sentence-transformers pytorch onnx safetensors bert mteb Sentence Transformers sentence-similarity multilingual af am ar as az be bg bn br bs ca cs cy da de el en eo es et eu fa fi fr fy ga gd gl gu ha he hi hr hu hy id is it ja jv ka kk km kn ko ku ky la lo lt lv mg mk ml mn mr ms my ne nl no om or pa pl ps pt ro ru sa sd si sk sl so sq sr su sv sw ta te th tl tr ug uk ur uz vi xh yi zh arxiv:2402.05672 arxiv:2108.08787 arxiv:2104.08663 arxiv:2210.07316 license:mit model-index autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- 'no'
- om
- or
- pa
- pl
- ps
- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
- su
- sv
- sw
- ta
- te
- th
- tl
- tr
- ug
- uk
- ur
- uz
- vi
- xh
- yi
- zh
license: mit
tags:
- mteb
- Sentence Transformers
- sentence-similarity
- sentence-transformers
model-index:
- name: intfloat/multilingual-e5-small
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.79104477611939
    - type: ap
      value: 36.9996434842022
    - type: f1
      value: 67.95453679103099
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (de)
      type: mteb/amazon_counterfactual
      config: de
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.64882226980728
    - type: ap
      value: 82.11942130026586
    - type: f1
      value: 69.87963421606715
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 75.8095952023988
    - type: ap
      value: 24.46869495579561
    - type: f1
      value: 63.00108480037597
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (ja)
      type: mteb/amazon_counterfactual
      config: ja
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 64.186295503212
    - type: ap
      value: 15.496804690197042
    - type: f1
      value: 52.07153895475031
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 88.699325
    - type: ap
      value: 85.27039559917269
    - type: f1
      value: 88.65556295032513
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 44.69799999999999
    - type: f1
      value: 43.73187348654165
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (de)
      type: mteb/amazon_reviews_multi
      config: de
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 40.245999999999995
    - type: f1
      value: 39.3863530637684
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (es)
      type: mteb/amazon_reviews_multi
      config: es
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 40.394
    - type: f1
      value: 39.301223469483446
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (fr)
      type: mteb/amazon_reviews_multi
      config: fr
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 38.864
    - type: f1
      value: 37.97974261868003
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (ja)
      type: mteb/amazon_reviews_multi
      config: ja
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 37.682
    - type: f1
      value: 37.07399369768313
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (zh)
      type: mteb/amazon_reviews_multi
      config: zh
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 37.504
    - type: f1
      value: 36.62317273874278
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: arguana
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 19.061
    - type: map_at_10
      value: 31.703
    - type: map_at_100
      value: 32.967
    - type: map_at_1000
      value: 33.001000000000005
    - type: map_at_3
      value: 27.466
    - type: map_at_5
      value: 29.564
    - type: mrr_at_1
      value: 19.559
    - type: mrr_at_10
      value: 31.874999999999996
    - type: mrr_at_100
      value: 33.146
    - type: mrr_at_1000
      value: 33.18
    - type: mrr_at_3
      value: 27.667
    - type: mrr_at_5
      value: 29.74
    - type: ndcg_at_1
      value: 19.061
    - type: ndcg_at_10
      value: 39.062999999999995
    - type: ndcg_at_100
      value: 45.184000000000005
    - type: ndcg_at_1000
      value: 46.115
    - type: ndcg_at_3
      value: 30.203000000000003
    - type: ndcg_at_5
      value: 33.953
    - type: precision_at_1
      value: 19.061
    - type: precision_at_10
      value: 6.279999999999999
    - type: precision_at_100
      value: 0.9129999999999999
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_3
      value: 12.706999999999999
    - type: precision_at_5
      value: 9.431000000000001
    - type: recall_at_1
      value: 19.061
    - type: recall_at_10
      value: 62.802
    - type: recall_at_100
      value: 91.323
    - type: recall_at_1000
      value: 98.72
    - type: recall_at_3
      value: 38.122
    - type: recall_at_5
      value: 47.155
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 39.22266660528253
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 30.79980849482483
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 57.8790068352054
    - type: mrr
      value: 71.78791276436706
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 82.36328364043163
    - type: cos_sim_spearman
      value: 82.26211536195868
    - type: euclidean_pearson
      value: 80.3183865039173
    - type: euclidean_spearman
