mteb model-index region:us
---
tags:
- mteb
model-index:
- name: l3_wordllama_fixed
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: None
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 67.40298507462687
    - type: ap
      value: 28.677454675181384
    - type: f1
      value: 60.58324071299079
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: None
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 63.75847499999999
    - type: ap
      value: 59.00482910406265
    - type: f1
      value: 63.59920748914567
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: None
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.09
    - type: f1
      value: 31.527306414565835
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: None
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 20.413
    - type: map_at_10
      value: 35.176
    - type: map_at_100
      value: 36.489
    - type: map_at_1000
      value: 36.507
    - type: map_at_3
      value: 30.69
    - type: map_at_5
      value: 32.859
    - type: mrr_at_1
      value: 21.124000000000002
    - type: mrr_at_10
      value: 35.44
    - type: mrr_at_100
      value: 36.753
    - type: mrr_at_1000
      value: 36.77
    - type: mrr_at_3
      value: 30.915
    - type: mrr_at_5
      value: 33.113
    - type: ndcg_at_1
      value: 20.413
    - type: ndcg_at_10
      value: 43.565
    - type: ndcg_at_100
      value: 49.329
    - type: ndcg_at_1000
      value: 49.757
    - type: ndcg_at_3
      value: 34.143
    - type: ndcg_at_5
      value: 38.046
    - type: precision_at_1
      value: 20.413
    - type: precision_at_10
      value: 7.048
    - type: precision_at_100
      value: 0.9610000000000001
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 14.723
    - type: precision_at_5
      value: 10.725
    - type: recall_at_1
      value: 20.413
    - type: recall_at_10
      value: 70.48400000000001
    - type: recall_at_100
      value: 96.088
    - type: recall_at_1000
      value: 99.36
    - type: recall_at_3
      value: 44.168
    - 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: 39.885229242790935
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: None
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 29.49720713710708
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: None
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 55.61953366105678
    - type: mrr
      value: 70.12344457635315
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: None
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 76.26075421266883
    - type: cos_sim_spearman
      value: 71.32873370732024
    - type: euclidean_pearson
      value: 74.59312194402976
    - type: euclidean_spearman
      value: 71.32873370732024
    - type: manhattan_pearson
      value: 74.5892678336525
    - type: manhattan_spearman
      value: 71.02450990790472
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: None
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 73.68506493506494
    - type: f1
      value: 72.88555102531198
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: None
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 33.29089107203252
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 25.19965378718348
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: None
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 21.508
    - type: map_at_10
      value: 29.088
    - type: map_at_100
      value: 30.279
    - type: map_at_1000
      value: 30.445
    - type: map_at_3
      value: 26.552999999999997
    - type: map_at_5
      value: 27.939000000000004
    - type: mrr_at_1
      value: 26.466
    - type: mrr_at_10
      value: 34.171
    - type: mrr_at_100
      value: 35.059000000000005
    - type: mrr_at_1000
      value: 35.137
    - type: mrr_at_3
      value: 31.855
    - type: mrr_at_5
      value: 33.093
    - type: ndcg_at_1
      value: 26.466
    - type: ndcg_at_10
      value: 34.097
    - type: ndcg_at_100
      value: 39.612
    - type: ndcg_at_1000
      value: 42.819
    - type: ndcg_at_3
      value: 29.918
    - type: ndcg_at_5
      value: 31.683
    - type: precision_at_1
      value: 26.466
    - type: precision_at_10
      value: 6.422999999999999
    - type: precision_at_100
      value: 1.15
    - type: precision_at_1000
      value: 0.17700000000000002
    - type: precision_at_3
      value: 13.972000000000001
    - type: precision_at_5
      value: 10.129000000000001
    - type: recall_at_1
      value: 21.508
    - type: recall_at_10
      value: 43.699
    - type: recall_at_100
      value: 68.404
    - type: recall_at_1000
      value: 89.687
    - type: recall_at_3
      value: 31.773
    - type: recall_at_5
      value: 36.687
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: None
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 16.865
    - type: map_at_10
      value: 23.164
    - type: map_at_100
      value: 24.15
    - type: map_at_1000
      value: 24.288
    - type: map_at_3
      value: 20.97
    - type: map_at_5
      value: 22.277
    - type: mrr_at_1
      value: 21.401
    - type: mrr_at_10
      value: 27.614
    - type: mrr_at_100
      value: 28.395
    - type: mrr_at_1000
      value: 28.469
    - type: mrr_at_3
      value: 25.594
    - type: mrr_at_5
      value: 26.735
    - type: ndcg_at_1
      value: 21.401
    - type: ndcg_at_10
      value: 27.343
    - type: ndcg_at_100
      value: 31.726
    - type: ndcg_at_1000
      value: 34.586
    - type: ndcg_at_3
      value: 23.723
    - type: ndcg_at_5
      value: 25.524
    - type: precision_at_1
      value: 21.401
    - type: precision_at_10
      value: 5.236
    - type: precision_at_100
      value: 0.9650000000000001
    - type: precision_at_1000
      value: 0.146
    - type: precision_at_3
      value: 11.444
    - type: precision_at_5
      value: 8.497
    - type: recall_at_1
      value: 16.865
    - type: recall_at_10
      value: 35.209
    - type: recall_at_100
      value: 54.371
    - type: recall_at_1000
      value: 73.651
    - type: recall_at_3
      value: 24.943
    - type: recall_at_5
      value: 29.634
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: None
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.424000000000003
    - type: map_at_10
      value: 34.318
    - type: map_at_100
      value: 35.461999999999996
    - type: map_at_1000
      value: 35.551
    - type: map_at_3
      value: 31.694
    - type: map_at_5
      value: 33.111000000000004
    - type: mrr_at_1
      value: 29.215999999999998
    - type: mrr_at_10
      value: 37.333
