mteb model-index region:us
---
tags:
- mteb
model-index:
- name: nomic_classification_nignore50
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.34328358208954
    - type: ap
      value: 35.68453876944336
    - type: f1
      value: 67.06992889373645
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 59.672925
    - type: ap
      value: 55.848120844301974
    - type: f1
      value: 59.45636290076794
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 30.610000000000003
    - type: f1
      value: 30.300316542261875
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.697
    - type: map_at_10
      value: 35.189
    - type: map_at_100
      value: 36.4
    - type: map_at_1000
      value: 36.425000000000004
    - type: map_at_3
      value: 30.714000000000002
    - type: map_at_5
      value: 32.918
    - type: mrr_at_1
      value: 21.337
    - type: mrr_at_10
      value: 35.424
    - type: mrr_at_100
      value: 36.634
    - type: mrr_at_1000
      value: 36.659000000000006
    - type: mrr_at_3
      value: 30.927
    - type: mrr_at_5
      value: 33.132
    - type: ndcg_at_1
      value: 20.697
    - type: ndcg_at_10
      value: 43.525999999999996
    - type: ndcg_at_100
      value: 48.978
    - type: ndcg_at_1000
      value: 49.527
    - type: ndcg_at_3
      value: 34.087
    - type: ndcg_at_5
      value: 38.080999999999996
    - type: precision_at_1
      value: 20.697
    - type: precision_at_10
      value: 7.034
    - type: precision_at_100
      value: 0.9490000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.628
    - type: precision_at_5
      value: 10.725
    - type: recall_at_1
      value: 20.697
    - type: recall_at_10
      value: 70.341
    - type: recall_at_100
      value: 94.879
    - type: recall_at_1000
      value: 99.004
    - type: recall_at_3
      value: 43.883
    - type: recall_at_5
      value: 53.627
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: None
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 35.49094114007186
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 24.389506327986794
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 54.325008936884444
    - type: mrr
      value: 69.04992745020445
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 83.44469574569193
    - type: cos_sim_spearman
      value: 80.2397801250519
    - type: euclidean_pearson
      value: 82.22256751323195
    - type: euclidean_spearman
      value: 80.2397801250519
    - type: manhattan_pearson
      value: 81.55829597082581
    - type: manhattan_spearman
      value: 79.90603758074258
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 71.56818181818181
    - type: f1
      value: 70.79234518018967
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.120028817225204
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 23.27141125132152
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 22.482
    - type: map_at_10
      value: 29.986
    - type: map_at_100
      value: 31.19
    - type: map_at_1000
      value: 31.339
    - type: map_at_3
      value: 27.869
    - type: map_at_5
      value: 28.83
    - type: mrr_at_1
      value: 28.326
    - type: mrr_at_10
      value: 35.675000000000004
    - type: mrr_at_100
      value: 36.559000000000005
    - type: mrr_at_1000
      value: 36.632999999999996
    - type: mrr_at_3
      value: 34.049
    - type: mrr_at_5
      value: 34.8
    - type: ndcg_at_1
      value: 28.326
    - type: ndcg_at_10
      value: 34.788000000000004
    - type: ndcg_at_100
      value: 40.162
    - type: ndcg_at_1000
      value: 43.145
    - type: ndcg_at_3
      value: 31.903
    - type: ndcg_at_5
      value: 32.74
    - type: precision_at_1
      value: 28.326
    - type: precision_at_10
      value: 6.552
    - type: precision_at_100
      value: 1.146
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 15.451
    - type: precision_at_5
      value: 10.644
    - type: recall_at_1
      value: 22.482
    - type: recall_at_10
      value: 42.995
    - type: recall_at_100
      value: 66.79899999999999
    - type: recall_at_1000
      value: 87.02600000000001
    - type: recall_at_3
      value: 33.495999999999995
    - type: recall_at_5
      value: 36.7
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 17.147000000000002
    - type: map_at_10
      value: 23.28
    - type: map_at_100
      value: 24.191
    - type: map_at_1000
      value: 24.309
    - type: map_at_3
      value: 21.542
    - type: map_at_5
      value: 22.486
    - type: mrr_at_1
      value: 21.529
    - type: mrr_at_10
      value: 27.366
    - type: mrr_at_100
      value: 28.138
    - type: mrr_at_1000
      value: 28.206999999999997
    - type: mrr_at_3
      value: 25.668999999999997
    - type: mrr_at_5
      value: 26.653
    - type: ndcg_at_1
      value: 21.529
    - type: ndcg_at_10
      value: 27.107999999999997
    - type: ndcg_at_100
      value: 31.381999999999998
    - type: ndcg_at_1000
      value: 34.050000000000004
    - type: ndcg_at_3
      value: 24.101
    - type: ndcg_at_5
      value: 25.465
    - type: precision_at_1
      value: 21.529
    - type: precision_at_10
      value: 4.9430000000000005
    - type: precision_at_100
      value: 0.8829999999999999
    - type: precision_at_1000
      value: 0.136
    - type: precision_at_3
      value: 11.591999999999999
    - type: precision_at_5
      value: 8.153
    - type: recall_at_1
      value: 17.147000000000002
    - type: recall_at_10
      value: 34.510000000000005
    - type: recall_at_100
      value: 53.337999999999994
    - type: recall_at_1000
      value: 71.25200000000001
    - type: recall_at_3
      value: 25.711000000000002
    - type: recall_at_5
      value: 29.448999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.628
    - type: map_at_10
      value: 34.53
    - type: map_at_100
      value: 35.648
    - type: map_at_1000
      value: 35.746
    - type: map_at_3
      value: 32.001000000000005
    - type: map_at_5
      value: 33.516
    - type: mrr_at_1
      value: 29.842999999999996
    - type: mrr_at_10
      value: 37.679
    - type: mrr_at_100
