - type: map_at_3
      value: 16.689999999999998
    - type: map_at_5
      value: 17.785
    - type: mrr_at_1
      value: 16.096
    - type: mrr_at_10
      value: 22.177
    - type: mrr_at_100
      value: 23.058
    - type: mrr_at_1000
      value: 23.154
    - type: mrr_at_3
      value: 20.166999999999998
    - type: mrr_at_5
      value: 21.263
    - type: ndcg_at_1
      value: 16.096
    - type: ndcg_at_10
      value: 22.555
    - type: ndcg_at_100
      value: 27.561000000000003
    - type: ndcg_at_1000
      value: 31.012
    - type: ndcg_at_3
      value: 18.897
    - type: ndcg_at_5
      value: 20.567
    - type: precision_at_1
      value: 16.096
    - type: precision_at_10
      value: 4.326
    - type: precision_at_100
      value: 0.8130000000000001
    - type: precision_at_1000
      value: 0.129
    - type: precision_at_3
      value: 9.209
    - type: precision_at_5
      value: 6.804
    - type: recall_at_1
      value: 12.742999999999999
    - type: recall_at_10
      value: 31.034
    - type: recall_at_100
      value: 52.913
    - type: recall_at_1000
      value: 77.389
    - type: recall_at_3
      value: 20.778
    - type: recall_at_5
      value: 25.112000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.406833333333333
    - type: map_at_10
      value: 19.934083333333334
    - type: map_at_100
      value: 20.85825
    - type: map_at_1000
      value: 20.98333333333333
    - type: map_at_3
      value: 18.2575
    - type: map_at_5
      value: 19.182499999999997
    - type: mrr_at_1
      value: 17.532666666666668
    - type: mrr_at_10
      value: 23.07375
    - type: mrr_at_100
      value: 23.89891666666667
    - type: mrr_at_1000
      value: 23.984416666666668
    - type: mrr_at_3
      value: 21.403166666666664
    - type: mrr_at_5
      value: 22.338
    - type: ndcg_at_1
      value: 17.532666666666668
    - type: ndcg_at_10
      value: 23.479833333333332
    - type: ndcg_at_100
      value: 28.046916666666664
    - type: ndcg_at_1000
      value: 31.1955
    - type: ndcg_at_3
      value: 20.464666666666666
    - type: ndcg_at_5
      value: 21.841500000000003
    - type: precision_at_1
      value: 17.532666666666668
    - type: precision_at_10
      value: 4.1924166666666665
    - type: precision_at_100
      value: 0.7695833333333333
    - type: precision_at_1000
      value: 0.12216666666666667
    - type: precision_at_3
      value: 9.573
    - type: precision_at_5
      value: 6.846333333333334
    - type: recall_at_1
      value: 14.406833333333333
    - type: recall_at_10
      value: 31.059000000000005
    - type: recall_at_100
      value: 51.878999999999984
    - type: recall_at_1000
      value: 74.73100000000001
    - type: recall_at_3
      value: 22.483916666666666
    - type: recall_at_5
      value: 26.078250000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 10.663
    - type: map_at_10
      value: 15.082999999999998
    - type: map_at_100
      value: 15.715000000000002
    - type: map_at_1000
      value: 15.792
    - type: map_at_3
      value: 13.69
    - type: map_at_5
      value: 14.334
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.253
    - type: mrr_at_100
      value: 17.897
    - type: mrr_at_1000
      value: 17.967
    - type: mrr_at_3
      value: 15.848999999999998
    - type: mrr_at_5
      value: 16.516000000000002
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.035999999999998
    - type: ndcg_at_100
      value: 21.682000000000002
    - type: ndcg_at_1000
      value: 24.154
    - type: ndcg_at_3
      value: 15.343000000000002
    - type: ndcg_at_5
      value: 16.342000000000002
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.16
    - type: precision_at_100
      value: 0.5459999999999999
    - type: precision_at_1000
      value: 0.083
    - type: precision_at_3
      value: 7.106
    - type: precision_at_5
      value: 5.0
    - type: recall_at_1
      value: 10.663
    - type: recall_at_10
      value: 25.131999999999998
    - type: recall_at_100
      value: 42.794
    - type: recall_at_1000
      value: 61.895999999999994
    - type: recall_at_3
      value: 17.408
    - type: recall_at_5
      value: 19.972
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.84
    - type: map_at_10
      value: 11.468
    - type: map_at_100
      value: 12.093
    - type: map_at_1000
      value: 12.218
    - type: map_at_3
      value: 10.407
    - type: map_at_5
      value: 10.994
    - type: mrr_at_1
      value: 9.635
    - type: mrr_at_10
      value: 13.725999999999999
    - type: mrr_at_100
      value: 14.350999999999999
    - type: mrr_at_1000
      value: 14.457