    - type: mrr_at_100
      value: 38.223
    - type: mrr_at_1000
      value: 38.282
    - type: mrr_at_3
      value: 35.004999999999995
    - type: mrr_at_5
      value: 36.272
    - type: ndcg_at_1
      value: 29.215999999999998
    - type: ndcg_at_10
      value: 39.309
    - type: ndcg_at_100
      value: 44.718999999999994
    - type: ndcg_at_1000
      value: 46.877
    - type: ndcg_at_3
      value: 34.449999999999996
    - type: ndcg_at_5
      value: 36.675999999999995
    - type: precision_at_1
      value: 29.215999999999998
    - type: precision_at_10
      value: 6.483
    - type: precision_at_100
      value: 1.0330000000000001
    - type: precision_at_1000
      value: 0.128
    - type: precision_at_3
      value: 15.298
    - type: precision_at_5
      value: 10.734
    - type: recall_at_1
      value: 25.424000000000003
    - type: recall_at_10
      value: 51.464
    - type: recall_at_100
      value: 75.87
    - type: recall_at_1000
      value: 91.77300000000001
    - type: recall_at_3
      value: 38.396
    - type: recall_at_5
      value: 43.759
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: None
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 14.674000000000001
    - type: map_at_10
      value: 18.984
    - type: map_at_100
      value: 19.867
    - type: map_at_1000
      value: 19.975
    - type: map_at_3
      value: 17.488999999999997
    - type: map_at_5
      value: 18.412
    - type: mrr_at_1
      value: 15.818999999999999
    - type: mrr_at_10
      value: 20.472
    - type: mrr_at_100
      value: 21.342
    - type: mrr_at_1000
      value: 21.431
    - type: mrr_at_3
      value: 18.908
    - type: mrr_at_5
      value: 19.811999999999998
    - type: ndcg_at_1
      value: 15.818999999999999
    - type: ndcg_at_10
      value: 21.823
    - type: ndcg_at_100
      value: 27.0
    - type: ndcg_at_1000
      value: 30.064999999999998
    - type: ndcg_at_3
      value: 18.776
    - type: ndcg_at_5
      value: 20.395
    - type: precision_at_1
      value: 15.818999999999999
    - type: precision_at_10
      value: 3.367
    - type: precision_at_100
      value: 0.649
    - type: precision_at_1000
      value: 0.095
    - type: precision_at_3
      value: 7.797
    - type: precision_at_5
      value: 5.582
    - type: recall_at_1
      value: 14.674000000000001
    - type: recall_at_10
      value: 29.087000000000003
    - type: recall_at_100
      value: 54.52
    - type: recall_at_1000
      value: 78.27
    - type: recall_at_3
      value: 21.075
    - type: recall_at_5
      value: 24.92
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: None
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 8.123
    - type: map_at_10
      value: 13.483
    - type: map_at_100
      value: 14.457999999999998
    - type: map_at_1000
      value: 14.579
    - type: map_at_3
      value: 11.271
    - type: map_at_5
      value: 12.418
    - type: mrr_at_1
      value: 10.323
    - type: mrr_at_10
      value: 16.244
    - type: mrr_at_100
      value: 17.186
    - type: mrr_at_1000
      value: 17.27
    - type: mrr_at_3
      value: 13.91
    - type: mrr_at_5
      value: 15.116
    - type: ndcg_at_1
      value: 10.323
    - type: ndcg_at_10
      value: 17.366999999999997
    - type: ndcg_at_100
      value: 22.553
    - type: ndcg_at_1000
      value: 25.817
    - type: ndcg_at_3
      value: 12.895000000000001
    - type: ndcg_at_5
      value: 14.856
    - type: precision_at_1
      value: 10.323
    - type: precision_at_10
      value: 3.5069999999999997
    - type: precision_at_100
      value: 0.711
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 6.3020000000000005
    - type: precision_at_5
      value: 5.0
    - type: recall_at_1
      value: 8.123
    - type: recall_at_10
      value: 26.889000000000003
    - type: recall_at_100
      value: 50.397999999999996
    - type: recall_at_1000
      value: 74.244
    - type: recall_at_3
      value: 14.691
    - type: recall_at_5
      value: 19.503
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: None
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.607000000000003
    - type: map_at_10
      value: 25.596000000000004
    - type: map_at_100
      value: 26.984
    - type: map_at_1000
      value: 27.125
    - type: map_at_3
      value: 22.917
    - type: map_at_5
      value: 24.201
    - type: mrr_at_1
      value: 22.907
    - type: mrr_at_10
      value: 30.384
    - type: mrr_at_100
      value: 31.432
    - type: mrr_at_1000
      value: 31.5
    - type: mrr_at_3
      value: 27.703
    - type: mrr_at_5
      value: 29.137
    - type: ndcg_at_1
      value: 22.907
    - type: ndcg_at_10
      value: 30.824
    - type: ndcg_at_100
      value: 37.265
    - type: ndcg_at_1000
      value: 40.191
    - type: ndcg_at_3
      value: 25.913000000000004
    - type: ndcg_at_5
      value: 27.849
    - type: precision_at_1
      value: 22.907
    - type: precision_at_10
      value: 5.9479999999999995
    - type: precision_at_100
      value: 1.094
    - type: precision_at_1000
      value: 0.155
    - type: precision_at_3
      value: 12.384
    - type: precision_at_5
      value: 9.009
    - type: recall_at_1
      value: 18.607000000000003
    - type: recall_at_10
      value: 42.082
    - type: recall_at_100
      value: 70.018
    - type: recall_at_1000
      value: 90.003
    - type: recall_at_3
      value: 27.932000000000002
    - type: recall_at_5
      value: 32.975
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: None
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 14.52
    - type: map_at_10
      value: 21.61
    - type: map_at_100
      value: 22.827
    - type: map_at_1000
      value: 22.964000000000002
    - type: map_at_3
      value: 19.500999999999998
    - type: map_at_5
      value: 20.798
    - type: mrr_at_1
      value: 17.694
    - type: mrr_at_10
      value: 25.161
    - type: mrr_at_100
      value: 26.180999999999997
    - type: mrr_at_1000
      value: 26.269
    - type: mrr_at_3
      value: 23.116
    - type: mrr_at_5
      value: 24.412
    - type: ndcg_at_1
      value: 17.694
    - type: ndcg_at_10
      value: 25.924000000000003
    - type: ndcg_at_100
      value: 31.615
    - type: ndcg_at_1000
      value: 34.955000000000005
    - type: ndcg_at_3
      value: 22.161
    - type: ndcg_at_5
      value: 24.16
    - type: precision_at_1
      value: 17.694
    - type: precision_at_10
      value: 4.874
    - type: precision_at_100
      value: 0.91
    - type: precision_at_1000
      value: 0.13799999999999998
    - type: precision_at_3