      value: 38.607
    - type: mrr_at_1000
      value: 38.671
    - type: mrr_at_3
      value: 35.528
    - type: mrr_at_5
      value: 36.747
    - type: ndcg_at_1
      value: 29.842999999999996
    - type: ndcg_at_10
      value: 39.271
    - type: ndcg_at_100
      value: 44.507000000000005
    - type: ndcg_at_1000
      value: 46.79
    - type: ndcg_at_3
      value: 34.699999999999996
    - type: ndcg_at_5
      value: 37.032
    - type: precision_at_1
      value: 29.842999999999996
    - type: precision_at_10
      value: 6.3759999999999994
    - type: precision_at_100
      value: 0.989
    - type: precision_at_1000
      value: 0.126
    - type: precision_at_3
      value: 15.507000000000001
    - type: precision_at_5
      value: 10.871
    - type: recall_at_1
      value: 25.628
    - type: recall_at_10
      value: 50.552
    - type: recall_at_100
      value: 74.008
    - type: recall_at_1000
      value: 90.518
    - type: recall_at_3
      value: 38.397
    - type: recall_at_5
      value: 44.052
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 13.07
    - type: map_at_10
      value: 17.630000000000003
    - type: map_at_100
      value: 18.502
    - type: map_at_1000
      value: 18.614
    - type: map_at_3
      value: 16.213
    - type: map_at_5
      value: 17.029
    - type: mrr_at_1
      value: 14.124
    - type: mrr_at_10
      value: 18.706999999999997
    - type: mrr_at_100
      value: 19.604
    - type: mrr_at_1000
      value: 19.705000000000002
    - type: mrr_at_3
      value: 17.326
    - type: mrr_at_5
      value: 18.099999999999998
    - type: ndcg_at_1
      value: 14.124
    - type: ndcg_at_10
      value: 20.368
    - type: ndcg_at_100
      value: 25.020999999999997
    - type: ndcg_at_1000
      value: 28.360000000000003
    - type: ndcg_at_3
      value: 17.518
    - type: ndcg_at_5
      value: 18.914
    - type: precision_at_1
      value: 14.124
    - type: precision_at_10
      value: 3.164
    - type: precision_at_100
      value: 0.577
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_3
      value: 7.457999999999999
    - type: precision_at_5
      value: 5.266
    - type: recall_at_1
      value: 13.07
    - type: recall_at_10
      value: 27.811000000000003
    - type: recall_at_100
      value: 49.874
    - type: recall_at_1000
      value: 75.786
    - type: recall_at_3
      value: 20.06
    - type: recall_at_5
      value: 23.397000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 6.646000000000001
    - type: map_at_10
      value: 10.141
    - type: map_at_100
      value: 10.9
    - type: map_at_1000
      value: 11.036999999999999
    - type: map_at_3
      value: 8.781
    - type: map_at_5
      value: 9.581000000000001
    - type: mrr_at_1
      value: 8.333
    - type: mrr_at_10
      value: 12.504000000000001
    - type: mrr_at_100
      value: 13.331000000000001
    - type: mrr_at_1000
      value: 13.435
    - type: mrr_at_3
      value: 11.007
    - type: mrr_at_5
      value: 11.909
    - type: ndcg_at_1
      value: 8.333
    - type: ndcg_at_10
      value: 12.796
    - type: ndcg_at_100
      value: 17.115
    - type: ndcg_at_1000
      value: 20.84
    - type: ndcg_at_3
      value: 10.171
    - type: ndcg_at_5
      value: 11.496
    - type: precision_at_1
      value: 8.333
    - type: precision_at_10
      value: 2.5
    - type: precision_at_100
      value: 0.5519999999999999
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 5.017
    - type: precision_at_5
      value: 3.955
    - type: recall_at_1
      value: 6.646000000000001
    - type: recall_at_10
      value: 18.725
    - type: recall_at_100
      value: 38.590999999999994
    - type: recall_at_1000
      value: 65.955
    - type: recall_at_3
      value: 11.376999999999999
    - type: recall_at_5
      value: 14.673
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 17.865000000000002
    - type: map_at_10
      value: 23.877000000000002
    - type: map_at_100
      value: 25.058000000000003
    - type: map_at_1000
      value: 25.202999999999996
    - type: map_at_3
      value: 21.861
    - type: map_at_5
      value: 22.958000000000002
    - type: mrr_at_1
      value: 22.137
    - type: mrr_at_10
      value: 28.391
    - type: mrr_at_100
      value: 29.364
    - type: mrr_at_1000
      value: 29.454
    - type: mrr_at_3
      value: 26.372
    - type: mrr_at_5
      value: 27.551
    - type: ndcg_at_1
      value: 22.137
    - type: ndcg_at_10
      value: 28.183999999999997
    - type: ndcg_at_100
      value: 33.806000000000004
    - type: ndcg_at_1000
      value: 37.099
    - type: ndcg_at_3
      value: 24.621000000000002
    - type: ndcg_at_5
      value: 26.235000000000003
    - type: precision_at_1
      value: 22.137
    - type: precision_at_10
      value: 5.178
    - type: precision_at_100
      value: 0.9440000000000001
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 11.613999999999999
    - type: precision_at_5
      value: 8.373
    - type: recall_at_1
      value: 17.865000000000002
    - type: recall_at_10
      value: 36.885
    - type: recall_at_100
      value: 61.49400000000001
    - type: recall_at_1000
      value: 84.309
    - type: recall_at_3
      value: 26.51
    - type: recall_at_5
      value: 30.788
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.691999999999998
    - type: map_at_10
      value: 19.463
    - type: map_at_100
      value: 20.558
    - type: map_at_1000
      value: 20.703
    - type: map_at_3
      value: 17.277
    - type: map_at_5
      value: 18.607000000000003
    - type: mrr_at_1
      value: 16.895
    - type: mrr_at_10
      value: 22.939999999999998
    - type: mrr_at_100
      value: 23.902
    - type: mrr_at_1000
      value: 23.993000000000002
    - type: mrr_at_3
      value: 20.89
    - type: mrr_at_5
      value: 22.158
    - type: ndcg_at_1
      value: 16.895
    - type: ndcg_at_10
      value: 23.308
    - type: ndcg_at_100
      value: 28.675
    - type: ndcg_at_1000
      value: 32.156
    - type: ndcg_at_3
      value: 19.53
    - type: ndcg_at_5
      value: 21.519