    - type: mrr_at_3
      value: 12.479999999999999
    - type: mrr_at_5
      value: 13.177
    - type: ndcg_at_1
      value: 9.635
    - type: ndcg_at_10
      value: 13.883000000000001
    - type: ndcg_at_100
      value: 17.405
    - type: ndcg_at_1000
      value: 20.951
    - type: ndcg_at_3
      value: 11.841
    - type: ndcg_at_5
      value: 12.792
    - type: precision_at_1
      value: 9.635
    - type: precision_at_10
      value: 2.581
    - type: precision_at_100
      value: 0.523
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 5.689
    - type: precision_at_5
      value: 4.178
    - type: recall_at_1
      value: 7.84
    - type: recall_at_10
      value: 18.947
    - type: recall_at_100
      value: 35.474
    - type: recall_at_1000
      value: 61.73800000000001
    - type: recall_at_3
      value: 13.311
    - type: recall_at_5
      value: 15.661
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 12.769
    - type: map_at_10
      value: 17.686
    - type: map_at_100
      value: 18.549
    - type: map_at_1000
      value: 18.672
    - type: map_at_3
      value: 16.253999999999998
    - type: map_at_5
      value: 17.000999999999998
    - type: mrr_at_1
      value: 15.392
    - type: mrr_at_10
      value: 20.598
    - type: mrr_at_100
      value: 21.468999999999998
    - type: mrr_at_1000
      value: 21.567
    - type: mrr_at_3
      value: 19.061
    - type: mrr_at_5
      value: 19.835
    - type: ndcg_at_1
      value: 15.392
    - type: ndcg_at_10
      value: 20.961
    - type: ndcg_at_100
      value: 25.308000000000003
    - type: ndcg_at_1000
      value: 28.685
    - type: ndcg_at_3
      value: 18.151
    - type: ndcg_at_5
      value: 19.317999999999998
    - type: precision_at_1
      value: 15.392
    - type: precision_at_10
      value: 3.582
    - type: precision_at_100
      value: 0.628
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 8.396
    - type: precision_at_5
      value: 5.821
    - type: recall_at_1
      value: 12.769
    - type: recall_at_10
      value: 28.26
    - type: recall_at_100
      value: 47.811
    - type: recall_at_1000
      value: 72.509
    - type: recall_at_3
      value: 20.357
    - type: recall_at_5
      value: 23.401
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.102
    - type: map_at_10
      value: 20.848
    - type: map_at_100
      value: 21.936
    - type: map_at_1000
      value: 22.125
    - type: map_at_3
      value: 19.093
    - type: map_at_5
      value: 20.074
    - type: mrr_at_1
      value: 17.787
    - type: mrr_at_10
      value: 24.442
    - type: mrr_at_100
      value: 25.296999999999997
    - type: mrr_at_1000
      value: 25.377
    - type: mrr_at_3
      value: 22.858999999999998
    - type: mrr_at_5
      value: 23.827
    - type: ndcg_at_1
      value: 17.787
    - type: ndcg_at_10
      value: 25.006
    - type: ndcg_at_100
      value: 29.798000000000002
    - type: ndcg_at_1000
      value: 33.355000000000004
    - type: ndcg_at_3
      value: 22.293
    - type: ndcg_at_5
      value: 23.555
    - type: precision_at_1
      value: 17.787
    - type: precision_at_10
      value: 4.96
    - type: precision_at_100
      value: 1.083
    - type: precision_at_1000
      value: 0.192
    - type: precision_at_3
      value: 11.001
    - type: precision_at_5
      value: 7.904999999999999
    - type: recall_at_1
      value: 14.102
    - type: recall_at_10
      value: 32.765
    - type: recall_at_100
      value: 55.206
    - type: recall_at_1000
      value: 79.739
    - type: recall_at_3
      value: 24.52
    - type: recall_at_5
      value: 28.175
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.472999999999999
    - type: map_at_10
      value: 15.783
    - type: map_at_100
      value: 16.552
    - type: map_at_1000
      value: 16.658
    - type: map_at_3
      value: 14.610000000000001
    - type: map_at_5
      value: 15.22
    - type: mrr_at_1
      value: 13.123999999999999
    - type: mrr_at_10
      value: 17.412
    - type: mrr_at_100
      value: 18.174
    - type: mrr_at_1000
      value: 18.268
    - type: mrr_at_3
      value: 16.051000000000002
    - type: mrr_at_5
      value: 16.836000000000002
    - type: ndcg_at_1
      value: 13.123999999999999
    - type: ndcg_at_10
      value: 18.437
    - type: ndcg_at_100
      value: 22.738
    - type: ndcg_at_1000
      value: 25.985000000000003
    - type: ndcg_at_3
      value: 15.937999999999999
    - type: ndcg_at_5
      value: 17.043
    - type: precision_at_1
      value: 13.123999999999999
    - type: precision_at_10
      value: 2.921
    - type: precision_at_100
