mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_nignore30
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.02985074626865
    - type: ap
      value: 36.54755879675939
    - type: f1
      value: 67.84911428462374
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 60.98745000000001
    - type: ap
      value: 56.79972495487593
    - type: f1
      value: 60.79607311981127
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.606000000000005
    - type: f1
      value: 31.20575804283948
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 21.266
    - type: map_at_10
      value: 35.579
    - type: map_at_100
      value: 36.867
    - type: map_at_1000
      value: 36.887
    - type: map_at_3
      value: 31.105
    - type: map_at_5
      value: 33.512
    - type: mrr_at_1
      value: 21.764
    - type: mrr_at_10
      value: 35.768
    - type: mrr_at_100
      value: 37.049
    - type: mrr_at_1000
      value: 37.069
    - type: mrr_at_3
      value: 31.354
    - type: mrr_at_5
      value: 33.694
    - type: ndcg_at_1
      value: 21.266
    - type: ndcg_at_10
      value: 43.697
    - type: ndcg_at_100
      value: 49.444
    - type: ndcg_at_1000
      value: 49.918
    - type: ndcg_at_3
      value: 34.415
    - type: ndcg_at_5
      value: 38.751999999999995
    - type: precision_at_1
      value: 21.266
    - type: precision_at_10
      value: 6.97
    - type: precision_at_100
      value: 0.954
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.674999999999999
    - type: precision_at_5
      value: 10.91
    - type: recall_at_1
      value: 21.266
    - type: recall_at_10
      value: 69.70100000000001
    - type: recall_at_100
      value: 95.448
    - type: recall_at_1000
      value: 99.075
    - type: recall_at_3
      value: 44.025999999999996
    - type: recall_at_5
      value: 54.552
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.45486521675564
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.270159650279354
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 53.62399843388994
    - type: mrr
      value: 68.1675680429143
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 83.62266587849676
    - type: cos_sim_spearman
      value: 80.48918339823612
    - type: euclidean_pearson
      value: 82.46661732971302
    - type: euclidean_spearman
      value: 80.48918339823612
    - type: manhattan_pearson
      value: 81.55398066885756
    - type: manhattan_spearman
      value: 80.27411825686711
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.07142857142857
    - type: f1
      value: 72.39723822054579
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.426645848653045
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.54829160604571
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 24.001
    - type: map_at_10
      value: 31.195
    - type: map_at_100
      value: 32.342999999999996
    - type: map_at_1000
      value: 32.489000000000004
    - type: map_at_3
      value: 28.814
    - type: map_at_5
      value: 30.014000000000003
    - type: mrr_at_1
      value: 30.186
    - type: mrr_at_10
      value: 37.034
    - type: mrr_at_100
      value: 37.881
    - type: mrr_at_1000
      value: 37.946000000000005
    - type: mrr_at_3
      value: 35.241
    - type: mrr_at_5
      value: 36.120999999999995
    - type: ndcg_at_1
      value: 30.186
    - type: ndcg_at_10
      value: 35.972
    - type: ndcg_at_100
      value: 41.25
    - type: ndcg_at_1000
      value: 44.171
    - type: ndcg_at_3
      value: 32.674
    - type: ndcg_at_5
      value: 33.833
    - type: precision_at_1
      value: 30.186
    - type: precision_at_10
      value: 6.723999999999999
    - type: precision_at_100
      value: 1.157
    - type: precision_at_1000
      value: 0.172
    - type: precision_at_3
      value: 15.451
    - type: precision_at_5
      value: 10.815
    - type: recall_at_1
      value: 24.001
    - type: recall_at_10
      value: 44.057
    - type: recall_at_100
      value: 67.72500000000001
    - type: recall_at_1000
      value: 87.464
    - type: recall_at_3
      value: 33.817
    - type: recall_at_5
      value: 37.684
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.766000000000002
    - type: map_at_10
      value: 23.07
    - type: map_at_100
      value: 24.062
    - type: map_at_1000
      value: 24.178
    - type: map_at_3
      value: 21.364
    - type: map_at_5
      value: 22.3
    - type: mrr_at_1
      value: 21.146
    - type: mrr_at_10
      value: 27.24
    - type: mrr_at_100
      value: 28.092
    - type: mrr_at_1000
      value: 28.163
    - type: mrr_at_3
      value: 25.605
    - type: mrr_at_5
      value: 26.567
    - type: ndcg_at_1
      value: 21.146
    - type: ndcg_at_10
      value: 27.031
    - type: ndcg_at_100
      value: 31.430999999999997
    - type: ndcg_at_1000
      value: 34.086
    - type: ndcg_at_3
      value: 24.136
    - type: ndcg_at_5
      value: 25.462
    - type: precision_at_1
      value: 21.146
    - type: precision_at_10
      value: 5.006
    - type: precision_at_100
      value: 0.901
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 11.762
    - type: precision_at_5
      value: 8.229000000000001
    - type: recall_at_1
      value: 16.766000000000002
    - type: recall_at_10
      value: 34.55
    - type: recall_at_100
      value: 53.542
    - type: recall_at_1000
      value: 71.66900000000001
    - type: recall_at_3
      value: 26.205000000000002
    - type: recall_at_5
      value: 29.854000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 26.579000000000004
    - type: map_at_10
      value: 35.482
    - type: map_at_100
      value: 36.564
    - type: map_at_1000
      value: 36.656
    - type: map_at_3
      value: 32.940999999999995
    - type: map_at_5
      value: 34.331
    - type: mrr_at_1
      value: 30.784
    - type: mrr_at_10
      value: 38.721
    - type: mrr_at_100
      value: 39.592
    - type: mrr_at_1000
      value: 39.653
    - type: mrr_at_3
      value: 36.468
    - type: mrr_at_5
      value: 37.688
    - type: ndcg_at_1