      value: 79.88495276296132
    - type: manhattan_pearson
      value: 80.14484480692127
    - type: manhattan_spearman
      value: 80.39279565980743
  - 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: 98.0375782881002
    - type: f1
      value: 97.86012526096033
    - type: precision
      value: 97.77139874739039
    - type: recall
      value: 98.0375782881002
  - 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: 93.35241030156286
    - type: f1
      value: 92.66050333846944
    - type: precision
      value: 92.3306919069631
    - type: recall
      value: 93.35241030156286
  - 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: 94.0699688257707
    - type: f1
      value: 93.50236693222492
    - type: precision
      value: 93.22791825424315
    - type: recall
      value: 94.0699688257707
  - 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: 89.25750394944708
    - type: f1
      value: 88.79234684921889
    - type: precision
      value: 88.57293312269616
    - type: recall
      value: 89.25750394944708
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 79.41558441558442
    - type: f1
      value: 79.25886487487219
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.747820820329736
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 27.045143830596146
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: BeIR/cqadupstack
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 24.252999999999997
    - type: map_at_10
      value: 31.655916666666666
    - type: map_at_100
      value: 32.680749999999996
    - type: map_at_1000
      value: 32.79483333333334
    - type: map_at_3
      value: 29.43691666666666
    - type: map_at_5
      value: 30.717416666666665
    - type: mrr_at_1
      value: 28.602750000000004
    - type: mrr_at_10
      value: 35.56875
    - type: mrr_at_100
      value: 36.3595
    - type: mrr_at_1000
      value: 36.427749999999996
    - type: mrr_at_3
      value: 33.586166666666664
    - type: mrr_at_5
      value: 34.73641666666666
    - type: ndcg_at_1
      value: 28.602750000000004
    - type: ndcg_at_10
      value: 36.06933333333334
    - type: ndcg_at_100
      value: 40.70141666666667
    - type: ndcg_at_1000
      value: 43.24341666666667
    - type: ndcg_at_3
      value: 32.307916666666664
    - type: ndcg_at_5
      value: 34.129999999999995
    - type: precision_at_1
      value: 28.602750000000004
    - type: precision_at_10
      value: 6.097666666666667
    - type: precision_at_100
      value: 0.9809166666666668
    - type: precision_at_1000
      value: 0.13766666666666663
    - type: precision_at_3
      value: 14.628166666666667
    - type: precision_at_5
      value: 10.266916666666667
    - type: recall_at_1
      value: 24.252999999999997
    - type: recall_at_10
      value: 45.31916666666667
    - type: recall_at_100
      value: 66.03575000000001
    - type: recall_at_1000
      value: 83.94708333333334
    - type: recall_at_3
      value: 34.71941666666666
    - type: recall_at_5
      value: 39.46358333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: climate-fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 9.024000000000001
    - type: map_at_10
      value: 15.644
    - type: map_at_100
      value: 17.154
    - type: map_at_1000
      value: 17.345
    - type: map_at_3
      value: 13.028
    - type: map_at_5
      value: 14.251
    - type: mrr_at_1
      value: 19.674
    - type: mrr_at_10
      value: 29.826999999999998
    - type: mrr_at_100
      value: 30.935000000000002
    - type: mrr_at_1000
      value: 30.987
    - type: mrr_at_3
      value: 26.645000000000003
    - type: mrr_at_5
      value: 28.29
    - type: ndcg_at_1
      value: 19.674
    - type: ndcg_at_10
      value: 22.545
    - type: ndcg_at_100
      value: 29.207
    - type: ndcg_at_1000
      value: 32.912
    - type: ndcg_at_3
      value: 17.952
    - type: ndcg_at_5
      value: 19.363
    - type: precision_at_1
      value: 19.674
    - type: precision_at_10
      value: 7.212000000000001
    - type: precision_at_100
      value: 1.435
    - type: precision_at_1000
      value: 0.212
    - type: precision_at_3
      value: 13.507
    - type: precision_at_5
      value: 10.397
    - type: recall_at_1
      value: 9.024000000000001
    - type: recall_at_10
      value: 28.077999999999996
    - type: recall_at_100
      value: 51.403
    - type: recall_at_1000
      value: 72.406
    - type: recall_at_3
      value: 16.768
    - type: recall_at_5
      value: 20.737
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: dbpedia-entity
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 8.012
    - type: map_at_10
      value: 17.138
    - type: map_at_100
      value: 24.146
    - type: map_at_1000
      value: 25.622
    - type: map_at_3
      value: 12.552
    - type: map_at_5
      value: 14.435
    - type: mrr_at_1
      value: 62.25000000000001
    - type: mrr_at_10
      value: 71.186
    - type: mrr_at_100
      value: 71.504
    - type: mrr_at_1000
      value: 71.514
    - type: mrr_at_3
      value: 69.333
    - type: mrr_at_5