      value: 10.731
    - type: precision_at_5
      value: 8.014000000000001
    - type: recall_at_1
      value: 14.52
    - type: recall_at_10
      value: 35.369
    - type: recall_at_100
      value: 60.0
    - type: recall_at_1000
      value: 83.66799999999999
    - type: recall_at_3
      value: 25.058999999999997
    - type: recall_at_5
      value: 30.131999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 15.35675
    - type: map_at_10
      value: 21.087750000000007
    - type: map_at_100
      value: 22.12925
    - type: map_at_1000
      value: 22.262
    - type: map_at_3
      value: 19.156249999999996
    - type: map_at_5
      value: 20.202916666666663
    - type: mrr_at_1
      value: 18.301583333333333
    - type: mrr_at_10
      value: 24.283083333333334
    - type: mrr_at_100
      value: 25.176583333333337
    - type: mrr_at_1000
      value: 25.262083333333337
    - type: mrr_at_3
      value: 22.38533333333333
    - type: mrr_at_5
      value: 23.408
    - type: ndcg_at_1
      value: 18.301583333333333
    - type: ndcg_at_10
      value: 24.931416666666667
    - type: ndcg_at_100
      value: 30.107249999999997
    - type: ndcg_at_1000
      value: 33.292500000000004
    - type: ndcg_at_3
      value: 21.380833333333335
    - type: ndcg_at_5
      value: 22.965416666666663
    - type: precision_at_1
      value: 18.301583333333333
    - type: precision_at_10
      value: 4.475583333333334
    - type: precision_at_100
      value: 0.84875
    - type: precision_at_1000
      value: 0.13066666666666668
    - type: precision_at_3
      value: 9.858500000000001
    - type: precision_at_5
      value: 7.125333333333334
    - type: recall_at_1
      value: 15.35675
    - type: recall_at_10
      value: 33.385666666666665
    - type: recall_at_100
      value: 57.03541666666667
    - type: recall_at_1000
      value: 80.00874999999999
    - type: recall_at_3
      value: 23.440833333333337
    - type: recall_at_5
      value: 27.48841666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: None
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 13.023000000000001
    - type: map_at_10
      value: 17.116999999999997
    - type: map_at_100
      value: 18.016
    - type: map_at_1000
      value: 18.124000000000002
    - type: map_at_3
      value: 15.654000000000002
    - type: map_at_5
      value: 16.494
    - type: mrr_at_1
      value: 14.877
    - type: mrr_at_10
      value: 19.061
    - type: mrr_at_100
      value: 19.933
    - type: mrr_at_1000
      value: 20.027
    - type: mrr_at_3
      value: 17.740000000000002
    - type: mrr_at_5
      value: 18.384
    - type: ndcg_at_1
      value: 14.877
    - type: ndcg_at_10
      value: 19.991999999999997
    - type: ndcg_at_100
      value: 24.836
    - type: ndcg_at_1000
      value: 27.922000000000004
    - type: ndcg_at_3
      value: 17.221
    - type: ndcg_at_5
      value: 18.496000000000002
    - type: precision_at_1
      value: 14.877
    - type: precision_at_10
      value: 3.298
    - type: precision_at_100
      value: 0.629
    - type: precision_at_1000
      value: 0.098
    - type: precision_at_3
      value: 7.617999999999999
    - type: precision_at_5
      value: 5.428999999999999
    - type: recall_at_1
      value: 13.023000000000001
    - type: recall_at_10
      value: 27.064
    - type: recall_at_100
      value: 49.971
    - type: recall_at_1000
      value: 73.195
    - type: recall_at_3
      value: 19.273
    - type: recall_at_5
      value: 22.465
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: None
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.86
    - type: map_at_10
      value: 12.806999999999999
    - type: map_at_100
      value: 13.55
    - type: map_at_1000
      value: 13.684
    - type: map_at_3
      value: 11.368
    - type: map_at_5
      value: 12.106
    - type: mrr_at_1
      value: 10.943
    - type: mrr_at_10
      value: 15.397
    - type: mrr_at_100
      value: 16.139
    - type: mrr_at_1000
      value: 16.242
    - type: mrr_at_3
      value: 13.805
    - type: mrr_at_5
      value: 14.601
    - type: ndcg_at_1
      value: 10.943
    - type: ndcg_at_10
      value: 15.693999999999999
    - type: ndcg_at_100
      value: 19.869
    - type: ndcg_at_1000
      value: 23.579
    - type: ndcg_at_3
      value: 12.920000000000002
    - type: ndcg_at_5
      value: 14.054
    - type: precision_at_1
      value: 10.943
    - type: precision_at_10
      value: 2.97
    - type: precision_at_100
      value: 0.609
    - type: precision_at_1000
      value: 0.11100000000000002
    - type: precision_at_3
      value: 6.148
    - type: precision_at_5
      value: 4.529
    - type: recall_at_1
      value: 8.86
    - type: recall_at_10
      value: 22.041
    - type: recall_at_100
      value: 41.528
    - type: recall_at_1000
      value: 68.917
    - type: recall_at_3
      value: 14.257
    - type: recall_at_5
      value: 17.191000000000003
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: None
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 14.508
    - type: map_at_10
      value: 19.814999999999998
    - type: map_at_100
      value: 20.761
    - type: map_at_1000
      value: 20.899
    - type: map_at_3
      value: 17.959
    - type: map_at_5
      value: 18.877
    - type: mrr_at_1
      value: 17.444000000000003
    - type: mrr_at_10
      value: 23.067
    - type: mrr_at_100
      value: 23.906
    - type: mrr_at_1000
      value: 24.015
    - type: mrr_at_3
      value: 21.191
    - type: mrr_at_5
      value: 22.124
    - type: ndcg_at_1
      value: 17.444000000000003
    - type: ndcg_at_10
      value: 23.519000000000002
    - type: ndcg_at_100
      value: 28.546
    - type: ndcg_at_1000
      value: 32.243
    - type: ndcg_at_3
      value: 19.958000000000002
    - type: ndcg_at_5
      value: 21.391
    - type: precision_at_1
      value: 17.444000000000003
    - type: precision_at_10
      value: 4.104
    - type: precision_at_100
      value: 0.758
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 9.142
    - type: precision_at_5
      value: 6.474
    - type: recall_at_1
      value: 14.508
    - type: recall_at_10
      value: 31.788
    - type: recall_at_100
      value: 55.047999999999995
    - type: recall_at_1000
      value: 82.155
    - type: recall_at_3
      value: 21.857
    - type: recall_at_5
      value: 25.549
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: None
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 16.733
    - type: map_at_10
      value: 21.721
    - type: map_at_100