      value: 30.784
    - type: ndcg_at_10
      value: 40.351
    - type: ndcg_at_100
      value: 45.499
    - type: ndcg_at_1000
      value: 47.641
    - type: ndcg_at_3
      value: 35.605
    - type: ndcg_at_5
      value: 37.798
    - type: precision_at_1
      value: 30.784
    - type: precision_at_10
      value: 6.564
    - type: precision_at_100
      value: 1.004
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 15.862000000000002
    - type: precision_at_5
      value: 11.008999999999999
    - type: recall_at_1
      value: 26.579000000000004
    - type: recall_at_10
      value: 51.978
    - type: recall_at_100
      value: 75.331
    - type: recall_at_1000
      value: 90.774
    - type: recall_at_3
      value: 39.149
    - type: recall_at_5
      value: 44.516
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.013
    - type: map_at_10
      value: 17.393
    - type: map_at_100
      value: 18.256
    - type: map_at_1000
      value: 18.364
    - type: map_at_3
      value: 15.812000000000001
    - type: map_at_5
      value: 16.601
    - type: mrr_at_1
      value: 14.237
    - type: mrr_at_10
      value: 18.706999999999997
    - type: mrr_at_100
      value: 19.553
    - type: mrr_at_1000
      value: 19.651
    - type: mrr_at_3
      value: 17.081
    - type: mrr_at_5
      value: 17.895
    - type: ndcg_at_1
      value: 14.237
    - type: ndcg_at_10
      value: 20.315
    - type: ndcg_at_100
      value: 24.914
    - type: ndcg_at_1000
      value: 28.244999999999997
    - type: ndcg_at_3
      value: 16.994
    - type: ndcg_at_5
      value: 18.396
    - type: precision_at_1
      value: 14.237
    - type: precision_at_10
      value: 3.198
    - type: precision_at_100
      value: 0.583
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 7.0809999999999995
    - type: precision_at_5
      value: 4.994
    - type: recall_at_1
      value: 13.013
    - type: recall_at_10
      value: 28.297
    - type: recall_at_100
      value: 50.113
    - type: recall_at_1000
      value: 76.19500000000001
    - type: recall_at_3
      value: 19.062
    - type: recall_at_5
      value: 22.527
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.783
    - type: map_at_10
      value: 10.439
    - type: map_at_100
      value: 11.26
    - type: map_at_1000
      value: 11.394
    - type: map_at_3
      value: 9.314
    - type: map_at_5
      value: 9.832
    - type: mrr_at_1
      value: 8.831
    - type: mrr_at_10
      value: 12.902
    - type: mrr_at_100
      value: 13.799
    - type: mrr_at_1000
      value: 13.901
    - type: mrr_at_3
      value: 11.692
    - type: mrr_at_5
      value: 12.200999999999999
    - type: ndcg_at_1
      value: 8.831
    - type: ndcg_at_10
      value: 12.973
    - type: ndcg_at_100
      value: 17.465
    - type: ndcg_at_1000
      value: 21.203
    - type: ndcg_at_3
      value: 10.778
    - type: ndcg_at_5
      value: 11.601
    - type: precision_at_1
      value: 8.831
    - type: precision_at_10
      value: 2.475
    - type: precision_at_100
      value: 0.553
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 5.265000000000001
    - type: precision_at_5
      value: 3.781
    - type: recall_at_1
      value: 6.783
    - type: recall_at_10
      value: 18.386
    - type: recall_at_100
      value: 38.885999999999996
    - type: recall_at_1000
      value: 66.621
    - type: recall_at_3
      value: 12.235
    - type: recall_at_5
      value: 14.374999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.946
    - type: map_at_10
      value: 24.188000000000002
    - type: map_at_100
      value: 25.402
    - type: map_at_1000
      value: 25.544
    - type: map_at_3
      value: 22.157
    - type: map_at_5
      value: 23.315
    - type: mrr_at_1
      value: 22.233
    - type: mrr_at_10
      value: 28.703
    - type: mrr_at_100
      value: 29.669
    - type: mrr_at_1000
      value: 29.748
    - type: mrr_at_3
      value: 26.676
    - type: mrr_at_5
      value: 27.894000000000002
    - type: ndcg_at_1
      value: 22.233
    - type: ndcg_at_10
      value: 28.483999999999998
    - type: ndcg_at_100
      value: 34.239999999999995
    - type: ndcg_at_1000
      value: 37.351
    - type: ndcg_at_3
      value: 25.018
    - type: ndcg_at_5
      value: 26.679000000000002
    - type: precision_at_1
      value: 22.233
    - type: precision_at_10
      value: 5.236
    - type: precision_at_100
      value: 0.962
    - type: precision_at_1000
      value: 0.14200000000000002
    - type: precision_at_3
      value: 11.806
    - type: precision_at_5
      value: 8.566
    - type: recall_at_1
      value: 17.946
    - type: recall_at_10
      value: 37.049
    - type: recall_at_100
      value: 62.473
    - type: recall_at_1000
      value: 83.829
    - type: recall_at_3
      value: 27.022000000000002
    - type: recall_at_5
      value: 31.435000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.966000000000001
    - type: map_at_10
      value: 19.797
    - type: map_at_100
      value: 20.764
    - type: map_at_1000
      value: 20.913
    - type: map_at_3
      value: 17.688000000000002
    - type: map_at_5
      value: 18.796
    - type: mrr_at_1
      value: 17.122999999999998
    - type: mrr_at_10
      value: 23.277
    - type: mrr_at_100
      value: 24.095
    - type: mrr_at_1000
      value: 24.197
    - type: mrr_at_3
      value: 21.176000000000002
    - type: mrr_at_5
      value: 22.323
    - type: ndcg_at_1
      value: 17.122999999999998
    - type: ndcg_at_10
      value: 23.860999999999997
    - type: ndcg_at_100
      value: 28.669
    - type: ndcg_at_1000
      value: 32.375
    - type: ndcg_at_3
      value: 19.983999999999998
    - type: ndcg_at_5
      value: 21.647
    - type: precision_at_1
      value: 17.122999999999998
    - type: precision_at_10
      value: 4.623
    - type: precision_at_100
      value: 0.839
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 9.551
    - type: precision_at_5
      value: 7.1
    - type: recall_at_1
      value: 13.966000000000001
