sentence-transformers pytorch bloom feature-extraction sentence-similarity mteb arxiv:2202.08904 model-index autotrain_compatible endpoints_compatible region:us
---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mteb
model-index:
- name: sgpt-bloom-7b1-msmarco
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
    metrics:
    - type: accuracy
      value: 68.05970149253731
    - type: ap
      value: 31.640363460776193
    - type: f1
      value: 62.50025574145796
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (de)
      type: mteb/amazon_counterfactual
      config: de
      split: test
      revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
    metrics:
    - type: accuracy
      value: 61.34903640256959
    - type: ap
      value: 75.18797161500426
    - type: f1
      value: 59.04772570730417
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
    metrics:
    - type: accuracy
      value: 67.78110944527737
    - type: ap
      value: 19.218916023322706
    - type: f1
      value: 56.24477391445512
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (ja)
      type: mteb/amazon_counterfactual
      config: ja
      split: test
      revision: 2d8a100785abf0ae21420d2a55b0c56e3e1ea996
    metrics:
    - type: accuracy
      value: 58.23340471092078
    - type: ap
      value: 13.20222967424681
    - type: f1
      value: 47.511718095460296
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: 80714f8dcf8cefc218ef4f8c5a966dd83f75a0e1
    metrics:
    - type: accuracy
      value: 68.97232499999998
    - type: ap
      value: 63.53632885535693
    - type: f1
      value: 68.62038513152868
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 33.855999999999995
    - type: f1
      value: 33.43468222830134
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (de)
      type: mteb/amazon_reviews_multi
      config: de
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 29.697999999999997
    - type: f1
      value: 29.39935388885501
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (es)
      type: mteb/amazon_reviews_multi
      config: es
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 35.974000000000004
    - type: f1
      value: 35.25910820714383
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (fr)
      type: mteb/amazon_reviews_multi
      config: fr
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 35.922
    - type: f1
      value: 35.38637028933444
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (ja)
      type: mteb/amazon_reviews_multi
      config: ja
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 27.636
    - type: f1
      value: 27.178349955978266
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: c379a6705fec24a2493fa68e011692605f44e119
    metrics:
    - type: accuracy
      value: 32.632
    - type: f1
      value: 32.08014766494587
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: 5b3e3697907184a9b77a3c99ee9ea1a9cbb1e4e3
    metrics:
    - type: map_at_1
      value: 23.684
    - type: map_at_10
      value: 38.507999999999996
    - type: map_at_100
      value: 39.677
    - type: map_at_1000
      value: 39.690999999999995
    - type: map_at_3
      value: 33.369
    - type: map_at_5
      value: 36.15
    - type: mrr_at_1
      value: 24.04
    - type: mrr_at_10
      value: 38.664
    - type: mrr_at_100
      value: 39.833
    - type: mrr_at_1000
      value: 39.847
    - type: mrr_at_3
      value: 33.476
    - type: mrr_at_5
      value: 36.306
    - type: ndcg_at_1
      value: 23.684
    - type: ndcg_at_10
      value: 47.282000000000004
    - type: ndcg_at_100
      value: 52.215
    - type: ndcg_at_1000
      value: 52.551
    - type: ndcg_at_3
      value: 36.628
    - type: ndcg_at_5
      value: 41.653
    - type: precision_at_1
      value: 23.684
    - type: precision_at_10
      value: 7.553
    - type: precision_at_100
      value: 0.97
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 15.363
    - type: precision_at_5
      value: 11.664
    - type: recall_at_1
      value: 23.684
    - type: recall_at_10
      value: 75.533
    - type: recall_at_100
      value: 97.013
    - type: recall_at_1000
      value: 99.57300000000001
    - type: recall_at_3
      value: 46.088
    - type: recall_at_5
      value: 58.321
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: 0bbdb47bcbe3a90093699aefeed338a0f28a7ee8
    metrics:
    - type: v_measure
      value: 44.59375023881131
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: b73bd54100e5abfa6e3a23dcafb46fe4d2438dc3
    metrics:
    - type: v_measure
      value: 38.02921907752556
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 4d853f94cd57d85ec13805aeeac3ae3e5eb4c49c
    metrics:
    - type: map
      value: 59.97321570342109
    - type: mrr
      value: 73.18284746955106
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: 9ee918f184421b6bd48b78f6c714d86546106103
    metrics:
    - type: cos_sim_pearson
      value: 89.09091435741429
    - type: cos_sim_spearman
      value: 85.31459455332202
    - type: euclidean_pearson
      value: 79.3587681410798
    - type: euclidean_spearman
      value: 76.8174129874685
    - type: manhattan_pearson
      value: 79.57051762121769
    - type: manhattan_spearman
      value: 76.75837549768094
  - task:
      type: BitextMining
    dataset:
      name: MTEB BUCC (de-en)
      type: mteb/bucc-bitext-mining
      config: de-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 54.27974947807933
    - type: f1
      value: 54.00144411132214
    - type: precision
      value: 53.87119374071357
    - type: recall
      value: 54.27974947807933
  - task:
      type: BitextMining
    dataset:
      name: MTEB BUCC (fr-en)
      type: mteb/bucc-bitext-mining
      config: fr-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 97.3365617433414
    - type: f1
      value: 97.06141316310809
    - type: precision
      value: 96.92567319685965
    - type: recall
      value: 97.3365617433414
  - task:
      type: BitextMining
    dataset:
      name: MTEB BUCC (ru-en)
      type: mteb/bucc-bitext-mining
      config: ru-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 46.05472809144441
    - type: f1
      value: 45.30319274690595
    - type: precision
      value: 45.00015469655234
    - type: recall
      value: 46.05472809144441
  - task:
      type: BitextMining
    dataset:
      name: MTEB BUCC (zh-en)
      type: mteb/bucc-bitext-mining
      config: zh-en
      split: test
      revision: d51519689f32196a32af33b075a01d0e7c51e252
    metrics:
    - type: accuracy
      value: 98.10426540284361
    - type: f1
      value: 97.96384061786905
    - type: precision
      value: 97.89362822538178
    - type: recall
      value: 98.10426540284361
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 44fa15921b4c889113cc5df03dd4901b49161ab7
    metrics:
    - type: accuracy
      value: 84.33441558441558
    - type: f1
      value: 84.31653077470322
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 11d0121201d1f1f280e8cc8f3d98fb9c4d9f9c55
    metrics:
    - type: v_measure
      value: 36.025318694698086
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: c0fab014e1bcb8d3a5e31b2088972a1e01547dc1
    metrics:
    - type: v_measure
      value: 32.484889034590346
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: 2b9f5791698b5be7bc5e10535c8690f20043c3db
    metrics:
    - type: map_at_1
      value: 30.203999999999997
    - type: map_at_10
      value: 41.314
    - type: map_at_100
      value: 42.66
    - type: map_at_1000
      value: 42.775999999999996
    - type: map_at_3
      value: 37.614999999999995
    - type: map_at_5
      value: 39.643
    - type: mrr_at_1
      value: 37.482
    - type: mrr_at_10
      value: 47.075
    - type: mrr_at_100
      value: 47.845
    - type: mrr_at_1000
      value: 47.887
    - type: mrr_at_3
      value: 44.635000000000005
    - type: mrr_at_5
      value: 45.966
    - type: ndcg_at_1
      value: 37.482
    - type: ndcg_at_10
      value: 47.676
    - type: ndcg_at_100
      value: 52.915
    - type: ndcg_at_1000
      value: 54.82900000000001
    - type: ndcg_at_3
      value: 42.562
    - type: ndcg_at_5
      value: 44.852
    - type: precision_at_1
      value: 37.482
    - type: precision_at_10
      value: 9.142
    - type: precision_at_100
      value: 1.436
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 20.458000000000002
    - type: precision_at_5
      value: 14.821000000000002
    - type: recall_at_1
      value: 30.203999999999997
    - type: recall_at_10
      value: 60.343
    - type: recall_at_100
      value: 82.58
    - type: recall_at_1000
      value: 94.813
    - type: recall_at_3
      value: 45.389
    - type: recall_at_5
      value: 51.800999999999995
    - type: map_at_1
      value: 30.889
    - type: map_at_10
      value: 40.949999999999996
    - type: map_at_100
      value: 42.131
    - type: map_at_1000
      value: 42.253
    - type: map_at_3
      value: 38.346999999999994
    - type: map_at_5
      value: 39.782000000000004
    - type: mrr_at_1
      value: 38.79
    - type: mrr_at_10
      value: 46.944
    - type: mrr_at_100
      value: 47.61
    - type: mrr_at_1000
      value: 47.650999999999996
    - type: mrr_at_3
      value: 45.053
    - type: mrr_at_5
      value: 46.101
    - type: ndcg_at_1
      value: 38.79
    - type: ndcg_at_10
      value: 46.286
    - type: ndcg_at_100
      value: 50.637
    - type: ndcg_at_1000
      value: 52.649
    - type: ndcg_at_3
      value: 42.851
    - type: ndcg_at_5
      value: 44.311
    - type: precision_at_1
      value: 38.79
    - type: precision_at_10
      value: 8.516
    - type: precision_at_100
      value: 1.3679999999999999
    - type: precision_at_1000
      value: 0.183
    - type: precision_at_3
      value: 20.637
    - type: precision_at_5
      value: 14.318
    - type: recall_at_1
      value: 30.889
    - type: recall_at_10
      value: 55.327000000000005
    - type: recall_at_100
      value: 74.091
    - type: recall_at_1000
      value: 86.75500000000001
    - type: recall_at_3
      value: 44.557
    - type: recall_at_5
      value: 49.064
    - type: map_at_1
      value: 39.105000000000004
    - type: map_at_10
      value: 50.928
    - type: map_at_100
      value: 51.958000000000006
    - type: map_at_1000
      value: 52.017
    - type: map_at_3
      value: 47.638999999999996
    - type: map_at_5
      value: 49.624
    - type: mrr_at_1
      value: 44.639
    - type: mrr_at_10
      value: 54.261
    - type: mrr_at_100
      value: 54.913999999999994
    - type: mrr_at_1000
      value: 54.945
    - type: mrr_at_3
      value: 51.681999999999995
    - type: mrr_at_5
      value: 53.290000000000006
    - type: ndcg_at_1
      value: 44.639
    - type: ndcg_at_10
      value: 56.678
    - type: ndcg_at_100
      value: 60.649
    - type: ndcg_at_1000
      value: 61.855000000000004
    - type: ndcg_at_3
      value: 51.092999999999996
    - type: ndcg_at_5
      value: 54.096999999999994
    - type: precision_at_1
      value: 44.639
    - type: precision_at_10
      value: 9.028
    - type: precision_at_100
      value: 1.194
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 22.508
    - type: precision_at_5
      value: 15.661
    - type: recall_at_1
      value: 39.105000000000004
    - type: recall_at_10
      value: 70.367
    - type: recall_at_100
      value: 87.359
    - type: recall_at_1000
      value: 95.88
    - type: recall_at_3
      value: 55.581
    - type: recall_at_5
      value: 62.821000000000005
    - type: map_at_1
      value: 23.777
    - type: map_at_10
      value: 32.297
    - type: map_at_100
      value: 33.516
    - type: map_at_1000
      value: 33.592
    - type: map_at_3
      value: 30.001
    - type: map_at_5
      value: 31.209999999999997
    - type: mrr_at_1
      value: 25.989
    - type: mrr_at_10
      value: 34.472
    - type: mrr_at_100
      value: 35.518
    - type: mrr_at_1000
      value: 35.577
    - type: mrr_at_3
      value: 32.185
    - type: mrr_at_5
      value: 33.399
    - type: ndcg_at_1
      value: 25.989
    - type: ndcg_at_10
      value: 37.037
    - type: ndcg_at_100
      value: 42.699
    - type: ndcg_at_1000
      value: 44.725
    - type: ndcg_at_3
      value: 32.485
    - type: ndcg_at_5
      value: 34.549
    - type: precision_at_1
      value: 25.989
    - type: precision_at_10
      value: 5.718
    - type: precision_at_100
      value: 0.89
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 14.049
    - type: precision_at_5
      value: 9.672
    - type: recall_at_1
      value: 23.777
    - type: recall_at_10
      value: 49.472
    - type: recall_at_100
      value: 74.857
    - type: recall_at_1000
      value: 90.289
    - type: recall_at_3
      value: 37.086000000000006
    - type: recall_at_5
      value: 42.065999999999995
    - type: map_at_1
      value: 13.377
    - type: map_at_10
      value: 21.444
    - type: map_at_100
      value: 22.663
    - type: map_at_1000
      value: 22.8
    - type: map_at_3
      value: 18.857
    - type: map_at_5
      value: 20.426
    - type: mrr_at_1
      value: 16.542
    - type: mrr_at_10
      value: 25.326999999999998
    - type: mrr_at_100
      value: 26.323
    - type: mrr_at_1000
      value: 26.406000000000002
    - type: mrr_at_3
      value: 22.823
    - type: mrr_at_5
      value: 24.340999999999998
    - type: ndcg_at_1
      value: 16.542
    - type: ndcg_at_10
      value: 26.479000000000003
    - type: ndcg_at_100
      value: 32.29
    - type: ndcg_at_1000
      value: 35.504999999999995
    - type: ndcg_at_3
      value: 21.619
    - type: ndcg_at_5
      value: 24.19
    - type: precision_at_1
      value: 16.542
    - type: precision_at_10
      value: 5.075
    - type: precision_at_100
      value: 0.9339999999999999
    - type: precision_at_1000
      value: 0.135
    - type: precision_at_3
      value: 10.697
    - type: precision_at_5
      value: 8.134
    - type: recall_at_1
      value: 13.377
    - type: recall_at_10
      value: 38.027
    - type: recall_at_100
      value: 63.439
    - type: recall_at_1000
      value: 86.354
    - type: recall_at_3
      value: 25.0
    - type: recall_at_5
      value: 31.306
    - type: map_at_1
      value: 28.368
    - type: map_at_10
      value: 39.305
    - type: map_at_100
      value: 40.637
    - type: map_at_1000
      value: 40.753
    - type: map_at_3
      value: 36.077999999999996
    - type: map_at_5
      value: 37.829
    - type: mrr_at_1
      value: 34.937000000000005
    - type: mrr_at_10
      value: 45.03
    - type: mrr_at_100
      value: 45.78
    - type: mrr_at_1000
      value: 45.827
    - type: mrr_at_3
      value: 42.348
    - type: mrr_at_5
      value: 43.807
    - type: ndcg_at_1
      value: 34.937000000000005
    - type: ndcg_at_10
      value: 45.605000000000004
    - type: ndcg_at_100
      value: 50.941
    - type: ndcg_at_1000
      value: 52.983000000000004
    - type: ndcg_at_3
      value: 40.366
    - type: ndcg_at_5
      value: 42.759
    - type: precision_at_1
      value: 34.937000000000005
    - type: precision_at_10
      value: 8.402
    - type: precision_at_100
      value: 1.2959999999999998
    - type: precision_at_1000
      value: 0.164
    - type: precision_at_3
      value: 19.217000000000002
    - type: precision_at_5
      value: 13.725000000000001
    - type: recall_at_1
      value: 28.368
    - type: recall_at_10
      value: 58.5
    - type: recall_at_100
      value: 80.67999999999999
    - type: recall_at_1000
      value: 93.925
    - type: recall_at_3
      value: 43.956
    - type: recall_at_5
      value: 50.065000000000005
    - type: map_at_1
      value: 24.851
    - type: map_at_10
      value: 34.758
    - type: map_at_100
      value: 36.081
    - type: map_at_1000
      value: 36.205999999999996
    - type: map_at_3
      value: 31.678
    - type: map_at_5
      value: 33.398
    - type: mrr_at_1
      value: 31.279
    - type: mrr_at_10
      value: 40.138
    - type: mrr_at_100
      value: 41.005
    - type: mrr_at_1000
      value: 41.065000000000005
    - type: mrr_at_3
      value: 37.519000000000005
    - type: mrr_at_5
      value: 38.986
    - type: ndcg_at_1
      value: 31.279
    - type: ndcg_at_10
      value: 40.534
    - type: ndcg_at_100
      value: 46.093
    - type: ndcg_at_1000
      value: 48.59
    - type: ndcg_at_3
      value: 35.473
    - type: ndcg_at_5
      value: 37.801
    - type: precision_at_1
      value: 31.279
    - type: precision_at_10
      value: 7.477
    - type: precision_at_100
      value: 1.2
    - type: precision_at_1000
      value: 0.159
    - type: precision_at_3
      value: 17.047
    - type: precision_at_5
      value: 12.306000000000001
    - type: recall_at_1
      value: 24.851
    - type: recall_at_10
      value: 52.528
    - type: recall_at_100
      value: 76.198
    - type: recall_at_1000
      value: 93.12
    - type: recall_at_3
      value: 38.257999999999996
    - type: recall_at_5
      value: 44.440000000000005
    - type: map_at_1
      value: 25.289833333333334
    - type: map_at_10
      value: 34.379333333333335
    - type: map_at_100
      value: 35.56916666666666
    - type: map_at_1000
      value: 35.68633333333333
    - type: map_at_3
      value: 31.63916666666666
    - type: map_at_5
      value: 33.18383333333334
    - type: mrr_at_1
      value: 30.081749999999996
    - type: mrr_at_10
      value: 38.53658333333333
    - type: mrr_at_100
      value: 39.37825
    - type: mrr_at_1000
      value: 39.43866666666666
    - type: mrr_at_3
      value: 36.19025
    - type: mrr_at_5
      value: 37.519749999999995
    - type: ndcg_at_1
      value: 30.081749999999996
    - type: ndcg_at_10
      value: 39.62041666666667
    - type: ndcg_at_100
      value: 44.74825
    - type: ndcg_at_1000
      value: 47.11366666666667
    - type: ndcg_at_3
      value: 35.000499999999995
    - type: ndcg_at_5
      value: 37.19283333333333
    - type: precision_at_1
      value: 30.081749999999996
    - type: precision_at_10
      value: 6.940249999999999
    - type: precision_at_100
      value: 1.1164166666666668
    - type: precision_at_1000
      value: 0.15025000000000002
    - type: precision_at_3
      value: 16.110416666666666
    - type: precision_at_5
      value: 11.474416666666668
    - type: recall_at_1