      value: 0.543
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.839
    - type: precision_at_5
      value: 4.843
    - type: recall_at_1
      value: 11.472999999999999
    - type: recall_at_10
      value: 25.219
    - type: recall_at_100
      value: 46.028999999999996
    - type: recall_at_1000
      value: 71.14399999999999
    - type: recall_at_3
      value: 18.343
    - type: recall_at_5
      value: 20.937
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.212
    - type: map_at_10
      value: 11.229
    - type: map_at_100
      value: 12.620999999999999
    - type: map_at_1000
      value: 12.812999999999999
    - type: map_at_3
      value: 9.027000000000001
    - type: map_at_5
      value: 10.135
    - type: mrr_at_1
      value: 13.29
    - type: mrr_at_10
      value: 22.08
    - type: mrr_at_100
      value: 23.244
    - type: mrr_at_1000
      value: 23.311999999999998
    - type: mrr_at_3
      value: 19.012
    - type: mrr_at_5
      value: 20.787
    - type: ndcg_at_1
      value: 13.29
    - type: ndcg_at_10
      value: 16.852
    - type: ndcg_at_100
      value: 23.425
    - type: ndcg_at_1000
      value: 27.465
    - type: ndcg_at_3
      value: 12.653
    - type: ndcg_at_5
      value: 14.24
    - type: precision_at_1
      value: 13.29
    - type: precision_at_10
      value: 5.7
    - type: precision_at_100
      value: 1.28
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 9.707
    - type: precision_at_5
      value: 7.9479999999999995
    - type: recall_at_1
      value: 6.212
    - type: recall_at_10
      value: 21.806
    - type: recall_at_100
      value: 45.243
    - type: recall_at_1000
      value: 68.709
    - type: recall_at_3
      value: 11.941
    - type: recall_at_5
      value: 15.844
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.373
    - type: map_at_10
      value: 9.591
    - type: map_at_100
      value: 13.075000000000001
    - type: map_at_1000
      value: 14.018
    - type: map_at_3
      value: 6.93
    - type: map_at_5
      value: 8.189
    - type: mrr_at_1
      value: 40.0
    - type: mrr_at_10
      value: 49.713
    - type: mrr_at_100
      value: 50.497
    - type: mrr_at_1000
      value: 50.527
    - type: mrr_at_3
      value: 47.083000000000006
    - type: mrr_at_5
      value: 48.333
    - type: ndcg_at_1
      value: 28.875
    - type: ndcg_at_10
      value: 23.486
    - type: ndcg_at_100
      value: 26.192
    - type: ndcg_at_1000
      value: 32.922000000000004
    - type: ndcg_at_3
      value: 26.246000000000002
    - type: ndcg_at_5
      value: 24.769
    - type: precision_at_1
      value: 40.0
    - type: precision_at_10
      value: 20.5
    - type: precision_at_100
      value: 6.3950000000000005
    - type: precision_at_1000
      value: 1.362
    - type: precision_at_3
      value: 30.917
    - type: precision_at_5
      value: 26.150000000000002
    - type: recall_at_1
      value: 4.373
    - type: recall_at_10
      value: 14.041999999999998
    - type: recall_at_100
      value: 32.055
    - type: recall_at_1000
      value: 54.351000000000006
    - type: recall_at_3
      value: 8.208
    - type: recall_at_5
      value: 10.615
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 45.045
    - type: f1
      value: 41.00531027586712
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 14.998000000000001
    - type: map_at_10
      value: 22.807
    - type: map_at_100
      value: 23.74
    - type: map_at_1000
      value: 23.816000000000003
    - type: map_at_3
      value: 20.333000000000002
    - type: map_at_5
      value: 21.712999999999997
    - type: mrr_at_1
      value: 16.006999999999998
    - type: mrr_at_10
      value: 24.233
    - type: mrr_at_100
      value: 25.163000000000004
    - type: mrr_at_1000
      value: 25.229000000000003
    - type: mrr_at_3
      value: 21.634999999999998
    - type: mrr_at_5
      value: 23.098
    - type: ndcg_at_1
      value: 16.006999999999998
    - type: ndcg_at_10
      value: 27.578000000000003
    - type: ndcg_at_100
      value: 32.391
    - type: ndcg_at_1000
      value: 34.504000000000005
    - type: ndcg_at_3
      value: 22.457
    - type: ndcg_at_5
      value: 24.947
    - type: precision_at_1
      value: 16.006999999999998
    - type: precision_at_10
      value: 4.487
    - type: precision_at_100
      value: 0.707
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 9.780999999999999
    - type: precision_at_5
      value: 7.2010000000000005
    - type: recall_at_1
      value: 14.998000000000001
    - type: recall_at_10
      value: 41.201
    - type: recall_at_100
      value: 63.800000000000004