    - type: recall_at_10
      value: 32.629999999999995
    - type: recall_at_100
      value: 53.842
    - type: recall_at_1000
      value: 80.583
    - type: recall_at_3
      value: 21.804000000000002
    - type: recall_at_5
      value: 26.101999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.974750000000004
    - type: map_at_10
      value: 20.34575
    - type: map_at_100
      value: 21.290416666666665
    - type: map_at_1000
      value: 21.41825
    - type: map_at_3
      value: 18.576500000000003
    - type: map_at_5
      value: 19.546166666666668
    - type: mrr_at_1
      value: 18.049249999999997
    - type: mrr_at_10
      value: 23.45216666666667
    - type: mrr_at_100
      value: 24.29241666666667
    - type: mrr_at_1000
      value: 24.37841666666667
    - type: mrr_at_3
      value: 21.728749999999998
    - type: mrr_at_5
      value: 22.680916666666665
    - type: ndcg_at_1
      value: 18.049249999999997
    - type: ndcg_at_10
      value: 23.90125
    - type: ndcg_at_100
      value: 28.57325
    - type: ndcg_at_1000
      value: 31.747583333333335
    - type: ndcg_at_3
      value: 20.71783333333333
    - type: ndcg_at_5
      value: 22.17008333333333
    - type: precision_at_1
      value: 18.049249999999997
    - type: precision_at_10
      value: 4.257666666666667
    - type: precision_at_100
      value: 0.7843333333333332
    - type: precision_at_1000
      value: 0.12375000000000003
    - type: precision_at_3
      value: 9.573750000000002
    - type: precision_at_5
      value: 6.871666666666666
    - type: recall_at_1
      value: 14.974750000000004
    - type: recall_at_10
      value: 31.535416666666666
    - type: recall_at_100
      value: 52.869583333333324
    - type: recall_at_1000
      value: 75.93208333333334
    - type: recall_at_3
      value: 22.561833333333333
    - type: recall_at_5
      value: 26.351583333333334
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.584
    - type: map_at_10
      value: 15.47
    - type: map_at_100
      value: 16.276
    - type: map_at_1000
      value: 16.361
    - type: map_at_3
      value: 14.022000000000002
    - type: map_at_5
      value: 14.884
    - type: mrr_at_1
      value: 13.65
    - type: mrr_at_10
      value: 17.566000000000003
    - type: mrr_at_100
      value: 18.335
    - type: mrr_at_1000
      value: 18.411
    - type: mrr_at_3
      value: 16.053
    - type: mrr_at_5
      value: 16.843
    - type: ndcg_at_1
      value: 13.65
    - type: ndcg_at_10
      value: 18.208
    - type: ndcg_at_100
      value: 22.352
    - type: ndcg_at_1000
      value: 24.969
    - type: ndcg_at_3
      value: 15.459
    - type: ndcg_at_5
      value: 16.817
    - type: precision_at_1
      value: 13.65
    - type: precision_at_10
      value: 3.083
    - type: precision_at_100
      value: 0.561
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 6.902
    - type: precision_at_5
      value: 4.968999999999999
    - type: recall_at_1
      value: 11.584
    - type: recall_at_10
      value: 24.629
    - type: recall_at_100
      value: 43.963
    - type: recall_at_1000
      value: 63.944
    - type: recall_at_3
      value: 17.155
    - type: recall_at_5
      value: 20.598
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.792000000000001
    - type: map_at_10
      value: 11.246
    - type: map_at_100
      value: 11.955
    - type: map_at_1000
      value: 12.076
    - type: map_at_3
      value: 10.176
    - type: map_at_5
      value: 10.802
    - type: mrr_at_1
      value: 9.67
    - type: mrr_at_10
      value: 13.591000000000001
    - type: mrr_at_100
      value: 14.285999999999998
    - type: mrr_at_1000
      value: 14.385
    - type: mrr_at_3
      value: 12.394
    - type: mrr_at_5
      value: 13.104
    - type: ndcg_at_1
      value: 9.67
    - type: ndcg_at_10
      value: 13.645
    - type: ndcg_at_100
      value: 17.562
    - type: ndcg_at_1000
      value: 21.101
    - type: ndcg_at_3
      value: 11.635
    - type: ndcg_at_5
      value: 12.638
    - type: precision_at_1
      value: 9.67
    - type: precision_at_10
      value: 2.54
    - type: precision_at_100
      value: 0.538
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 5.632000000000001
    - type: precision_at_5
      value: 4.136
    - type: recall_at_1
      value: 7.792000000000001
    - type: recall_at_10
      value: 18.63
    - type: recall_at_100
      value: 37.047999999999995
    - type: recall_at_1000
      value: 63.391
    - type: recall_at_3
      value: 12.956999999999999
    - type: recall_at_5
      value: 15.581
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.358999999999998
    - type: map_at_10
      value: 18.154999999999998
    - type: map_at_100
      value: 19.008
    - type: map_at_1000
      value: 19.125
    - type: map_at_3
      value: 16.645
    - type: map_at_5
      value: 17.544999999999998
    - type: mrr_at_1
      value: 15.672
    - type: mrr_at_10
      value: 20.973
    - type: mrr_at_100
      value: 21.782
    - type: mrr_at_1000
      value: 21.88
    - type: mrr_at_3
      value: 19.356
    - type: mrr_at_5
      value: 20.28
    - type: ndcg_at_1
      value: 15.672
    - type: ndcg_at_10
      value: 21.391
    - type: ndcg_at_100
      value: 25.71
    - type: ndcg_at_1000
      value: 29.016
    - type: ndcg_at_3
      value: 18.489
    - type: ndcg_at_5
      value: 19.916
    - type: precision_at_1
      value: 15.672
    - type: precision_at_10
      value: 3.573
    - type: precision_at_100
      value: 0.636
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 8.488999999999999
    - type: precision_at_5
      value: 5.989
    - type: recall_at_1
      value: 13.358999999999998
    - type: recall_at_10
      value: 28.695999999999998
    - type: recall_at_100
      value: 48.165
    - type: recall_at_1000
      value: 72.64500000000001
    - type: recall_at_3
      value: 20.573
    - type: recall_at_5
      value: 24.284
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.881
    - type: map_at_10
      value: 21.754