      value: 25.289833333333334
    - type: recall_at_10
      value: 51.01591666666667
    - type: recall_at_100
      value: 73.55275000000002
    - type: recall_at_1000
      value: 90.02666666666667
    - type: recall_at_3
      value: 38.15208333333334
    - type: recall_at_5
      value: 43.78458333333334
    - type: map_at_1
      value: 23.479
    - type: map_at_10
      value: 31.2
    - type: map_at_100
      value: 32.11
    - type: map_at_1000
      value: 32.214
    - type: map_at_3
      value: 29.093999999999998
    - type: map_at_5
      value: 30.415
    - type: mrr_at_1
      value: 26.840000000000003
    - type: mrr_at_10
      value: 34.153
    - type: mrr_at_100
      value: 34.971000000000004
    - type: mrr_at_1000
      value: 35.047
    - type: mrr_at_3
      value: 32.285000000000004
    - type: mrr_at_5
      value: 33.443
    - type: ndcg_at_1
      value: 26.840000000000003
    - type: ndcg_at_10
      value: 35.441
    - type: ndcg_at_100
      value: 40.150000000000006
    - type: ndcg_at_1000
      value: 42.74
    - type: ndcg_at_3
      value: 31.723000000000003
    - type: ndcg_at_5
      value: 33.71
    - type: precision_at_1
      value: 26.840000000000003
    - type: precision_at_10
      value: 5.552
    - type: precision_at_100
      value: 0.859
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 13.804
    - type: precision_at_5
      value: 9.600999999999999
    - type: recall_at_1
      value: 23.479
    - type: recall_at_10
      value: 45.442
    - type: recall_at_100
      value: 67.465
    - type: recall_at_1000
      value: 86.53
    - type: recall_at_3
      value: 35.315999999999995
    - type: recall_at_5
      value: 40.253
    - type: map_at_1
      value: 16.887
    - type: map_at_10
      value: 23.805
    - type: map_at_100
      value: 24.804000000000002
    - type: map_at_1000
      value: 24.932000000000002
    - type: map_at_3
      value: 21.632
    - type: map_at_5
      value: 22.845
    - type: mrr_at_1
      value: 20.75
    - type: mrr_at_10
      value: 27.686
    - type: mrr_at_100
      value: 28.522
    - type: mrr_at_1000
      value: 28.605000000000004
    - type: mrr_at_3
      value: 25.618999999999996
    - type: mrr_at_5
      value: 26.723999999999997
    - type: ndcg_at_1
      value: 20.75
    - type: ndcg_at_10
      value: 28.233000000000004
    - type: ndcg_at_100
      value: 33.065
    - type: ndcg_at_1000
      value: 36.138999999999996
    - type: ndcg_at_3
      value: 24.361
    - type: ndcg_at_5
      value: 26.111
    - type: precision_at_1
      value: 20.75
    - type: precision_at_10
      value: 5.124
    - type: precision_at_100
      value: 0.8750000000000001
    - type: precision_at_1000
      value: 0.131
    - type: precision_at_3
      value: 11.539000000000001
    - type: precision_at_5
      value: 8.273
    - type: recall_at_1
      value: 16.887
    - type: recall_at_10
      value: 37.774
    - type: recall_at_100
      value: 59.587
    - type: recall_at_1000
      value: 81.523
    - type: recall_at_3
      value: 26.837
    - type: recall_at_5
      value: 31.456
    - type: map_at_1
      value: 25.534000000000002
    - type: map_at_10
      value: 33.495999999999995
    - type: map_at_100
      value: 34.697
    - type: map_at_1000
      value: 34.805
    - type: map_at_3
      value: 31.22
    - type: map_at_5
      value: 32.277
    - type: mrr_at_1
      value: 29.944
    - type: mrr_at_10
      value: 37.723
    - type: mrr_at_100
      value: 38.645
    - type: mrr_at_1000
      value: 38.712999999999994
    - type: mrr_at_3
      value: 35.665
    - type: mrr_at_5
      value: 36.681999999999995
    - type: ndcg_at_1
      value: 29.944
    - type: ndcg_at_10
      value: 38.407000000000004
    - type: ndcg_at_100
      value: 43.877
    - type: ndcg_at_1000
      value: 46.312
    - type: ndcg_at_3
      value: 34.211000000000006
    - type: ndcg_at_5
      value: 35.760999999999996
    - type: precision_at_1
      value: 29.944
    - type: precision_at_10
      value: 6.343
    - type: precision_at_100
      value: 1.023
    - type: precision_at_1000
      value: 0.133
    - type: precision_at_3
      value: 15.360999999999999
    - type: precision_at_5
      value: 10.428999999999998
    - type: recall_at_1
      value: 25.534000000000002
    - type: recall_at_10
      value: 49.204
    - type: recall_at_100
      value: 72.878
    - type: recall_at_1000
      value: 89.95
    - type: recall_at_3
      value: 37.533
    - type: recall_at_5
      value: 41.611
    - type: map_at_1
      value: 26.291999999999998
    - type: map_at_10
      value: 35.245
    - type: map_at_100
      value: 36.762
    - type: map_at_1000
      value: 36.983
    - type: map_at_3
      value: 32.439
    - type: map_at_5
      value: 33.964
    - type: mrr_at_1
      value: 31.423000000000002
    - type: mrr_at_10
      value: 39.98
    - type: mrr_at_100
      value: 40.791
    - type: mrr_at_1000
      value: 40.854
    - type: mrr_at_3
      value: 37.451
    - type: mrr_at_5
      value: 38.854
    - type: ndcg_at_1
      value: 31.423000000000002
    - type: ndcg_at_10
      value: 40.848
    - type: ndcg_at_100
      value: 46.35
    - type: ndcg_at_1000
      value: 49.166
    - type: ndcg_at_3
      value: 36.344
    - type: ndcg_at_5
      value: 38.36
    - type: precision_at_1
      value: 31.423000000000002
    - type: precision_at_10
      value: 7.767
    - type: precision_at_100
      value: 1.498
    - type: precision_at_1000
      value: 0.23700000000000002
    - type: precision_at_3
      value: 16.733
    - type: precision_at_5
      value: 12.213000000000001
    - type: recall_at_1
      value: 26.291999999999998
    - type: recall_at_10
      value: 51.184
    - type: recall_at_100
      value: 76.041
    - type: recall_at_1000
      value: 94.11500000000001
    - type: recall_at_3
      value: 38.257000000000005
    - type: recall_at_5
      value: 43.68
    - type: map_at_1
      value: 20.715
    - type: map_at_10
      value: 27.810000000000002
    - type: map_at_100
      value: 28.810999999999996
    - type: map_at_1000
      value: 28.904999999999998
    - type: map_at_3
      value: 25.069999999999997
    - type: map_at_5
      value: 26.793
    - type: mrr_at_1
      value: 22.366
    - type: mrr_at_10
      value: 29.65
    - type: mrr_at_100
      value: 30.615
    - type: mrr_at_1000
      value: 30.686999999999998
    - type: mrr_at_3
      value: 27.017999999999997
    - type: mrr_at_5
      value: 28.644
    - type: ndcg_at_1
      value: 22.366
    - type: ndcg_at_10
      value: 32.221
    - type: ndcg_at_100
      value: 37.313
    - type: ndcg_at_1000
      value: 39.871
    - type: ndcg_at_3
      value: 26.918
    - type: ndcg_at_5
      value: 29.813000000000002
    - type: precision_at_1
      value: 22.366
    - type: precision_at_10
      value: 5.139
    - type: precision_at_100
      value: 0.8240000000000001
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 11.275
    - type: precision_at_5
      value: 8.540000000000001
    - type: recall_at_1
      value: 20.715
    - type: recall_at_10
      value: 44.023
    - type: recall_at_100
      value: 67.458
    - type: recall_at_1000
      value: 87.066
    - type: recall_at_3
      value: 30.055
    - type: recall_at_5
      value: 36.852000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: 392b78eb68c07badcd7c2cd8f39af108375dfcce
    metrics:
    - type: map_at_1
      value: 11.859
    - type: map_at_10
      value: 20.625
    - type: map_at_100
      value: 22.5
    - type: map_at_1000
      value: 22.689
    - type: map_at_3
      value: 16.991
    - type: map_at_5
      value: 18.781
    - type: mrr_at_1
      value: 26.906000000000002
    - type: mrr_at_10
      value: 39.083
    - type: mrr_at_100
      value: 39.978
    - type: mrr_at_1000
      value: 40.014
    - type: mrr_at_3
      value: 35.44
    - type: mrr_at_5
      value: 37.619
    - type: ndcg_at_1
      value: 26.906000000000002
    - type: ndcg_at_10
      value: 29.386000000000003
    - type: ndcg_at_100
      value: 36.510999999999996
    - type: ndcg_at_1000
      value: 39.814
    - type: ndcg_at_3
      value: 23.558
    - type: ndcg_at_5
      value: 25.557999999999996
    - type: precision_at_1
      value: 26.906000000000002
    - type: precision_at_10
      value: 9.342
    - type: precision_at_100
      value: 1.6969999999999998
    - type: precision_at_1000
      value: 0.231
    - type: precision_at_3
      value: 17.503
    - type: precision_at_5
      value: 13.655000000000001
    - type: recall_at_1
      value: 11.859
    - type: recall_at_10
      value: 35.929
    - type: recall_at_100
      value: 60.21300000000001
    - type: recall_at_1000
      value: 78.606
    - type: recall_at_3
      value: 21.727
    - type: recall_at_5
      value: 27.349
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: f097057d03ed98220bc7309ddb10b71a54d667d6
    metrics:
    - type: map_at_1
      value: 8.627
    - type: map_at_10
      value: 18.248
    - type: map_at_100
      value: 25.19
    - type: map_at_1000
      value: 26.741
    - type: map_at_3
      value: 13.286000000000001
    - type: map_at_5
      value: 15.126000000000001
    - type: mrr_at_1
      value: 64.75
    - type: mrr_at_10
      value: 71.865
    - type: mrr_at_100
      value: 72.247
    - type: mrr_at_1000
      value: 72.255
    - type: mrr_at_3
      value: 69.958
    - type: mrr_at_5
      value: 71.108
    - type: ndcg_at_1
      value: 53.25
    - type: ndcg_at_10
      value: 39.035
    - type: ndcg_at_100
      value: 42.735
    - type: ndcg_at_1000
      value: 50.166
    - type: ndcg_at_3
      value: 43.857
    - type: ndcg_at_5
      value: 40.579
    - type: precision_at_1
      value: 64.75
    - type: precision_at_10
      value: 30.75
    - type: precision_at_100
      value: 9.54
    - type: precision_at_1000
      value: 2.035
    - type: precision_at_3
      value: 47.333
    - type: precision_at_5
      value: 39.0
    - type: recall_at_1
      value: 8.627
    - type: recall_at_10
      value: 23.413
    - type: recall_at_100
      value: 48.037
    - type: recall_at_1000
      value: 71.428
    - type: recall_at_3
      value: 14.158999999999999
    - type: recall_at_5
      value: 17.002
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 829147f8f75a25f005913200eb5ed41fae320aa1
    metrics:
    - type: accuracy
      value: 44.865
    - type: f1
      value: 41.56625743266997
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: 1429cf27e393599b8b359b9b72c666f96b2525f9
    metrics:
    - type: map_at_1
      value: 57.335
    - type: map_at_10
      value: 68.29499999999999
    - type: map_at_100
      value: 68.69800000000001
    - type: map_at_1000
      value: 68.714
    - type: map_at_3
      value: 66.149
    - type: map_at_5
      value: 67.539
    - type: mrr_at_1
      value: 61.656
    - type: mrr_at_10
      value: 72.609
    - type: mrr_at_100
      value: 72.923
    - type: mrr_at_1000
      value: 72.928
    - type: mrr_at_3
      value: 70.645
    - type: mrr_at_5
      value: 71.938
    - type: ndcg_at_1
      value: 61.656
    - type: ndcg_at_10
      value: 73.966
    - type: ndcg_at_100
      value: 75.663
    - type: ndcg_at_1000
      value: 75.986
    - type: ndcg_at_3
      value: 69.959
    - type: ndcg_at_5
      value: 72.269
    - type: precision_at_1
      value: 61.656
    - type: precision_at_10
      value: 9.581000000000001
    - type: precision_at_100
      value: 1.054
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 27.743000000000002
    - type: precision_at_5
      value: 17.939
    - type: recall_at_1
      value: 57.335
    - type: recall_at_10
      value: 87.24300000000001
    - type: recall_at_100
      value: 94.575
    - type: recall_at_1000
      value: 96.75399999999999
    - type: recall_at_3
      value: 76.44800000000001
    - type: recall_at_5
      value: 82.122
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: 41b686a7f28c59bcaaa5791efd47c67c8ebe28be
    metrics:
    - type: map_at_1
      value: 17.014000000000003
    - type: map_at_10
      value: 28.469
    - type: map_at_100
      value: 30.178
    - type: map_at_1000
      value: 30.369
    - type: map_at_3
      value: 24.63
    - type: map_at_5
      value: 26.891
    - type: mrr_at_1
      value: 34.259
    - type: mrr_at_10
      value: 43.042
    - type: mrr_at_100
      value: 43.91
    - type: mrr_at_1000
      value: 43.963
    - type: mrr_at_3
      value: 40.483999999999995
    - type: mrr_at_5
      value: 42.135
    - type: ndcg_at_1
      value: 34.259
    - type: ndcg_at_10
      value: 35.836
    - type: ndcg_at_100
      value: 42.488
    - type: ndcg_at_1000
      value: 45.902
    - type: ndcg_at_3
      value: 32.131
    - type: ndcg_at_5
      value: 33.697
    - type: precision_at_1
      value: 34.259
    - type: precision_at_10
      value: 10.0
    - type: precision_at_100
      value: 1.699
    - type: precision_at_1000
      value: 0.22999999999999998
    - type: precision_at_3
      value: 21.502
    - type: precision_at_5
      value: 16.296
    - type: recall_at_1
      value: 17.014000000000003
    - type: recall_at_10
      value: 42.832
    - type: recall_at_100
      value: 67.619
    - type: recall_at_1000
      value: 88.453
    - type: recall_at_3
      value: 29.537000000000003
    - type: recall_at_5
      value: 35.886
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: 766870b35a1b9ca65e67a0d1913899973551fc6c
    metrics:
    - type: map_at_1
      value: 34.558
    - type: map_at_10
      value: 48.039
    - type: map_at_100
      value: 48.867
    - type: map_at_1000
      value: 48.941
    - type: map_at_3
      value: 45.403
    - type: map_at_5
      value: 46.983999999999995
    - type: mrr_at_1
      value: 69.11500000000001
    - type: mrr_at_10
      value: 75.551
    - type: mrr_at_100
      value: 75.872
    - type: mrr_at_1000
      value: 75.887
    - type: mrr_at_3
      value: 74.447
    - type: mrr_at_5
      value: 75.113
    - type: ndcg_at_1
      value: 69.11500000000001
    - type: ndcg_at_10
      value: 57.25599999999999
    - type: ndcg_at_100
      value: 60.417
    - type: ndcg_at_1000
      value: 61.976
    - type: ndcg_at_3
      value: 53.258
    - type: ndcg_at_5
      value: 55.374
    - type: precision_at_1
      value: 69.11500000000001
    - type: precision_at_10
      value: 11.689
    - type: precision_at_100
      value: 1.418
    - type: precision_at_1000
      value: 0.163
    - type: precision_at_3
      value: 33.018
    - type: precision_at_5
      value: 21.488
    - type: recall_at_1
      value: 34.558
    - type: recall_at_10
      value: 58.447
    - type: recall_at_100
      value: 70.91199999999999
    - type: recall_at_1000
      value: 81.31
    - type: recall_at_3
      value: 49.527
    - type: recall_at_5
      value: 53.72
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 8d743909f834c38949e8323a8a6ce8721ea6c7f4
    metrics:
    - type: accuracy
      value: 61.772000000000006
    - type: ap
      value: 57.48217702943605
    - type: f1
      value: 61.20495351356274
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: validation
      revision: e6838a846e2408f22cf5cc337ebc83e0bcf77849
    metrics:
    - type: map_at_1
      value: 22.044
    - type: map_at_10
      value: 34.211000000000006
    - type: map_at_100
      value: 35.394
    - type: map_at_1000
      value: 35.443000000000005
    - type: map_at_3
      value: 30.318
    - type: map_at_5
      value: 32.535
    - type: mrr_at_1
      value: 22.722
    - type: mrr_at_10
      value: 34.842
    - type: mrr_at_100
      value: 35.954
    - type: mrr_at_1000
      value: 35.997
    - type: mrr_at_3
      value: 30.991000000000003
    - type: mrr_at_5
      value: 33.2
    - type: ndcg_at_1
      value: 22.722
    - type: ndcg_at_10
      value: 41.121
    - type: ndcg_at_100
      value: 46.841
    - type: ndcg_at_1000
      value: 48.049
    - type: ndcg_at_3
      value: 33.173
    - type: ndcg_at_5
      value: 37.145
    - type: precision_at_1
      value: 22.722
    - type: precision_at_10
      value: 6.516
    - type: precision_at_100
      value: 0.9400000000000001
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.093
    - type: precision_at_5
      value: 10.473
    - type: recall_at_1
      value: 22.044
    - type: recall_at_10
      value: 62.382000000000005
    - type: recall_at_100
      value: 88.914
    - type: recall_at_1000
      value: 98.099
    - type: recall_at_3
      value: 40.782000000000004
    - type: recall_at_5
      value: 50.322
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 93.68217054263563
    - type: f1
      value: 93.25810075739523
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (de)
      type: mteb/mtop_domain
      config: de
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 82.05409974640745
    - type: f1
      value: 80.42814140324903
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (es)
      type: mteb/mtop_domain
      config: es
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 93.54903268845896
    - type: f1
      value: 92.8909878077932
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 90.98340119010334
    - type: f1
      value: 90.51522537281313
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (hi)
      type: mteb/mtop_domain
      config: hi
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 89.33309429903191
    - type: f1
      value: 88.60371305209185
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (th)
      type: mteb/mtop_domain
      config: th
      split: test
      revision: a7e2a951126a26fc8c6a69f835f33a346ba259e3
    metrics:
    - type: accuracy
      value: 60.4882459312839
    - type: f1
      value: 59.02590456131682
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 71.34290925672595
    - type: f1
      value: 54.44803151449109
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (de)
      type: mteb/mtop_intent
      config: de
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 61.92448577063963
    - type: f1
      value: 43.125939975781854
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (es)
      type: mteb/mtop_intent
      config: es
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 74.48965977318213
    - type: f1
      value: 51.855353687466696
