mteb model-index region:us
---
tags:
- mteb
model-index:
- name: bert_1b3_mixlang_newstep3
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.11940298507463
    - type: ap
      value: 32.37756187516329
    - type: f1
      value: 63.92312669545795
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 92.950675
    - type: ap
      value: 89.69186819088316
    - type: f1
      value: 92.94108521905532
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 50.522
    - type: f1
      value: 48.76020527037862
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 14.865
    - type: map_at_10
      value: 26.026
    - type: map_at_100
      value: 27.586
    - type: map_at_1000
      value: 27.622999999999998
    - type: map_at_3
      value: 21.859
    - type: map_at_5
      value: 24.049
    - type: mrr_at_1
      value: 15.504999999999999
    - type: mrr_at_10
      value: 26.265
    - type: mrr_at_100
      value: 27.810000000000002
    - type: mrr_at_1000
      value: 27.847
    - type: mrr_at_3
      value: 22.06
    - type: mrr_at_5
      value: 24.247
    - type: ndcg_at_1
      value: 14.865
    - type: ndcg_at_10
      value: 32.934999999999995
    - type: ndcg_at_100
      value: 40.627
    - type: ndcg_at_1000
      value: 41.524
    - type: ndcg_at_3
      value: 24.153
    - type: ndcg_at_5
      value: 28.133999999999997
    - type: precision_at_1
      value: 14.865
    - type: precision_at_10
      value: 5.541
    - type: precision_at_100
      value: 0.9159999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 10.266
    - type: precision_at_5
      value: 8.108
    - type: recall_at_1
      value: 14.865
    - type: recall_at_10
      value: 55.405
    - type: recall_at_100
      value: 91.607
    - type: recall_at_1000
      value: 98.506
    - type: recall_at_3
      value: 30.797
    - type: recall_at_5
      value: 40.541
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 47.028296913559814
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 38.38123118365735
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 58.9616553564134
    - type: mrr
      value: 72.16033504814668
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 87.00899493452621
    - type: cos_sim_spearman
      value: 83.85673000958819
    - type: euclidean_pearson
      value: 85.65567511199598
    - type: euclidean_spearman
      value: 83.90311660870698
    - type: manhattan_pearson
      value: 85.37147829428248
    - type: manhattan_spearman
      value: 83.74588411039522
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.5909090909091
    - type: f1
      value: 74.476632049175
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 38.981180962194216
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 34.9394829907367
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 31.277
    - type: map_at_10
      value: 42.153
    - type: map_at_100
      value: 43.683
    - type: map_at_1000
      value: 43.817
    - type: map_at_3
      value: 38.454
    - type: map_at_5
      value: 40.721000000000004
    - type: mrr_at_1
      value: 38.913
    - type: mrr_at_10
      value: 48.232
    - type: mrr_at_100
      value: 48.888
    - type: mrr_at_1000
      value: 48.929
    - type: mrr_at_3
      value: 45.279
    - type: mrr_at_5
      value: 47.089
    - type: ndcg_at_1
      value: 38.913
    - type: ndcg_at_10
      value: 48.518
    - type: ndcg_at_100
      value: 53.797
    - type: ndcg_at_1000
      value: 55.754999999999995
    - type: ndcg_at_3
      value: 43.122
    - type: ndcg_at_5
      value: 45.869
    - type: precision_at_1
      value: 38.913
    - type: precision_at_10
      value: 9.413
    - type: precision_at_100
      value: 1.567
    - type: precision_at_1000
      value: 0.20600000000000002
    - type: precision_at_3
      value: 20.791999999999998
    - type: precision_at_5
      value: 15.193000000000001
    - type: recall_at_1
      value: 31.277
    - type: recall_at_10
      value: 60.475
    - type: recall_at_100
      value: 82.675
    - type: recall_at_1000
      value: 95.298
    - type: recall_at_3
      value: 44.388
    - type: recall_at_5
      value: 52.242999999999995
    - type: map_at_1
      value: 25.593
    - type: map_at_10
      value: 35.089999999999996
    - type: map_at_100
      value: 36.269
    - type: map_at_1000
      value: 36.419000000000004
    - type: map_at_3
      value: 32.449
    - type: map_at_5
      value: 33.952
    - type: mrr_at_1
      value: 32.484
    - type: mrr_at_10
      value: 40.725
    - type: mrr_at_100
      value: 41.465999999999994
    - type: mrr_at_1000
      value: 41.521
    - type: mrr_at_3
      value: 38.757999999999996
    - type: mrr_at_5
      value: 39.869
    - type: ndcg_at_1
      value: 32.484
    - type: ndcg_at_10
      value: 40.384
    - type: ndcg_at_100
      value: 44.984
    - type: ndcg_at_1000
      value: 47.528
    - type: ndcg_at_3
      value: 36.77
    - type: ndcg_at_5
      value: 38.505
    - type: precision_at_1
      value: 32.484
    - type: precision_at_10
      value: 7.866
    - type: precision_at_100
      value: 1.2959999999999998
    - type: precision_at_1000
      value: 0.185
    - type: precision_at_3
      value: 18.195
    - type: precision_at_5
      value: 13.032
    - type: recall_at_1
      value: 25.593
    - type: recall_at_10
      value: 49.289
    - type: recall_at_100
      value: 69.84700000000001
    - type: recall_at_1000
      value: 86.329
    - type: recall_at_3
      value: 38.51
    - type: recall_at_5
      value: 43.349
    - type: map_at_1
      value: 35.116
    - type: map_at_10
      value: 45.908
    - type: map_at_100
      value: 46.979
    - type: map_at_1000
      value: 47.046
    - type: map_at_3
      value: 42.724000000000004
    - type: map_at_5
      value: 44.507999999999996
    - type: mrr_at_1
      value: 40.313
    - type: mrr_at_10
      value: 49.195
    - type: mrr_at_100
      value: 49.996
    - type: mrr_at_1000
      value: 50.03300000000001
    - type: mrr_at_3
      value: 46.708
    - type: mrr_at_5