    - type: map_at_100
      value: 22.88
    - type: map_at_1000
      value: 23.087
    - type: map_at_3
      value: 19.827
    - type: map_at_5
      value: 20.964
    - type: mrr_at_1
      value: 19.564999999999998
    - type: mrr_at_10
      value: 25.246000000000002
    - type: mrr_at_100
      value: 26.163999999999998
    - type: mrr_at_1000
      value: 26.240999999999996
    - type: mrr_at_3
      value: 23.352999999999998
    - type: mrr_at_5
      value: 24.587999999999997
    - type: ndcg_at_1
      value: 19.564999999999998
    - type: ndcg_at_10
      value: 25.740000000000002
    - type: ndcg_at_100
      value: 30.977
    - type: ndcg_at_1000
      value: 34.486
    - type: ndcg_at_3
      value: 22.625
    - type: ndcg_at_5
      value: 24.294
    - type: precision_at_1
      value: 19.564999999999998
    - type: precision_at_10
      value: 5.0200000000000005
    - type: precision_at_100
      value: 1.146
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 10.738
    - type: precision_at_5
      value: 8.103
    - type: recall_at_1
      value: 15.881
    - type: recall_at_10
      value: 32.918
    - type: recall_at_100
      value: 58.184000000000005
    - type: recall_at_1000
      value: 81.76299999999999
    - type: recall_at_3
      value: 23.992
    - type: recall_at_5
      value: 28.265
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 12.027000000000001
    - type: map_at_10
      value: 15.959999999999999
    - type: map_at_100
      value: 16.715
    - type: map_at_1000
      value: 16.832
    - type: map_at_3
      value: 14.158000000000001
    - type: map_at_5
      value: 15.17
    - type: mrr_at_1
      value: 13.494
    - type: mrr_at_10
      value: 17.466
    - type: mrr_at_100
      value: 18.261
    - type: mrr_at_1000
      value: 18.365000000000002
    - type: mrr_at_3
      value: 15.65
    - type: mrr_at_5
      value: 16.667
    - type: ndcg_at_1
      value: 13.494
    - type: ndcg_at_10
      value: 18.844
    - type: ndcg_at_100
      value: 22.81
    - type: ndcg_at_1000
      value: 26.327
    - type: ndcg_at_3
      value: 15.217
    - type: ndcg_at_5
      value: 16.96
    - type: precision_at_1
      value: 13.494
    - type: precision_at_10
      value: 3.05
    - type: precision_at_100
      value: 0.532
    - type: precision_at_1000
      value: 0.091
    - type: precision_at_3
      value: 6.346
    - type: precision_at_5
      value: 4.769
    - type: recall_at_1
      value: 12.027000000000001
    - type: recall_at_10
      value: 26.605
    - type: recall_at_100
      value: 45.163
    - type: recall_at_1000
      value: 72.307
    - type: recall_at_3
      value: 16.771
    - type: recall_at_5
      value: 20.998
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.479
    - type: map_at_10
      value: 11.559
    - type: map_at_100
      value: 12.936
    - type: map_at_1000
      value: 13.120000000000001
    - type: map_at_3
      value: 9.377
    - type: map_at_5
      value: 10.494
    - type: mrr_at_1
      value: 14.396999999999998
    - type: mrr_at_10
      value: 23.039
    - type: mrr_at_100
      value: 24.141000000000002
    - type: mrr_at_1000
      value: 24.215999999999998
    - type: mrr_at_3
      value: 19.814999999999998
    - type: mrr_at_5
      value: 21.656
    - type: ndcg_at_1
      value: 14.396999999999998
    - type: ndcg_at_10
      value: 17.258000000000003
    - type: ndcg_at_100
      value: 23.615
    - type: ndcg_at_1000
      value: 27.605
    - type: ndcg_at_3
      value: 13.114999999999998
    - type: ndcg_at_5
      value: 14.698
    - type: precision_at_1
      value: 14.396999999999998
    - type: precision_at_10
      value: 5.713
    - type: precision_at_100
      value: 1.25
    - type: precision_at_1000
      value: 0.198
    - type: precision_at_3
      value: 9.924
    - type: precision_at_5
      value: 8.104
    - type: recall_at_1
      value: 6.479
    - type: recall_at_10
      value: 22.088
    - type: recall_at_100
      value: 44.681
    - type: recall_at_1000
      value: 67.869
    - type: recall_at_3
      value: 12.203
    - type: recall_at_5
      value: 16.275000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.618
    - type: map_at_10
      value: 10.217
    - type: map_at_100
      value: 14.038999999999998
    - type: map_at_1000
      value: 15.03
    - type: map_at_3
      value: 7.523000000000001
    - type: map_at_5
      value: 8.688
    - type: mrr_at_1
      value: 41.75
    - type: mrr_at_10
      value: 51.991
    - type: mrr_at_100
      value: 52.711
    - type: mrr_at_1000
      value: 52.746
    - type: mrr_at_3
      value: 49.5
    - type: mrr_at_5
      value: 50.961999999999996
    - type: ndcg_at_1
      value: 30.875000000000004
    - type: ndcg_at_10
      value: 24.709999999999997
    - type: ndcg_at_100
      value: 27.584999999999997
    - type: ndcg_at_1000
      value: 34.508
    - type: ndcg_at_3
      value: 27.88
    - type: ndcg_at_5
      value: 26.168999999999997
    - type: precision_at_1
      value: 41.75
    - type: precision_at_10
      value: 21.45
    - type: precision_at_100
      value: 6.795
    - type: precision_at_1000
      value: 1.43
    - type: precision_at_3
      value: 33.083
    - type: precision_at_5
      value: 27.750000000000004
    - type: recall_at_1
      value: 4.618
    - type: recall_at_10
      value: 14.898
    - type: recall_at_100
      value: 33.027
    - type: recall_at_1000
      value: 57.036
    - type: recall_at_3
      value: 8.995000000000001
    - type: recall_at_5
      value: 11.23
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.19499999999999
    - type: f1
      value: 40.60048839070268
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 17.11
    - type: map_at_10
      value: 25.478
    - type: map_at_100
      value: 26.436
    - type: map_at_1000
      value: 26.51
    - type: map_at_3
      value: 22.996
    - type: map_at_5
      value: 24.329
    - type: mrr_at_1
      value: 18.317
    - type: mrr_at_10
      value: 27.090999999999998
    - type: mrr_at_100