      value: 70.408
    - type: ndcg_at_1
      value: 49.75
    - type: ndcg_at_10
      value: 37.76
    - type: ndcg_at_100
      value: 42.071
    - type: ndcg_at_1000
      value: 49.309
    - type: ndcg_at_3
      value: 41.644
    - type: ndcg_at_5
      value: 39.812999999999995
    - type: precision_at_1
      value: 62.25000000000001
    - type: precision_at_10
      value: 30.15
    - type: precision_at_100
      value: 9.753
    - type: precision_at_1000
      value: 1.9189999999999998
    - type: precision_at_3
      value: 45.667
    - type: precision_at_5
      value: 39.15
    - type: recall_at_1
      value: 8.012
    - type: recall_at_10
      value: 22.599
    - type: recall_at_100
      value: 48.068
    - type: recall_at_1000
      value: 71.328
    - type: recall_at_3
      value: 14.043
    - type: recall_at_5
      value: 17.124
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 42.455
    - type: f1
      value: 37.59462649781862
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: fever
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 58.092
    - type: map_at_10
      value: 69.586
    - type: map_at_100
      value: 69.968
    - type: map_at_1000
      value: 69.982
    - type: map_at_3
      value: 67.48100000000001
    - type: map_at_5
      value: 68.915
    - type: mrr_at_1
      value: 62.166
    - type: mrr_at_10
      value: 73.588
    - type: mrr_at_100
      value: 73.86399999999999
    - type: mrr_at_1000
      value: 73.868
    - type: mrr_at_3
      value: 71.6
    - type: mrr_at_5
      value: 72.99
    - type: ndcg_at_1
      value: 62.166
    - type: ndcg_at_10
      value: 75.27199999999999
    - type: ndcg_at_100
      value: 76.816
    - type: ndcg_at_1000
      value: 77.09700000000001
    - type: ndcg_at_3
      value: 71.36
    - type: ndcg_at_5
      value: 73.785
    - type: precision_at_1
      value: 62.166
    - type: precision_at_10
      value: 9.716
    - type: precision_at_100
      value: 1.065
    - type: precision_at_1000
      value: 0.11
    - type: precision_at_3
      value: 28.278
    - type: precision_at_5
      value: 18.343999999999998
    - type: recall_at_1
      value: 58.092
    - type: recall_at_10
      value: 88.73400000000001
    - type: recall_at_100
      value: 95.195
    - type: recall_at_1000
      value: 97.04599999999999
    - type: recall_at_3
      value: 78.45
    - type: recall_at_5
      value: 84.316
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: fiqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 16.649
    - type: map_at_10
      value: 26.457000000000004
    - type: map_at_100
      value: 28.169
    - type: map_at_1000
      value: 28.352
    - type: map_at_3
      value: 23.305
    - type: map_at_5
      value: 25.169000000000004
    - type: mrr_at_1
      value: 32.407000000000004
    - type: mrr_at_10
      value: 40.922
    - type: mrr_at_100
      value: 41.931000000000004
    - type: mrr_at_1000
      value: 41.983
    - type: mrr_at_3
      value: 38.786
    - type: mrr_at_5
      value: 40.205999999999996
    - type: ndcg_at_1
      value: 32.407000000000004
    - type: ndcg_at_10
      value: 33.314
    - type: ndcg_at_100
      value: 40.312
    - type: ndcg_at_1000
      value: 43.685
    - type: ndcg_at_3
      value: 30.391000000000002
    - type: ndcg_at_5
      value: 31.525
    - type: precision_at_1
      value: 32.407000000000004
    - type: precision_at_10
      value: 8.966000000000001
    - type: precision_at_100
      value: 1.6019999999999999
    - type: precision_at_1000
      value: 0.22200000000000003
    - type: precision_at_3
      value: 20.165
    - type: precision_at_5
      value: 14.722
    - type: recall_at_1
      value: 16.649
    - type: recall_at_10
      value: 39.117000000000004
    - type: recall_at_100
      value: 65.726
    - type: recall_at_1000
      value: 85.784
    - type: recall_at_3
      value: 27.914
    - type: recall_at_5
      value: 33.289
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: hotpotqa
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 36.253
    - type: map_at_10
      value: 56.16799999999999
    - type: map_at_100
      value: 57.06099999999999
    - type: map_at_1000
      value: 57.126
    - type: map_at_3
      value: 52.644999999999996
    - type: map_at_5
      value: 54.909
    - type: mrr_at_1
      value: 72.505
    - type: mrr_at_10
      value: 79.66
    - type: mrr_at_100
      value: 79.869
    - type: mrr_at_1000
      value: 79.88
    - type: mrr_at_3
      value: 78.411
    - type: mrr_at_5
      value: 79.19800000000001
    - type: ndcg_at_1
      value: 72.505
    - type: ndcg_at_10
      value: 65.094
    - type: ndcg_at_100
      value: 68.219
    - type: ndcg_at_1000
      value: 69.515
    - type: ndcg_at_3
      value: 59.99
    - type: ndcg_at_5
      value: 62.909000000000006
    - type: precision_at_1
      value: 72.505
    - type: precision_at_10
      value: 13.749
    - type: precision_at_100
      value: 1.619
    - type: precision_at_1000
      value: 0.179