      value: 48.187999999999995
    - type: ndcg_at_1
      value: 40.313
    - type: ndcg_at_10
      value: 51.43600000000001
    - type: ndcg_at_100
      value: 55.873
    - type: ndcg_at_1000
      value: 57.288
    - type: ndcg_at_3
      value: 46.038000000000004
    - type: ndcg_at_5
      value: 48.729
    - type: precision_at_1
      value: 40.313
    - type: precision_at_10
      value: 8.382000000000001
    - type: precision_at_100
      value: 1.145
    - type: precision_at_1000
      value: 0.132
    - type: precision_at_3
      value: 20.480999999999998
    - type: precision_at_5
      value: 14.219000000000001
    - type: recall_at_1
      value: 35.116
    - type: recall_at_10
      value: 64.524
    - type: recall_at_100
      value: 83.859
    - type: recall_at_1000
      value: 93.977
    - type: recall_at_3
      value: 50.102999999999994
    - type: recall_at_5
      value: 56.818000000000005
    - type: map_at_1
      value: 18.488
    - type: map_at_10
      value: 25.667
    - type: map_at_100
      value: 26.541999999999998
    - type: map_at_1000
      value: 26.637
    - type: map_at_3
      value: 23.483
    - type: map_at_5
      value: 24.667
    - type: mrr_at_1
      value: 20.0
    - type: mrr_at_10
      value: 27.178
    - type: mrr_at_100
      value: 27.989000000000004
    - type: mrr_at_1000
      value: 28.07
    - type: mrr_at_3
      value: 25.122
    - type: mrr_at_5
      value: 26.275
    - type: ndcg_at_1
      value: 20.0
    - type: ndcg_at_10
      value: 29.736
    - type: ndcg_at_100
      value: 34.358
    - type: ndcg_at_1000
      value: 37.036
    - type: ndcg_at_3
      value: 25.405
    - type: ndcg_at_5
      value: 27.441
    - type: precision_at_1
      value: 20.0
    - type: precision_at_10
      value: 4.712000000000001
    - type: precision_at_100
      value: 0.751
    - type: precision_at_1000
      value: 0.101
    - type: precision_at_3
      value: 10.885
    - type: precision_at_5
      value: 7.706
    - type: recall_at_1
      value: 18.488
    - type: recall_at_10
      value: 40.83
    - type: recall_at_100
      value: 62.707
    - type: recall_at_1000
      value: 83.41199999999999
    - type: recall_at_3
      value: 29.21
    - type: recall_at_5
      value: 34.009
    - type: map_at_1
      value: 9.532
    - type: map_at_10
      value: 15.193000000000001
    - type: map_at_100
      value: 16.381
    - type: map_at_1000
      value: 16.524
    - type: map_at_3
      value: 13.386000000000001
    - type: map_at_5
      value: 14.261
    - type: mrr_at_1
      value: 11.940000000000001
    - type: mrr_at_10
      value: 18.285
    - type: mrr_at_100
      value: 19.373
    - type: mrr_at_1000
      value: 19.467000000000002
    - type: mrr_at_3
      value: 16.252
    - type: mrr_at_5
      value: 17.26
    - type: ndcg_at_1
      value: 11.940000000000001
    - type: ndcg_at_10
      value: 19.095000000000002
    - type: ndcg_at_100
      value: 25.214
    - type: ndcg_at_1000
      value: 28.619
    - type: ndcg_at_3
      value: 15.482000000000001
    - type: ndcg_at_5
      value: 16.892
    - type: precision_at_1
      value: 11.940000000000001
    - type: precision_at_10
      value: 3.744
    - type: precision_at_100
      value: 0.815
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_3
      value: 7.710999999999999
    - type: precision_at_5
      value: 5.647
    - type: recall_at_1
      value: 9.532
    - type: recall_at_10
      value: 28.026
    - type: recall_at_100
      value: 55.253
    - type: recall_at_1000
      value: 79.86999999999999
    - type: recall_at_3
      value: 18.084
    - type: recall_at_5
      value: 21.553
    - type: map_at_1
      value: 23.416
    - type: map_at_10
      value: 32.649
    - type: map_at_100
      value: 33.983000000000004
    - type: map_at_1000
      value: 34.107
    - type: map_at_3
      value: 29.254
    - type: map_at_5
      value: 31.339
    - type: mrr_at_1
      value: 28.778
    - type: mrr_at_10
      value: 37.513999999999996
    - type: mrr_at_100
      value: 38.458999999999996
    - type: mrr_at_1000
      value: 38.517
    - type: mrr_at_3
      value: 34.585
    - type: mrr_at_5
      value: 36.514
    - type: ndcg_at_1
      value: 28.778
    - type: ndcg_at_10
      value: 38.233
    - type: ndcg_at_100
      value: 44.14
    - type: ndcg_at_1000
      value: 46.583000000000006
    - type: ndcg_at_3
      value: 32.718
    - type: ndcg_at_5
      value: 35.778999999999996
    - type: precision_at_1
      value: 28.778
    - type: precision_at_10
      value: 7.2090000000000005
    - type: precision_at_100
      value: 1.194
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_3
      value: 15.495999999999999
    - type: precision_at_5
      value: 11.781
    - type: recall_at_1
      value: 23.416
    - type: recall_at_10
      value: 50.063
    - type: recall_at_100
      value: 75.4
    - type: recall_at_1000
      value: 91.74799999999999
    - type: recall_at_3
      value: 35.113
    - type: recall_at_5
      value: 42.620999999999995
    - type: map_at_1
      value: 18.891
    - type: map_at_10
      value: 28.000000000000004
    - type: map_at_100
      value: 29.354999999999997
    - type: map_at_1000
      value: 29.453000000000003
    - type: map_at_3
      value: 24.551000000000002
    - type: map_at_5
      value: 26.383000000000003
    - type: mrr_at_1
      value: 23.402
    - type: mrr_at_10
      value: 32.308
    - type: mrr_at_100
      value: 33.242
    - type: mrr_at_1000
      value: 33.294000000000004
    - type: mrr_at_3
      value: 29.262
    - type: mrr_at_5
      value: 30.997000000000003
    - type: ndcg_at_1
      value: 23.402
    - type: ndcg_at_10
      value: 33.932
    - type: ndcg_at_100
      value: 39.925
    - type: ndcg_at_1000
      value: 42.126999999999995
    - type: ndcg_at_3
      value: 27.816999999999997
    - type: ndcg_at_5
      value: 30.554
    - type: precision_at_1
      value: 23.402
    - type: precision_at_10
      value: 6.747
    - type: precision_at_100
      value: 1.147