      value: 28.037
    - type: mrr_at_1000
      value: 28.102
    - type: mrr_at_3
      value: 24.532
    - type: mrr_at_5
      value: 25.918999999999997
    - type: ndcg_at_1
      value: 18.317
    - type: ndcg_at_10
      value: 30.448999999999998
    - type: ndcg_at_100
      value: 35.302
    - type: ndcg_at_1000
      value: 37.325
    - type: ndcg_at_3
      value: 25.326999999999998
    - type: ndcg_at_5
      value: 27.716
    - type: precision_at_1
      value: 18.317
    - type: precision_at_10
      value: 4.8469999999999995
    - type: precision_at_100
      value: 0.747
    - type: precision_at_1000
      value: 0.094
    - type: precision_at_3
      value: 10.975999999999999
    - type: precision_at_5
      value: 7.846
    - type: recall_at_1
      value: 17.11
    - type: recall_at_10
      value: 44.466
    - type: recall_at_100
      value: 67.06299999999999
    - type: recall_at_1000
      value: 82.64200000000001
    - type: recall_at_3
      value: 30.509999999999998
    - type: recall_at_5
      value: 36.27
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.446999999999999
    - type: map_at_10
      value: 12.188
    - type: map_at_100
      value: 13.241
    - type: map_at_1000
      value: 13.450000000000001
    - type: map_at_3
      value: 10.184999999999999
    - type: map_at_5
      value: 11.266
    - type: mrr_at_1
      value: 15.123000000000001
    - type: mrr_at_10
      value: 21.397
    - type: mrr_at_100
      value: 22.303
    - type: mrr_at_1000
      value: 22.398
    - type: mrr_at_3
      value: 19.187
    - type: mrr_at_5
      value: 20.383000000000003
    - type: ndcg_at_1
      value: 15.123000000000001
    - type: ndcg_at_10
      value: 16.957
    - type: ndcg_at_100
      value: 22.147
    - type: ndcg_at_1000
      value: 26.759
    - type: ndcg_at_3
      value: 14.091000000000001
    - type: ndcg_at_5
      value: 15.135000000000002
    - type: precision_at_1
      value: 15.123000000000001
    - type: precision_at_10
      value: 4.938
    - type: precision_at_100
      value: 1.019
    - type: precision_at_1000
      value: 0.18
    - type: precision_at_3
      value: 9.568
    - type: precision_at_5
      value: 7.438000000000001
    - type: recall_at_1
      value: 7.446999999999999
    - type: recall_at_10
      value: 22.094
    - type: recall_at_100
      value: 42.397
    - type: recall_at_1000
      value: 71.15700000000001
    - type: recall_at_3
      value: 12.879
    - type: recall_at_5
      value: 16.49
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 18.285
    - type: map_at_10
      value: 25.703
    - type: map_at_100
      value: 26.634
    - type: map_at_1000
      value: 26.741999999999997
    - type: map_at_3
      value: 23.642
    - type: map_at_5
      value: 24.826
    - type: mrr_at_1
      value: 36.57
    - type: mrr_at_10
      value: 43.772
    - type: mrr_at_100
      value: 44.51
    - type: mrr_at_1000
      value: 44.561
    - type: mrr_at_3
      value: 41.787
    - type: mrr_at_5
      value: 42.964
    - type: ndcg_at_1
      value: 36.57
    - type: ndcg_at_10
      value: 32.763999999999996
    - type: ndcg_at_100
      value: 37.077
    - type: ndcg_at_1000
      value: 39.666000000000004
    - type: ndcg_at_3
      value: 28.906
    - type: ndcg_at_5
      value: 30.86
    - type: precision_at_1
      value: 36.57
    - type: precision_at_10
      value: 7.202
    - type: precision_at_100
      value: 1.065
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 18.231
    - type: precision_at_5
      value: 12.483
    - type: recall_at_1
      value: 18.285
    - type: recall_at_10
      value: 36.009
    - type: recall_at_100
      value: 53.27499999999999
    - type: recall_at_1000
      value: 70.635
    - type: recall_at_3
      value: 27.345999999999997
    - type: recall_at_5
      value: 31.208999999999996
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 61.361999999999995
    - type: ap
      value: 57.09674595597791
    - type: f1
      value: 60.94720401382382
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.686
    - type: map_at_10
      value: 11.454
    - type: map_at_100
      value: 12.342
    - type: map_at_1000
      value: 12.447
    - type: map_at_3
      value: 9.722
    - type: map_at_5
      value: 10.632
    - type: mrr_at_1
      value: 6.891
    - type: mrr_at_10
      value: 11.768
    - type: mrr_at_100
      value: 12.651000000000002
    - type: mrr_at_1000
      value: 12.753
    - type: mrr_at_3
      value: 10.001999999999999
    - type: mrr_at_5
      value: 10.918999999999999
    - type: ndcg_at_1
      value: 6.848
    - type: ndcg_at_10
      value: 14.466000000000001
    - type: ndcg_at_100
      value: 19.301
    - type: ndcg_at_1000
      value: 22.458
    - type: ndcg_at_3
      value: 10.836
    - type: ndcg_at_5
      value: 12.475
    - type: precision_at_1
      value: 6.848
    - type: precision_at_10
      value: 2.48
    - type: precision_at_100
      value: 0.49899999999999994
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.766
    - type: precision_at_5
      value: 3.682
    - type: recall_at_1
      value: 6.686
    - type: recall_at_10
      value: 23.82
    - type: recall_at_100
      value: 47.349999999999994
    - type: recall_at_1000
      value: 72.66
    - type: recall_at_3
      value: 13.811000000000002
    - type: recall_at_5
      value: 17.76
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.67213862289103
    - type: f1
      value: 86.45841301738238
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.82170542635659
    - type: f1
      value: 39.12615117855274
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.18829858776058
    - type: f1
      value: 58.617914607265064
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 66.45595158036315
    - type: f1
      value: 64.9778374481982
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.531989286141012
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.070324322784792
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.516858081965257