      value: 22.986
    - type: map_at_1000
      value: 23.198
    - type: map_at_3
      value: 20.229
    - type: map_at_5
      value: 21.066
    - type: mrr_at_1
      value: 19.96
    - type: mrr_at_10
      value: 25.683
    - type: mrr_at_100
      value: 26.662000000000003
    - type: mrr_at_1000
      value: 26.749000000000002
    - type: mrr_at_3
      value: 24.209
    - type: mrr_at_5
      value: 25.049
    - type: ndcg_at_1
      value: 19.96
    - type: ndcg_at_10
      value: 25.413999999999998
    - type: ndcg_at_100
      value: 30.916
    - type: ndcg_at_1000
      value: 34.678
    - type: ndcg_at_3
      value: 23.138
    - type: ndcg_at_5
      value: 24.169
    - type: precision_at_1
      value: 19.96
    - type: precision_at_10
      value: 4.743
    - type: precision_at_100
      value: 1.126
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 10.935
    - type: precision_at_5
      value: 7.707999999999999
    - type: recall_at_1
      value: 16.733
    - type: recall_at_10
      value: 31.512
    - type: recall_at_100
      value: 57.079
    - type: recall_at_1000
      value: 82.661
    - type: recall_at_3
      value: 24.252000000000002
    - type: recall_at_5
      value: 27.317000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: None
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 11.436
    - type: map_at_10
      value: 15.35
    - type: map_at_100
      value: 16.211000000000002
    - type: map_at_1000
      value: 16.311999999999998
    - type: map_at_3
      value: 14.27
    - type: map_at_5
      value: 14.735999999999999
    - type: mrr_at_1
      value: 12.568999999999999
    - type: mrr_at_10
      value: 16.81
    - type: mrr_at_100
      value: 17.660999999999998
    - type: mrr_at_1000
      value: 17.754
    - type: mrr_at_3
      value: 15.588
    - type: mrr_at_5
      value: 16.161
    - type: ndcg_at_1
      value: 12.568999999999999
    - type: ndcg_at_10
      value: 17.871000000000002
    - type: ndcg_at_100
      value: 22.63
    - type: ndcg_at_1000
      value: 25.778000000000002
    - type: ndcg_at_3
      value: 15.497
    - type: ndcg_at_5
      value: 16.332
    - type: precision_at_1
      value: 12.568999999999999
    - type: precision_at_10
      value: 2.754
    - type: precision_at_100
      value: 0.551
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_3
      value: 6.531000000000001
    - type: precision_at_5
      value: 4.399
    - type: recall_at_1
      value: 11.436
    - type: recall_at_10
      value: 24.424
    - type: recall_at_100
      value: 47.217999999999996
    - type: recall_at_1000
      value: 71.881
    - type: recall_at_3
      value: 17.782
    - type: recall_at_5
      value: 19.729
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: None
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 6.822
    - type: map_at_10
      value: 12.872
    - type: map_at_100
      value: 14.504
    - type: map_at_1000
      value: 14.712
    - type: map_at_3
      value: 10.357
    - type: map_at_5
      value: 11.700000000000001
    - type: mrr_at_1
      value: 15.895999999999999
    - type: mrr_at_10
      value: 26.407999999999998
    - type: mrr_at_100
      value: 27.528999999999996
    - type: mrr_at_1000
      value: 27.586
    - type: mrr_at_3
      value: 22.714000000000002
    - type: mrr_at_5
      value: 24.762999999999998
    - type: ndcg_at_1
      value: 15.895999999999999
    - type: ndcg_at_10
      value: 19.643
    - type: ndcg_at_100
      value: 26.863999999999997
    - type: ndcg_at_1000
      value: 30.804
    - type: ndcg_at_3
      value: 14.914
    - type: ndcg_at_5
      value: 16.723
    - type: precision_at_1
      value: 15.895999999999999
    - type: precision_at_10
      value: 6.612
    - type: precision_at_100
      value: 1.434
    - type: precision_at_1000
      value: 0.216
    - type: precision_at_3
      value: 11.488
    - type: precision_at_5
      value: 9.354999999999999
    - type: recall_at_1
      value: 6.822
    - type: recall_at_10
      value: 25.478
    - type: recall_at_100
      value: 50.94
    - type: recall_at_1000
      value: 73.264
    - type: recall_at_3
      value: 14.228
    - type: recall_at_5
      value: 18.91
  - 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: 9.225999999999999
    - type: map_at_100
      value: 12.692
    - type: map_at_1000
      value: 13.65
    - type: map_at_3
      value: 6.883
    - type: map_at_5
      value: 7.904
    - type: mrr_at_1
      value: 34.0
    - type: mrr_at_10
      value: 45.83
    - type: mrr_at_100
      value: 46.608
    - type: mrr_at_1000
      value: 46.635
    - type: mrr_at_3
      value: 42.583
    - type: mrr_at_5
      value: 44.721
    - type: ndcg_at_1
      value: 24.75
    - type: ndcg_at_10
      value: 21.092
    - type: ndcg_at_100
      value: 25.288
    - type: ndcg_at_1000
      value: 32.550000000000004
    - type: ndcg_at_3
      value: 22.808999999999997
    - type: ndcg_at_5
      value: 21.931
    - type: precision_at_1
      value: 34.0
    - type: precision_at_10
      value: 18.525
    - type: precision_at_100
      value: 6.265
    - type: precision_at_1000
      value: 1.395
    - type: precision_at_3
      value: 27.500000000000004
    - type: precision_at_5
      value: 23.799999999999997
    - type: recall_at_1
      value: 4.601999999999999
    - type: recall_at_10
      value: 13.578000000000001
    - type: recall_at_100
      value: 32.438
    - type: recall_at_1000
      value: 57.067
    - type: recall_at_3
      value: 8.013
    - type: recall_at_5
      value: 10.057
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: None
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 39.0
    - type: f1
      value: 35.038106148143335
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: None
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 16.577
    - type: map_at_10
      value: 25.397
    - type: map_at_100
      value: 26.493
    - type: map_at_1000
      value: 26.56
    - type: map_at_3
      value: 22.523
    - type: map_at_5
      value: 24.102
    - type: mrr_at_1
      value: 17.717
    - type: mrr_at_10
      value: 26.999000000000002
    - type: mrr_at_100
      value: 28.084999999999997
    - type: mrr_at_1000
      value: 28.144999999999996
    - type: mrr_at_3
      value: 24.01
    - type: mrr_at_5
      value: 25.669999999999998
    - type: ndcg_at_1
      value: 17.717
    - type: ndcg_at_10
      value: 30.836999999999996
    - type: ndcg_at_100
      value: 36.278
    - type: ndcg_at_1000
      value: 38.139
    - type: ndcg_at_3