    - type: recall_at_1000
      value: 80.15299999999999
    - type: recall_at_3
      value: 27.288
    - type: recall_at_5
      value: 33.263999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 6.297
    - type: map_at_10
      value: 10.769
    - type: map_at_100
      value: 11.923
    - type: map_at_1000
      value: 12.117
    - type: map_at_3
      value: 9.28
    - type: map_at_5
      value: 10.001
    - type: mrr_at_1
      value: 12.963
    - type: mrr_at_10
      value: 18.951999999999998
    - type: mrr_at_100
      value: 19.976
    - type: mrr_at_1000
      value: 20.073
    - type: mrr_at_3
      value: 16.847
    - type: mrr_at_5
      value: 17.904
    - type: ndcg_at_1
      value: 12.963
    - type: ndcg_at_10
      value: 14.979999999999999
    - type: ndcg_at_100
      value: 20.588
    - type: ndcg_at_1000
      value: 25.121
    - type: ndcg_at_3
      value: 12.697
    - type: ndcg_at_5
      value: 13.337
    - type: precision_at_1
      value: 12.963
    - type: precision_at_10
      value: 4.367
    - type: precision_at_100
      value: 0.9950000000000001
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 8.693
    - type: precision_at_5
      value: 6.419999999999999
    - type: recall_at_1
      value: 6.297
    - type: recall_at_10
      value: 19.400000000000002
    - type: recall_at_100
      value: 41.400999999999996
    - type: recall_at_1000
      value: 70.163
    - type: recall_at_3
      value: 11.884
    - type: recall_at_5
      value: 14.549999999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 17.677
    - type: map_at_10
      value: 24.685000000000002
    - type: map_at_100
      value: 25.604
    - type: map_at_1000
      value: 25.717000000000002
    - type: map_at_3
      value: 22.747
    - type: map_at_5
      value: 23.846
    - type: mrr_at_1
      value: 35.354
    - type: mrr_at_10
      value: 42.126999999999995
    - type: mrr_at_100
      value: 42.867
    - type: mrr_at_1000
      value: 42.925000000000004
    - type: mrr_at_3
      value: 40.241
    - type: mrr_at_5
      value: 41.3
    - type: ndcg_at_1
      value: 35.354
    - type: ndcg_at_10
      value: 31.438
    - type: ndcg_at_100
      value: 35.666
    - type: ndcg_at_1000
      value: 38.346000000000004
    - type: ndcg_at_3
      value: 27.766999999999996
    - type: ndcg_at_5
      value: 29.572
    - type: precision_at_1
      value: 35.354
    - type: precision_at_10
      value: 6.8870000000000005
    - type: precision_at_100
      value: 1.026
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 17.424999999999997
    - type: precision_at_5
      value: 11.889
    - type: recall_at_1
      value: 17.677
    - type: recall_at_10
      value: 34.436
    - type: recall_at_100
      value: 51.303
    - type: recall_at_1000
      value: 69.18299999999999
    - type: recall_at_3
      value: 26.138
    - type: recall_at_5
      value: 29.723
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 64.3004
    - type: ap
      value: 59.425036750361784
    - type: f1
      value: 64.15840309881166
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.418
    - type: map_at_10
      value: 11.181000000000001
    - type: map_at_100
      value: 12.078
    - type: map_at_1000
      value: 12.18
    - type: map_at_3
      value: 9.414
    - type: map_at_5
      value: 10.359
    - type: mrr_at_1
      value: 6.59
    - type: mrr_at_10
      value: 11.479000000000001
    - type: mrr_at_100
      value: 12.377
    - type: mrr_at_1000
      value: 12.475
    - type: mrr_at_3
      value: 9.678
    - type: mrr_at_5
      value: 10.639999999999999
    - type: ndcg_at_1
      value: 6.59
    - type: ndcg_at_10
      value: 14.152000000000001
    - type: ndcg_at_100
      value: 19.037000000000003
    - type: ndcg_at_1000
      value: 22.125
    - type: ndcg_at_3
      value: 10.456
    - type: ndcg_at_5
      value: 12.166
    - type: precision_at_1
      value: 6.59
    - type: precision_at_10
      value: 2.436
    - type: precision_at_100
      value: 0.49699999999999994
    - type: precision_at_1000
      value: 0.076
    - type: precision_at_3
      value: 4.556
    - type: precision_at_5
      value: 3.6020000000000003
    - type: recall_at_1
      value: 6.418
    - type: recall_at_10
      value: 23.385
    - type: recall_at_100
      value: 47.169
    - type: recall_at_1000
      value: 71.995
    - type: recall_at_3
      value: 13.209000000000001
    - type: recall_at_5
      value: 17.335
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.67852257181941
    - type: f1
      value: 88.95204075691726
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.597355221158224