    - type: mrr
      value: 30.51047930520146
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 4.131
    - type: map_at_10
      value: 8.826
    - type: map_at_100
      value: 11.094999999999999
    - type: map_at_1000
      value: 12.484
    - type: map_at_3
      value: 6.723
    - type: map_at_5
      value: 7.683
    - type: mrr_at_1
      value: 34.985
    - type: mrr_at_10
      value: 44.921
    - type: mrr_at_100
      value: 45.62
    - type: mrr_at_1000
      value: 45.676
    - type: mrr_at_3
      value: 42.931000000000004
    - type: mrr_at_5
      value: 44.385999999999996
    - type: ndcg_at_1
      value: 32.507999999999996
    - type: ndcg_at_10
      value: 26.773000000000003
    - type: ndcg_at_100
      value: 24.751
    - type: ndcg_at_1000
      value: 34.19
    - type: ndcg_at_3
      value: 31.213
    - type: ndcg_at_5
      value: 29.249000000000002
    - type: precision_at_1
      value: 34.985
    - type: precision_at_10
      value: 20.247999999999998
    - type: precision_at_100
      value: 6.907000000000001
    - type: precision_at_1000
      value: 2.031
    - type: precision_at_3
      value: 30.341
    - type: precision_at_5
      value: 25.759
    - type: recall_at_1
      value: 4.131
    - type: recall_at_10
      value: 12.465
    - type: recall_at_100
      value: 25.776
    - type: recall_at_1000
      value: 59.876
    - type: recall_at_3
      value: 7.968
    - type: recall_at_5
      value: 9.968
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 9.277000000000001
    - type: map_at_10
      value: 15.709999999999999
    - type: map_at_100
      value: 16.980999999999998
    - type: map_at_1000
      value: 17.074
    - type: map_at_3
      value: 13.157
    - type: map_at_5
      value: 14.571000000000002
    - type: mrr_at_1
      value: 10.574
    - type: mrr_at_10
      value: 17.344
    - type: mrr_at_100
      value: 18.506
    - type: mrr_at_1000
      value: 18.584999999999997
    - type: mrr_at_3
      value: 14.677000000000001
    - type: mrr_at_5
      value: 16.213
    - type: ndcg_at_1
      value: 10.574
    - type: ndcg_at_10
      value: 20.044
    - type: ndcg_at_100
      value: 26.447
    - type: ndcg_at_1000
      value: 29.084
    - type: ndcg_at_3
      value: 14.787
    - type: ndcg_at_5
      value: 17.362
    - type: precision_at_1
      value: 10.574
    - type: precision_at_10
      value: 3.7600000000000002
    - type: precision_at_100
      value: 0.738
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 6.933
    - type: precision_at_5
      value: 5.608
    - type: recall_at_1
      value: 9.277000000000001
    - type: recall_at_10
      value: 31.948
    - type: recall_at_100
      value: 61.708
    - type: recall_at_1000
      value: 82.07799999999999
    - type: recall_at_3
      value: 18.045
    - type: recall_at_5
      value: 24.038999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 64.268
    - type: map_at_10
      value: 77.19500000000001
    - type: map_at_100
      value: 77.95299999999999
    - type: map_at_1000
      value: 77.986
    - type: map_at_3
      value: 74.30499999999999
    - type: map_at_5
      value: 76.054
    - type: mrr_at_1
      value: 74.09
    - type: mrr_at_10
      value: 81.384
    - type: mrr_at_100
      value: 81.592
    - type: mrr_at_1000
      value: 81.597
    - type: mrr_at_3
      value: 80.00500000000001
    - type: mrr_at_5
      value: 80.876
    - type: ndcg_at_1
      value: 74.16
    - type: ndcg_at_10
      value: 81.813
    - type: ndcg_at_100
      value: 83.787
    - type: ndcg_at_1000
      value: 84.11800000000001
    - type: ndcg_at_3
      value: 78.389
    - type: ndcg_at_5
      value: 80.123
    - type: precision_at_1
      value: 74.16
    - type: precision_at_10
      value: 12.35
    - type: precision_at_100
      value: 1.466
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 34.067
    - type: precision_at_5
      value: 22.442
    - type: recall_at_1
      value: 64.268
    - type: recall_at_10
      value: 90.67
    - type: recall_at_100
      value: 97.935
    - type: recall_at_1000
      value: 99.703
    - type: recall_at_3
      value: 80.752
    - type: recall_at_5
      value: 85.63300000000001
    - type: map_at_1
      value: 2.948
    - type: map_at_10
      value: 7.126
    - type: map_at_100
      value: 8.462
    - type: map_at_1000
      value: 8.713
    - type: map_at_3
      value: 5.143
    - type: map_at_5
      value: 6.117
    - type: mrr_at_1
      value: 14.499999999999998
    - type: mrr_at_10
      value: 22.455
    - type: mrr_at_100
      value: 23.666
    - type: mrr_at_1000
      value: 23.745
    - type: mrr_at_3
      value: 19.417
    - type: mrr_at_5
      value: 21.117
    - type: ndcg_at_1
      value: 14.499999999999998
    - type: ndcg_at_10
      value: 12.666
    - type: ndcg_at_100
      value: 18.993
    - type: ndcg_at_1000
      value: 24.09
    - type: ndcg_at_3
      value: 11.655999999999999
    - type: ndcg_at_5
      value: 10.342
    - type: precision_at_1
      value: 14.499999999999998
    - type: precision_at_10
      value: 6.65
    - type: precision_at_100
      value: 1.598
    - type: precision_at_1000
      value: 0.28300000000000003
    - type: precision_at_3
      value: 10.8
    - type: precision_at_5
      value: 9.1
    - type: recall_at_1
      value: 2.948
    - type: recall_at_10
      value: 13.492
    - type: recall_at_100
      value: 32.448
    - type: recall_at_1000
      value: 57.553
    - type: recall_at_3
      value: 6.578
    - type: recall_at_5
      value: 9.242
    - type: map_at_1
      value: 0.129
    - type: map_at_10
      value: 0.6890000000000001
    - type: map_at_100
      value: 3.511
    - type: map_at_1000
      value: 8.943
    - type: map_at_3
      value: 0.304
    - type: map_at_5
      value: 0.42700000000000005
    - type: mrr_at_1
      value: 56.00000000000001
    - type: mrr_at_10
      value: 65.908
    - type: mrr_at_100
      value: 66.60199999999999
    - type: mrr_at_1000