    - type: precision_at_1
      value: 16.895
    - type: precision_at_10
      value: 4.417999999999999
    - type: precision_at_100
      value: 0.844
    - type: precision_at_1000
      value: 0.134
    - type: precision_at_3
      value: 9.399000000000001
    - type: precision_at_5
      value: 7.146
    - type: recall_at_1
      value: 13.691999999999998
    - type: recall_at_10
      value: 31.424000000000003
    - type: recall_at_100
      value: 55.223
    - type: recall_at_1000
      value: 79.842
    - type: recall_at_3
      value: 20.949
    - type: recall_at_5
      value: 26.166
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 14.61475
    - type: map_at_10
      value: 19.97075
    - type: map_at_100
      value: 20.916083333333333
    - type: map_at_1000
      value: 21.046
    - type: map_at_3
      value: 18.229250000000004
    - type: map_at_5
      value: 19.20266666666667
    - type: mrr_at_1
      value: 17.608083333333333
    - type: mrr_at_10
      value: 23.027083333333334
    - type: mrr_at_100
      value: 23.87941666666667
    - type: mrr_at_1000
      value: 23.96783333333333
    - type: mrr_at_3
      value: 21.377083333333335
    - type: mrr_at_5
      value: 22.300833333333333
    - type: ndcg_at_1
      value: 17.608083333333333
    - type: ndcg_at_10
      value: 23.473083333333335
    - type: ndcg_at_100
      value: 28.176750000000002
    - type: ndcg_at_1000
      value: 31.36625
    - type: ndcg_at_3
      value: 20.38383333333334
    - type: ndcg_at_5
      value: 21.82283333333333
    - type: precision_at_1
      value: 17.608083333333333
    - type: precision_at_10
      value: 4.162666666666666
    - type: precision_at_100
      value: 0.7761666666666668
    - type: precision_at_1000
      value: 0.12325000000000001
    - type: precision_at_3
      value: 9.466000000000001
    - type: precision_at_5
      value: 6.79
    - type: recall_at_1
      value: 14.61475
    - type: recall_at_10
      value: 31.009500000000003
    - type: recall_at_100
      value: 52.470000000000006
    - type: recall_at_1000
      value: 75.52175
    - type: recall_at_3
      value: 22.22875
    - type: recall_at_5
      value: 26.018083333333337
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 11.016
    - type: map_at_10
      value: 15.293999999999999
    - type: map_at_100
      value: 16.08
    - type: map_at_1000
      value: 16.177
    - type: map_at_3
      value: 13.898
    - type: map_at_5
      value: 14.637
    - type: mrr_at_1
      value: 12.883
    - type: mrr_at_10
      value: 17.279
    - type: mrr_at_100
      value: 18.082
    - type: mrr_at_1000
      value: 18.169
    - type: mrr_at_3
      value: 15.9
    - type: mrr_at_5
      value: 16.667
    - type: ndcg_at_1
      value: 12.883
    - type: ndcg_at_10
      value: 18.073
    - type: ndcg_at_100
      value: 22.142
    - type: ndcg_at_1000
      value: 24.887999999999998
    - type: ndcg_at_3
      value: 15.405
    - type: ndcg_at_5
      value: 16.622999999999998
    - type: precision_at_1
      value: 12.883
    - type: precision_at_10
      value: 3.052
    - type: precision_at_100
      value: 0.5519999999999999
    - type: precision_at_1000
      value: 0.086
    - type: precision_at_3
      value: 7.0040000000000004
    - type: precision_at_5
      value: 4.939
    - type: recall_at_1
      value: 11.016
    - type: recall_at_10
      value: 24.72
    - type: recall_at_100
      value: 43.553999999999995
    - type: recall_at_1000
      value: 64.189
    - type: recall_at_3
      value: 17.308
    - type: recall_at_5
      value: 20.455000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 7.148000000000001
    - type: map_at_10
      value: 10.878
    - type: map_at_100
      value: 11.547
    - type: map_at_1000
      value: 11.67
    - type: map_at_3
      value: 9.679
    - type: map_at_5
      value: 10.41
    - type: mrr_at_1
      value: 8.878
    - type: mrr_at_10
      value: 13.142999999999999
    - type: mrr_at_100
      value: 13.825999999999999
    - type: mrr_at_1000
      value: 13.927999999999999
    - type: mrr_at_3
      value: 11.786000000000001
    - type: mrr_at_5
      value: 12.623999999999999
    - type: ndcg_at_1
      value: 8.878
    - type: ndcg_at_10
      value: 13.414000000000001
    - type: ndcg_at_100
      value: 17.129
    - type: ndcg_at_1000
      value: 20.754
    - type: ndcg_at_3
      value: 11.135
    - type: ndcg_at_5
      value: 12.333
    - type: precision_at_1
      value: 8.878
    - type: precision_at_10
      value: 2.564
    - type: precision_at_100
      value: 0.525
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 5.448
    - type: precision_at_5
      value: 4.136
    - type: recall_at_1
      value: 7.148000000000001
    - type: recall_at_10
      value: 18.875
    - type: recall_at_100
      value: 36.321999999999996
    - type: recall_at_1000
      value: 63.273999999999994
    - type: recall_at_3
      value: 12.590000000000002
    - type: recall_at_5
      value: 15.6
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 13.178
    - type: map_at_10
      value: 17.538
    - type: map_at_100
      value: 18.343999999999998
    - type: map_at_1000
      value: 18.462999999999997
    - type: map_at_3
      value: 15.984000000000002
    - type: map_at_5
      value: 16.78
    - type: mrr_at_1
      value: 15.672
    - type: mrr_at_10
      value: 20.385
    - type: mrr_at_100
      value: 21.160999999999998
    - type: mrr_at_1000
      value: 21.252
    - type: mrr_at_3
      value: 18.766
    - type: mrr_at_5
      value: 19.554
    - type: ndcg_at_1
      value: 15.672
    - type: ndcg_at_10
      value: 20.785
    - type: ndcg_at_100
      value: 25.089
    - type: ndcg_at_1000
      value: 28.396
    - type: ndcg_at_3
      value: 17.701
    - type: ndcg_at_5
      value: 18.968
    - type: precision_at_1
      value: 15.672
    - type: precision_at_10
      value: 3.5069999999999997
    - type: precision_at_100
      value: 0.633
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 8.022
    - type: precision_at_5
      value: 5.634
    - type: recall_at_1