    - type: precision_at_1000
      value: 0.15
    - type: precision_at_3
      value: 13.469999999999999
    - type: precision_at_5
      value: 10.32
    - type: recall_at_1
      value: 18.891
    - type: recall_at_10
      value: 47.58
    - type: recall_at_100
      value: 73.668
    - type: recall_at_1000
      value: 88.77000000000001
    - type: recall_at_3
      value: 30.726
    - type: recall_at_5
      value: 37.547000000000004
    - type: map_at_1
      value: 20.303499999999996
    - type: map_at_10
      value: 28.263499999999997
    - type: map_at_100
      value: 29.431250000000002
    - type: map_at_1000
      value: 29.555166666666665
    - type: map_at_3
      value: 25.59133333333333
    - type: map_at_5
      value: 27.091500000000003
    - type: mrr_at_1
      value: 24.19725
    - type: mrr_at_10
      value: 31.803750000000004
    - type: mrr_at_100
      value: 32.691916666666664
    - type: mrr_at_1000
      value: 32.760083333333334
    - type: mrr_at_3
      value: 29.447749999999996
    - type: mrr_at_5
      value: 30.79858333333334
    - type: ndcg_at_1
      value: 24.19725
    - type: ndcg_at_10
      value: 33.11925000000001
    - type: ndcg_at_100
      value: 38.384916666666655
    - type: ndcg_at_1000
      value: 40.991499999999995
    - type: ndcg_at_3
      value: 28.5115
    - type: ndcg_at_5
      value: 30.718833333333333
    - type: precision_at_1
      value: 24.19725
    - type: precision_at_10
      value: 6.061666666666666
    - type: precision_at_100
      value: 1.0404166666666665
    - type: precision_at_1000
      value: 0.14583333333333337
    - type: precision_at_3
      value: 13.347083333333334
    - type: precision_at_5
      value: 9.747916666666667
    - type: recall_at_1
      value: 20.303499999999996
    - type: recall_at_10
      value: 43.93183333333334
    - type: recall_at_100
      value: 67.47800000000001
    - type: recall_at_1000
      value: 85.91425000000001
    - type: recall_at_3
      value: 31.160083333333333
    - type: recall_at_5
      value: 36.76633333333333
    - type: map_at_1
      value: 12.666
    - type: map_at_10
      value: 18.448999999999998
    - type: map_at_100
      value: 19.448
    - type: map_at_1000
      value: 19.54
    - type: map_at_3
      value: 16.581000000000003
    - type: map_at_5
      value: 17.485999999999997
    - type: mrr_at_1
      value: 14.11
    - type: mrr_at_10
      value: 19.796
    - type: mrr_at_100
      value: 20.785999999999998
    - type: mrr_at_1000
      value: 20.861
    - type: mrr_at_3
      value: 18.175
    - type: mrr_at_5
      value: 18.926000000000002
    - type: ndcg_at_1
      value: 14.11
    - type: ndcg_at_10
      value: 21.83
    - type: ndcg_at_100
      value: 27.017999999999997
    - type: ndcg_at_1000
      value: 29.520999999999997
    - type: ndcg_at_3
      value: 18.358
    - type: ndcg_at_5
      value: 19.719
    - type: precision_at_1
      value: 14.11
    - type: precision_at_10
      value: 3.819
    - type: precision_at_100
      value: 0.701
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_3
      value: 8.384
    - type: precision_at_5
      value: 5.92
    - type: recall_at_1
      value: 12.666
    - type: recall_at_10
      value: 30.746000000000002
    - type: recall_at_100
      value: 54.675
    - type: recall_at_1000
      value: 73.57900000000001
    - type: recall_at_3
      value: 21.196
    - type: recall_at_5
      value: 24.552
    - type: map_at_1
      value: 12.53
    - type: map_at_10
      value: 17.881
    - type: map_at_100
      value: 18.923000000000002
    - type: map_at_1000
      value: 19.049
    - type: map_at_3
      value: 16.088
    - type: map_at_5
      value: 17.0
    - type: mrr_at_1
      value: 15.244
    - type: mrr_at_10
      value: 20.906
    - type: mrr_at_100
      value: 21.83
    - type: mrr_at_1000
      value: 21.913
    - type: mrr_at_3
      value: 19.104
    - type: mrr_at_5
      value: 19.994999999999997
    - type: ndcg_at_1
      value: 15.244
    - type: ndcg_at_10
      value: 21.541
    - type: ndcg_at_100
      value: 26.799
    - type: ndcg_at_1000
      value: 29.927
    - type: ndcg_at_3
      value: 18.208
    - type: ndcg_at_5
      value: 19.573999999999998
    - type: precision_at_1
      value: 15.244
    - type: precision_at_10
      value: 4.04
    - type: precision_at_100
      value: 0.808
    - type: precision_at_1000
      value: 0.125
    - type: precision_at_3
      value: 8.672
    - type: precision_at_5
      value: 6.283999999999999
    - type: recall_at_1
      value: 12.53
    - type: recall_at_10
      value: 29.601
    - type: recall_at_100
      value: 53.615
    - type: recall_at_1000
      value: 76.344
    - type: recall_at_3
      value: 20.159
    - type: recall_at_5
      value: 23.746000000000002
    - type: map_at_1
      value: 21.849
    - type: map_at_10
      value: 28.937
    - type: map_at_100
      value: 30.003999999999998
    - type: map_at_1000
      value: 30.122
    - type: map_at_3
      value: 26.150000000000002
    - type: map_at_5
      value: 27.744000000000003
    - type: mrr_at_1
      value: 25.093
    - type: mrr_at_10
      value: 32.143
    - type: mrr_at_100
      value: 33.053
    - type: mrr_at_1000
      value: 33.134
    - type: mrr_at_3
      value: 29.586000000000002
    - type: mrr_at_5
      value: 31.116
    - type: ndcg_at_1
      value: 25.093
    - type: ndcg_at_10
      value: 33.631
    - type: ndcg_at_100
      value: 38.893
    - type: ndcg_at_1000
      value: 41.692
    - type: ndcg_at_3
      value: 28.497
    - type: ndcg_at_5
      value: 31.028
    - type: precision_at_1
      value: 25.093
    - type: precision_at_10
      value: 5.765
    - type: precision_at_100
      value: 0.947
    - type: precision_at_1000
      value: 0.13
    - type: precision_at_3
      value: 12.623999999999999
    - type: precision_at_5
      value: 9.347
    - type: recall_at_1
      value: 21.849
    - type: recall_at_10
      value: 44.767
    - type: recall_at_100
      value: 68.298
    - type: recall_at_1000