      value: 66.60199999999999
    - type: mrr_at_3
      value: 63.333
    - type: mrr_at_5
      value: 64.23299999999999
    - type: ndcg_at_1
      value: 51.0
    - type: ndcg_at_10
      value: 39.304
    - type: ndcg_at_100
      value: 29.392000000000003
    - type: ndcg_at_1000
      value: 26.044
    - type: ndcg_at_3
      value: 45.408
    - type: ndcg_at_5
      value: 41.997
    - type: precision_at_1
      value: 56.00000000000001
    - type: precision_at_10
      value: 40.8
    - type: precision_at_100
      value: 30.48
    - type: precision_at_1000
      value: 12.692
    - type: precision_at_3
      value: 48.0
    - type: precision_at_5
      value: 43.6
    - type: recall_at_1
      value: 0.129
    - type: recall_at_10
      value: 0.893
    - type: recall_at_100
      value: 6.324000000000001
    - type: recall_at_1000
      value: 24.964
    - type: recall_at_3
      value: 0.33999999999999997
    - type: recall_at_5
      value: 0.505
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.191626251430044
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 47.00784930616429
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 75.38146213095916
    - type: cos_sim_spearman
      value: 65.36914729991646
    - type: euclidean_pearson
      value: 70.34893420889419
    - type: euclidean_spearman
      value: 65.36925972117625
    - type: manhattan_pearson
      value: 68.16816720045782
    - type: manhattan_spearman
      value: 64.0884396246228
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.45813185900207
    - type: cos_sim_spearman
      value: 68.03206487736479
    - type: euclidean_pearson
      value: 70.55331228911669
    - type: euclidean_spearman
      value: 68.03330456319067
    - type: manhattan_pearson
      value: 68.32513309931606
    - type: manhattan_spearman
      value: 66.90519361570585
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 77.32203252223916
    - type: cos_sim_spearman
      value: 78.44952447167366
    - type: euclidean_pearson
      value: 78.18870184193474
    - type: euclidean_spearman
      value: 78.44956228059971
    - type: manhattan_pearson
      value: 77.82417744157945
    - type: manhattan_spearman
      value: 78.17317129725184
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.98515479114604
    - type: cos_sim_spearman
      value: 74.70914230860409
    - type: euclidean_pearson
      value: 76.81874418213698
    - type: euclidean_spearman
      value: 74.70913261737951
    - type: manhattan_pearson
      value: 75.54410520012546
    - type: manhattan_spearman
      value: 73.74596322038998
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.34912352314105
    - type: cos_sim_spearman
      value: 82.13479378308254
    - type: euclidean_pearson
      value: 82.07291865315551
    - type: euclidean_spearman
      value: 82.13479226815167
    - type: manhattan_pearson
      value: 81.51909627091456
    - type: manhattan_spearman
      value: 81.70075499671213
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.1116492955691
    - type: cos_sim_spearman
      value: 77.19800116078945
    - type: euclidean_pearson
      value: 76.8231316467101
    - type: euclidean_spearman
      value: 77.19883015620502
    - type: manhattan_pearson
      value: 77.10588536013977
    - type: manhattan_spearman
      value: 77.50215416532438
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 84.10770264372314
    - type: cos_sim_spearman
      value: 84.97403648808209
    - type: euclidean_pearson
      value: 84.41825024902698
    - type: euclidean_spearman
      value: 84.97491009412074
    - type: manhattan_pearson
      value: 84.16827578787243
    - type: manhattan_spearman
      value: 84.92739867128569
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 62.91807215204278
    - type: cos_sim_spearman
      value: 59.61282196137074
    - type: euclidean_pearson
      value: 62.702286829442436
    - type: euclidean_spearman
      value: 59.61282196137074
    - type: manhattan_pearson
      value: 62.26491120673072
    - type: manhattan_spearman
      value: 59.7161013914999
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.43114398442724
    - type: cos_sim_spearman
      value: 77.35423527756463
    - type: euclidean_pearson
      value: 78.2269102978861
    - type: euclidean_spearman
      value: 77.35428366374488
    - type: manhattan_pearson
      value: 77.26973789544932
    - type: manhattan_spearman
      value: 76.58307796792111
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.61932743075317
    - type: mrr
      value: 91.38920810489437
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 36.861
    - type: map_at_10
      value: 45.93
    - type: map_at_100
      value: 46.861000000000004
    - type: map_at_1000
      value: 46.924
    - type: map_at_3
      value: 43.283
    - type: map_at_5
      value: 44.675
    - type: mrr_at_1
      value: 39.333
    - type: mrr_at_10
      value: 47.906
    - type: mrr_at_100
      value: 48.665000000000006
    - type: mrr_at_1000
      value: 48.722
    - type: mrr_at_3
      value: 45.611000000000004
    - type: mrr_at_5
      value: 46.778
    - type: ndcg_at_1
      value: 39.333
    - type: ndcg_at_10
      value: 50.970000000000006
    - type: ndcg_at_100
      value: 55.491
    - type: ndcg_at_1000
      value: 57.099
    - type: ndcg_at_3
      value: 45.837
    - type: ndcg_at_5
      value: 48.081
    - type: precision_at_1
      value: 39.333
    - type: precision_at_10
      value: 7.199999999999999
    - type: precision_at_100
      value: 0.9730000000000001
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 18.333
    - type: precision_at_5
      value: 12.4
    - type: recall_at_1
      value: 36.861
    - type: recall_at_10
      value: 64.839
    - type: recall_at_100
      value: 85.983
    - type: recall_at_1000
      value: 98.467
    - type: recall_at_3
      value: 50.678
    - type: recall_at_5
      value: 56.24400000000001
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.75742574257426
    - type: cos_sim_ap