      value: 13.178
    - type: recall_at_10
      value: 28.227999999999998
    - type: recall_at_100
      value: 48.022999999999996
    - type: recall_at_1000
      value: 72.475
    - type: recall_at_3
      value: 19.425
    - type: recall_at_5
      value: 22.783
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.662999999999998
    - type: map_at_10
      value: 21.191
    - type: map_at_100
      value: 22.436
    - type: map_at_1000
      value: 22.634999999999998
    - type: map_at_3
      value: 19.493
    - type: map_at_5
      value: 20.543
    - type: mrr_at_1
      value: 19.368
    - type: mrr_at_10
      value: 24.866
    - type: mrr_at_100
      value: 25.875999999999998
    - type: mrr_at_1000
      value: 25.958
    - type: mrr_at_3
      value: 23.551
    - type: mrr_at_5
      value: 24.233
    - type: ndcg_at_1
      value: 19.368
    - type: ndcg_at_10
      value: 24.869
    - type: ndcg_at_100
      value: 30.54
    - type: ndcg_at_1000
      value: 33.994
    - type: ndcg_at_3
      value: 22.522000000000002
    - type: ndcg_at_5
      value: 23.674
    - type: precision_at_1
      value: 19.368
    - type: precision_at_10
      value: 4.704
    - type: precision_at_100
      value: 1.1400000000000001
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 10.671999999999999
    - type: precision_at_5
      value: 7.668
    - type: recall_at_1
      value: 15.662999999999998
    - type: recall_at_10
      value: 31.03
    - type: recall_at_100
      value: 57.861
    - type: recall_at_1000
      value: 81.179
    - type: recall_at_3
      value: 23.843
    - type: recall_at_5
      value: 27.223999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.842
    - type: map_at_10
      value: 15.841
    - type: map_at_100
      value: 16.539
    - type: map_at_1000
      value: 16.656000000000002
    - type: map_at_3
      value: 14.152999999999999
    - type: map_at_5
      value: 15.055
    - type: mrr_at_1
      value: 13.309000000000001
    - type: mrr_at_10
      value: 17.39
    - type: mrr_at_100
      value: 18.102999999999998
    - type: mrr_at_1000
      value: 18.209
    - type: mrr_at_3
      value: 15.681000000000001
    - type: mrr_at_5
      value: 16.614
    - type: ndcg_at_1
      value: 13.309000000000001
    - type: ndcg_at_10
      value: 18.712999999999997
    - type: ndcg_at_100
      value: 22.553
    - type: ndcg_at_1000
      value: 25.923000000000002
    - type: ndcg_at_3
      value: 15.299
    - type: ndcg_at_5
      value: 16.875
    - type: precision_at_1
      value: 13.309000000000001
    - type: precision_at_10
      value: 2.994
    - type: precision_at_100
      value: 0.529
    - type: precision_at_1000
      value: 0.089
    - type: precision_at_3
      value: 6.4079999999999995
    - type: precision_at_5
      value: 4.695
    - type: recall_at_1
      value: 11.842
    - type: recall_at_10
      value: 26.358999999999998
    - type: recall_at_100
      value: 44.553
    - type: recall_at_1000
      value: 70.456
    - type: recall_at_3
      value: 17.079
    - type: recall_at_5
      value: 20.93
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.841
    - type: map_at_10
      value: 11.955
    - type: map_at_100
      value: 13.322000000000001
    - type: map_at_1000
      value: 13.517000000000001
    - type: map_at_3
      value: 9.818
    - type: map_at_5
      value: 10.875
    - type: mrr_at_1
      value: 15.504999999999999
    - type: mrr_at_10
      value: 24.087
    - type: mrr_at_100
      value: 25.149
    - type: mrr_at_1000
      value: 25.221
    - type: mrr_at_3
      value: 20.923
    - type: mrr_at_5
      value: 22.64
    - type: ndcg_at_1
      value: 15.504999999999999
    - type: ndcg_at_10
      value: 17.787
    - type: ndcg_at_100
      value: 24.032
    - type: ndcg_at_1000
      value: 28.058
    - type: ndcg_at_3
      value: 13.729
    - type: ndcg_at_5
      value: 15.165999999999999
    - type: precision_at_1
      value: 15.504999999999999
    - type: precision_at_10
      value: 5.811
    - type: precision_at_100
      value: 1.246
    - type: precision_at_1000
      value: 0.197
    - type: precision_at_3
      value: 10.228
    - type: precision_at_5
      value: 8.155999999999999
    - type: recall_at_1
      value: 6.841
    - type: recall_at_10
      value: 22.451999999999998
    - type: recall_at_100
      value: 44.588
    - type: recall_at_1000
      value: 67.806
    - type: recall_at_3
      value: 12.824
    - type: recall_at_5
      value: 16.59
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: None
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 4.601999999999999
    - type: map_at_10
      value: 10.209
    - type: map_at_100
      value: 14.172
    - type: map_at_1000
      value: 15.121
    - type: map_at_3
      value: 7.59
    - type: map_at_5
      value: 8.853
    - type: mrr_at_1
      value: 41.75
    - type: mrr_at_10
      value: 51.949
    - type: mrr_at_100
      value: 52.678000000000004
    - type: mrr_at_1000
      value: 52.708
    - type: mrr_at_3
      value: 49.542
    - type: mrr_at_5
      value: 51.054
    - type: ndcg_at_1
      value: 31.125000000000004
    - type: ndcg_at_10
      value: 24.581
    - type: ndcg_at_100
      value: 27.894999999999996
    - type: ndcg_at_1000
      value: 34.438
    - type: ndcg_at_3
      value: 27.877999999999997
    - type: ndcg_at_5
      value: 26.273000000000003
    - type: precision_at_1
      value: 41.75
    - type: precision_at_10
      value: 21.15
    - type: precision_at_100
      value: 6.787999999999999
    - type: precision_at_1000
      value: 1.394
    - type: precision_at_3
      value: 32.917
    - type: precision_at_5
      value: 28.000000000000004
    - type: recall_at_1
      value: 4.601999999999999
    - type: recall_at_10
      value: 14.434
    - type: recall_at_100
      value: 33.838
    - type: recall_at_1000
      value: 56.438
    - type: recall_at_3
      value: 9.073
    - type: recall_at_5
      value: 11.395
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.364999999999995
    - type: f1