    - type: f1
      value: 41.690585365044186
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.056489576328175
    - type: f1
      value: 60.956720996001664
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.88231338264963
    - type: f1
      value: 68.65445434231955
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.16245614593283
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.243876419694487
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.22788130698314
    - type: mrr
      value: 30.181799152132406
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.611
    - type: map_at_10
      value: 7.911
    - type: map_at_100
      value: 9.895
    - type: map_at_1000
      value: 11.193999999999999
    - type: map_at_3
      value: 5.93
    - type: map_at_5
      value: 6.979
    - type: mrr_at_1
      value: 32.817
    - type: mrr_at_10
      value: 42.955
    - type: mrr_at_100
      value: 43.657000000000004
    - type: mrr_at_1000
      value: 43.723
    - type: mrr_at_3
      value: 40.351
    - type: mrr_at_5
      value: 42.224000000000004
    - type: ndcg_at_1
      value: 30.186
    - type: ndcg_at_10
      value: 24.783
    - type: ndcg_at_100
      value: 22.906000000000002
    - type: ndcg_at_1000
      value: 32.609
    - type: ndcg_at_3
      value: 27.786
    - type: ndcg_at_5
      value: 27.322999999999997
    - type: precision_at_1
      value: 32.817
    - type: precision_at_10
      value: 18.39
    - type: precision_at_100
      value: 6.297
    - type: precision_at_1000
      value: 1.9539999999999997
    - type: precision_at_3
      value: 26.625
    - type: precision_at_5
      value: 24.149
    - type: recall_at_1
      value: 3.611
    - type: recall_at_10
      value: 12.184000000000001
    - type: recall_at_100
      value: 24.642
    - type: recall_at_1000
      value: 59.829
    - type: recall_at_3
      value: 7.317
    - type: recall_at_5
      value: 9.702
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.258
    - type: map_at_10
      value: 15.838
    - type: map_at_100
      value: 16.97
    - type: map_at_1000
      value: 17.072000000000003
    - type: map_at_3
      value: 13.285
    - type: map_at_5
      value: 14.606
    - type: mrr_at_1
      value: 10.545
    - type: mrr_at_10
      value: 17.453
    - type: mrr_at_100
      value: 18.516
    - type: mrr_at_1000
      value: 18.601
    - type: mrr_at_3
      value: 14.813
    - type: mrr_at_5
      value: 16.189999999999998
    - type: ndcg_at_1
      value: 10.545
    - type: ndcg_at_10
      value: 20.278
    - type: ndcg_at_100
      value: 26.200000000000003
    - type: ndcg_at_1000
      value: 28.956
    - type: ndcg_at_3
      value: 14.963000000000001
    - type: ndcg_at_5
      value: 17.347
    - type: precision_at_1
      value: 10.545
    - type: precision_at_10
      value: 3.8350000000000004
    - type: precision_at_100
      value: 0.722
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 7.03
    - type: precision_at_5
      value: 5.556
    - type: recall_at_1
      value: 9.258
    - type: recall_at_10
      value: 32.551
    - type: recall_at_100
      value: 60.39
    - type: recall_at_1000
      value: 81.441
    - type: recall_at_3
      value: 18.346999999999998
    - type: recall_at_5
      value: 23.947
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.037
    - type: map_at_10
      value: 75.644
    - type: map_at_100
      value: 76.417
    - type: map_at_1000
      value: 76.452
    - type: map_at_3
      value: 72.71600000000001
    - type: map_at_5
      value: 74.504
    - type: mrr_at_1
      value: 72.69
    - type: mrr_at_10
      value: 80.037
    - type: mrr_at_100
      value: 80.291
    - type: mrr_at_1000
      value: 80.296
    - type: mrr_at_3
      value: 78.615
    - type: mrr_at_5
      value: 79.54
    - type: ndcg_at_1
      value: 72.75
    - type: ndcg_at_10
      value: 80.316
    - type: ndcg_at_100
      value: 82.48299999999999
    - type: ndcg_at_1000
      value: 82.876
    - type: ndcg_at_3
      value: 76.778
    - type: ndcg_at_5
      value: 78.63900000000001
    - type: precision_at_1
      value: 72.75
    - type: precision_at_10
      value: 12.110999999999999
    - type: precision_at_100
      value: 1.452
    - type: precision_at_1000
      value: 0.154
    - type: precision_at_3
      value: 33.243
    - type: precision_at_5
      value: 21.974
    - type: recall_at_1
      value: 63.037
    - type: recall_at_10
      value: 89.183
    - type: recall_at_100
      value: 97.38799999999999
    - type: recall_at_1000
      value: 99.591