      value: 88.107
    - type: recall_at_3
      value: 30.968
    - type: recall_at_5
      value: 37.19
    - type: map_at_1
      value: 18.409
    - type: map_at_10
      value: 27.750999999999998
    - type: map_at_100
      value: 29.241
    - type: map_at_1000
      value: 29.467
    - type: map_at_3
      value: 24.29
    - type: map_at_5
      value: 26.448
    - type: mrr_at_1
      value: 22.53
    - type: mrr_at_10
      value: 31.887999999999998
    - type: mrr_at_100
      value: 32.89
    - type: mrr_at_1000
      value: 32.956
    - type: mrr_at_3
      value: 28.854000000000003
    - type: mrr_at_5
      value: 30.751
    - type: ndcg_at_1
      value: 22.53
    - type: ndcg_at_10
      value: 33.827
    - type: ndcg_at_100
      value: 39.749
    - type: ndcg_at_1000
      value: 42.677
    - type: ndcg_at_3
      value: 28.101
    - type: ndcg_at_5
      value: 31.380999999999997
    - type: precision_at_1
      value: 22.53
    - type: precision_at_10
      value: 6.976
    - type: precision_at_100
      value: 1.443
    - type: precision_at_1000
      value: 0.23700000000000002
    - type: precision_at_3
      value: 13.966000000000001
    - type: precision_at_5
      value: 10.909
    - type: recall_at_1
      value: 18.409
    - type: recall_at_10
      value: 46.217000000000006
    - type: recall_at_100
      value: 72.882
    - type: recall_at_1000
      value: 91.625
    - type: recall_at_3
      value: 30.64
    - type: recall_at_5
      value: 38.948
    - type: map_at_1
      value: 15.875
    - type: map_at_10
      value: 21.484
    - type: map_at_100
      value: 22.367
    - type: map_at_1000
      value: 22.481
    - type: map_at_3
      value: 19.686
    - type: map_at_5
      value: 20.589
    - type: mrr_at_1
      value: 17.560000000000002
    - type: mrr_at_10
      value: 23.474999999999998
    - type: mrr_at_100
      value: 24.331
    - type: mrr_at_1000
      value: 24.426000000000002
    - type: mrr_at_3
      value: 21.688
    - type: mrr_at_5
      value: 22.603
    - type: ndcg_at_1
      value: 17.560000000000002
    - type: ndcg_at_10
      value: 25.268
    - type: ndcg_at_100
      value: 29.869
    - type: ndcg_at_1000
      value: 33.145
    - type: ndcg_at_3
      value: 21.622
    - type: ndcg_at_5
      value: 23.155
    - type: precision_at_1
      value: 17.560000000000002
    - type: precision_at_10
      value: 4.067
    - type: precision_at_100
      value: 0.6709999999999999
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 9.489
    - type: precision_at_5
      value: 6.617000000000001
    - type: recall_at_1
      value: 15.875
    - type: recall_at_10
      value: 35.064
    - type: recall_at_100
      value: 56.857
    - type: recall_at_1000
      value: 81.91199999999999
    - type: recall_at_3
      value: 24.823999999999998
    - type: recall_at_5
      value: 28.62
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 10.637
    - type: map_at_10
      value: 18.401999999999997
    - type: map_at_100
      value: 20.121
    - type: map_at_1000
      value: 20.305999999999997
    - type: map_at_3
      value: 15.348
    - type: map_at_5
      value: 16.841
    - type: mrr_at_1
      value: 23.909
    - type: mrr_at_10
      value: 34.512
    - type: mrr_at_100
      value: 35.485
    - type: mrr_at_1000
      value: 35.528999999999996
    - type: mrr_at_3
      value: 31.368000000000002
    - type: mrr_at_5
      value: 33.137
    - type: ndcg_at_1
      value: 23.909
    - type: ndcg_at_10
      value: 25.94
    - type: ndcg_at_100
      value: 33.116
    - type: ndcg_at_1000
      value: 36.502
    - type: ndcg_at_3
      value: 21.046
    - type: ndcg_at_5
      value: 22.715
    - type: precision_at_1
      value: 23.909
    - type: precision_at_10
      value: 8.195
    - type: precision_at_100
      value: 1.593
    - type: precision_at_1000
      value: 0.22200000000000003
    - type: precision_at_3
      value: 15.744
    - type: precision_at_5
      value: 12.142999999999999
    - type: recall_at_1
      value: 10.637
    - type: recall_at_10
      value: 31.251
    - type: recall_at_100
      value: 56.477999999999994
    - type: recall_at_1000
      value: 75.52600000000001
    - type: recall_at_3
      value: 19.482
    - type: recall_at_5
      value: 24.145
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 7.786999999999999
    - type: map_at_10
      value: 16.182
    - type: map_at_100
      value: 22.698
    - type: map_at_1000
      value: 24.192
    - type: map_at_3
      value: 11.84
    - type: map_at_5
      value: 13.602
    - type: mrr_at_1
      value: 56.99999999999999
    - type: mrr_at_10
      value: 66.702
    - type: mrr_at_100
      value: 67.291
    - type: mrr_at_1000
      value: 67.301
    - type: mrr_at_3
      value: 64.708
    - type: mrr_at_5
      value: 65.946
    - type: ndcg_at_1
      value: 46.75
    - type: ndcg_at_10
      value: 35.469
    - type: ndcg_at_100
      value: 40.077
    - type: ndcg_at_1000
      value: 47.252
    - type: ndcg_at_3
      value: 39.096
    - type: ndcg_at_5
      value: 36.766
    - type: precision_at_1
      value: 56.99999999999999
    - type: precision_at_10
      value: 28.175
    - type: precision_at_100
      value: 9.423
    - type: precision_at_1000
      value: 2.017
    - type: precision_at_3
      value: 41.667
    - type: precision_at_5
      value: 35.199999999999996
    - type: recall_at_1
      value: 7.786999999999999
    - type: recall_at_10
      value: 21.428
    - type: recall_at_100
      value: 45.86
    - type: recall_at_1000
      value: 68.83
    - type: recall_at_3
      value: 12.992
    - type: recall_at_5
      value: 16.091
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 45.985
    - type: f1
      value: 39.52034839578244
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 39.141999999999996
    - type: map_at_10
      value: 50.255
    - type: map_at_100
      value: 50.938
    - type: map_at_1000
      value: 50.975
    - type: map_at_3
      value: 47.4
    - type: map_at_5
      value: 49.172
    - type: mrr_at_1