      value: 41.05024359810464
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 17.078
    - type: map_at_10
      value: 25.590000000000003
    - type: map_at_100
      value: 26.581
    - type: map_at_1000
      value: 26.651000000000003
    - type: map_at_3
      value: 23.113
    - type: map_at_5
      value: 24.457
    - type: mrr_at_1
      value: 18.257
    - type: mrr_at_10
      value: 27.171
    - type: mrr_at_100
      value: 28.147
    - type: mrr_at_1000
      value: 28.206999999999997
    - type: mrr_at_3
      value: 24.607
    - type: mrr_at_5
      value: 26.005
    - type: ndcg_at_1
      value: 18.257
    - type: ndcg_at_10
      value: 30.617
    - type: ndcg_at_100
      value: 35.625
    - type: ndcg_at_1000
      value: 37.566
    - type: ndcg_at_3
      value: 25.488
    - type: ndcg_at_5
      value: 27.897
    - type: precision_at_1
      value: 18.257
    - type: precision_at_10
      value: 4.877
    - type: precision_at_100
      value: 0.76
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 11.081000000000001
    - type: precision_at_5
      value: 7.933
    - type: recall_at_1
      value: 17.078
    - type: recall_at_10
      value: 44.866
    - type: recall_at_100
      value: 68.148
    - type: recall_at_1000
      value: 83.134
    - type: recall_at_3
      value: 30.830999999999996
    - type: recall_at_5
      value: 36.629
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.515
    - type: map_at_10
      value: 11.788
    - type: map_at_100
      value: 12.974
    - type: map_at_1000
      value: 13.177
    - type: map_at_3
      value: 9.844
    - type: map_at_5
      value: 10.8
    - type: mrr_at_1
      value: 14.352
    - type: mrr_at_10
      value: 20.134
    - type: mrr_at_100
      value: 21.288
    - type: mrr_at_1000
      value: 21.384
    - type: mrr_at_3
      value: 18.133
    - type: mrr_at_5
      value: 19.097
    - type: ndcg_at_1
      value: 14.352
    - type: ndcg_at_10
      value: 16.203
    - type: ndcg_at_100
      value: 21.891
    - type: ndcg_at_1000
      value: 26.653
    - type: ndcg_at_3
      value: 13.369
    - type: ndcg_at_5
      value: 14.327000000000002
    - type: precision_at_1
      value: 14.352
    - type: precision_at_10
      value: 4.645
    - type: precision_at_100
      value: 1.028
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 8.796
    - type: precision_at_5
      value: 6.728000000000001
    - type: recall_at_1
      value: 7.515
    - type: recall_at_10
      value: 21.018
    - type: recall_at_100
      value: 42.887
    - type: recall_at_1000
      value: 72.898
    - type: recall_at_3
      value: 12.215
    - type: recall_at_5
      value: 15.612
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 18.332
    - type: map_at_10
      value: 25.791999999999998
    - type: map_at_100
      value: 26.706999999999997
    - type: map_at_1000
      value: 26.810000000000002
    - type: map_at_3
      value: 23.742
    - type: map_at_5
      value: 24.903
    - type: mrr_at_1
      value: 36.664
    - type: mrr_at_10
      value: 44.067
    - type: mrr_at_100
      value: 44.756
    - type: mrr_at_1000
      value: 44.806000000000004
    - type: mrr_at_3
      value: 42.091
    - type: mrr_at_5
      value: 43.206
    - type: ndcg_at_1
      value: 36.664
    - type: ndcg_at_10
      value: 32.938
    - type: ndcg_at_100
      value: 37.184
    - type: ndcg_at_1000
      value: 39.723000000000006
    - type: ndcg_at_3
      value: 29.087000000000003
    - type: ndcg_at_5
      value: 30.986000000000004
    - type: precision_at_1
      value: 36.664
    - type: precision_at_10
      value: 7.245
    - type: precision_at_100
      value: 1.0670000000000002
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 18.37
    - type: precision_at_5
      value: 12.527
    - type: recall_at_1
      value: 18.332
    - type: recall_at_10
      value: 36.226
    - type: recall_at_100
      value: 53.342
    - type: recall_at_1000
      value: 70.42500000000001
    - type: recall_at_3
      value: 27.556000000000004
    - type: recall_at_5
      value: 31.317
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 58.64719999999999
    - type: ap
      value: 55.19966477229678
    - type: f1
      value: 58.24961396114563
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.459
    - type: map_at_10
      value: 11.254999999999999
    - type: map_at_100
      value: 12.132
    - type: map_at_1000
      value: 12.237
    - type: map_at_3
      value: 9.522
    - type: map_at_5
      value: 10.456999999999999
    - type: mrr_at_1
      value: 6.633
    - type: mrr_at_10
      value: 11.518
    - type: mrr_at_100
      value: 12.395
    - type: mrr_at_1000
      value: 12.497
    - type: mrr_at_3
      value: 9.751999999999999
    - type: mrr_at_5
      value: 10.708
    - type: ndcg_at_1
      value: 6.59
    - type: ndcg_at_10
      value: 14.264
    - type: ndcg_at_100
      value: 19.070999999999998
    - type: ndcg_at_1000
      value: 22.235
    - type: ndcg_at_3
      value: 10.631
    - type: ndcg_at_5
      value: 12.339
    - type: precision_at_1
      value: 6.59
    - type: precision_at_10
      value: 2.461
    - type: precision_at_100
      value: 0.496
    - type: precision_at_1000
      value: 0.077
    - type: precision_at_3
      value: 4.6850000000000005
    - type: precision_at_5
      value: 3.6790000000000003
    - type: recall_at_1
      value: 6.459
    - type: recall_at_10
      value: 23.649
    - type: recall_at_100
      value: 47.13
    - type: recall_at_1000
      value: 72.51100000000001
    - type: recall_at_3
      value: 13.641
    - type: recall_at_5
      value: 17.787
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.75695394436845
    - type: f1
      value: 84.39448911327825
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 54.072047423620596
    - type: f1
      value: 36.95943939246465
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.78614660390047
    - type: f1
      value: 57.44347017992026
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.28379287155346
    - type: f1