    - type: precision_at_3
      value: 38.357
    - type: precision_at_5
      value: 25.313000000000002
    - type: recall_at_1
      value: 36.253
    - type: recall_at_10
      value: 68.744
    - type: recall_at_100
      value: 80.925
    - type: recall_at_1000
      value: 89.534
    - type: recall_at_3
      value: 57.535000000000004
    - type: recall_at_5
      value: 63.282000000000004
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 80.82239999999999
    - type: ap
      value: 75.65895781725314
    - type: f1
      value: 80.75880969095746
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: msmarco
      config: default
      split: dev
      revision: None
    metrics:
    - type: map_at_1
      value: 21.624
    - type: map_at_10
      value: 34.075
    - type: map_at_100
      value: 35.229
    - type: map_at_1000
      value: 35.276999999999994
    - type: map_at_3
      value: 30.245
    - type: map_at_5
      value: 32.42
    - type: mrr_at_1
      value: 22.264
    - type: mrr_at_10
      value: 34.638000000000005
    - type: mrr_at_100
      value: 35.744
    - type: mrr_at_1000
      value: 35.787
    - type: mrr_at_3
      value: 30.891000000000002
    - type: mrr_at_5
      value: 33.042
    - type: ndcg_at_1
      value: 22.264
    - type: ndcg_at_10
      value: 40.991
    - type: ndcg_at_100
      value: 46.563
    - type: ndcg_at_1000
      value: 47.743
    - type: ndcg_at_3
      value: 33.198
    - type: ndcg_at_5
      value: 37.069
    - type: precision_at_1
      value: 22.264
    - type: precision_at_10
      value: 6.5089999999999995
    - type: precision_at_100
      value: 0.9299999999999999
    - type: precision_at_1000
      value: 0.10300000000000001
    - type: precision_at_3
      value: 14.216999999999999
    - type: precision_at_5
      value: 10.487
    - type: recall_at_1
      value: 21.624
    - type: recall_at_10
      value: 62.303
    - type: recall_at_100
      value: 88.124
    - type: recall_at_1000
      value: 97.08
    - type: recall_at_3
      value: 41.099999999999994
    - type: recall_at_5
      value: 50.381
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.06703146374831
    - type: f1
      value: 90.86867815863172
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (de)
      type: mteb/mtop_domain
      config: de
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 87.46970977740209
    - type: f1
      value: 86.36832872036588
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (es)
      type: mteb/mtop_domain
      config: es
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.26951300867245
    - type: f1
      value: 88.93561193959502
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (fr)
      type: mteb/mtop_domain
      config: fr
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 84.22799874725963
    - type: f1
      value: 84.30490069236556
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (hi)
      type: mteb/mtop_domain
      config: hi
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 86.02007888131948
    - type: f1
      value: 85.39376041027991
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (th)
      type: mteb/mtop_domain
      config: th
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 85.34900542495481
    - type: f1
      value: 85.39859673336713
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 71.078431372549
    - type: f1
      value: 53.45071102002276
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (de)
      type: mteb/mtop_intent
      config: de
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 65.85798816568047
    - type: f1
      value: 46.53112748993529
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (es)
      type: mteb/mtop_intent
      config: es
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 67.96864576384256
    - type: f1
      value: 45.966703022829506
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (fr)
      type: mteb/mtop_intent
      config: fr
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 61.31537738803633
    - type: f1
      value: 45.52601712835461
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (hi)
      type: mteb/mtop_intent
      config: hi
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 66.29616349946218
    - type: f1
      value: 47.24166485726613
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (th)
      type: mteb/mtop_intent
      config: th
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 67.51537070524412
    - type: f1
      value: 49.463476319014276
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (af)
      type: mteb/amazon_massive_intent
      config: af
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 57.06792199058508
    - type: f1
      value: 54.094921857502285
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (am)
      type: mteb/amazon_massive_intent
      config: am
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 51.960322797579025
    - type: f1
      value: 48.547371223370945
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ar)