      value: 41.794
    - type: mrr_at_10
      value: 53.198
    - type: mrr_at_100
      value: 53.82900000000001
    - type: mrr_at_1000
      value: 53.857
    - type: mrr_at_3
      value: 50.32
    - type: mrr_at_5
      value: 52.105999999999995
    - type: ndcg_at_1
      value: 41.794
    - type: ndcg_at_10
      value: 56.411
    - type: ndcg_at_100
      value: 59.663
    - type: ndcg_at_1000
      value: 60.590999999999994
    - type: ndcg_at_3
      value: 50.73
    - type: ndcg_at_5
      value: 53.823
    - type: precision_at_1
      value: 41.794
    - type: precision_at_10
      value: 7.9159999999999995
    - type: precision_at_100
      value: 0.968
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_3
      value: 20.627000000000002
    - type: precision_at_5
      value: 14.038
    - type: recall_at_1
      value: 39.141999999999996
    - type: recall_at_10
      value: 72.695
    - type: recall_at_100
      value: 87.44800000000001
    - type: recall_at_1000
      value: 94.313
    - type: recall_at_3
      value: 57.415000000000006
    - type: recall_at_5
      value: 64.851
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 18.715
    - type: map_at_10
      value: 30.253999999999998
    - type: map_at_100
      value: 32.123000000000005
    - type: map_at_1000
      value: 32.303
    - type: map_at_3
      value: 26.203
    - type: map_at_5
      value: 28.585
    - type: mrr_at_1
      value: 36.42
    - type: mrr_at_10
      value: 45.456
    - type: mrr_at_100
      value: 46.314
    - type: mrr_at_1000
      value: 46.356
    - type: mrr_at_3
      value: 42.798
    - type: mrr_at_5
      value: 44.365
    - type: ndcg_at_1
      value: 36.42
    - type: ndcg_at_10
      value: 37.747
    - type: ndcg_at_100
      value: 44.714999999999996
    - type: ndcg_at_1000
      value: 47.866
    - type: ndcg_at_3
      value: 34.166999999999994
    - type: ndcg_at_5
      value: 35.54
    - type: precision_at_1
      value: 36.42
    - type: precision_at_10
      value: 10.602
    - type: precision_at_100
      value: 1.773
    - type: precision_at_1000
      value: 0.234
    - type: precision_at_3
      value: 22.84
    - type: precision_at_5
      value: 17.315
    - type: recall_at_1
      value: 18.715
    - type: recall_at_10
      value: 44.199
    - type: recall_at_100
      value: 70.097
    - type: recall_at_1000
      value: 89.13600000000001
    - type: recall_at_3
      value: 30.543
    - type: recall_at_5
      value: 36.705
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 30.608
    - type: map_at_10
      value: 45.829
    - type: map_at_100
      value: 46.786
    - type: map_at_1000
      value: 46.869
    - type: map_at_3
      value: 42.834
    - type: map_at_5
      value: 44.566
    - type: mrr_at_1
      value: 61.214999999999996
    - type: mrr_at_10
      value: 69.072
    - type: mrr_at_100
      value: 69.492
    - type: mrr_at_1000
      value: 69.512
    - type: mrr_at_3
      value: 67.553
    - type: mrr_at_5
      value: 68.446
    - type: ndcg_at_1
      value: 61.214999999999996
    - type: ndcg_at_10
      value: 54.66
    - type: ndcg_at_100
      value: 58.342000000000006
    - type: ndcg_at_1000
      value: 60.101000000000006
    - type: ndcg_at_3
      value: 49.932
    - type: ndcg_at_5
      value: 52.342999999999996
    - type: precision_at_1
      value: 61.214999999999996
    - type: precision_at_10
      value: 11.65
    - type: precision_at_100
      value: 1.4529999999999998
    - type: precision_at_1000
      value: 0.169
    - type: precision_at_3
      value: 31.78
    - type: precision_at_5
      value: 20.979999999999997
    - type: recall_at_1
      value: 30.608
    - type: recall_at_10
      value: 58.251
    - type: recall_at_100
      value: 72.667
    - type: recall_at_1000
      value: 84.396
    - type: recall_at_3
      value: 47.67
    - type: recall_at_5
      value: 52.451
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 90.21999999999998
    - type: ap
      value: 85.88889163834975
    - type: f1
      value: 90.20542534971861
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 19.785
    - type: map_at_10
      value: 31.596000000000004
    - type: map_at_100
      value: 32.849000000000004
    - type: map_at_1000
      value: 32.903999999999996
    - type: map_at_3
      value: 27.772000000000002
    - type: map_at_5
      value: 29.952
    - type: mrr_at_1
      value: 20.344
    - type: mrr_at_10
      value: 32.146
    - type: mrr_at_100
      value: 33.349000000000004
    - type: mrr_at_1000
      value: 33.396
    - type: mrr_at_3
      value: 28.403
    - type: mrr_at_5
      value: 30.542
    - type: ndcg_at_1
      value: 20.358
    - type: ndcg_at_10
      value: 38.288
    - type: ndcg_at_100
      value: 44.383
    - type: ndcg_at_1000
      value: 45.714
    - type: ndcg_at_3
      value: 30.525999999999996
    - type: ndcg_at_5
      value: 34.393
    - type: precision_at_1
      value: 20.358
    - type: precision_at_10
      value: 6.16
    - type: precision_at_100
      value: 0.9209999999999999
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 13.08
    - type: precision_at_5
      value: 9.799
    - type: recall_at_1
      value: 19.785
    - type: recall_at_10
      value: 58.916000000000004
    - type: recall_at_100
      value: 87.24
    - type: recall_at_1000
      value: 97.37599999999999
    - type: recall_at_3
      value: 37.872
    - type: recall_at_5
      value: 47.116
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 88.63429092567262
    - type: f1
      value: 88.58612904162257
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 58.080255357957135
    - type: f1
      value: 39.561402859935
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.03026227303296
    - type: f1
      value: 61.10334739098155
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.05245460659046
    - type: f1
      value: 69.96280851244295
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 33.9762359299763
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 31.670044418802444