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 69.11994989038521
    - type: f1
      value: 50.57872704171278
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (hi)
      type: mteb/mtop_intent
      config: hi
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 64.84761563284331
    - type: f1
      value: 43.61322970761394
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (th)
      type: mteb/mtop_intent
      config: th
      split: test
      revision: 6299947a7777084cc2d4b64235bf7190381ce755
    metrics:
    - type: accuracy
      value: 49.35623869801085
    - type: f1
      value: 33.48547326952042
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (af)
      type: mteb/amazon_massive_intent
      config: af
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 47.85474108944183
    - type: f1
      value: 46.50175016795915
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (am)
      type: mteb/amazon_massive_intent
      config: am
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 33.29858776059179
    - type: f1
      value: 31.803027601259082
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ar)
      type: mteb/amazon_massive_intent
      config: ar
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 59.24680564895763
    - type: f1
      value: 57.037691806846865
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (az)
      type: mteb/amazon_massive_intent
      config: az
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 45.23537323470073
    - type: f1
      value: 44.81126398428613
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (bn)
      type: mteb/amazon_massive_intent
      config: bn
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 61.590450571620714
    - type: f1
      value: 59.247442149977104
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (cy)
      type: mteb/amazon_massive_intent
      config: cy
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 44.9226630800269
    - type: f1
      value: 44.076183379991654
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (da)
      type: mteb/amazon_massive_intent
      config: da
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 51.23066577000672
    - type: f1
      value: 50.20719330417618
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (de)
      type: mteb/amazon_massive_intent
      config: de
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 56.0995292535306
    - type: f1
      value: 53.29421532133969
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (el)
      type: mteb/amazon_massive_intent
      config: el
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 46.12642905178211
    - type: f1
      value: 44.441530267639635
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 69.67047747141896
    - type: f1
      value: 68.38493366054783
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (es)
      type: mteb/amazon_massive_intent
      config: es
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 66.3483523873571
    - type: f1
      value: 65.13046416817832
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fa)
      type: mteb/amazon_massive_intent
      config: fa
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 51.20040349697378
    - type: f1
      value: 49.02889836601541
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fi)
      type: mteb/amazon_massive_intent
      config: fi
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 45.33288500336248
    - type: f1
      value: 42.91893101970983
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 66.95359784801613
    - type: f1
      value: 64.98788914810562
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (he)
      type: mteb/amazon_massive_intent
      config: he
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 43.18090114324143
    - type: f1
      value: 41.31250407417542
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hi)
      type: mteb/amazon_massive_intent
      config: hi
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 63.54068594485541
    - type: f1
      value: 61.94829361488948
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hu)
      type: mteb/amazon_massive_intent
      config: hu
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 44.7343644922663
    - type: f1
      value: 43.23001702247849
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hy)
      type: mteb/amazon_massive_intent
      config: hy
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 38.1271015467384
    - type: f1
      value: 36.94700198241727
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (id)
      type: mteb/amazon_massive_intent
      config: id
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 64.05514458641561
    - type: f1
      value: 62.35033731674541
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (is)
      type: mteb/amazon_massive_intent
      config: is
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 44.351042367182245
    - type: f1
      value: 43.13370397574502
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (it)
      type: mteb/amazon_massive_intent
      config: it
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 60.77000672494955
    - type: f1
      value: 59.71546868957779
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ja)
      type: mteb/amazon_massive_intent
      config: ja
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 61.22057834566241
    - type: f1
      value: 59.447639306287044
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (jv)
      type: mteb/amazon_massive_intent
      config: jv
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 50.9448554135844
    - type: f1
      value: 48.524338247875214
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ka)
      type: mteb/amazon_massive_intent
      config: ka
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 33.8399462004035
    - type: f1
      value: 33.518999997305535
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (km)
      type: mteb/amazon_massive_intent
      config: km
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 37.34028244788165
    - type: f1
      value: 35.6156599064704
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (kn)
      type: mteb/amazon_massive_intent
      config: kn
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 53.544048419636844
    - type: f1
      value: 51.29299915455352
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ko)
      type: mteb/amazon_massive_intent
      config: ko
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 53.35574983187625
    - type: f1
      value: 51.463936565192945
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (lv)
      type: mteb/amazon_massive_intent
      config: lv
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 46.503026227303295
    - type: f1
      value: 46.049497734375514
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ml)
      type: mteb/amazon_massive_intent
      config: ml
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 58.268325487558826
    - type: f1
      value: 56.10849656896158
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (mn)
      type: mteb/amazon_massive_intent
      config: mn
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 40.27572293207801
    - type: f1
      value: 40.20097238549224
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ms)
      type: mteb/amazon_massive_intent
      config: ms
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 59.64694014794889
    - type: f1
      value: 58.39584148789066
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (my)
      type: mteb/amazon_massive_intent
      config: my
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 37.41761936785474
    - type: f1
      value: 35.04551731363685
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (nb)
      type: mteb/amazon_massive_intent
      config: nb
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 49.408204438466704
    - type: f1
      value: 48.39369057638714
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (nl)
      type: mteb/amazon_massive_intent
      config: nl
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 52.09482178883659
    - type: f1
      value: 49.91518031712698
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (pl)
      type: mteb/amazon_massive_intent
      config: pl
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 50.477471418964356
    - type: f1
      value: 48.429495257184705
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (pt)
      type: mteb/amazon_massive_intent
      config: pt
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 66.69468728984532
    - type: f1
      value: 65.40306868707009
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ro)
      type: mteb/amazon_massive_intent
      config: ro
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 50.52790854068594
    - type: f1
      value: 49.780400354514
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ru)
      type: mteb/amazon_massive_intent
      config: ru
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 58.31540013449899
    - type: f1
      value: 56.144142926685134
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (sl)
      type: mteb/amazon_massive_intent
      config: sl
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 47.74041694687289
    - type: f1
      value: 46.16767322761359
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (sq)
      type: mteb/amazon_massive_intent
      config: sq
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 48.94418291862811
    - type: f1
      value: 48.445352284756325
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (sv)
      type: mteb/amazon_massive_intent
      config: sv
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 50.78681909885676
    - type: f1
      value: 49.64882295494536
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (sw)
      type: mteb/amazon_massive_intent
      config: sw
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 49.811701412239415
    - type: f1
      value: 48.213234514449375
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ta)
      type: mteb/amazon_massive_intent
      config: ta
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 56.39542703429725
    - type: f1
      value: 54.031981085233795
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (te)
      type: mteb/amazon_massive_intent
      config: te
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 54.71082716879623
    - type: f1
      value: 52.513144113474596
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (th)
      type: mteb/amazon_massive_intent
      config: th
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 44.425016812373904
    - type: f1
      value: 43.96016300057656
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (tl)
      type: mteb/amazon_massive_intent
      config: tl
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 50.205110961667785
    - type: f1
      value: 48.86669996798709
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (tr)
      type: mteb/amazon_massive_intent
      config: tr
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 46.56355077336921
    - type: f1
      value: 45.18252022585022
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ur)
      type: mteb/amazon_massive_intent
      config: ur
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 56.748486886348346
    - type: f1
      value: 54.29884570375382
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (vi)
      type: mteb/amazon_massive_intent
      config: vi
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 64.52589105581708
    - type: f1
      value: 62.97947342861603
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-CN)
      type: mteb/amazon_massive_intent
      config: zh-CN
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 67.06792199058508
    - type: f1
      value: 65.36025601634017
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (zh-TW)
      type: mteb/amazon_massive_intent
      config: zh-TW
      split: test
      revision: 072a486a144adf7f4479a4a0dddb2152e161e1ea
    metrics:
    - type: accuracy
      value: 62.89172831203766
    - type: f1
      value: 62.69803707054342
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (af)
      type: mteb/amazon_massive_scenario
      config: af
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 51.47276395427035
    - type: f1
      value: 49.37463208130799
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (am)
      type: mteb/amazon_massive_scenario
      config: am
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 34.86886348352387
    - type: f1
      value: 33.74178074349636
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ar)
      type: mteb/amazon_massive_scenario
      config: ar
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.20511096166778
    - type: f1
      value: 65.85812500602437
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (az)
      type: mteb/amazon_massive_scenario
      config: az
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 45.578345662407536
    - type: f1
      value: 44.44514917028003
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (bn)
      type: mteb/amazon_massive_scenario
      config: bn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.29657027572293
    - type: f1
      value: 67.24477523937466
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (cy)
      type: mteb/amazon_massive_scenario
      config: cy
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 46.29455279085407
    - type: f1
      value: 43.8563839951935
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (da)
      type: mteb/amazon_massive_scenario
      config: da
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 53.52387357094821
    - type: f1
      value: 51.70977848027552
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (de)
      type: mteb/amazon_massive_scenario
      config: de
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 61.741761936785466
    - type: f1
      value: 60.219169644792295
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (el)
      type: mteb/amazon_massive_scenario
      config: el
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 48.957632817753876
    - type: f1
      value: 46.878428264460034
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 75.33624747814393
    - type: f1
      value: 75.9143846211171
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (es)
      type: mteb/amazon_massive_scenario
      config: es
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.34229993275049
    - type: f1
      value: 73.78165397558983
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fa)
      type: mteb/amazon_massive_scenario
      config: fa
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 53.174176193678555
    - type: f1
      value: 51.709679227778985
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fi)
      type: mteb/amazon_massive_scenario
      config: fi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 44.6906523201076
    - type: f1
      value: 41.54881682785664
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (fr)
      type: mteb/amazon_massive_scenario
      config: fr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 72.9119031607263
    - type: f1
      value: 73.2742013056326
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (he)
      type: mteb/amazon_massive_scenario
      config: he
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 43.10356422326832
    - type: f1
      value: 40.8859122581252
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (hi)
      type: mteb/amazon_massive_scenario
      config: hi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 69.27370544720914
    - type: f1
      value: 69.39544506405082
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (hu)
      type: mteb/amazon_massive_scenario
      config: hu
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 45.16476126429052
    - type: f1
      value: 42.74022531579054
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (hy)
      type: mteb/amazon_massive_scenario
      config: hy
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 38.73234700739744
    - type: f1
      value: 37.40546754951026
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (id)
      type: mteb/amazon_massive_scenario
      config: id
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.12777404169468
    - type: f1
      value: 70.27219152812738
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (is)
      type: mteb/amazon_massive_scenario
      config: is
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 44.21318090114325
    - type: f1
      value: 41.934593213829366
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (it)
      type: mteb/amazon_massive_scenario
      config: it
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.57162071284466
    - type: f1
      value: 64.83341759045335
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ja)
      type: mteb/amazon_massive_scenario
      config: ja
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.75991930060525
    - type: f1
      value: 65.16549875504951
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (jv)
      type: mteb/amazon_massive_scenario
      config: jv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 54.79488903833223
    - type: f1
      value: 54.03616401426859
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ka)
      type: mteb/amazon_massive_scenario
      config: ka
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 32.992602555480836
    - type: f1
      value: 31.820068470018846
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (km)
      type: mteb/amazon_massive_scenario
      config: km
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 39.34431741761937
    - type: f1
      value: 36.436221665290105
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (kn)
      type: mteb/amazon_massive_scenario
      config: kn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 60.501008742434436
    - type: f1
      value: 60.051013712579085
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ko)
      type: mteb/amazon_massive_scenario
      config: ko
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 55.689307330195035
    - type: f1