      value: 62.76816678345901
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 29.671378352049466
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 25.86783118767072
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.346696390536565
    - type: mrr
      value: 30.303238754879626
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 3.9190000000000005
    - type: map_at_10
      value: 8.742999999999999
    - type: map_at_100
      value: 11.073
    - type: map_at_1000
      value: 12.447999999999999
    - type: map_at_3
      value: 6.2379999999999995
    - type: map_at_5
      value: 7.443
    - type: mrr_at_1
      value: 34.365
    - type: mrr_at_10
      value: 44.238
    - type: mrr_at_100
      value: 44.857
    - type: mrr_at_1000
      value: 44.91
    - type: mrr_at_3
      value: 41.744
    - type: mrr_at_5
      value: 43.478
    - type: ndcg_at_1
      value: 32.353
    - type: ndcg_at_10
      value: 26.695
    - type: ndcg_at_100
      value: 24.728
    - type: ndcg_at_1000
      value: 34.013
    - type: ndcg_at_3
      value: 30.268
    - type: ndcg_at_5
      value: 28.95
    - type: precision_at_1
      value: 34.365
    - type: precision_at_10
      value: 20.31
    - type: precision_at_100
      value: 6.984999999999999
    - type: precision_at_1000
      value: 2.019
    - type: precision_at_3
      value: 28.896
    - type: precision_at_5
      value: 25.697
    - type: recall_at_1
      value: 3.9190000000000005
    - type: recall_at_10
      value: 13.046
    - type: recall_at_100
      value: 26.08
    - type: recall_at_1000
      value: 60.207
    - type: recall_at_3
      value: 7.255000000000001
    - type: recall_at_5
      value: 9.853000000000002
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 8.408
    - type: map_at_10
      value: 15.064
    - type: map_at_100
      value: 16.282
    - type: map_at_1000
      value: 16.384999999999998
    - type: map_at_3
      value: 12.605
    - type: map_at_5
      value: 13.866
    - type: mrr_at_1
      value: 9.589
    - type: mrr_at_10
      value: 16.598
    - type: mrr_at_100
      value: 17.716
    - type: mrr_at_1000
      value: 17.8
    - type: mrr_at_3
      value: 14.021
    - type: mrr_at_5
      value: 15.39
    - type: ndcg_at_1
      value: 9.589
    - type: ndcg_at_10
      value: 19.408
    - type: ndcg_at_100
      value: 25.549
    - type: ndcg_at_1000
      value: 28.344
    - type: ndcg_at_3
      value: 14.258000000000001
    - type: ndcg_at_5
      value: 16.549
    - type: precision_at_1
      value: 9.589
    - type: precision_at_10
      value: 3.711
    - type: precision_at_100
      value: 0.717
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 6.769
    - type: precision_at_5
      value: 5.359
    - type: recall_at_1
      value: 8.408
    - type: recall_at_10
      value: 31.442999999999998
    - type: recall_at_100
      value: 59.931
    - type: recall_at_1000
      value: 81.40899999999999
    - type: recall_at_3
      value: 17.654
    - type: recall_at_5
      value: 22.982
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 64.35600000000001
    - type: map_at_10
      value: 77.12400000000001
    - type: map_at_100
      value: 77.873
    - type: map_at_1000
      value: 77.905
    - type: map_at_3
      value: 74.18599999999999
    - type: map_at_5
      value: 76.00099999999999
    - type: mrr_at_1
      value: 74.22
    - type: mrr_at_10
      value: 81.326
    - type: mrr_at_100
      value: 81.54
    - type: mrr_at_1000
      value: 81.545
    - type: mrr_at_3
      value: 79.912
    - type: mrr_at_5
      value: 80.833
    - type: ndcg_at_1
      value: 74.26
    - type: ndcg_at_10
      value: 81.709
    - type: ndcg_at_100
      value: 83.688
    - type: ndcg_at_1000
      value: 84.029
    - type: ndcg_at_3
      value: 78.214
    - type: ndcg_at_5
      value: 80.07
    - type: precision_at_1
      value: 74.26
    - type: precision_at_10
      value: 12.334
    - type: precision_at_100
      value: 1.463
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 33.977000000000004
    - type: precision_at_5
      value: 22.442
    - type: recall_at_1
      value: 64.35600000000001
    - type: recall_at_10
      value: 90.50200000000001
    - type: recall_at_100
      value: 97.833
    - type: recall_at_1000
      value: 99.681
    - type: recall_at_3
      value: 80.426
    - type: recall_at_5
      value: 85.627
    - type: map_at_1
      value: 2.988
    - type: map_at_10
      value: 7.183000000000001
    - type: map_at_100
      value: 8.522
    - type: map_at_1000
      value: 8.769
    - type: map_at_3
      value: 5.29
    - type: map_at_5
      value: 6.249
    - type: mrr_at_1
      value: 14.7
    - type: mrr_at_10
      value: 22.526
    - type: mrr_at_100
      value: 23.749000000000002
    - type: mrr_at_1000
      value: 23.827
    - type: mrr_at_3
      value: 19.617
    - type: mrr_at_5
      value: 21.322
    - type: ndcg_at_1
      value: 14.7
    - type: ndcg_at_10
      value: 12.666
    - type: ndcg_at_100
      value: 18.999
    - type: ndcg_at_1000
      value: 24.060000000000002
    - type: ndcg_at_3
      value: 11.908000000000001
    - type: ndcg_at_5
      value: 10.517999999999999
    - type: precision_at_1
      value: 14.7
    - type: precision_at_10
      value: 6.59
    - type: precision_at_100
      value: 1.592
    - type: precision_at_1000
      value: 0.28200000000000003
    - type: precision_at_3
      value: 11.1
    - type: precision_at_5
      value: 9.28
    - type: recall_at_1
      value: 2.988
    - type: recall_at_10
      value: 13.361999999999998
    - type: recall_at_100
      value: 32.312999999999995
    - type: recall_at_1000
      value: 57.293000000000006
    - type: recall_at_3
      value: 6.768000000000001
    - type: recall_at_5
      value: 9.408
    - type: map_at_1
      value: 0.15
    - type: map_at_10
      value: 0.732
    - type: map_at_100
      value: 3.402
    - type: map_at_1000
      value: 8.562
    - type: map_at_3
      value: 0.311
    - type: map_at_5
      value: 0.45799999999999996
    - type: mrr_at_1