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.32330726926572
    - type: mrr
      value: 30.16727607430052
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 4.552
    - type: map_at_10
      value: 10.692
    - type: map_at_100
      value: 13.835
    - type: map_at_1000
      value: 15.305
    - type: map_at_3
      value: 7.5009999999999994
    - type: map_at_5
      value: 8.988
    - type: mrr_at_1
      value: 39.318999999999996
    - type: mrr_at_10
      value: 48.809000000000005
    - type: mrr_at_100
      value: 49.382
    - type: mrr_at_1000
      value: 49.442
    - type: mrr_at_3
      value: 46.078
    - type: mrr_at_5
      value: 48.091
    - type: ndcg_at_1
      value: 37.152
    - type: ndcg_at_10
      value: 30.159000000000002
    - type: ndcg_at_100
      value: 28.371000000000002
    - type: ndcg_at_1000
      value: 37.632
    - type: ndcg_at_3
      value: 34.662
    - type: ndcg_at_5
      value: 32.814
    - type: precision_at_1
      value: 38.7
    - type: precision_at_10
      value: 23.034
    - type: precision_at_100
      value: 7.588
    - type: precision_at_1000
      value: 2.0709999999999997
    - type: precision_at_3
      value: 33.024
    - type: precision_at_5
      value: 29.164
    - type: recall_at_1
      value: 4.552
    - type: recall_at_10
      value: 14.827000000000002
    - type: recall_at_100
      value: 29.256
    - type: recall_at_1000
      value: 61.739
    - type: recall_at_3
      value: 8.38
    - type: recall_at_5
      value: 11.123
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 25.424999999999997
    - type: map_at_10
      value: 39.972
    - type: map_at_100
      value: 41.163
    - type: map_at_1000
      value: 41.202
    - type: map_at_3
      value: 35.546
    - type: map_at_5
      value: 38.146
    - type: mrr_at_1
      value: 28.794999999999998
    - type: mrr_at_10
      value: 42.315999999999995
    - type: mrr_at_100
      value: 43.253
    - type: mrr_at_1000
      value: 43.282
    - type: mrr_at_3
      value: 38.649
    - type: mrr_at_5
      value: 40.858
    - type: ndcg_at_1
      value: 28.766000000000002
    - type: ndcg_at_10
      value: 47.614000000000004
    - type: ndcg_at_100
      value: 52.676
    - type: ndcg_at_1000
      value: 53.574
    - type: ndcg_at_3
      value: 39.292
    - type: ndcg_at_5
      value: 43.633
    - type: precision_at_1
      value: 28.766000000000002
    - type: precision_at_10
      value: 8.201
    - type: precision_at_100
      value: 1.099
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 18.201999999999998
    - type: precision_at_5
      value: 13.447000000000001
    - type: recall_at_1
      value: 25.424999999999997
    - type: recall_at_10
      value: 68.586
    - type: recall_at_100
      value: 90.556
    - type: recall_at_1000
      value: 97.197
    - type: recall_at_3
      value: 47.033
    - type: recall_at_5
      value: 57.044
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 70.054
    - type: map_at_10
      value: 83.991
    - type: map_at_100
      value: 84.63000000000001
    - type: map_at_1000
      value: 84.648
    - type: map_at_3
      value: 80.982
    - type: map_at_5
      value: 82.857
    - type: mrr_at_1
      value: 80.76
    - type: mrr_at_10
      value: 87.079
    - type: mrr_at_100
      value: 87.185
    - type: mrr_at_1000
      value: 87.18599999999999
    - type: mrr_at_3
      value: 86.03
    - type: mrr_at_5
      value: 86.771
    - type: ndcg_at_1
      value: 80.75
    - type: ndcg_at_10
      value: 87.85300000000001
    - type: ndcg_at_100
      value: 89.105
    - type: ndcg_at_1000
      value: 89.213
    - type: ndcg_at_3
      value: 84.87400000000001
    - type: ndcg_at_5
      value: 86.51299999999999
    - type: precision_at_1
      value: 80.75
    - type: precision_at_10
      value: 13.352
    - type: precision_at_100
      value: 1.528
    - type: precision_at_1000
      value: 0.157
    - type: precision_at_3
      value: 37.113
    - type: precision_at_5
      value: 24.424
    - type: recall_at_1
      value: 70.054
    - type: recall_at_10
      value: 95.209
    - type: recall_at_100
      value: 99.497
    - type: recall_at_1000
      value: 99.973
    - type: recall_at_3
      value: 86.654
    - type: recall_at_5
      value: 91.313
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 42.71909082787674
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 56.92567540870805
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.225
    - type: map_at_10
      value: 5.785
    - type: map_at_100
      value: 7.6240000000000006
    - type: map_at_1000
      value: 8.094999999999999
    - type: map_at_3
      value: 3.882
    - type: map_at_5
      value: 4.715
    - type: mrr_at_1
      value: 11.0
    - type: mrr_at_10
      value: 18.049
    - type: mrr_at_100
      value: 19.475
    - type: mrr_at_1000
      value: 19.599
    - type: mrr_at_3
      value: 15.082999999999998
    - type: mrr_at_5
      value: 16.583000000000002
    - type: ndcg_at_1
      value: 11.0
    - type: ndcg_at_10
      value: 10.59
    - type: ndcg_at_100
      value: 18.68
    - type: ndcg_at_1000
      value: 27.327
    - type: ndcg_at_3
      value: 8.932
    - type: ndcg_at_5
      value: 8.126
    - type: precision_at_1
      value: 11.0
    - type: precision_at_10
      value: 5.89
    - type: precision_at_100
      value: 1.778
    - type: precision_at_1000
      value: 0.385
    - type: precision_at_3
      value: 8.333
    - type: precision_at_5
      value: 7.3
    - type: recall_at_1
      value: 2.225
    - type: recall_at_10
      value: 11.948
    - type: recall_at_100
      value: 36.097
    - type: recall_at_1000
      value: 78.145
    - type: recall_at_3
      value: 5.078
    - type: recall_at_5
      value: 7.4079999999999995
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 83.87898494199837
    - type: cos_sim_spearman
      value: 79.3815141247343
    - type: euclidean_pearson
      value: 80.984944764735
    - type: euclidean_spearman