      value: 53.94058032286942
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (lv)
      type: mteb/amazon_massive_scenario
      config: lv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 44.351042367182245
    - type: f1
      value: 42.05421666771541
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ml)
      type: mteb/amazon_massive_scenario
      config: ml
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 65.53127101546738
    - type: f1
      value: 65.98462024333497
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (mn)
      type: mteb/amazon_massive_scenario
      config: mn
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 38.71553463349025
    - type: f1
      value: 37.44327037149584
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ms)
      type: mteb/amazon_massive_scenario
      config: ms
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.98991257565567
    - type: f1
      value: 63.87720198978004
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (my)
      type: mteb/amazon_massive_scenario
      config: my
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 36.839273705447205
    - type: f1
      value: 35.233967279698376
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (nb)
      type: mteb/amazon_massive_scenario
      config: nb
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 51.79892400806993
    - type: f1
      value: 49.66926632125972
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (nl)
      type: mteb/amazon_massive_scenario
      config: nl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 56.31809011432415
    - type: f1
      value: 53.832185336179826
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (pl)
      type: mteb/amazon_massive_scenario
      config: pl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 49.979825151311374
    - type: f1
      value: 48.83013175441888
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (pt)
      type: mteb/amazon_massive_scenario
      config: pt
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.45595158036315
    - type: f1
      value: 72.08708814699702
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ro)
      type: mteb/amazon_massive_scenario
      config: ro
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 53.68527236045729
    - type: f1
      value: 52.23278593929981
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ru)
      type: mteb/amazon_massive_scenario
      config: ru
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 61.60390047074647
    - type: f1
      value: 60.50391482195116
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sl)
      type: mteb/amazon_massive_scenario
      config: sl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 48.036314727639535
    - type: f1
      value: 46.43480413383716
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sq)
      type: mteb/amazon_massive_scenario
      config: sq
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 50.05716207128445
    - type: f1
      value: 48.85821859948888
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sv)
      type: mteb/amazon_massive_scenario
      config: sv
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 51.728312037659705
    - type: f1
      value: 49.89292996950847
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (sw)
      type: mteb/amazon_massive_scenario
      config: sw
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 54.21990585070613
    - type: f1
      value: 52.8711542984193
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ta)
      type: mteb/amazon_massive_scenario
      config: ta
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 62.770679219905844
    - type: f1
      value: 63.09441501491594
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (te)
      type: mteb/amazon_massive_scenario
      config: te
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 62.58574310692671
    - type: f1
      value: 61.61370697612978
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (th)
      type: mteb/amazon_massive_scenario
      config: th
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 45.17821116341628
    - type: f1
      value: 43.85143229183324
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tl)
      type: mteb/amazon_massive_scenario
      config: tl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 52.064559515803644
    - type: f1
      value: 50.94356892049626
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tr)
      type: mteb/amazon_massive_scenario
      config: tr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 47.205783456624076
    - type: f1
      value: 47.04223644120489
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ur)
      type: mteb/amazon_massive_scenario
      config: ur
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 64.25689307330195
    - type: f1
      value: 63.89944944984115
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (vi)
      type: mteb/amazon_massive_scenario
      config: vi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.60524546065905
    - type: f1
      value: 71.5634157334358
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-CN)
      type: mteb/amazon_massive_scenario
      config: zh-CN
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.95427034297242
    - type: f1
      value: 74.39706882311063
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (zh-TW)
      type: mteb/amazon_massive_scenario
      config: zh-TW
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.29926025554808
    - type: f1
      value: 71.32045932560297
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: dcefc037ef84348e49b0d29109e891c01067226b
    metrics:
    - type: v_measure
      value: 31.054474964883806
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 3cd0e71dfbe09d4de0f9e5ecba43e7ce280959dc
    metrics:
    - type: v_measure
      value: 29.259725940477523
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 31.785007883256572
    - type: mrr
      value: 32.983556622438456
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: 7eb63cc0c1eb59324d709ebed25fcab851fa7610
    metrics:
    - type: map_at_1
      value: 5.742
    - type: map_at_10
      value: 13.074
    - type: map_at_100
      value: 16.716
    - type: map_at_1000
      value: 18.238
    - type: map_at_3
      value: 9.600999999999999
    - type: map_at_5
      value: 11.129999999999999
    - type: mrr_at_1
      value: 47.988
    - type: mrr_at_10
      value: 55.958
    - type: mrr_at_100
      value: 56.58800000000001
    - type: mrr_at_1000
      value: 56.620000000000005
    - type: mrr_at_3
      value: 54.025
    - type: mrr_at_5
      value: 55.31
    - type: ndcg_at_1
      value: 46.44
    - type: ndcg_at_10
      value: 35.776
    - type: ndcg_at_100
      value: 32.891999999999996
    - type: ndcg_at_1000
      value: 41.835
    - type: ndcg_at_3
      value: 41.812
    - type: ndcg_at_5
      value: 39.249
    - type: precision_at_1
      value: 48.297000000000004
    - type: precision_at_10
      value: 26.687
    - type: precision_at_100
      value: 8.511000000000001
    - type: precision_at_1000
      value: 2.128
    - type: precision_at_3
      value: 39.009
    - type: precision_at_5
      value: 33.994
    - type: recall_at_1
      value: 5.742
    - type: recall_at_10
      value: 16.993
    - type: recall_at_100
      value: 33.69
    - type: recall_at_1000
      value: 66.75
    - type: recall_at_3
      value: 10.817
    - type: recall_at_5
      value: 13.256
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: 6062aefc120bfe8ece5897809fb2e53bfe0d128c
    metrics:
    - type: map_at_1
      value: 30.789
    - type: map_at_10
      value: 45.751999999999995
    - type: map_at_100
      value: 46.766000000000005
    - type: map_at_1000
      value: 46.798
    - type: map_at_3
      value: 41.746
    - type: map_at_5
      value: 44.046
    - type: mrr_at_1
      value: 34.618
    - type: mrr_at_10
      value: 48.288
    - type: mrr_at_100
      value: 49.071999999999996
    - type: mrr_at_1000
      value: 49.094
    - type: mrr_at_3
      value: 44.979
    - type: mrr_at_5
      value: 46.953
    - type: ndcg_at_1
      value: 34.589
    - type: ndcg_at_10
      value: 53.151
    - type: ndcg_at_100
      value: 57.537000000000006
    - type: ndcg_at_1000
      value: 58.321999999999996
    - type: ndcg_at_3
      value: 45.628
    - type: ndcg_at_5
      value: 49.474000000000004
    - type: precision_at_1
      value: 34.589
    - type: precision_at_10
      value: 8.731
    - type: precision_at_100
      value: 1.119
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 20.819
    - type: precision_at_5
      value: 14.728
    - type: recall_at_1
      value: 30.789
    - type: recall_at_10
      value: 73.066
    - type: recall_at_100
      value: 92.27
    - type: recall_at_1000
      value: 98.18
    - type: recall_at_3
      value: 53.632999999999996
    - type: recall_at_5
      value: 62.476
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: 6205996560df11e3a3da9ab4f926788fc30a7db4
    metrics:
    - type: map_at_1
      value: 54.993
    - type: map_at_10
      value: 69.07600000000001
    - type: map_at_100
      value: 70.05799999999999
    - type: map_at_1000
      value: 70.09
    - type: map_at_3
      value: 65.456
    - type: map_at_5
      value: 67.622
    - type: mrr_at_1
      value: 63.07000000000001
    - type: mrr_at_10
      value: 72.637
    - type: mrr_at_100
      value: 73.029
    - type: mrr_at_1000
      value: 73.033
    - type: mrr_at_3
      value: 70.572
    - type: mrr_at_5
      value: 71.86399999999999
    - type: ndcg_at_1
      value: 63.07000000000001
    - type: ndcg_at_10
      value: 74.708
    - type: ndcg_at_100
      value: 77.579
    - type: ndcg_at_1000
      value: 77.897
    - type: ndcg_at_3
      value: 69.69999999999999
    - type: ndcg_at_5
      value: 72.321
    - type: precision_at_1
      value: 63.07000000000001
    - type: precision_at_10
      value: 11.851
    - type: precision_at_100
      value: 1.481
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 30.747000000000003
    - type: precision_at_5
      value: 20.830000000000002
    - type: recall_at_1
      value: 54.993
    - type: recall_at_10
      value: 87.18900000000001
    - type: recall_at_100
      value: 98.137
    - type: recall_at_1000
      value: 99.833
    - type: recall_at_3
      value: 73.654
    - type: recall_at_5
      value: 80.36
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: b2805658ae38990172679479369a78b86de8c390
    metrics:
    - type: v_measure
      value: 35.53178375429036
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 54.520782970558265
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: 5c59ef3e437a0a9651c8fe6fde943e7dce59fba5
    metrics:
    - type: map_at_1
      value: 4.3229999999999995
    - type: map_at_10
      value: 10.979999999999999
    - type: map_at_100
      value: 12.867
    - type: map_at_1000
      value: 13.147
    - type: map_at_3
      value: 7.973
    - type: map_at_5
      value: 9.513
    - type: mrr_at_1
      value: 21.3
    - type: mrr_at_10
      value: 32.34
    - type: mrr_at_100
      value: 33.428999999999995
    - type: mrr_at_1000
      value: 33.489999999999995
    - type: mrr_at_3
      value: 28.999999999999996
    - type: mrr_at_5
      value: 31.019999999999996
    - type: ndcg_at_1
      value: 21.3
    - type: ndcg_at_10
      value: 18.619
    - type: ndcg_at_100
      value: 26.108999999999998
    - type: ndcg_at_1000
      value: 31.253999999999998
    - type: ndcg_at_3
      value: 17.842
    - type: ndcg_at_5
      value: 15.673
    - type: precision_at_1
      value: 21.3
    - type: precision_at_10
      value: 9.55
    - type: precision_at_100
      value: 2.0340000000000003
    - type: precision_at_1000
      value: 0.327
    - type: precision_at_3
      value: 16.667
    - type: precision_at_5
      value: 13.76
    - type: recall_at_1
      value: 4.3229999999999995
    - type: recall_at_10
      value: 19.387
    - type: recall_at_100
      value: 41.307
    - type: recall_at_1000
      value: 66.475
    - type: recall_at_3
      value: 10.143
    - type: recall_at_5
      value: 14.007
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 78.77975189382573
    - type: cos_sim_spearman
      value: 69.81522686267631
    - type: euclidean_pearson
      value: 71.37617936889518
    - type: euclidean_spearman
      value: 65.71738481148611
    - type: manhattan_pearson
      value: 71.58222165832424
    - type: manhattan_spearman
      value: 65.86851365286654
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: fdf84275bb8ce4b49c971d02e84dd1abc677a50f
    metrics:
    - type: cos_sim_pearson
      value: 77.75509450443367
    - type: cos_sim_spearman
      value: 69.66180222442091
    - type: euclidean_pearson
      value: 74.98512779786111
    - type: euclidean_spearman
      value: 69.5997451409469
    - type: manhattan_pearson
      value: 75.50135090962459
    - type: manhattan_spearman
      value: 69.94984748475302
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 1591bfcbe8c69d4bf7fe2a16e2451017832cafb9
    metrics:
    - type: cos_sim_pearson
      value: 79.42363892383264
    - type: cos_sim_spearman
      value: 79.66529244176742
    - type: euclidean_pearson
      value: 79.50429208135942
    - type: euclidean_spearman
      value: 80.44767586416276
    - type: manhattan_pearson
      value: 79.58563944997708
    - type: manhattan_spearman
      value: 80.51452267103
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: e2125984e7df8b7871f6ae9949cf6b6795e7c54b
    metrics:
    - type: cos_sim_pearson
      value: 79.2749401478149
    - type: cos_sim_spearman
      value: 74.6076920702392
    - type: euclidean_pearson
      value: 73.3302002952881
    - type: euclidean_spearman
      value: 70.67029803077013
    - type: manhattan_pearson
      value: 73.52699344010296
    - type: manhattan_spearman
      value: 70.8517556194297
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: 1cd7298cac12a96a373b6a2f18738bb3e739a9b6
    metrics:
    - type: cos_sim_pearson
      value: 83.20884740785921
    - type: cos_sim_spearman
      value: 83.80600789090722
    - type: euclidean_pearson
      value: 74.9154089816344
    - type: euclidean_spearman
      value: 75.69243899592276
    - type: manhattan_pearson
      value: 75.0312832634451
    - type: manhattan_spearman
      value: 75.78324960357642
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 360a0b2dff98700d09e634a01e1cc1624d3e42cd
    metrics:
    - type: cos_sim_pearson
      value: 79.63194141000497
    - type: cos_sim_spearman
      value: 80.40118418350866
    - type: euclidean_pearson
      value: 72.07354384551088
    - type: euclidean_spearman
      value: 72.28819150373845
    - type: manhattan_pearson
      value: 72.08736119834145
    - type: manhattan_spearman
      value: 72.28347083261288
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 66.78512789499386
    - type: cos_sim_spearman
      value: 66.89125587193288
    - type: euclidean_pearson
      value: 58.74535708627959
    - type: euclidean_spearman
      value: 59.62103716794647
    - type: manhattan_pearson
      value: 59.00494529143961
    - type: manhattan_spearman
      value: 59.832257846799806
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 75.48960503523992
    - type: cos_sim_spearman
      value: 76.4223037534204
    - type: euclidean_pearson
      value: 64.93966381820944
    - type: euclidean_spearman
      value: 62.39697395373789
    - type: manhattan_pearson
      value: 65.54480770061505
    - type: manhattan_spearman
      value: 62.944204863043105
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 77.7331440643619
    - type: cos_sim_spearman
      value: 78.0748413292835
    - type: euclidean_pearson
      value: 38.533108233460304
    - type: euclidean_spearman
      value: 35.37638615280026
    - type: manhattan_pearson
      value: 41.0639726746513
    - type: manhattan_spearman
      value: 37.688161243671765
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 58.4628923720782
    - type: cos_sim_spearman
      value: 59.10093128795948
    - type: euclidean_pearson
      value: 30.422902393436836
    - type: euclidean_spearman
      value: 27.837806030497457
    - type: manhattan_pearson
      value: 32.51576984630963
    - type: manhattan_spearman
      value: 29.181887010982514
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 86.87447904613737
    - type: cos_sim_spearman
      value: 87.06554974065622
    - type: euclidean_pearson
      value: 76.82669047851108
    - type: euclidean_spearman
      value: 75.45711985511991
    - type: manhattan_pearson
      value: 77.46644556452847
    - type: manhattan_spearman
      value: 76.0249120007112
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 17.784495723497468
    - type: cos_sim_spearman
      value: 11.79629537128697
    - type: euclidean_pearson
      value: -4.354328445994008
    - type: euclidean_spearman
      value: -6.984566116230058
    - type: manhattan_pearson
      value: -4.166751901507852
    - type: manhattan_spearman
      value: -6.984143198323786
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 76.9009642643449
    - type: cos_sim_spearman
      value: 78.21764726338341
    - type: euclidean_pearson
      value: 50.578959144342925
    - type: euclidean_spearman
      value: 51.664379260719606
    - type: manhattan_pearson
      value: 53.95690880393329
    - type: manhattan_spearman
      value: 54.910058464050785
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 86.41638022270219
    - type: cos_sim_spearman
      value: 86.00477030366811
    - type: euclidean_pearson
      value: 79.7224037788285
    - type: euclidean_spearman
      value: 79.21417626867616
    - type: manhattan_pearson
      value: 80.29412412756984
    - type: manhattan_spearman
      value: 79.49460867616206
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 79.90432664091082
    - type: cos_sim_spearman
      value: 80.46007940700204
    - type: euclidean_pearson
      value: 49.25348015214428
    - type: euclidean_spearman
      value: 47.13113020475859
    - type: manhattan_pearson
      value: 54.57291204043908
    - type: manhattan_spearman
      value: 51.98559736896087