      value: 24.868000000000002
    - type: ndcg_at_5
      value: 27.701999999999998
    - type: precision_at_1
      value: 17.717
    - type: precision_at_10
      value: 5.0569999999999995
    - type: precision_at_100
      value: 0.791
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 10.850999999999999
    - type: precision_at_5
      value: 8.004999999999999
    - type: recall_at_1
      value: 16.577
    - type: recall_at_10
      value: 46.451
    - type: recall_at_100
      value: 71.61800000000001
    - type: recall_at_1000
      value: 85.902
    - type: recall_at_3
      value: 30.130000000000003
    - type: recall_at_5
      value: 36.902
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: None
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 7.0680000000000005
    - type: map_at_10
      value: 12.424
    - type: map_at_100
      value: 13.750000000000002
    - type: map_at_1000
      value: 13.963999999999999
    - type: map_at_3
      value: 10.41
    - type: map_at_5
      value: 11.459999999999999
    - type: mrr_at_1
      value: 14.506
    - type: mrr_at_10
      value: 21.644
    - type: mrr_at_100
      value: 22.708000000000002
    - type: mrr_at_1000
      value: 22.811
    - type: mrr_at_3
      value: 19.084
    - type: mrr_at_5
      value: 20.543
    - type: ndcg_at_1
      value: 14.506
    - type: ndcg_at_10
      value: 17.485
    - type: ndcg_at_100
      value: 23.565
    - type: ndcg_at_1000
      value: 28.177000000000003
    - type: ndcg_at_3
      value: 14.423
    - type: ndcg_at_5
      value: 15.536
    - type: precision_at_1
      value: 14.506
    - type: precision_at_10
      value: 5.122999999999999
    - type: precision_at_100
      value: 1.13
    - type: precision_at_1000
      value: 0.193
    - type: precision_at_3
      value: 9.722
    - type: precision_at_5
      value: 7.623
    - type: recall_at_1
      value: 7.0680000000000005
    - type: recall_at_10
      value: 23.423
    - type: recall_at_100
      value: 46.682
    - type: recall_at_1000
      value: 75.22999999999999
    - type: recall_at_3
      value: 13.544999999999998
    - type: recall_at_5
      value: 17.448
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: None
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 21.837
    - type: map_at_10
      value: 30.614
    - type: map_at_100
      value: 31.6
    - type: map_at_1000
      value: 31.71
    - type: map_at_3
      value: 28.219
    - type: map_at_5
      value: 29.598000000000003
    - type: mrr_at_1
      value: 43.673
    - type: mrr_at_10
      value: 51.627
    - type: mrr_at_100
      value: 52.323
    - type: mrr_at_1000
      value: 52.364
    - type: mrr_at_3
      value: 49.527
    - type: mrr_at_5
      value: 50.76500000000001
    - type: ndcg_at_1
      value: 43.673
    - type: ndcg_at_10
      value: 38.696000000000005
    - type: ndcg_at_100
      value: 43.124
    - type: ndcg_at_1000
      value: 45.552
    - type: ndcg_at_3
      value: 34.338
    - type: ndcg_at_5
      value: 36.553000000000004
    - type: precision_at_1
      value: 43.673
    - type: precision_at_10
      value: 8.432
    - type: precision_at_100
      value: 1.198
    - type: precision_at_1000
      value: 0.152
    - type: precision_at_3
      value: 21.58
    - type: precision_at_5
      value: 14.706
    - type: recall_at_1
      value: 21.837
    - type: recall_at_10
      value: 42.161
    - type: recall_at_100
      value: 59.899
    - type: recall_at_1000
      value: 76.036
    - type: recall_at_3
      value: 32.37
    - type: recall_at_5
      value: 36.766
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: None
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 65.0232
    - type: ap
      value: 59.81346113056583
    - type: f1
      value: 64.78827292080608
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: None
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 6.614000000000001
    - type: map_at_10
      value: 11.733
    - type: map_at_100
      value: 12.757
    - type: map_at_1000
      value: 12.873999999999999
    - type: map_at_3
      value: 9.783999999999999
    - type: map_at_5
      value: 10.807
    - type: mrr_at_1
      value: 6.834
    - type: mrr_at_10
      value: 12.074
    - type: mrr_at_100
      value: 13.099
    - type: mrr_at_1000
      value: 13.211
    - type: mrr_at_3
      value: 10.098
    - type: mrr_at_5
      value: 11.132
    - type: ndcg_at_1
      value: 6.834
    - type: ndcg_at_10
      value: 15.046000000000001
    - type: ndcg_at_100
      value: 20.657
    - type: ndcg_at_1000
      value: 24.112000000000002
    - type: ndcg_at_3
      value: 10.95
    - type: ndcg_at_5
      value: 12.796
    - type: precision_at_1
      value: 6.834
    - type: precision_at_10
      value: 2.633
    - type: precision_at_100
      value: 0.555
    - type: precision_at_1000
      value: 0.08499999999999999
    - type: precision_at_3
      value: 4.842
    - type: precision_at_5
      value: 3.8249999999999997
    - type: recall_at_1
      value: 6.614000000000001
    - type: recall_at_10
      value: 25.39
    - type: recall_at_100
      value: 52.793
    - type: recall_at_1000
      value: 80.415
    - type: recall_at_3
      value: 14.033000000000001
    - type: recall_at_5
      value: 18.496000000000002
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: None
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.58139534883719
    - type: f1
      value: 84.72133199480218
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: None
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 56.2608299133607
    - type: f1
      value: 36.74698315617003
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: None
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.993947545393404
    - type: f1
      value: 59.68762807193991
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: None
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.49361129791525
    - type: f1
      value: 67.16568787114376
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: None
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.675655693797378
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: None
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.87954369022046
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: None
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.47254787311633
    - type: mrr
      value: 31.476216991631862
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: None
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 2.703