      value: 60.0
    - type: mrr_at_10
      value: 66.297
    - type: mrr_at_100
      value: 67.486
    - type: mrr_at_1000
      value: 67.495
    - type: mrr_at_3
      value: 64.667
    - type: mrr_at_5
      value: 65.567
    - type: ndcg_at_1
      value: 53.0
    - type: ndcg_at_10
      value: 39.839999999999996
    - type: ndcg_at_100
      value: 28.401
    - type: ndcg_at_1000
      value: 24.781
    - type: ndcg_at_3
      value: 45.173
    - type: ndcg_at_5
      value: 42.543
    - type: precision_at_1
      value: 57.99999999999999
    - type: precision_at_10
      value: 41.199999999999996
    - type: precision_at_100
      value: 29.299999999999997
    - type: precision_at_1000
      value: 12.06
    - type: precision_at_3
      value: 46.666999999999994
    - type: precision_at_5
      value: 44.0
    - type: recall_at_1
      value: 0.15
    - type: recall_at_10
      value: 0.928
    - type: recall_at_100
      value: 6.021
    - type: recall_at_1000
      value: 23.61
    - type: recall_at_3
      value: 0.332
    - type: recall_at_5
      value: 0.521
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 36.774788977863864
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 46.77683019813603
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 74.41889076801608
    - type: cos_sim_spearman
      value: 64.0943040174807
    - type: euclidean_pearson
      value: 68.82034211304835
    - type: euclidean_spearman
      value: 64.09442214998937
    - type: manhattan_pearson
      value: 67.28965034113492
    - type: manhattan_spearman
      value: 63.44420264246327
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 74.19404151109595
    - type: cos_sim_spearman
      value: 67.74306846452986
    - type: euclidean_pearson
      value: 70.18395120349778
    - type: euclidean_spearman
      value: 67.74435929212751
    - type: manhattan_pearson
      value: 68.00233535704764
    - type: manhattan_spearman
      value: 66.49484254678912
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.87296571665527
    - type: cos_sim_spearman
      value: 77.89561218206916
    - type: euclidean_pearson
      value: 77.69387561554153
    - type: euclidean_spearman
      value: 77.89564999542652
    - type: manhattan_pearson
      value: 77.2962286612409
    - type: manhattan_spearman
      value: 77.62183070015116
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.57868393517904
    - type: cos_sim_spearman
      value: 74.3463323181872
    - type: euclidean_pearson
      value: 76.34645562235912
    - type: euclidean_spearman
      value: 74.34632262739605
    - type: manhattan_pearson
      value: 75.18605845598414
    - type: manhattan_spearman
      value: 73.37658913779082
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.3634602887491
    - type: cos_sim_spearman
      value: 82.08782263146122
    - type: euclidean_pearson
      value: 81.98650592402285
    - type: euclidean_spearman
      value: 82.08782111739671
    - type: manhattan_pearson
      value: 81.3116524025808
    - type: manhattan_spearman
      value: 81.48861424628144
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.87657339764795
    - type: cos_sim_spearman
      value: 76.85063393951995
    - type: euclidean_pearson
      value: 76.4294473355708
    - type: euclidean_spearman
      value: 76.85118422928095
    - type: manhattan_pearson
      value: 76.64930860894692
    - type: manhattan_spearman
      value: 77.10013496496948
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 83.34326345648941
    - type: cos_sim_spearman
      value: 83.88446362725742
    - type: euclidean_pearson
      value: 83.46533085232362
    - type: euclidean_spearman
      value: 83.8853378609005
    - type: manhattan_pearson
      value: 83.1484584186202
    - type: manhattan_spearman
      value: 83.95137720105474
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 63.83321542257857
    - type: cos_sim_spearman
      value: 60.82336431262449
    - type: euclidean_pearson
      value: 63.11807243264151
    - type: euclidean_spearman
      value: 60.82336431262449
    - type: manhattan_pearson
      value: 62.08662855750554
    - type: manhattan_spearman
      value: 59.96327210016991
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.52565754458857
    - type: cos_sim_spearman
      value: 77.31638441143197
    - type: euclidean_pearson
      value: 78.14871856195552
    - type: euclidean_spearman
      value: 77.31637278095369
    - type: manhattan_pearson
      value: 77.18966645743699
    - type: manhattan_spearman
      value: 76.60273070312653
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.10656484834338
    - type: mrr
      value: 90.98610811846106
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 39.75
    - type: map_at_10
      value: 47.549
    - type: map_at_100
      value: 48.579
    - type: map_at_1000
      value: 48.653
    - type: map_at_3
      value: 45.135
    - type: map_at_5
      value: 46.444
    - type: mrr_at_1
      value: 42.0
    - type: mrr_at_10
      value: 49.418
    - type: mrr_at_100
      value: 50.253
    - type: mrr_at_1000
      value: 50.319
    - type: mrr_at_3
      value: 47.221999999999994
    - type: mrr_at_5
      value: 48.439
    - type: ndcg_at_1
      value: 42.0
    - type: ndcg_at_10
      value: 51.922999999999995
    - type: ndcg_at_100
      value: 56.607
    - type: ndcg_at_1000
      value: 58.3
    - type: ndcg_at_3
      value: 47.316
    - type: ndcg_at_5
      value: 49.446
    - type: precision_at_1
      value: 42.0
    - type: precision_at_10
      value: 7.066999999999999
    - type: precision_at_100
      value: 0.963
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 18.556
    - type: precision_at_5
      value: 12.4
    - type: recall_at_1
      value: 39.75
    - type: recall_at_10
      value: 63.727999999999994
    - type: recall_at_100
      value: 84.983
    - type: recall_at_1000
      value: 97.8
    - type: recall_at_3
      value: 51.233
    - type: recall_at_5
      value: 56.494
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.77623762376237