    - type: recall_at_3
      value: 79.041
    - type: recall_at_5
      value: 84.25200000000001
    - type: map_at_1
      value: 3.013
    - type: map_at_10
      value: 6.869
    - type: map_at_100
      value: 8.216
    - type: map_at_1000
      value: 8.462
    - type: map_at_3
      value: 5.042
    - type: map_at_5
      value: 5.970000000000001
    - type: mrr_at_1
      value: 14.799999999999999
    - type: mrr_at_10
      value: 22.184
    - type: mrr_at_100
      value: 23.485
    - type: mrr_at_1000
      value: 23.57
    - type: mrr_at_3
      value: 19.383
    - type: mrr_at_5
      value: 20.938000000000002
    - type: ndcg_at_1
      value: 14.799999999999999
    - type: ndcg_at_10
      value: 12.223
    - type: ndcg_at_100
      value: 18.508
    - type: ndcg_at_1000
      value: 23.544
    - type: ndcg_at_3
      value: 11.488
    - type: ndcg_at_5
      value: 10.095
    - type: precision_at_1
      value: 14.799999999999999
    - type: precision_at_10
      value: 6.329999999999999
    - type: precision_at_100
      value: 1.546
    - type: precision_at_1000
      value: 0.27599999999999997
    - type: precision_at_3
      value: 10.567
    - type: precision_at_5
      value: 8.799999999999999
    - type: recall_at_1
      value: 3.013
    - type: recall_at_10
      value: 12.828000000000001
    - type: recall_at_100
      value: 31.408
    - type: recall_at_1000
      value: 56.157000000000004
    - type: recall_at_3
      value: 6.433
    - type: recall_at_5
      value: 8.903
    - type: map_at_1
      value: 0.11299999999999999
    - type: map_at_10
      value: 0.707
    - type: map_at_100
      value: 3.7159999999999997
    - type: map_at_1000
      value: 9.451
    - type: map_at_3
      value: 0.296
    - type: map_at_5
      value: 0.43299999999999994
    - type: mrr_at_1
      value: 50.0
    - type: mrr_at_10
      value: 63.507999999999996
    - type: mrr_at_100
      value: 63.696
    - type: mrr_at_1000
      value: 63.696
    - type: mrr_at_3
      value: 60.0
    - type: mrr_at_5
      value: 61.4
    - type: ndcg_at_1
      value: 43.0
    - type: ndcg_at_10
      value: 40.248
    - type: ndcg_at_100
      value: 30.162
    - type: ndcg_at_1000
      value: 27.334999999999997
    - type: ndcg_at_3
      value: 44.665
    - type: ndcg_at_5
      value: 42.51
    - type: precision_at_1
      value: 48.0
    - type: precision_at_10
      value: 43.0
    - type: precision_at_100
      value: 31.36
    - type: precision_at_1000
      value: 13.475999999999999
    - type: precision_at_3
      value: 49.333
    - type: precision_at_5
      value: 46.400000000000006
    - type: recall_at_1
      value: 0.11299999999999999
    - type: recall_at_10
      value: 0.968
    - type: recall_at_100
      value: 6.5329999999999995
    - type: recall_at_1000
      value: 26.447
    - type: recall_at_3
      value: 0.33999999999999997
    - type: recall_at_5
      value: 0.516
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 38.90354115378983
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 45.41196647530998
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 76.5160077089625
    - type: cos_sim_spearman
      value: 67.28825297023138
    - type: euclidean_pearson
      value: 72.39938443269206
    - type: euclidean_spearman
      value: 67.28835245540397
    - type: manhattan_pearson
      value: 69.46413862678756
    - type: manhattan_spearman
      value: 65.04853993701172
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.53773965480292
    - type: cos_sim_spearman
      value: 67.41284745598715
    - type: euclidean_pearson
      value: 70.57848011423972
    - type: euclidean_spearman
      value: 67.4141763023251
    - type: manhattan_pearson
      value: 70.0268534606741
    - type: manhattan_spearman
      value: 67.8439837728854
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 78.2216356861313
    - type: cos_sim_spearman
      value: 79.37038668590753
    - type: euclidean_pearson
      value: 79.01512518225226
    - type: euclidean_spearman
      value: 79.37042448746669
    - type: manhattan_pearson
      value: 78.96268955680836
    - type: manhattan_spearman
      value: 79.54073298193023
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 78.3544215128133
    - type: cos_sim_spearman
      value: 75.07229525913817
    - type: euclidean_pearson
      value: 77.35598390483041
    - type: euclidean_spearman
      value: 75.07228556747974
    - type: manhattan_pearson
      value: 76.27348311336605
    - type: manhattan_spearman
      value: 74.50258040498937
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 80.86410111924121