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 52.55164822309034
    - type: cos_sim_spearman
      value: 51.57629192137736
    - type: euclidean_pearson
      value: 16.63360593235354
    - type: euclidean_spearman
      value: 14.479679923782912
    - type: manhattan_pearson
      value: 18.524867185117472
    - type: manhattan_spearman
      value: 16.65940056664755
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: 9fc37e8c632af1c87a3d23e685d49552a02582a0
    metrics:
    - type: cos_sim_pearson
      value: 46.83690919715875
    - type: cos_sim_spearman
      value: 45.84993650002922
    - type: euclidean_pearson
      value: 6.173128686815117
    - type: euclidean_spearman
      value: 6.260781946306191
    - type: manhattan_pearson
      value: 7.328440452367316
    - type: manhattan_spearman
      value: 7.370842306497447
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 64.97916914277232
    - type: cos_sim_spearman
      value: 66.13392188807865
    - type: euclidean_pearson
      value: 65.3921146908468
    - type: euclidean_spearman
      value: 65.8381588635056
    - type: manhattan_pearson
      value: 65.8866165769975
    - type: manhattan_spearman
      value: 66.27774050472219
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 25.605130445111545
    - type: cos_sim_spearman
      value: 30.054844562369254
    - type: euclidean_pearson
      value: 23.890611005408196
    - type: euclidean_spearman
      value: 29.07902600726761
    - type: manhattan_pearson
      value: 24.239478426621833
    - type: manhattan_spearman
      value: 29.48547576782375
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 61.6665616159781
    - type: cos_sim_spearman
      value: 65.41310206289988
    - type: euclidean_pearson
      value: 68.38805493215008
    - type: euclidean_spearman
      value: 65.22777377603435
    - type: manhattan_pearson
      value: 69.37445390454346
    - type: manhattan_spearman
      value: 66.02437701858754
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 15.302891825626372
    - type: cos_sim_spearman
      value: 31.134517255070097
    - type: euclidean_pearson
      value: 12.672592658843143
    - type: euclidean_spearman
      value: 29.14881036784207
    - type: manhattan_pearson
      value: 13.528545327757735
    - type: manhattan_spearman
      value: 29.56217928148797
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (tr)
      type: mteb/sts22-crosslingual-sts
      config: tr
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 28.79299114515319
    - type: cos_sim_spearman
      value: 47.135864983626206
    - type: euclidean_pearson
      value: 40.66410787594309
    - type: euclidean_spearman
      value: 45.09585593138228
    - type: manhattan_pearson
      value: 42.02561630700308
    - type: manhattan_spearman
      value: 45.43979983670554
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ar)
      type: mteb/sts22-crosslingual-sts
      config: ar
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 46.00096625052943
    - type: cos_sim_spearman
      value: 58.67147426715496
    - type: euclidean_pearson
      value: 54.7154367422438
    - type: euclidean_spearman
      value: 59.003235142442634
    - type: manhattan_pearson
      value: 56.3116235357115
    - type: manhattan_spearman
      value: 60.12956331404423
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 29.3396354650316
    - type: cos_sim_spearman
      value: 43.3632935734809
    - type: euclidean_pearson
      value: 31.18506539466593
    - type: euclidean_spearman
      value: 37.531745324803815
    - type: manhattan_pearson
      value: 32.829038232529015
    - type: manhattan_spearman
      value: 38.04574361589953
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 62.9596148375188
    - type: cos_sim_spearman
      value: 66.77653412402461
    - type: euclidean_pearson
      value: 64.53156585980886
    - type: euclidean_spearman
      value: 66.2884373036083
    - type: manhattan_pearson
      value: 65.2831035495143
    - type: manhattan_spearman
      value: 66.83641945244322
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 79.9138821493919
    - type: cos_sim_spearman
      value: 80.38097535004677
    - type: euclidean_pearson
      value: 76.2401499094322
    - type: euclidean_spearman
      value: 77.00897050735907
    - type: manhattan_pearson
      value: 76.69531453728563
    - type: manhattan_spearman
      value: 77.83189696428695
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 51.27009640779202
    - type: cos_sim_spearman
      value: 51.16120562029285
    - type: euclidean_pearson
      value: 52.20594985566323
    - type: euclidean_spearman
      value: 52.75331049709882
    - type: manhattan_pearson
      value: 52.2725118792549
    - type: manhattan_spearman
      value: 53.614847968995115
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 70.46044814118835
    - type: cos_sim_spearman
      value: 75.05760236668672
    - type: euclidean_pearson
      value: 72.80128921879461
    - type: euclidean_spearman
      value: 73.81164755219257
    - type: manhattan_pearson
      value: 72.7863795809044
    - type: manhattan_spearman
      value: 73.65932033818906
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (it)
      type: mteb/sts22-crosslingual-sts
      config: it
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 61.89276840435938
    - type: cos_sim_spearman
      value: 65.65042955732055
    - type: euclidean_pearson
      value: 61.22969491863841
    - type: euclidean_spearman
      value: 63.451215637904724
    - type: manhattan_pearson
      value: 61.16138956945465
    - type: manhattan_spearman
      value: 63.34966179331079
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 56.377577221753626
    - type: cos_sim_spearman
      value: 53.31223653270353
    - type: euclidean_pearson
      value: 26.488793041564307
    - type: euclidean_spearman
      value: 19.524551741701472
    - type: manhattan_pearson
      value: 24.322868054606474
    - type: manhattan_spearman
      value: 19.50371443994939
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 69.3634693673425
    - type: cos_sim_spearman
      value: 68.45051245419702
    - type: euclidean_pearson
      value: 56.1417414374769
    - type: euclidean_spearman
      value: 55.89891749631458
    - type: manhattan_pearson
      value: 57.266417430882925
    - type: manhattan_spearman
      value: 56.57927102744128
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-it)
      type: mteb/sts22-crosslingual-sts
      config: es-it
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 60.04169437653179
    - type: cos_sim_spearman
      value: 65.49531007553446
    - type: euclidean_pearson
      value: 58.583860732586324
    - type: euclidean_spearman
      value: 58.80034792537441
    - type: manhattan_pearson
      value: 59.02513161664622
    - type: manhattan_spearman
      value: 58.42942047904558
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 48.81035211493999
    - type: cos_sim_spearman
      value: 53.27599246786967
    - type: euclidean_pearson
      value: 52.25710699032889
    - type: euclidean_spearman
      value: 55.22995695529873
    - type: manhattan_pearson
      value: 51.894901893217884
    - type: manhattan_spearman
      value: 54.95919975149795
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 36.75993101477816
    - type: cos_sim_spearman
      value: 43.050156692479355
    - type: euclidean_pearson
      value: 51.49021084746248
    - type: euclidean_spearman
      value: 49.54771253090078
    - type: manhattan_pearson
      value: 54.68410760796417
    - type: manhattan_spearman
      value: 48.19277197691717
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: 2de6ce8c1921b71a755b262c6b57fef195dd7906
    metrics:
    - type: cos_sim_pearson
      value: 48.553763306386486
    - type: cos_sim_spearman
      value: 28.17180849095055
    - type: euclidean_pearson
      value: 17.50739087826514
    - type: euclidean_spearman
      value: 16.903085094570333
    - type: manhattan_pearson
      value: 20.750046512534112
    - type: manhattan_spearman
      value: 5.634361698190111
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: 8913289635987208e6e7c72789e4be2fe94b6abd
    metrics:
    - type: cos_sim_pearson
      value: 82.17107190594417
    - type: cos_sim_spearman
      value: 80.89611873505183
    - type: euclidean_pearson
      value: 71.82491561814403
    - type: euclidean_spearman
      value: 70.33608835403274
    - type: manhattan_pearson
      value: 71.89538332420133
    - type: manhattan_spearman
      value: 70.36082395775944
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: 56a6d0140cf6356659e2a7c1413286a774468d44
    metrics:
    - type: map
      value: 79.77047154974562
    - type: mrr
      value: 94.25887021475256
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: a75ae049398addde9b70f6b268875f5cbce99089
    metrics:
    - type: map_at_1
      value: 56.328
    - type: map_at_10
      value: 67.167
    - type: map_at_100
      value: 67.721
    - type: map_at_1000
      value: 67.735
    - type: map_at_3
      value: 64.20400000000001
    - type: map_at_5
      value: 65.904
    - type: mrr_at_1
      value: 59.667
    - type: mrr_at_10
      value: 68.553
    - type: mrr_at_100
      value: 68.992
    - type: mrr_at_1000
      value: 69.004
    - type: mrr_at_3
      value: 66.22200000000001
    - type: mrr_at_5
      value: 67.739
    - type: ndcg_at_1
      value: 59.667
    - type: ndcg_at_10
      value: 72.111
    - type: ndcg_at_100
      value: 74.441
    - type: ndcg_at_1000
      value: 74.90599999999999
    - type: ndcg_at_3
      value: 67.11399999999999
    - type: ndcg_at_5
      value: 69.687
    - type: precision_at_1
      value: 59.667
    - type: precision_at_10
      value: 9.733
    - type: precision_at_100
      value: 1.09
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 26.444000000000003
    - type: precision_at_5
      value: 17.599999999999998
    - type: recall_at_1
      value: 56.328
    - type: recall_at_10
      value: 85.8
    - type: recall_at_100
      value: 96.167
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_3
      value: 72.433
    - type: recall_at_5
      value: 78.972
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: 5a8256d0dff9c4bd3be3ba3e67e4e70173f802ea
    metrics:
    - type: cos_sim_accuracy
      value: 99.8019801980198
    - type: cos_sim_ap
      value: 94.92527097094644
    - type: cos_sim_f1
      value: 89.91935483870968
    - type: cos_sim_precision
      value: 90.65040650406505
    - type: cos_sim_recall
      value: 89.2
    - type: dot_accuracy
      value: 99.51782178217822
    - type: dot_ap
      value: 81.30756869559929
    - type: dot_f1
      value: 75.88235294117648
    - type: dot_precision
      value: 74.42307692307692
    - type: dot_recall
      value: 77.4
    - type: euclidean_accuracy
      value: 99.73069306930694
    - type: euclidean_ap
      value: 91.05040371796932
    - type: euclidean_f1
      value: 85.7889237199582
    - type: euclidean_precision
      value: 89.82494529540482
    - type: euclidean_recall
      value: 82.1
    - type: manhattan_accuracy
      value: 99.73762376237623
    - type: manhattan_ap
      value: 91.4823412839869
    - type: manhattan_f1
      value: 86.39836984207845
    - type: manhattan_precision
      value: 88.05815160955348
    - type: manhattan_recall
      value: 84.8
    - type: max_accuracy
      value: 99.8019801980198
    - type: max_ap
      value: 94.92527097094644
    - type: max_f1
      value: 89.91935483870968
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 70a89468f6dccacc6aa2b12a6eac54e74328f235
    metrics:
    - type: v_measure
      value: 55.13046832022158
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: d88009ab563dd0b16cfaf4436abaf97fa3550cf0
    metrics:
    - type: v_measure
      value: 34.31252463546675
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: ef807ea29a75ec4f91b50fd4191cb4ee4589a9f9
    metrics:
    - type: map
      value: 51.06639688231414
    - type: mrr
      value: 51.80205415499534
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: 8753c2788d36c01fc6f05d03fe3f7268d63f9122
    metrics:
    - type: cos_sim_pearson
      value: 31.963331462886956
    - type: cos_sim_spearman
      value: 33.59510652629926
    - type: dot_pearson
      value: 29.033733540882125
    - type: dot_spearman
      value: 31.550290638315506
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: 2c8041b2c07a79b6f7ba8fe6acc72e5d9f92d217
    metrics:
    - type: map_at_1
      value: 0.23600000000000002
    - type: map_at_10
      value: 2.09
    - type: map_at_100
      value: 12.466000000000001
    - type: map_at_1000
      value: 29.852
    - type: map_at_3
      value: 0.6859999999999999
    - type: map_at_5
      value: 1.099
    - type: mrr_at_1
      value: 88.0
    - type: mrr_at_10
      value: 94.0
    - type: mrr_at_100
      value: 94.0
    - type: mrr_at_1000
      value: 94.0
    - type: mrr_at_3
      value: 94.0
    - type: mrr_at_5
      value: 94.0
    - type: ndcg_at_1
      value: 86.0
    - type: ndcg_at_10
      value: 81.368
    - type: ndcg_at_100
      value: 61.879
    - type: ndcg_at_1000
      value: 55.282
    - type: ndcg_at_3
      value: 84.816
    - type: ndcg_at_5
      value: 82.503
    - type: precision_at_1
      value: 88.0
    - type: precision_at_10
      value: 85.6
    - type: precision_at_100
      value: 63.85999999999999
    - type: precision_at_1000
      value: 24.682000000000002
    - type: precision_at_3
      value: 88.667
    - type: precision_at_5
      value: 86.0
    - type: recall_at_1
      value: 0.23600000000000002
    - type: recall_at_10
      value: 2.25
    - type: recall_at_100
      value: 15.488
    - type: recall_at_1000
      value: 52.196
    - type: recall_at_3
      value: 0.721
    - type: recall_at_5
      value: 1.159
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (sqi-eng)
      type: mteb/tatoeba-bitext-mining
      config: sqi-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 12.7
    - type: f1
      value: 10.384182044950325
    - type: precision
      value: 9.805277385275312
    - type: recall
      value: 12.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fry-eng)
      type: mteb/tatoeba-bitext-mining
      config: fry-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 30.63583815028902
    - type: f1
      value: 24.623726947426373
    - type: precision
      value: 22.987809919828013
    - type: recall
      value: 30.63583815028902
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kur-eng)
      type: mteb/tatoeba-bitext-mining
      config: kur-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 10.487804878048781
    - type: f1
      value: 8.255945048627975
    - type: precision
      value: 7.649047253615001
    - type: recall
      value: 10.487804878048781
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tur-eng)
      type: mteb/tatoeba-bitext-mining
      config: tur-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.5
    - type: f1
      value: 6.154428783776609
    - type: precision
      value: 5.680727638128585
    - type: recall
      value: 8.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (deu-eng)
      type: mteb/tatoeba-bitext-mining
      config: deu-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 73.0
    - type: f1
      value: 70.10046605876393
    - type: precision
      value: 69.0018253968254
    - type: recall
      value: 73.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nld-eng)
      type: mteb/tatoeba-bitext-mining
      config: nld-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 32.7
    - type: f1
      value: 29.7428583868239
    - type: precision
      value: 28.81671359506905
    - type: recall
      value: 32.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ron-eng)
      type: mteb/tatoeba-bitext-mining
      config: ron-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 31.5
    - type: f1
      value: 27.228675552174003
    - type: precision
      value: 25.950062299847747
    - type: recall
      value: 31.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ang-eng)
      type: mteb/tatoeba-bitext-mining
      config: ang-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 35.82089552238806
    - type: f1
      value: 28.75836980510979
    - type: precision
      value: 26.971643613434658
    - type: recall
      value: 35.82089552238806
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ido-eng)
      type: mteb/tatoeba-bitext-mining
      config: ido-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 49.8
    - type: f1
      value: 43.909237401451776
    - type: precision
      value: 41.944763440988936
    - type: recall
      value: 49.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (jav-eng)
      type: mteb/tatoeba-bitext-mining
      config: jav-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 18.536585365853657
    - type: f1
      value: 15.020182570246751
    - type: precision
      value: 14.231108073213337
    - type: recall
      value: 18.536585365853657
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (isl-eng)
      type: mteb/tatoeba-bitext-mining
      config: isl-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.7
    - type: f1
      value: 6.2934784902885355
    - type: precision
      value: 5.685926293425392
    - type: recall
      value: 8.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (slv-eng)
      type: mteb/tatoeba-bitext-mining
      config: slv-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 12.879708383961116
    - type: f1
      value: 10.136118341751114
    - type: precision
      value: 9.571444036679436
    - type: recall
      value: 12.879708383961116
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cym-eng)
      type: mteb/tatoeba-bitext-mining
      config: cym-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 9.217391304347826
    - type: f1
      value: 6.965003297761793
    - type: precision
      value: 6.476093529199119
    - type: recall
      value: 9.217391304347826
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kaz-eng)
      type: mteb/tatoeba-bitext-mining
      config: kaz-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 4.3478260869565215
    - type: f1