    - type: cos_sim_ap
      value: 94.03474205524832
    - type: cos_sim_f1
      value: 88.17533129459734
    - type: cos_sim_precision
      value: 89.91683991683992
    - type: cos_sim_recall
      value: 86.5
    - type: dot_accuracy
      value: 99.77623762376237
    - type: dot_ap
      value: 94.03474205524832
    - type: dot_f1
      value: 88.17533129459734
    - type: dot_precision
      value: 89.91683991683992
    - type: dot_recall
      value: 86.5
    - type: euclidean_accuracy
      value: 99.77623762376237
    - type: euclidean_ap
      value: 94.03474205524832
    - type: euclidean_f1
      value: 88.17533129459734
    - type: euclidean_precision
      value: 89.91683991683992
    - type: euclidean_recall
      value: 86.5
    - type: manhattan_accuracy
      value: 99.77722772277228
    - type: manhattan_ap
      value: 94.18601558420747
    - type: manhattan_f1
      value: 88.37209302325581
    - type: manhattan_precision
      value: 91.44385026737967
    - type: manhattan_recall
      value: 85.5
    - type: max_accuracy
      value: 99.77722772277228
    - type: max_ap
      value: 94.18601558420747
    - type: max_f1
      value: 88.37209302325581
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 39.59223629185949
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 29.72427682478714
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 42.58781744864796
    - type: mrr
      value: 43.04660311094135
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.162875776593765
    - type: cos_sim_spearman
      value: 29.469578163520644
    - type: dot_pearson
      value: 29.16287568844527
    - type: dot_spearman
      value: 29.491226084003042
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 1.6969999999999998
    - type: map_at_10
      value: 7.6579999999999995
    - type: map_at_100
      value: 14.119000000000002
    - type: map_at_1000
      value: 15.695999999999998
    - type: map_at_3
      value: 3.599
    - type: map_at_5
      value: 5.076
    - type: mrr_at_1
      value: 26.531
    - type: mrr_at_10
      value: 43.033
    - type: mrr_at_100
      value: 43.957
    - type: mrr_at_1000
      value: 43.976
    - type: mrr_at_3
      value: 38.435
    - type: mrr_at_5
      value: 42.211
    - type: ndcg_at_1
      value: 24.490000000000002
    - type: ndcg_at_10
      value: 22.114
    - type: ndcg_at_100
      value: 35.583999999999996
    - type: ndcg_at_1000
      value: 46.697
    - type: ndcg_at_3
      value: 23.521
    - type: ndcg_at_5
      value: 23.363
    - type: precision_at_1
      value: 26.531
    - type: precision_at_10
      value: 20.408
    - type: precision_at_100
      value: 8.265
    - type: precision_at_1000
      value: 1.551
    - type: precision_at_3
      value: 25.169999999999998
    - type: precision_at_5
      value: 24.490000000000002
    - type: recall_at_1
      value: 1.6969999999999998
    - type: recall_at_10
      value: 14.554
    - type: recall_at_100
      value: 49.858000000000004
    - type: recall_at_1000
      value: 83.635
    - type: recall_at_3
      value: 4.822
    - type: recall_at_5
      value: 7.933
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 68.9474
    - type: ap
      value: 13.286323018191338
    - type: f1
      value: 52.98797630385014
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 47.993774759479344
    - type: f1
      value: 48.15808612169315
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 34.53065734021412
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.61906181081243
    - type: cos_sim_ap
      value: 61.91869955453384
    - type: cos_sim_f1
      value: 59.794798377475544
    - type: cos_sim_precision
      value: 54.57317073170732
    - type: cos_sim_recall
      value: 66.12137203166228
    - type: dot_accuracy
      value: 82.61906181081243
    - type: dot_ap
      value: 61.91869955453384
    - type: dot_f1
      value: 59.794798377475544
    - type: dot_precision
      value: 54.57317073170732
    - type: dot_recall
      value: 66.12137203166228
    - type: euclidean_accuracy
      value: 82.61906181081243
    - type: euclidean_ap
      value: 61.91869955453384
    - type: euclidean_f1
      value: 59.794798377475544
    - type: euclidean_precision
      value: 54.57317073170732
    - type: euclidean_recall
      value: 66.12137203166228
    - type: manhattan_accuracy
      value: 81.89187578232104
    - type: manhattan_ap
      value: 59.62564983212156
    - type: manhattan_f1
      value: 57.711442786069654
    - type: manhattan_precision
      value: 52.364574376612204
    - type: manhattan_recall
      value: 64.27440633245382
    - type: max_accuracy
      value: 82.61906181081243
    - type: max_ap
      value: 61.91869955453384
    - type: max_f1
      value: 59.794798377475544
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.49563395040167
    - type: cos_sim_ap
      value: 82.90539955967866
    - type: cos_sim_f1
      value: 74.9081462237892
    - type: cos_sim_precision
      value: 72.30780253636169
    - type: cos_sim_recall
      value: 77.70249461040962
    - type: dot_accuracy
      value: 87.49563395040167
    - type: dot_ap
      value: 82.90539958269324
    - type: dot_f1
      value: 74.9081462237892
    - type: dot_precision
      value: 72.30780253636169
    - type: dot_recall
      value: 77.70249461040962
    - type: euclidean_accuracy
      value: 87.49563395040167
    - type: euclidean_ap
      value: 82.9054181491746
    - type: euclidean_f1
      value: 74.9081462237892
    - type: euclidean_precision
      value: 72.30780253636169
    - type: euclidean_recall
      value: 77.70249461040962
    - type: manhattan_accuracy
      value: 87.37920596111304
    - type: manhattan_ap
      value: 82.78475210950901
    - type: manhattan_f1
      value: 74.73338499575631
    - type: manhattan_precision
      value: 71.7596201544894
    - type: manhattan_recall
      value: 77.96427471512165
    - type: max_accuracy
      value: 87.49563395040167
    - type: max_ap
      value: 82.9054181491746
    - type: max_f1
      value: 74.9081462237892
---