    - type: cos_sim_spearman
      value: 81.79657437718866
    - type: euclidean_pearson
      value: 81.77144036632458
    - type: euclidean_spearman
      value: 81.79657286849607
    - type: manhattan_pearson
      value: 81.87491956950679
    - type: manhattan_spearman
      value: 82.16993847726854
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.43507688364112
    - type: cos_sim_spearman
      value: 77.63882301316933
    - type: euclidean_pearson
      value: 77.25501398026381
    - type: euclidean_spearman
      value: 77.63965196736244
    - type: manhattan_pearson
      value: 77.67118978923139
    - type: manhattan_spearman
      value: 78.01084214592416
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.39964672680482
    - type: cos_sim_spearman
      value: 85.4075592513342
    - type: euclidean_pearson
      value: 85.111606756296
    - type: euclidean_spearman
      value: 85.40843260765956
    - type: manhattan_pearson
      value: 84.8842901249278
    - type: manhattan_spearman
      value: 85.63868618596224
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.75456403534724
    - type: cos_sim_spearman
      value: 60.22663871632273
    - type: euclidean_pearson
      value: 62.65086137572171
    - type: euclidean_spearman
      value: 60.22663871632273
    - type: manhattan_pearson
      value: 62.250953520717104
    - type: manhattan_spearman
      value: 60.3533574497436
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.68220902816006
    - type: cos_sim_spearman
      value: 77.52592408424563
    - type: euclidean_pearson
      value: 78.64874043891504
    - type: euclidean_spearman
      value: 77.5259126306683
    - type: manhattan_pearson
      value: 77.84730420742085
    - type: manhattan_spearman
      value: 76.87780210711085
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.3409090022697
    - type: mrr
      value: 90.91359620771387
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 33.75
    - type: map_at_10
      value: 42.137
    - type: map_at_100
      value: 43.376
    - type: map_at_1000
      value: 43.449
    - type: map_at_3
      value: 39.856
    - type: map_at_5
      value: 41.447
    - type: mrr_at_1
      value: 36.0
    - type: mrr_at_10
      value: 44.0
    - type: mrr_at_100
      value: 45.057
    - type: mrr_at_1000
      value: 45.115
    - type: mrr_at_3
      value: 42.056
    - type: mrr_at_5
      value: 43.372
    - type: ndcg_at_1
      value: 36.0
    - type: ndcg_at_10
      value: 46.627
    - type: ndcg_at_100
      value: 52.38
    - type: ndcg_at_1000
      value: 54.022000000000006
    - type: ndcg_at_3
      value: 42.341
    - type: ndcg_at_5
      value: 44.962
    - type: precision_at_1
      value: 36.0
    - type: precision_at_10
      value: 6.4670000000000005
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 17.111
    - type: precision_at_5
      value: 11.733
    - type: recall_at_1
      value: 33.75
    - type: recall_at_10
      value: 58.789
    - type: recall_at_100
      value: 85.017
    - type: recall_at_1000
      value: 97.467
    - type: recall_at_3
      value: 47.067
    - type: recall_at_5
      value: 53.65
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.70990099009902
    - type: cos_sim_ap
      value: 91.32913696282823
    - type: cos_sim_f1
      value: 85.01006036217304
    - type: cos_sim_precision
      value: 85.52631578947368
    - type: cos_sim_recall
      value: 84.5
    - type: dot_accuracy
      value: 99.70990099009902
    - type: dot_ap
      value: 91.32913696282823
    - type: dot_f1
      value: 85.01006036217304
    - type: dot_precision
      value: 85.52631578947368
    - type: dot_recall
      value: 84.5
    - type: euclidean_accuracy
      value: 99.70990099009902
    - type: euclidean_ap
      value: 91.32913696282823
    - type: euclidean_f1
      value: 85.01006036217304
    - type: euclidean_precision
      value: 85.52631578947368
    - type: euclidean_recall
      value: 84.5
    - type: manhattan_accuracy
      value: 99.76138613861386
    - type: manhattan_ap
      value: 93.79556639749748
    - type: manhattan_f1
      value: 87.80246913580247
    - type: manhattan_precision
      value: 86.73170731707317
    - type: manhattan_recall
      value: 88.9
    - type: max_accuracy
      value: 99.76138613861386
    - type: max_ap
      value: 93.79556639749748
    - type: max_f1
      value: 87.80246913580247
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 44.241414720398396
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.365666490943998
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.57844146880517