    - type: map_at_10
      value: 6.99
    - type: map_at_100
      value: 9.191
    - type: map_at_1000
      value: 10.385
    - type: map_at_3
      value: 5.015
    - type: map_at_5
      value: 5.904
    - type: mrr_at_1
      value: 30.031000000000002
    - type: mrr_at_10
      value: 40.001
    - type: mrr_at_100
      value: 40.724
    - type: mrr_at_1000
      value: 40.778
    - type: mrr_at_3
      value: 37.358000000000004
    - type: mrr_at_5
      value: 38.426
    - type: ndcg_at_1
      value: 28.483000000000004
    - type: ndcg_at_10
      value: 23.229
    - type: ndcg_at_100
      value: 22.115000000000002
    - type: ndcg_at_1000
      value: 31.263
    - type: ndcg_at_3
      value: 26.432
    - type: ndcg_at_5
      value: 25.074999999999996
    - type: precision_at_1
      value: 30.031000000000002
    - type: precision_at_10
      value: 17.957
    - type: precision_at_100
      value: 6.3
    - type: precision_at_1000
      value: 1.909
    - type: precision_at_3
      value: 26.006
    - type: precision_at_5
      value: 22.786
    - type: recall_at_1
      value: 2.703
    - type: recall_at_10
      value: 11.333
    - type: recall_at_100
      value: 24.629
    - type: recall_at_1000
      value: 57.162
    - type: recall_at_3
      value: 6.148
    - type: recall_at_5
      value: 7.902000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: None
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 10.904
    - type: map_at_10
      value: 18.551000000000002
    - type: map_at_100
      value: 19.913
    - type: map_at_1000
      value: 20.008
    - type: map_at_3
      value: 15.8
    - type: map_at_5
      value: 17.261000000000003
    - type: mrr_at_1
      value: 12.457
    - type: mrr_at_10
      value: 20.319000000000003
    - type: mrr_at_100
      value: 21.532999999999998
    - type: mrr_at_1000
      value: 21.61
    - type: mrr_at_3
      value: 17.449
    - type: mrr_at_5
      value: 19.023
    - type: ndcg_at_1
      value: 12.457
    - type: ndcg_at_10
      value: 23.488999999999997
    - type: ndcg_at_100
      value: 30.109
    - type: ndcg_at_1000
      value: 32.725
    - type: ndcg_at_3
      value: 17.73
    - type: ndcg_at_5
      value: 20.387
    - type: precision_at_1
      value: 12.457
    - type: precision_at_10
      value: 4.3709999999999996
    - type: precision_at_100
      value: 0.8109999999999999
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 8.333
    - type: precision_at_5
      value: 6.489000000000001
    - type: recall_at_1
      value: 10.904
    - type: recall_at_10
      value: 37.143
    - type: recall_at_100
      value: 67.432
    - type: recall_at_1000
      value: 87.59400000000001
    - type: recall_at_3
      value: 21.734
    - type: recall_at_5
      value: 27.927999999999997
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: None
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 63.499
    - type: map_at_10
      value: 77.088
    - type: map_at_100
      value: 77.91
    - type: map_at_1000
      value: 77.935
    - type: map_at_3
      value: 73.88900000000001
    - type: map_at_5
      value: 75.797
    - type: mrr_at_1
      value: 73.2
    - type: mrr_at_10
      value: 80.927
    - type: mrr_at_100
      value: 81.146
    - type: mrr_at_1000
      value: 81.148
    - type: mrr_at_3
      value: 79.427
    - type: mrr_at_5
      value: 80.363
    - type: ndcg_at_1
      value: 73.22999999999999
    - type: ndcg_at_10
      value: 81.926
    - type: ndcg_at_100
      value: 83.929
    - type: ndcg_at_1000
      value: 84.127
    - type: ndcg_at_3
      value: 78.071
    - type: ndcg_at_5
      value: 80.015
    - type: precision_at_1
      value: 73.22999999999999
    - type: precision_at_10
      value: 12.639
    - type: precision_at_100
      value: 1.5110000000000001
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 34.217
    - type: precision_at_5
      value: 22.722
    - type: recall_at_1
      value: 63.499
    - type: recall_at_10
      value: 91.646
    - type: recall_at_100
      value: 98.92999999999999
    - type: recall_at_1000
      value: 99.914
    - type: recall_at_3
      value: 80.703
    - type: recall_at_5
      value: 86.048
    - type: map_at_1
      value: 3.773
    - type: map_at_10
      value: 9.305
    - type: map_at_100
      value: 11.469
    - type: map_at_1000
      value: 11.828
    - type: map_at_3
      value: 6.675000000000001
    - type: map_at_5
      value: 7.965
    - type: mrr_at_1
      value: 18.6
    - type: mrr_at_10
      value: 28.392
    - type: mrr_at_100
      value: 29.664
    - type: mrr_at_1000
      value: 29.724
    - type: mrr_at_3
      value: 25.183
    - type: mrr_at_5
      value: 26.893
    - type: ndcg_at_1
      value: 18.6
    - type: ndcg_at_10
      value: 16.292
    - type: ndcg_at_100
      value: 25.0
    - type: ndcg_at_1000
      value: 31.136000000000003
    - type: ndcg_at_3
      value: 15.212
    - type: ndcg_at_5
      value: 13.354
    - type: precision_at_1
      value: 18.6
    - type: precision_at_10
      value: 8.57
    - type: precision_at_100
      value: 2.122
    - type: precision_at_1000
      value: 0.359
    - type: precision_at_3
      value: 14.267
    - type: precision_at_5
      value: 11.799999999999999
    - type: recall_at_1
      value: 3.773
    - type: recall_at_10
      value: 17.352999999999998
    - type: recall_at_100
      value: 43.062
    - type: recall_at_1000
      value: 72.775
    - type: recall_at_3
      value: 8.677999999999999
    - type: recall_at_5
      value: 11.958
    - type: map_at_1
      value: 0.186
    - type: map_at_10
      value: 1.304
    - type: map_at_100
      value: 6.688
    - type: map_at_1000
      value: 15.162
    - type: map_at_3
      value: 0.46499999999999997
    - type: map_at_5
      value: 0.7100000000000001
    - type: mrr_at_1
      value: 72.0
    - type: mrr_at_10
      value: 79.51899999999999
    - type: mrr_at_100
      value: 79.673
    - type: mrr_at_1000
      value: 79.673
    - type: mrr_at_3
      value: 77.667
    - type: mrr_at_5
      value: 78.567
    - type: ndcg_at_1
      value: 66.0
    - type: ndcg_at_10
      value: 58.172000000000004
    - type: ndcg_at_100
      value: 41.583999999999996
    - type: ndcg_at_1000
      value: 34.916000000000004
    - type: ndcg_at_3
      value: 62.0
    - type: ndcg_at_5
      value: 60.104
    - type: precision_at_1
      value: 72.0
    - type: precision_at_10
      value: 62.0
    - type: precision_at_100
      value: 43.32
    - type: precision_at_1000
      value: 15.962000000000002