      type: mteb/amazon_massive_intent
      config: ar
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 54.425016812373904
    - type: f1
      value: 50.47069202054312
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (az)
      type: mteb/amazon_massive_intent
      config: az
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 59.798251513113655
    - type: f1
      value: 57.05013069086648
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (bn)
      type: mteb/amazon_massive_intent
      config: bn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 59.37794216543376
    - type: f1
      value: 56.3607992649805
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (cy)
      type: mteb/amazon_massive_intent
      config: cy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 46.56018829858777
    - type: f1
      value: 43.87319715715134
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (da)
      type: mteb/amazon_massive_intent
      config: da
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.9724277067922
    - type: f1
      value: 59.36480066245562
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (de)
      type: mteb/amazon_massive_intent
      config: de
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 62.72696704774715
    - type: f1
      value: 59.143595966615855
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (el)
      type: mteb/amazon_massive_intent
      config: el
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.5971755211836
    - type: f1
      value: 59.169445724946726
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 70.29589778076665
    - type: f1
      value: 67.7577001808977
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (es)
      type: mteb/amazon_massive_intent
      config: es
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 66.31136516476126
    - type: f1
      value: 64.52032955983242
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fa)
      type: mteb/amazon_massive_intent
      config: fa
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.54472091459314
    - type: f1
      value: 61.47903120066317
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fi)
      type: mteb/amazon_massive_intent
      config: fi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.45595158036314
    - type: f1
      value: 58.0891846024637
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (fr)
      type: mteb/amazon_massive_intent
      config: fr
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.47074646940149
    - type: f1
      value: 62.84830858877575
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (he)
      type: mteb/amazon_massive_intent
      config: he
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.046402151983855
    - type: f1
      value: 55.269074430533195
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hi)
      type: mteb/amazon_massive_intent
      config: hi
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 64.06523201075991
    - type: f1
      value: 61.35339643021369
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hu)
      type: mteb/amazon_massive_intent
      config: hu
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.954942837928726
    - type: f1
      value: 57.07035922704846
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (hy)
      type: mteb/amazon_massive_intent
      config: hy
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 57.404169468728995
    - type: f1
      value: 53.94259011839138
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (id)
      type: mteb/amazon_massive_intent
      config: id
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 64.16610625420309
    - type: f1
      value: 61.337103431499365
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (is)
      type: mteb/amazon_massive_intent
      config: is
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 52.262945527908535
    - type: f1
      value: 49.7610691598921
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (it)
      type: mteb/amazon_massive_intent
      config: it
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.54472091459314
    - type: f1
      value: 63.469099018440154
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ja)
      type: mteb/amazon_massive_intent
      config: ja
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 68.22797579018157
    - type: f1
      value: 64.89098471083001
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (jv)
      type: mteb/amazon_massive_intent
      config: jv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 50.847343644922674
    - type: f1
      value: 47.8536963168393
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ka)
      type: mteb/amazon_massive_intent
      config: ka
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 48.45326160053799
    - type: f1
      value: 46.370078045805556
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (km)
      type: mteb/amazon_massive_intent
      config: km
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 42.83120376597175
    - type: f1