    - type: mrr
      value: 44.13609572616926
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.0154193888818
    - type: cos_sim_spearman
      value: 30.147164982667924
    - type: dot_pearson
      value: 30.015419367262712
    - type: dot_spearman
      value: 30.1547894792066
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.16
    - type: map_at_10
      value: 8.245
    - type: map_at_100
      value: 13.763
    - type: map_at_1000
      value: 15.334
    - type: map_at_3
      value: 4.577
    - type: map_at_5
      value: 5.847
    - type: mrr_at_1
      value: 30.612000000000002
    - type: mrr_at_10
      value: 42.482
    - type: mrr_at_100
      value: 43.362
    - type: mrr_at_1000
      value: 43.364999999999995
    - type: mrr_at_3
      value: 37.755
    - type: mrr_at_5
      value: 40.102
    - type: ndcg_at_1
      value: 28.571
    - type: ndcg_at_10
      value: 21.613
    - type: ndcg_at_100
      value: 34.297
    - type: ndcg_at_1000
      value: 45.528
    - type: ndcg_at_3
      value: 24.886
    - type: ndcg_at_5
      value: 22.752
    - type: precision_at_1
      value: 30.612000000000002
    - type: precision_at_10
      value: 19.592000000000002
    - type: precision_at_100
      value: 7.754999999999999
    - type: precision_at_1000
      value: 1.494
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 22.448999999999998
    - type: recall_at_1
      value: 2.16
    - type: recall_at_10
      value: 13.361999999999998
    - type: recall_at_100
      value: 46.162
    - type: recall_at_1000
      value: 80.794
    - type: recall_at_3
      value: 5.418
    - type: recall_at_5
      value: 7.670000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 70.35860000000001
    - type: ap
      value: 13.90249255744945
    - type: f1
      value: 54.08442274867805
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.3010752688172
    - type: f1
      value: 54.493273092344666
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.712743713596815
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.88269654884664
    - type: cos_sim_ap
      value: 66.09276985843528
    - type: cos_sim_f1
      value: 63.225649744959924
    - type: cos_sim_precision
      value: 58.573357335733576
    - type: cos_sim_recall
      value: 68.68073878627968
    - type: dot_accuracy
      value: 83.88269654884664
    - type: dot_ap
      value: 66.09276747019544
    - type: dot_f1
      value: 63.225649744959924
    - type: dot_precision
      value: 58.573357335733576
    - type: dot_recall
      value: 68.68073878627968
    - type: euclidean_accuracy
      value: 83.88269654884664
    - type: euclidean_ap
      value: 66.09276985843528
    - type: euclidean_f1
      value: 63.225649744959924
    - type: euclidean_precision
      value: 58.573357335733576
    - type: euclidean_recall
      value: 68.68073878627968
    - type: manhattan_accuracy
      value: 82.69058830541813
    - type: manhattan_ap
      value: 62.74574997540533
    - type: manhattan_f1
      value: 59.96326905417815
    - type: manhattan_precision
      value: 53.06785859406745
    - type: manhattan_recall
      value: 68.91820580474935
    - type: max_accuracy
      value: 83.88269654884664
    - type: max_ap
      value: 66.09276985843528
    - type: max_f1
      value: 63.225649744959924
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.57519307641557
    - type: cos_sim_ap
      value: 83.25474211186804
    - type: cos_sim_f1
      value: 75.56529680365297
    - type: cos_sim_precision
      value: 71.89129074859248
    - type: cos_sim_recall
      value: 79.63504773637203
    - type: dot_accuracy
      value: 87.57519307641557
    - type: dot_ap
      value: 83.25474240805171
    - type: dot_f1
      value: 75.56529680365297
    - type: dot_precision
      value: 71.89129074859248
    - type: dot_recall
      value: 79.63504773637203
    - type: euclidean_accuracy
      value: 87.57519307641557
    - type: euclidean_ap
      value: 83.25474211186805
    - type: euclidean_f1
      value: 75.56529680365297
    - type: euclidean_precision
      value: 71.89129074859248
    - type: euclidean_recall
      value: 79.63504773637203
    - type: manhattan_accuracy
      value: 87.60041914076145
    - type: manhattan_ap
      value: 83.11911507311108
    - type: manhattan_f1
      value: 75.27478546649627
    - type: manhattan_precision
      value: 71.59130374383552
    - type: manhattan_recall
      value: 79.35786880197105
    - type: max_accuracy
      value: 87.60041914076145
    - type: max_ap
      value: 83.25474240805171
    - type: max_f1
      value: 75.56529680365297
---