      value: 3.3186971707677397
    - type: precision
      value: 3.198658632552104
    - type: recall
      value: 4.3478260869565215
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (est-eng)
      type: mteb/tatoeba-bitext-mining
      config: est-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 6.9
    - type: f1
      value: 4.760708297894056
    - type: precision
      value: 4.28409511756074
    - type: recall
      value: 6.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (heb-eng)
      type: mteb/tatoeba-bitext-mining
      config: heb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 2.1999999999999997
    - type: f1
      value: 1.6862703878117107
    - type: precision
      value: 1.6048118233915603
    - type: recall
      value: 2.1999999999999997
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gla-eng)
      type: mteb/tatoeba-bitext-mining
      config: gla-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 3.0156815440289506
    - type: f1
      value: 2.0913257250659134
    - type: precision
      value: 1.9072775486461648
    - type: recall
      value: 3.0156815440289506
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mar-eng)
      type: mteb/tatoeba-bitext-mining
      config: mar-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 49.0
    - type: f1
      value: 45.5254456536713
    - type: precision
      value: 44.134609250398725
    - type: recall
      value: 49.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lat-eng)
      type: mteb/tatoeba-bitext-mining
      config: lat-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 33.5
    - type: f1
      value: 28.759893973182564
    - type: precision
      value: 27.401259116024836
    - type: recall
      value: 33.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bel-eng)
      type: mteb/tatoeba-bitext-mining
      config: bel-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 10.2
    - type: f1
      value: 8.030039981676275
    - type: precision
      value: 7.548748077210127
    - type: recall
      value: 10.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pms-eng)
      type: mteb/tatoeba-bitext-mining
      config: pms-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 38.095238095238095
    - type: f1
      value: 31.944999250262406
    - type: precision
      value: 30.04452690166976
    - type: recall
      value: 38.095238095238095
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gle-eng)
      type: mteb/tatoeba-bitext-mining
      config: gle-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 4.8
    - type: f1
      value: 3.2638960786708067
    - type: precision
      value: 3.0495382950729644
    - type: recall
      value: 4.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pes-eng)
      type: mteb/tatoeba-bitext-mining
      config: pes-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 15.8
    - type: f1
      value: 12.131087470371275
    - type: precision
      value: 11.141304011547815
    - type: recall
      value: 15.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nob-eng)
      type: mteb/tatoeba-bitext-mining
      config: nob-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 23.3
    - type: f1
      value: 21.073044636921384
    - type: precision
      value: 20.374220568287285
    - type: recall
      value: 23.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bul-eng)
      type: mteb/tatoeba-bitext-mining
      config: bul-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 24.9
    - type: f1
      value: 20.091060685364987
    - type: precision
      value: 18.899700591081224
    - type: recall
      value: 24.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cbk-eng)
      type: mteb/tatoeba-bitext-mining
      config: cbk-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 70.1
    - type: f1
      value: 64.62940836940835
    - type: precision
      value: 62.46559523809524
    - type: recall
      value: 70.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hun-eng)
      type: mteb/tatoeba-bitext-mining
      config: hun-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.199999999999999
    - type: f1
      value: 5.06613460576115
    - type: precision
      value: 4.625224463391809
    - type: recall
      value: 7.199999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (uig-eng)
      type: mteb/tatoeba-bitext-mining
      config: uig-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 1.7999999999999998
    - type: f1
      value: 1.2716249514772895
    - type: precision
      value: 1.2107445914723798
    - type: recall
      value: 1.7999999999999998
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (rus-eng)
      type: mteb/tatoeba-bitext-mining
      config: rus-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 65.5
    - type: f1
      value: 59.84399711399712
    - type: precision
      value: 57.86349567099567
    - type: recall
      value: 65.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (spa-eng)
      type: mteb/tatoeba-bitext-mining
      config: spa-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 95.7
    - type: f1
      value: 94.48333333333333
    - type: precision
      value: 93.89999999999999
    - type: recall
      value: 95.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hye-eng)
      type: mteb/tatoeba-bitext-mining
      config: hye-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 0.8086253369272237
    - type: f1
      value: 0.4962046191492002
    - type: precision
      value: 0.47272438578554393
    - type: recall
      value: 0.8086253369272237
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tel-eng)
      type: mteb/tatoeba-bitext-mining
      config: tel-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 69.23076923076923
    - type: f1
      value: 64.6227941099736
    - type: precision
      value: 63.03795877325289
    - type: recall
      value: 69.23076923076923
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (afr-eng)
      type: mteb/tatoeba-bitext-mining
      config: afr-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 20.599999999999998
    - type: f1
      value: 16.62410040660465
    - type: precision
      value: 15.598352437967069
    - type: recall
      value: 20.599999999999998
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mon-eng)
      type: mteb/tatoeba-bitext-mining
      config: mon-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 4.318181818181818
    - type: f1
      value: 2.846721192535661
    - type: precision
      value: 2.6787861417537147
    - type: recall
      value: 4.318181818181818
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (arz-eng)
      type: mteb/tatoeba-bitext-mining
      config: arz-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 74.84276729559748
    - type: f1
      value: 70.6638714185884
    - type: precision
      value: 68.86792452830188
    - type: recall
      value: 74.84276729559748
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hrv-eng)
      type: mteb/tatoeba-bitext-mining
      config: hrv-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 15.9
    - type: f1
      value: 12.793698974586706
    - type: precision
      value: 12.088118017657736
    - type: recall
      value: 15.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nov-eng)
      type: mteb/tatoeba-bitext-mining
      config: nov-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 59.92217898832685
    - type: f1
      value: 52.23086900129701
    - type: precision
      value: 49.25853869433636
    - type: recall
      value: 59.92217898832685
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gsw-eng)
      type: mteb/tatoeba-bitext-mining
      config: gsw-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 27.350427350427353
    - type: f1
      value: 21.033781033781032
    - type: precision
      value: 19.337955491801644
    - type: recall
      value: 27.350427350427353
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nds-eng)
      type: mteb/tatoeba-bitext-mining
      config: nds-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 29.299999999999997
    - type: f1
      value: 23.91597452425777
    - type: precision
      value: 22.36696598364942
    - type: recall
      value: 29.299999999999997
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ukr-eng)
      type: mteb/tatoeba-bitext-mining
      config: ukr-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 27.3
    - type: f1
      value: 22.059393517688886
    - type: precision
      value: 20.503235534170887
    - type: recall
      value: 27.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (uzb-eng)
      type: mteb/tatoeba-bitext-mining
      config: uzb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.177570093457943
    - type: f1
      value: 4.714367017906037
    - type: precision
      value: 4.163882933965758
    - type: recall
      value: 8.177570093457943
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lit-eng)
      type: mteb/tatoeba-bitext-mining
      config: lit-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 5.800000000000001
    - type: f1
      value: 4.4859357432293825
    - type: precision
      value: 4.247814465614043
    - type: recall
      value: 5.800000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ina-eng)
      type: mteb/tatoeba-bitext-mining
      config: ina-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 78.4
    - type: f1
      value: 73.67166666666667
    - type: precision
      value: 71.83285714285714
    - type: recall
      value: 78.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lfn-eng)
      type: mteb/tatoeba-bitext-mining
      config: lfn-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 50.3
    - type: f1
      value: 44.85221545883311
    - type: precision
      value: 43.04913026243909
    - type: recall
      value: 50.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (zsm-eng)
      type: mteb/tatoeba-bitext-mining
      config: zsm-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 83.5
    - type: f1
      value: 79.95151515151515
    - type: precision
      value: 78.53611111111111
    - type: recall
      value: 83.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ita-eng)
      type: mteb/tatoeba-bitext-mining
      config: ita-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 69.89999999999999
    - type: f1
      value: 65.03756269256269
    - type: precision
      value: 63.233519536019536
    - type: recall
      value: 69.89999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cmn-eng)
      type: mteb/tatoeba-bitext-mining
      config: cmn-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 93.2
    - type: f1
      value: 91.44666666666666
    - type: precision
      value: 90.63333333333333
    - type: recall
      value: 93.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lvs-eng)
      type: mteb/tatoeba-bitext-mining
      config: lvs-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.3
    - type: f1
      value: 6.553388144729963
    - type: precision
      value: 6.313497782829976
    - type: recall
      value: 8.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (glg-eng)
      type: mteb/tatoeba-bitext-mining
      config: glg-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 83.6
    - type: f1
      value: 79.86243107769424
    - type: precision
      value: 78.32555555555555
    - type: recall
      value: 83.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ceb-eng)
      type: mteb/tatoeba-bitext-mining
      config: ceb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 9.166666666666666
    - type: f1
      value: 6.637753604420271
    - type: precision
      value: 6.10568253585495
    - type: recall
      value: 9.166666666666666
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bre-eng)
      type: mteb/tatoeba-bitext-mining
      config: bre-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.3999999999999995
    - type: f1
      value: 4.6729483612322165
    - type: precision
      value: 4.103844520292658
    - type: recall
      value: 7.3999999999999995
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ben-eng)
      type: mteb/tatoeba-bitext-mining
      config: ben-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 80.30000000000001
    - type: f1
      value: 75.97666666666667
    - type: precision
      value: 74.16
    - type: recall
      value: 80.30000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swg-eng)
      type: mteb/tatoeba-bitext-mining
      config: swg-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 23.214285714285715
    - type: f1
      value: 16.88988095238095
    - type: precision
      value: 15.364937641723353
    - type: recall
      value: 23.214285714285715
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (arq-eng)
      type: mteb/tatoeba-bitext-mining
      config: arq-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 33.15038419319429
    - type: f1
      value: 27.747873024072415
    - type: precision
      value: 25.99320572578704
    - type: recall
      value: 33.15038419319429
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kab-eng)
      type: mteb/tatoeba-bitext-mining
      config: kab-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 2.6
    - type: f1
      value: 1.687059048752127
    - type: precision
      value: 1.5384884521299
    - type: recall
      value: 2.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fra-eng)
      type: mteb/tatoeba-bitext-mining
      config: fra-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 93.30000000000001
    - type: f1
      value: 91.44000000000001
    - type: precision
      value: 90.59166666666667
    - type: recall
      value: 93.30000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (por-eng)
      type: mteb/tatoeba-bitext-mining
      config: por-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 94.1
    - type: f1
      value: 92.61666666666667
    - type: precision
      value: 91.88333333333333
    - type: recall
      value: 94.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tat-eng)
      type: mteb/tatoeba-bitext-mining
      config: tat-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 5.0
    - type: f1
      value: 3.589591971281927
    - type: precision
      value: 3.3046491614532854
    - type: recall
      value: 5.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (oci-eng)
      type: mteb/tatoeba-bitext-mining
      config: oci-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 45.9
    - type: f1
      value: 40.171969141969136
    - type: precision
      value: 38.30764368870302
    - type: recall
      value: 45.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pol-eng)
      type: mteb/tatoeba-bitext-mining
      config: pol-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 16.900000000000002
    - type: f1
      value: 14.094365204207351
    - type: precision
      value: 13.276519841269844
    - type: recall
      value: 16.900000000000002
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (war-eng)
      type: mteb/tatoeba-bitext-mining
      config: war-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 12.8
    - type: f1
      value: 10.376574912567156
    - type: precision
      value: 9.758423963284509
    - type: recall
      value: 12.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (aze-eng)
      type: mteb/tatoeba-bitext-mining
      config: aze-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.1
    - type: f1
      value: 6.319455355175778
    - type: precision
      value: 5.849948830628881
    - type: recall
      value: 8.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (vie-eng)
      type: mteb/tatoeba-bitext-mining
      config: vie-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 95.5
    - type: f1
      value: 94.19666666666667
    - type: precision
      value: 93.60000000000001
    - type: recall
      value: 95.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nno-eng)
      type: mteb/tatoeba-bitext-mining
      config: nno-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 19.1
    - type: f1
      value: 16.280080686081906
    - type: precision
      value: 15.451573089395668
    - type: recall
      value: 19.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cha-eng)
      type: mteb/tatoeba-bitext-mining
      config: cha-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 30.656934306569344
    - type: f1
      value: 23.2568647897115
    - type: precision
      value: 21.260309034031664
    - type: recall
      value: 30.656934306569344
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mhr-eng)
      type: mteb/tatoeba-bitext-mining
      config: mhr-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 2.1999999999999997
    - type: f1
      value: 1.556861047295521
    - type: precision
      value: 1.4555993437238521
    - type: recall
      value: 2.1999999999999997
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dan-eng)
      type: mteb/tatoeba-bitext-mining
      config: dan-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 27.500000000000004
    - type: f1
      value: 23.521682636223492
    - type: precision
      value: 22.345341306967683
    - type: recall
      value: 27.500000000000004
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ell-eng)
      type: mteb/tatoeba-bitext-mining
      config: ell-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.3999999999999995
    - type: f1
      value: 5.344253880846173
    - type: precision
      value: 4.999794279068863
    - type: recall
      value: 7.3999999999999995
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (amh-eng)
      type: mteb/tatoeba-bitext-mining
      config: amh-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 0.5952380952380952
    - type: f1
      value: 0.026455026455026457
    - type: precision
      value: 0.013528138528138528
    - type: recall
      value: 0.5952380952380952
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pam-eng)
      type: mteb/tatoeba-bitext-mining
      config: pam-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.3
    - type: f1
      value: 5.853140211779251
    - type: precision
      value: 5.505563080945322
    - type: recall
      value: 7.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hsb-eng)
      type: mteb/tatoeba-bitext-mining