    - type: precision_at_3
      value: 65.333
    - type: precision_at_5
      value: 63.6
    - type: recall_at_1
      value: 0.186
    - type: recall_at_10
      value: 1.525
    - type: recall_at_100
      value: 9.600999999999999
    - type: recall_at_1000
      value: 32.72
    - type: recall_at_3
      value: 0.492
    - type: recall_at_5
      value: 0.782
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: None
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 43.80644854168368
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: None
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 48.708800185514974
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: None
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 77.70369570699015
    - type: cos_sim_spearman
      value: 67.00421728409633
    - type: euclidean_pearson
      value: 71.7303217538682
    - type: euclidean_spearman
      value: 67.00421728409633
    - type: manhattan_pearson
      value: 71.62358736603595
    - type: manhattan_spearman
      value: 66.93696271331966
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: None
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 72.3464707081196
    - type: cos_sim_spearman
      value: 63.91086584602619
    - type: euclidean_pearson
      value: 68.22390430027092
    - type: euclidean_spearman
      value: 63.91086584602619
    - type: manhattan_pearson
      value: 68.14984324829423
    - type: manhattan_spearman
      value: 63.86219497566778
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: None
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 72.80276772789091
    - type: cos_sim_spearman
      value: 73.34700075766551
    - type: euclidean_pearson
      value: 72.88415583236083
    - type: euclidean_spearman
      value: 73.34700075766551
    - type: manhattan_pearson
      value: 72.71141307415924
    - type: manhattan_spearman
      value: 73.10626124984765
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: None
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 74.00122656955553
    - type: cos_sim_spearman
      value: 69.07090069837032
    - type: euclidean_pearson
      value: 71.79931055857548
    - type: euclidean_spearman
      value: 69.07090069837032
    - type: manhattan_pearson
      value: 71.71577354549707
    - type: manhattan_spearman
      value: 69.0177557195104
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: None
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.17450916936498
    - type: cos_sim_spearman
      value: 81.53568053124042
    - type: euclidean_pearson
      value: 81.04779414575466
    - type: euclidean_spearman
      value: 81.53568053124042
    - type: manhattan_pearson
      value: 80.95262960295437
    - type: manhattan_spearman
      value: 81.43365291054681
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: None
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 75.7401837172966
    - type: cos_sim_spearman
      value: 76.13099867057305
    - type: euclidean_pearson
      value: 75.56851096153042
    - type: euclidean_spearman
      value: 76.13099867057305
    - type: manhattan_pearson
      value: 75.4483276223799
    - type: manhattan_spearman
      value: 75.96804558062843
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: None
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 85.0294369233462
    - type: cos_sim_spearman
      value: 85.17543345937065
    - type: euclidean_pearson
      value: 84.55546274084796
    - type: euclidean_spearman
      value: 85.17543345937065
    - type: manhattan_pearson
      value: 84.48053547013386
    - type: manhattan_spearman
      value: 85.1543300887167
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: None
      config: en
      split: test
      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
    metrics:
    - type: cos_sim_pearson
      value: 61.225097153955176
    - type: cos_sim_spearman
      value: 60.16234340521003
    - type: euclidean_pearson
      value: 62.59204214787284
    - type: euclidean_spearman
      value: 60.16234340521003
    - type: manhattan_pearson
      value: 62.17494761193987
    - type: manhattan_spearman
      value: 59.80098747946264
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: None
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.76720129845401
    - type: cos_sim_spearman
      value: 77.01581381977705
    - type: euclidean_pearson
      value: 78.25405293225397
    - type: euclidean_spearman
      value: 77.01581381977705
    - type: manhattan_pearson
      value: 78.1737464440924
    - type: manhattan_spearman
      value: 76.98020258619971
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: None
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 83.38429389881968
    - type: mrr
      value: 94.92898441427853
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: None
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 39.306000000000004
    - type: map_at_10
      value: 49.913000000000004
    - type: map_at_100
      value: 50.965
    - type: map_at_1000
      value: 51.022999999999996
    - type: map_at_3
      value: 47.398
    - type: map_at_5
      value: 48.962
    - type: mrr_at_1
      value: 41.0
    - type: mrr_at_10
      value: 51.147
    - type: mrr_at_100
      value: 52.022
    - type: mrr_at_1000
      value: 52.073
    - type: mrr_at_3
      value: 48.888999999999996
    - type: mrr_at_5
      value: 50.239
    - type: ndcg_at_1
      value: 41.0
    - type: ndcg_at_10
      value: 55.033
    - type: ndcg_at_100
      value: 59.364
    - type: ndcg_at_1000
      value: 60.849
    - type: ndcg_at_3
      value: 50.159
    - type: ndcg_at_5
      value: 52.788999999999994
    - type: precision_at_1
      value: 41.0
    - type: precision_at_10
      value: 7.632999999999999
    - type: precision_at_100
      value: 0.997
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 20.222
    - type: precision_at_5
      value: 13.667000000000002
    - type: recall_at_1
      value: 39.306000000000004
    - type: recall_at_10
      value: 69.45599999999999
    - type: recall_at_100
      value: 88.022
    - type: recall_at_1000
      value: 99.6
    - type: recall_at_3
      value: 56.27799999999999
    - type: recall_at_5
      value: 62.639
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: None
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.73960396039604
    - type: cos_sim_ap
      value: 91.77061379171414
    - type: cos_sim_f1
      value: 86.49746192893402
    - type: cos_sim_precision
      value: 87.83505154639175