      value: 79.37984688714191
    - type: manhattan_pearson
      value: 80.96139326762788
    - type: manhattan_spearman
      value: 79.34882764221987
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 82.94123934276303
    - type: cos_sim_spearman
      value: 73.64821774752144
    - type: euclidean_pearson
      value: 79.09149672589201
    - type: euclidean_spearman
      value: 73.64174833442063
    - type: manhattan_pearson
      value: 79.05135129686983
    - type: manhattan_spearman
      value: 73.57858840270084
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 71.37047316191514
    - type: cos_sim_spearman
      value: 75.56797051373606
    - type: euclidean_pearson
      value: 74.59038333631109
    - type: euclidean_spearman
      value: 75.55966023907652
    - type: manhattan_pearson
      value: 74.56600039917967
    - type: manhattan_spearman
      value: 75.52139454559969
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 71.75410054949431
    - type: cos_sim_spearman
      value: 72.09826786050286
    - type: euclidean_pearson
      value: 72.30015801748517
    - type: euclidean_spearman
      value: 72.09347126863909
    - type: manhattan_pearson
      value: 72.2692656804079
    - type: manhattan_spearman
      value: 72.07403601010577
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 83.09663528706463
    - type: cos_sim_spearman
      value: 85.6296813586495
    - type: euclidean_pearson
      value: 84.14347920777777
    - type: euclidean_spearman
      value: 85.62948425849926
    - type: manhattan_pearson
      value: 84.08840896634038
    - type: manhattan_spearman
      value: 85.56264430897471
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 78.55984417539631
    - type: cos_sim_spearman
      value: 82.06700938579174
    - type: euclidean_pearson
      value: 80.92277218507344
    - type: euclidean_spearman
      value: 82.06297899287695
    - type: manhattan_pearson
      value: 80.89292734584946
    - type: manhattan_spearman
      value: 82.01121177547141
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 88.70738419575085
    - type: cos_sim_spearman
      value: 88.99910283221313
    - type: euclidean_pearson
      value: 88.91458218447116
    - type: euclidean_spearman
      value: 88.97188755639708
    - type: manhattan_pearson
      value: 88.93397958768632
    - type: manhattan_spearman
      value: 89.0514960821245
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 65.30101408630514
    - type: cos_sim_spearman
      value: 66.15672143838582
    - type: euclidean_pearson
      value: 66.61257552376895
    - type: euclidean_spearman
      value: 66.00319920690566
    - type: manhattan_pearson
      value: 66.81435622246758
    - type: manhattan_spearman
      value: 66.35221377631379
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 81.94191078286725
    - type: cos_sim_spearman
      value: 83.69085688689903
    - type: euclidean_pearson
      value: 83.28942607749994
    - type: euclidean_spearman
      value: 83.69370814043747
    - type: manhattan_pearson
      value: 83.3553242227074
    - type: manhattan_spearman
      value: 83.74306572840383
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 88.02503921524934
    - type: mrr
      value: 96.47891777793738
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 51.24999999999999
    - type: map_at_10
      value: 61.472
    - type: map_at_100
      value: 62.132
    - type: map_at_1000
      value: 62.161
    - type: map_at_3
      value: 58.18299999999999
    - type: map_at_5
      value: 60.246
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_10
      value: 62.395
    - type: mrr_at_100
      value: 62.936
    - type: mrr_at_1000
      value: 62.965
    - type: mrr_at_3
      value: 59.833000000000006
    - type: mrr_at_5
      value: 61.5
    - type: ndcg_at_1
      value: 54.0
    - type: ndcg_at_10
      value: 66.235
    - type: ndcg_at_100
      value: 69.279
    - type: ndcg_at_1000
      value: 70.044
    - type: ndcg_at_3
      value: 60.679
    - type: ndcg_at_5
      value: 63.80200000000001
    - type: precision_at_1
      value: 54.0
    - type: precision_at_10
      value: 9.167
    - type: precision_at_100
      value: 1.0699999999999998
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 24.111
    - type: precision_at_5
      value: 16.333000000000002
    - type: recall_at_1
      value: 51.24999999999999
    - type: recall_at_10
      value: 79.833
    - type: recall_at_100
      value: 94.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 65.267
    - type: recall_at_5
      value: 72.956
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.62673267326733
    - type: cos_sim_ap
      value: 87.07482534376774
    - type: cos_sim_f1
      value: 80.63687724704674
    - type: cos_sim_precision
      value: 82.89334741288279
    - type: cos_sim_recall
      value: 78.5
    - type: dot_accuracy
      value: 99.63564356435643
    - type: dot_ap
      value: 86.98432756163903
    - type: dot_f1
      value: 80.91286307053943
    - type: dot_precision
      value: 84.05172413793103
    - type: dot_recall
      value: 78.0
    - type: euclidean_accuracy
      value: 99.62673267326733
    - type: euclidean_ap
      value: 87.0756316041764
    - type: euclidean_f1
      value: 80.53553038105046
    - type: euclidean_precision
      value: 83.01486199575372
    - type: euclidean_recall
      value: 78.2
    - type: manhattan_accuracy
      value: 99.62574257425743
    - type: manhattan_ap
      value: 87.05953308523233
    - type: manhattan_f1
      value: 80.50632911392405
    - type: manhattan_precision
      value: 81.53846153846153
    - type: manhattan_recall
      value: 79.5
    - type: max_accuracy
      value: 99.63564356435643
    - type: max_ap
      value: 87.0756316041764
    - type: max_f1
      value: 80.91286307053943
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 53.59692640735744
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.86771187657918
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 45.705711066037644
    - type: mrr