      config: hsb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 13.250517598343686
    - type: f1
      value: 9.676349506190704
    - type: precision
      value: 8.930392053553216
    - type: recall
      value: 13.250517598343686
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (srp-eng)
      type: mteb/tatoeba-bitext-mining
      config: srp-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 14.499999999999998
    - type: f1
      value: 11.68912588067557
    - type: precision
      value: 11.024716513105519
    - type: recall
      value: 14.499999999999998
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (epo-eng)
      type: mteb/tatoeba-bitext-mining
      config: epo-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 30.099999999999998
    - type: f1
      value: 26.196880936315146
    - type: precision
      value: 25.271714086169478
    - type: recall
      value: 30.099999999999998
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kzj-eng)
      type: mteb/tatoeba-bitext-mining
      config: kzj-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 6.4
    - type: f1
      value: 5.1749445942023335
    - type: precision
      value: 4.975338142029625
    - type: recall
      value: 6.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (awa-eng)
      type: mteb/tatoeba-bitext-mining
      config: awa-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 39.39393939393939
    - type: f1
      value: 35.005707393767096
    - type: precision
      value: 33.64342032053631
    - type: recall
      value: 39.39393939393939
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fao-eng)
      type: mteb/tatoeba-bitext-mining
      config: fao-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 18.3206106870229
    - type: f1
      value: 12.610893447220345
    - type: precision
      value: 11.079228765297467
    - type: recall
      value: 18.3206106870229
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mal-eng)
      type: mteb/tatoeba-bitext-mining
      config: mal-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 85.58951965065502
    - type: f1
      value: 83.30363944928548
    - type: precision
      value: 82.40026591554977
    - type: recall
      value: 85.58951965065502
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ile-eng)
      type: mteb/tatoeba-bitext-mining
      config: ile-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 65.7
    - type: f1
      value: 59.589642857142856
    - type: precision
      value: 57.392826797385624
    - type: recall
      value: 65.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bos-eng)
      type: mteb/tatoeba-bitext-mining
      config: bos-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 18.07909604519774
    - type: f1
      value: 13.65194306689995
    - type: precision
      value: 12.567953943826327
    - type: recall
      value: 18.07909604519774
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cor-eng)
      type: mteb/tatoeba-bitext-mining
      config: cor-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 4.6
    - type: f1
      value: 2.8335386392505013
    - type: precision
      value: 2.558444143575722
    - type: recall
      value: 4.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cat-eng)
      type: mteb/tatoeba-bitext-mining
      config: cat-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 90.7
    - type: f1
      value: 88.30666666666666
    - type: precision
      value: 87.195
    - type: recall
      value: 90.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (eus-eng)
      type: mteb/tatoeba-bitext-mining
      config: eus-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 57.699999999999996
    - type: f1
      value: 53.38433067253876
    - type: precision
      value: 51.815451335350346
    - type: recall
      value: 57.699999999999996
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (yue-eng)
      type: mteb/tatoeba-bitext-mining
      config: yue-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 80.60000000000001
    - type: f1
      value: 77.0290354090354
    - type: precision
      value: 75.61685897435898
    - type: recall
      value: 80.60000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swe-eng)
      type: mteb/tatoeba-bitext-mining
      config: swe-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 24.6
    - type: f1
      value: 19.52814960069739
    - type: precision
      value: 18.169084599880502
    - type: recall
      value: 24.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dtp-eng)
      type: mteb/tatoeba-bitext-mining
      config: dtp-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 5.0
    - type: f1
      value: 3.4078491753102376
    - type: precision
      value: 3.1757682319102387
    - type: recall
      value: 5.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kat-eng)
      type: mteb/tatoeba-bitext-mining
      config: kat-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 1.2064343163538873
    - type: f1
      value: 0.4224313053283095
    - type: precision
      value: 0.3360484946842894
    - type: recall
      value: 1.2064343163538873
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (jpn-eng)
      type: mteb/tatoeba-bitext-mining
      config: jpn-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 76.1
    - type: f1
      value: 71.36246031746032
    - type: precision
      value: 69.5086544011544
    - type: recall
      value: 76.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (csb-eng)
      type: mteb/tatoeba-bitext-mining
      config: csb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 14.229249011857709
    - type: f1
      value: 10.026578603653704
    - type: precision
      value: 9.09171178352764
    - type: recall
      value: 14.229249011857709
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (xho-eng)
      type: mteb/tatoeba-bitext-mining
      config: xho-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 8.450704225352112
    - type: f1
      value: 5.51214407186151
    - type: precision
      value: 4.928281812084629
    - type: recall
      value: 8.450704225352112
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (orv-eng)
      type: mteb/tatoeba-bitext-mining
      config: orv-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.664670658682635
    - type: f1
      value: 5.786190079917295
    - type: precision
      value: 5.3643643579244
    - type: recall
      value: 7.664670658682635
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ind-eng)
      type: mteb/tatoeba-bitext-mining
      config: ind-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 90.5
    - type: f1
      value: 88.03999999999999
    - type: precision
      value: 86.94833333333334
    - type: recall
      value: 90.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tuk-eng)
      type: mteb/tatoeba-bitext-mining
      config: tuk-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 7.389162561576355
    - type: f1
      value: 5.482366349556517
    - type: precision
      value: 5.156814449917898
    - type: recall
      value: 7.389162561576355
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (max-eng)
      type: mteb/tatoeba-bitext-mining
      config: max-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 41.54929577464789
    - type: f1
      value: 36.13520282534367
    - type: precision
      value: 34.818226488560995
    - type: recall
      value: 41.54929577464789
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swh-eng)
      type: mteb/tatoeba-bitext-mining
      config: swh-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 20.76923076923077
    - type: f1
      value: 16.742497560177643
    - type: precision
      value: 15.965759712090138
    - type: recall
      value: 20.76923076923077
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hin-eng)
      type: mteb/tatoeba-bitext-mining
      config: hin-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 88.1
    - type: f1
      value: 85.23176470588236
    - type: precision
      value: 84.04458333333334
    - type: recall
      value: 88.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dsb-eng)
      type: mteb/tatoeba-bitext-mining
      config: dsb-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 11.899791231732777
    - type: f1
      value: 8.776706659565102
    - type: precision
      value: 8.167815946521582
    - type: recall
      value: 11.899791231732777
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ber-eng)
      type: mteb/tatoeba-bitext-mining
      config: ber-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 6.1
    - type: f1
      value: 4.916589537178435
    - type: precision
      value: 4.72523017415345
    - type: recall
      value: 6.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tam-eng)
      type: mteb/tatoeba-bitext-mining
      config: tam-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 76.54723127035831
    - type: f1
      value: 72.75787187839306
    - type: precision
      value: 71.43338442869005
    - type: recall
      value: 76.54723127035831
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (slk-eng)
      type: mteb/tatoeba-bitext-mining
      config: slk-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 11.700000000000001
    - type: f1
      value: 9.975679190026007
    - type: precision
      value: 9.569927715653522
    - type: recall
      value: 11.700000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tgl-eng)
      type: mteb/tatoeba-bitext-mining
      config: tgl-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 13.100000000000001
    - type: f1
      value: 10.697335850115408
    - type: precision
      value: 10.113816082086341
    - type: recall
      value: 13.100000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ast-eng)
      type: mteb/tatoeba-bitext-mining
      config: ast-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 76.37795275590551
    - type: f1
      value: 71.12860892388451
    - type: precision
      value: 68.89763779527559
    - type: recall
      value: 76.37795275590551
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mkd-eng)
      type: mteb/tatoeba-bitext-mining
      config: mkd-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 13.700000000000001
    - type: f1
      value: 10.471861684067568
    - type: precision
      value: 9.602902567641697
    - type: recall
      value: 13.700000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (khm-eng)
      type: mteb/tatoeba-bitext-mining
      config: khm-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 0.554016620498615
    - type: f1
      value: 0.37034084643642423
    - type: precision
      value: 0.34676040281208437
    - type: recall
      value: 0.554016620498615
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ces-eng)
      type: mteb/tatoeba-bitext-mining
      config: ces-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 12.4
    - type: f1
      value: 9.552607451092534
    - type: precision
      value: 8.985175505050504
    - type: recall
      value: 12.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tzl-eng)
      type: mteb/tatoeba-bitext-mining
      config: tzl-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 33.65384615384615
    - type: f1
      value: 27.820512820512818
    - type: precision
      value: 26.09432234432234
    - type: recall
      value: 33.65384615384615
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (urd-eng)
      type: mteb/tatoeba-bitext-mining
      config: urd-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 74.5
    - type: f1
      value: 70.09686507936507
    - type: precision
      value: 68.3117857142857
    - type: recall
      value: 74.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ara-eng)
      type: mteb/tatoeba-bitext-mining
      config: ara-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 88.3
    - type: f1
      value: 85.37333333333333
    - type: precision
      value: 84.05833333333334
    - type: recall
      value: 88.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kor-eng)
      type: mteb/tatoeba-bitext-mining
      config: kor-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 25.0
    - type: f1
      value: 22.393124632031995
    - type: precision
      value: 21.58347686592367
    - type: recall
      value: 25.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (yid-eng)
      type: mteb/tatoeba-bitext-mining
      config: yid-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 0.589622641509434
    - type: f1
      value: 0.15804980033762941
    - type: precision
      value: 0.1393275384872965
    - type: recall
      value: 0.589622641509434
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fin-eng)
      type: mteb/tatoeba-bitext-mining
      config: fin-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 4.1000000000000005
    - type: f1
      value: 3.4069011332551775
    - type: precision
      value: 3.1784507042253516
    - type: recall
      value: 4.1000000000000005
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tha-eng)
      type: mteb/tatoeba-bitext-mining
      config: tha-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 3.102189781021898
    - type: f1
      value: 2.223851811694751
    - type: precision
      value: 2.103465682299194
    - type: recall
      value: 3.102189781021898
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (wuu-eng)
      type: mteb/tatoeba-bitext-mining
      config: wuu-eng
      split: test
      revision: ed9e4a974f867fd9736efcf222fc3a26487387a5
    metrics:
    - type: accuracy
      value: 83.1
    - type: f1
      value: 79.58255835667599
    - type: precision
      value: 78.09708333333333
    - type: recall
      value: 83.1
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: 527b7d77e16e343303e68cb6af11d6e18b9f7b3b
    metrics:
    - type: map_at_1
      value: 2.322
    - type: map_at_10
      value: 8.959999999999999
    - type: map_at_100
      value: 15.136
    - type: map_at_1000
      value: 16.694
    - type: map_at_3
      value: 4.837000000000001
    - type: map_at_5
      value: 6.196
    - type: mrr_at_1
      value: 28.571
    - type: mrr_at_10
      value: 47.589999999999996
    - type: mrr_at_100
      value: 48.166
    - type: mrr_at_1000
      value: 48.169000000000004
    - type: mrr_at_3
      value: 43.197
    - type: mrr_at_5
      value: 45.646
    - type: ndcg_at_1
      value: 26.531
    - type: ndcg_at_10
      value: 23.982
    - type: ndcg_at_100
      value: 35.519
    - type: ndcg_at_1000
      value: 46.878
    - type: ndcg_at_3
      value: 26.801000000000002
    - type: ndcg_at_5
      value: 24.879
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 22.041
    - type: precision_at_100
      value: 7.4079999999999995
    - type: precision_at_1000
      value: 1.492
    - type: precision_at_3
      value: 28.571
    - type: precision_at_5
      value: 25.306
    - type: recall_at_1
      value: 2.322
    - type: recall_at_10
      value: 15.443999999999999
    - type: recall_at_100
      value: 45.918
    - type: recall_at_1000
      value: 79.952
    - type: recall_at_3
      value: 6.143
    - type: recall_at_5
      value: 8.737
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 66.5452
    - type: ap
      value: 12.99191723223892
    - type: f1
      value: 51.667665096195734
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: 62146448f05be9e52a36b8ee9936447ea787eede
    metrics:
    - type: accuracy
      value: 55.854555744199196
    - type: f1
      value: 56.131766302254185
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 091a54f9a36281ce7d6590ec8c75dd485e7e01d4
    metrics:
    - type: v_measure
      value: 37.27891385518074
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.53102461703523
    - type: cos_sim_ap
      value: 65.30753664579191
    - type: cos_sim_f1
      value: 61.739943872778305
    - type: cos_sim_precision
      value: 55.438891222175556
    - type: cos_sim_recall
      value: 69.65699208443272
    - type: dot_accuracy
      value: 80.38981939560112
    - type: dot_ap
      value: 53.52081118421347
    - type: dot_f1
      value: 54.232957844617346
    - type: dot_precision
      value: 48.43393486828459
    - type: dot_recall
      value: 61.60949868073878
    - type: euclidean_accuracy
      value: 82.23758717291531
    - type: euclidean_ap
      value: 60.361102792772535
    - type: euclidean_f1
      value: 57.50518791791561
    - type: euclidean_precision
      value: 51.06470106470107
    - type: euclidean_recall
      value: 65.8047493403694
    - type: manhattan_accuracy
      value: 82.14221851344102
    - type: manhattan_ap
      value: 60.341937223793366
    - type: manhattan_f1
      value: 57.53803596127247
    - type: manhattan_precision
      value: 51.08473188702415
    - type: manhattan_recall
      value: 65.85751978891821
    - type: max_accuracy
      value: 83.53102461703523
    - type: max_ap
      value: 65.30753664579191
    - type: max_f1
      value: 61.739943872778305
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.75305623471883
    - type: cos_sim_ap
      value: 85.46387153880272
    - type: cos_sim_f1
      value: 77.91527673159008
    - type: cos_sim_precision
      value: 72.93667315828353
    - type: cos_sim_recall
      value: 83.62334462580844
    - type: dot_accuracy
      value: 85.08169363915086
    - type: dot_ap
      value: 74.96808060965559
    - type: dot_f1
      value: 71.39685033990366
    - type: dot_precision
      value: 64.16948111759288
    - type: dot_recall
      value: 80.45888512473051
    - type: euclidean_accuracy
      value: 85.84235650250321
    - type: euclidean_ap
      value: 78.42045145247211
    - type: euclidean_f1
      value: 70.32669630775179
    - type: euclidean_precision
      value: 70.6298050788227
    - type: euclidean_recall
      value: 70.02617801047121
    - type: manhattan_accuracy
      value: 85.86176116738464
    - type: manhattan_ap
      value: 78.54012451558276
    - type: manhattan_f1
      value: 70.56508080693389
    - type: manhattan_precision
      value: 69.39626293456413
    - type: manhattan_recall
      value: 71.77394518016631
    - type: max_accuracy
      value: 88.75305623471883
    - type: max_ap
      value: 85.46387153880272
    - type: max_f1
      value: 77.91527673159008
---