    - type: cos_sim_recall
      value: 85.2
    - type: dot_accuracy
      value: 99.73960396039604
    - type: dot_ap
      value: 91.77061379171414
    - type: dot_f1
      value: 86.49746192893402
    - type: dot_precision
      value: 87.83505154639175
    - type: dot_recall
      value: 85.2
    - type: euclidean_accuracy
      value: 99.73960396039604
    - type: euclidean_ap
      value: 91.77061379171414
    - type: euclidean_f1
      value: 86.49746192893402
    - type: euclidean_precision
      value: 87.83505154639175
    - type: euclidean_recall
      value: 85.2
    - type: manhattan_accuracy
      value: 99.73861386138614
    - type: manhattan_ap
      value: 91.73584684604442
    - type: manhattan_f1
      value: 86.41722193746797
    - type: manhattan_precision
      value: 88.64353312302839
    - type: manhattan_recall
      value: 84.3
    - type: max_accuracy
      value: 99.73960396039604
    - type: max_ap
      value: 91.77061379171414
    - type: max_f1
      value: 86.49746192893402
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: None
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 53.7931704300123
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: None
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.48651577951652
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: None
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 41.818447756127505
    - type: mrr
      value: 42.1808155080214
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: None
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.799110359832028
    - type: cos_sim_spearman
      value: 30.826213689865888
    - type: dot_pearson
      value: 29.79911097173556
    - type: dot_spearman
      value: 30.8964325010969
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: None
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 2.6100000000000003
    - type: map_at_10
      value: 10.317
    - type: map_at_100
      value: 16.651
    - type: map_at_1000
      value: 18.4
    - type: map_at_3
      value: 4.952999999999999
    - type: map_at_5
      value: 7.037
    - type: mrr_at_1
      value: 34.694
    - type: mrr_at_10
      value: 51.351
    - type: mrr_at_100
      value: 51.912000000000006
    - type: mrr_at_1000
      value: 51.912000000000006
    - type: mrr_at_3
      value: 46.599000000000004
    - type: mrr_at_5
      value: 49.762
    - type: ndcg_at_1
      value: 31.633
    - type: ndcg_at_10
      value: 27.601
    - type: ndcg_at_100
      value: 39.080999999999996
    - type: ndcg_at_1000
      value: 50.308
    - type: ndcg_at_3
      value: 30.020000000000003
    - type: ndcg_at_5
      value: 29.465999999999998
    - type: precision_at_1
      value: 34.694
    - type: precision_at_10
      value: 26.122
    - type: precision_at_100
      value: 8.530999999999999
    - type: precision_at_1000
      value: 1.5650000000000002
    - type: precision_at_3
      value: 31.973000000000003
    - type: precision_at_5
      value: 31.019999999999996
    - type: recall_at_1
      value: 2.6100000000000003
    - type: recall_at_10
      value: 17.166
    - type: recall_at_100
      value: 50.480999999999995
    - type: recall_at_1000
      value: 84.87599999999999
    - type: recall_at_3
      value: 6.026
    - type: recall_at_5
      value: 10.165000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: None
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 66.8218
    - type: ap
      value: 11.906071313412117
    - type: f1
      value: 50.99103419180737
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: None
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 50.1188455008489
    - type: f1
      value: 50.19144196024773
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: None
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.550995025713995
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: None
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 79.29307981164689
    - type: cos_sim_ap
      value: 48.474835734978406
    - type: cos_sim_f1
      value: 48.95389383959706
    - type: cos_sim_precision
      value: 38.674625038261404
    - type: cos_sim_recall
      value: 66.6754617414248
    - type: dot_accuracy
      value: 79.29307981164689
    - type: dot_ap
      value: 48.4748345893063
    - type: dot_f1
      value: 48.95389383959706
    - type: dot_precision
      value: 38.674625038261404
    - type: dot_recall
      value: 66.6754617414248
    - type: euclidean_accuracy
      value: 79.29307981164689
    - type: euclidean_ap
      value: 48.47484295524529
    - type: euclidean_f1
      value: 48.95389383959706
    - type: euclidean_precision
      value: 38.674625038261404
    - type: euclidean_recall
      value: 66.6754617414248
    - type: manhattan_accuracy
      value: 79.34672468260118
    - type: manhattan_ap
      value: 48.423218655778356
    - type: manhattan_f1
      value: 48.93181153058239
    - type: manhattan_precision
      value: 38.81752050766135
    - type: manhattan_recall
      value: 66.17414248021109
    - type: max_accuracy
      value: 79.34672468260118
    - type: max_ap
      value: 48.47484295524529
    - type: max_f1
      value: 48.95389383959706
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: None
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.65541196103544
    - type: cos_sim_ap
      value: 80.9065470343605
    - type: cos_sim_f1
      value: 73.7394283267316
    - type: cos_sim_precision
      value: 68.7196541403392
    - type: cos_sim_recall
      value: 79.55035417308285
    - type: dot_accuracy
      value: 86.65541196103544
    - type: dot_ap
      value: 80.90654522467446
    - type: dot_f1
      value: 73.7394283267316
    - type: dot_precision
      value: 68.7196541403392
    - type: dot_recall
      value: 79.55035417308285
    - type: euclidean_accuracy
      value: 86.65541196103544
    - type: euclidean_ap
      value: 80.90654748736512
    - type: euclidean_f1
      value: 73.7394283267316
    - type: euclidean_precision
      value: 68.7196541403392
    - type: euclidean_recall
      value: 79.55035417308285
    - type: manhattan_accuracy
      value: 86.61272169829627
    - type: manhattan_ap
      value: 80.85801370403492
    - type: manhattan_f1
      value: 73.63878299647558
    - type: manhattan_precision
      value: 69.0916452962613
    - type: manhattan_recall
      value: 78.8266091777025
    - type: max_accuracy
      value: 86.65541196103544
    - type: max_ap
      value: 80.90654748736512
    - type: max_f1
      value: 73.7394283267316
---