      value: 46.25163133435192
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.066382997227624
    - type: cos_sim_spearman
      value: 31.00934876843689
    - type: dot_pearson
      value: 30.419206995727873
    - type: dot_spearman
      value: 31.046571150093747
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.173
    - type: map_at_10
      value: 1.154
    - type: map_at_100
      value: 5.8180000000000005
    - type: map_at_1000
      value: 14.892
    - type: map_at_3
      value: 0.415
    - type: map_at_5
      value: 0.641
    - type: mrr_at_1
      value: 68.0
    - type: mrr_at_10
      value: 76.869
    - type: mrr_at_100
      value: 77.264
    - type: mrr_at_1000
      value: 77.264
    - type: mrr_at_3
      value: 75.333
    - type: mrr_at_5
      value: 76.333
    - type: ndcg_at_1
      value: 62.0
    - type: ndcg_at_10
      value: 50.81
    - type: ndcg_at_100
      value: 37.659
    - type: ndcg_at_1000
      value: 37.444
    - type: ndcg_at_3
      value: 55.11200000000001
    - type: ndcg_at_5
      value: 51.858000000000004
    - type: precision_at_1
      value: 68.0
    - type: precision_at_10
      value: 54.800000000000004
    - type: precision_at_100
      value: 38.36
    - type: precision_at_1000
      value: 16.88
    - type: precision_at_3
      value: 57.99999999999999
    - type: precision_at_5
      value: 54.800000000000004
    - type: recall_at_1
      value: 0.173
    - type: recall_at_10
      value: 1.435
    - type: recall_at_100
      value: 9.259
    - type: recall_at_1000
      value: 36.033
    - type: recall_at_3
      value: 0.447
    - type: recall_at_5
      value: 0.74
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 1.228
    - type: map_at_10
      value: 4.633
    - type: map_at_100
      value: 9.171
    - type: map_at_1000
      value: 10.58
    - type: map_at_3
      value: 2.413
    - type: map_at_5
      value: 3.3640000000000003
    - type: mrr_at_1
      value: 16.326999999999998
    - type: mrr_at_10
      value: 27.071
    - type: mrr_at_100
      value: 28.454
    - type: mrr_at_1000
      value: 28.475
    - type: mrr_at_3
      value: 19.048000000000002
    - type: mrr_at_5
      value: 24.354
    - type: ndcg_at_1
      value: 14.285999999999998
    - type: ndcg_at_10
      value: 13.312
    - type: ndcg_at_100
      value: 25.587
    - type: ndcg_at_1000
      value: 37.879000000000005
    - type: ndcg_at_3
      value: 11.591
    - type: ndcg_at_5
      value: 12.536
    - type: precision_at_1
      value: 16.326999999999998
    - type: precision_at_10
      value: 13.264999999999999
    - type: precision_at_100
      value: 6.061
    - type: precision_at_1000
      value: 1.4040000000000001
    - type: precision_at_3
      value: 12.245000000000001
    - type: precision_at_5
      value: 13.877999999999998
    - type: recall_at_1
      value: 1.228
    - type: recall_at_10
      value: 9.759
    - type: recall_at_100
      value: 38.809
    - type: recall_at_1000
      value: 76.229
    - type: recall_at_3
      value: 2.738
    - type: recall_at_5
      value: 5.510000000000001
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.33179999999999
    - type: ap
      value: 14.379598043710034
    - type: f1
      value: 53.89665138084001
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 58.245614035087726
    - type: f1
      value: 58.3152945231724
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 38.38161204174159
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.60118018716099
    - type: cos_sim_ap
      value: 62.5064927795416
    - type: cos_sim_f1
      value: 59.50177935943061
    - type: cos_sim_precision
      value: 54.05172413793103
    - type: cos_sim_recall
      value: 66.17414248021109
    - type: dot_accuracy
      value: 82.52369315133814
    - type: dot_ap
      value: 62.36545569178682
    - type: dot_f1
      value: 59.5539204414808
    - type: dot_precision
      value: 52.77098614506927
    - type: dot_recall
      value: 68.33773087071239
    - type: euclidean_accuracy
      value: 82.62502235202956
    - type: euclidean_ap
      value: 62.51708062651598
    - type: euclidean_f1
      value: 59.48887837198297
    - type: euclidean_precision
      value: 53.925353925353924
    - type: euclidean_recall
      value: 66.33245382585751
    - type: manhattan_accuracy
      value: 82.57733802229242
    - type: manhattan_ap
      value: 62.4034159268756
    - type: manhattan_f1
      value: 59.42896615242921
    - type: manhattan_precision
      value: 52.716503267973856
    - type: manhattan_recall
      value: 68.10026385224275
    - type: max_accuracy
      value: 82.62502235202956
    - type: max_ap
      value: 62.51708062651598
    - type: max_f1
      value: 59.5539204414808
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 86.74079248651377
    - type: cos_sim_ap
      value: 81.11128912769627
    - type: cos_sim_f1
      value: 73.39903296054331
    - type: cos_sim_precision
      value: 70.49273307337823
    - type: cos_sim_recall
      value: 76.55528179858331
    - type: dot_accuracy
      value: 86.71362595567975
    - type: dot_ap
      value: 81.07587927324371
    - type: dot_f1
      value: 73.36112443280334
    - type: dot_precision
      value: 70.42283447836249
    - type: dot_recall
      value: 76.55528179858331
    - type: euclidean_accuracy
      value: 86.73109015407304
    - type: euclidean_ap
      value: 81.11249921439843
    - type: euclidean_f1
      value: 73.39903296054331
    - type: euclidean_precision
      value: 70.49273307337823
    - type: euclidean_recall
      value: 76.55528179858331
    - type: manhattan_accuracy
      value: 86.7252687546086
    - type: manhattan_ap
      value: 81.05990290681223
    - type: manhattan_f1
      value: 73.29173525245952
    - type: manhattan_precision
      value: 72.88161400837457
    - type: manhattan_recall
      value: 73.70649830612874
    - type: max_accuracy
      value: 86.74079248651377
    - type: max_ap
      value: 81.11249921439843
    - type: max_f1
      value: 73.39903296054331
---