## Usage

For usage instructions, refer to: https://github.com/Muennighoff/sgpt#asymmetric-semantic-search-be

The model was trained with the command
```bash
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 accelerate launch examples/training/ms_marco/train_bi-encoder_mnrl.py --model_name bigscience/bloom-7b1 --train_batch_size 32 --eval_batch_size 16 --freezenonbias --specb --lr 4e-4 --wandb --wandbwatchlog gradients --pooling weightedmean --gradcache --chunksize 8
```

## Evaluation Results


`{"ndcgs": {"sgpt-bloom-7b1-msmarco": {"scifact": {"NDCG@10": 0.71824}, "nfcorpus": {"NDCG@10": 0.35748}, "arguana": {"NDCG@10": 0.47281}, "scidocs": {"NDCG@10": 0.18435}, "fiqa": {"NDCG@10": 0.35736}, "cqadupstack": {"NDCG@10": 0.3708525}, "quora": {"NDCG@10": 0.74655}, "trec-covid": {"NDCG@10": 0.82731}, "webis-touche2020": {"NDCG@10": 0.2365}}}`

See the evaluation folder or [MTEB](https://huggingface.co/spaces/mteb/leaderboard) for more results.

## Training
The model was trained with the parameters:

**DataLoader**:

`torch.utils.data.dataloader.DataLoader` of length 15600 with parameters:
```
{'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
```

The model uses BitFit, weighted-mean pooling & GradCache, for details see: https://arxiv.org/abs/2202.08904

**Loss**:

`sentence_transformers.losses.MultipleNegativesRankingLoss.MNRLGradCache` 

Parameters of the fit()-Method:
```
{
    "epochs": 10,
    "evaluation_steps": 0,
    "evaluator": "NoneType",
    "max_grad_norm": 1,
    "optimizer_class": "<class 'transformers.optimization.AdamW'>",
    "optimizer_params": {
        "lr": 0.0004
    },
    "scheduler": "WarmupLinear",
    "steps_per_epoch": null,
    "warmup_steps": 1000,
    "weight_decay": 0.01
}
```


## Full Model Architecture
```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 300, 'do_lower_case': False}) with Transformer model: BloomModel 
  (1): Pooling({'word_embedding_dimension': 4096, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': True, 'pooling_mode_lasttoken': False})
)
```

## Citing & Authors

```bibtex
@article{muennighoff2022sgpt,
  title={SGPT: GPT Sentence Embeddings for Semantic Search},
  author={Muennighoff, Niklas},
  journal={arXiv preprint arXiv:2202.08904},
  year={2022}
}
```