      value: 93.4938177052363
    - type: cos_sim_f1
      value: 87.45019920318725
    - type: cos_sim_precision
      value: 87.10317460317461
    - type: cos_sim_recall
      value: 87.8
    - type: dot_accuracy
      value: 99.75742574257426
    - type: dot_ap
      value: 93.4938177052363
    - type: dot_f1
      value: 87.45019920318725
    - type: dot_precision
      value: 87.10317460317461
    - type: dot_recall
      value: 87.8
    - type: euclidean_accuracy
      value: 99.75742574257426
    - type: euclidean_ap
      value: 93.4938177052363
    - type: euclidean_f1
      value: 87.45019920318725
    - type: euclidean_precision
      value: 87.10317460317461
    - type: euclidean_recall
      value: 87.8
    - type: manhattan_accuracy
      value: 99.77425742574258
    - type: manhattan_ap
      value: 94.11582049960462
    - type: manhattan_f1
      value: 88.3367139959432
    - type: manhattan_precision
      value: 89.60905349794238
    - type: manhattan_recall
      value: 87.1
    - type: max_accuracy
      value: 99.77425742574258
    - type: max_ap
      value: 94.11582049960462
    - type: max_f1
      value: 88.3367139959432
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 40.69098529569445
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.68544212745689
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 43.065922067847836
    - type: mrr
      value: 43.64432136490961
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.750957237960492
    - type: cos_sim_spearman
      value: 30.099771071145582
    - type: dot_pearson
      value: 29.75095720371408
    - type: dot_spearman
      value: 30.128683537072114
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.6179999999999999
    - type: map_at_10
      value: 8.232000000000001
    - type: map_at_100
      value: 14.643999999999998
    - type: map_at_1000
      value: 16.259
    - type: map_at_3
      value: 4.2090000000000005
    - type: map_at_5
      value: 5.401
    - type: mrr_at_1
      value: 24.490000000000002
    - type: mrr_at_10
      value: 43.963
    - type: mrr_at_100
      value: 45.022
    - type: mrr_at_1000
      value: 45.039
    - type: mrr_at_3
      value: 42.177
    - type: mrr_at_5
      value: 42.687000000000005
    - type: ndcg_at_1
      value: 23.469
    - type: ndcg_at_10
      value: 22.526
    - type: ndcg_at_100
      value: 36.411
    - type: ndcg_at_1000
      value: 47.461
    - type: ndcg_at_3
      value: 27.176000000000002
    - type: ndcg_at_5
      value: 23.787
    - type: precision_at_1
      value: 24.490000000000002
    - type: precision_at_10
      value: 20.0
    - type: precision_at_100
      value: 8.286
    - type: precision_at_1000
      value: 1.543
    - type: precision_at_3
      value: 29.252
    - type: precision_at_5
      value: 23.265
    - type: recall_at_1
      value: 1.6179999999999999
    - type: recall_at_10
      value: 14.443
    - type: recall_at_100
      value: 50.073
    - type: recall_at_1000
      value: 83.56700000000001
    - type: recall_at_3
      value: 5.831
    - type: recall_at_5
      value: 7.797
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.5932
    - type: ap
      value: 13.748287764670659
    - type: f1
      value: 53.6121537777008
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 48.60498019241653
    - type: f1
      value: 48.8190614849162
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 37.40279692338929
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.11378673183525
    - type: cos_sim_ap
      value: 63.412004464549696
    - type: cos_sim_f1
      value: 60.880921286952386
    - type: cos_sim_precision
      value: 55.34211094323332
    - type: cos_sim_recall
      value: 67.65171503957784
    - type: dot_accuracy
      value: 83.11378673183525
    - type: dot_ap
      value: 63.412004464549696
    - type: dot_f1
      value: 60.880921286952386
    - type: dot_precision
      value: 55.34211094323332
    - type: dot_recall
      value: 67.65171503957784
    - type: euclidean_accuracy
      value: 83.11378673183525
    - type: euclidean_ap
      value: 63.412004464549696
    - type: euclidean_f1
      value: 60.880921286952386
    - type: euclidean_precision
      value: 55.34211094323332
    - type: euclidean_recall
      value: 67.65171503957784
    - type: manhattan_accuracy
      value: 82.13625797222389
    - type: manhattan_ap
      value: 60.704142220415335
    - type: manhattan_f1
      value: 58.10686319668357
    - type: manhattan_precision
      value: 51.55292194523907
    - type: manhattan_recall
      value: 66.56992084432719
    - type: max_accuracy
      value: 83.11378673183525
    - type: max_ap
      value: 63.412004464549696
    - type: max_f1
      value: 60.880921286952386
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.48593161796096
    - type: cos_sim_ap
      value: 83.09276630048417
    - type: cos_sim_f1
      value: 75.22376690154258
    - type: cos_sim_precision
      value: 74.4328031958996
    - type: cos_sim_recall
      value: 76.03172158915923
    - type: dot_accuracy
      value: 87.48593161796096
    - type: dot_ap
      value: 83.09276630048417
    - type: dot_f1
      value: 75.22376690154258
    - type: dot_precision
      value: 74.4328031958996
    - type: dot_recall
      value: 76.03172158915923
    - type: euclidean_accuracy
      value: 87.48593161796096
    - type: euclidean_ap
      value: 83.09276683624702
    - type: euclidean_f1
      value: 75.22376690154258
    - type: euclidean_precision
      value: 74.4328031958996
    - type: euclidean_recall
      value: 76.03172158915923
    - type: manhattan_accuracy
      value: 87.49369348391353
    - type: manhattan_ap
      value: 82.94869347657408
    - type: manhattan_f1
      value: 74.95875695376942
    - type: manhattan_precision
      value: 74.70367821365757
    - type: manhattan_recall
      value: 75.21558361564522
    - type: max_accuracy
      value: 87.49369348391353
    - type: max_ap
      value: 83.09276683624702
    - type: max_f1
      value: 75.22376690154258
---