      value: 39.68948521599982
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (kn)
      type: mteb/amazon_massive_intent
      config: kn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 57.5084061869536
    - type: f1
      value: 53.961876160401545
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ko)
      type: mteb/amazon_massive_intent
      config: ko
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 63.7895090786819
    - type: f1
      value: 61.134223684676
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (lv)
      type: mteb/amazon_massive_intent
      config: lv
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 54.98991257565569
    - type: f1
      value: 52.579862862826296
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ml)
      type: mteb/amazon_massive_intent
      config: ml
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.90316072629456
    - type: f1
      value: 58.203024538290336
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (mn)
      type: mteb/amazon_massive_intent
      config: mn
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 57.09818426361802
    - type: f1
      value: 54.22718458445455
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ms)
      type: mteb/amazon_massive_intent
      config: ms
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 58.991257565568255
    - type: f1
      value: 55.84892781767421
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (my)
      type: mteb/amazon_massive_intent
      config: my
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 55.901143241425686
    - type: f1
      value: 52.25264332199797
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (nb)
      type: mteb/amazon_massive_intent
      config: nb
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 61.96368527236047
    - type: f1
      value: 58.927243876153454
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (nl)
      type: mteb/amazon_massive_intent
      config: nl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.64223268325489
    - type: f1
      value: 62.340453718379706
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (pl)
      type: mteb/amazon_massive_intent
      config: pl
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 64.52589105581708
    - type: f1
      value: 61.661113187022174
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (pt)
      type: mteb/amazon_massive_intent
      config: pt
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 66.84599865501009
    - type: f1
      value: 64.59342572873005
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (ro)
      type: mteb/amazon_massive_intent
      config: ro
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 60.81035642232684
    - type: f1
      value: 57.5169089806797
  - task:
      type: Classification
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      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
    dataset:
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  - task:
      type: Classification
    dataset:
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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      type: mteb/amazon_massive_intent
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  - task:
      type: Classification
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      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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  - task:
      type: Classification
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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      value: 63.792945486912856
  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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    - type: main_score
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  - task:
      type: Classification
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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    - type: f1
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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      value: 58.15063887020847
    - type: f1
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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      value: 59.43846671149966
    - type: f1
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  - task:
      type: Classification
    dataset:
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      type: mteb/amazon_massive_scenario
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      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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      value: 60.8507061197041
    - type: f1
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  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (th)
      type: mteb/amazon_massive_scenario
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      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
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    - type: accuracy
      value: 70.65568258238063
    - type: f1
      value: 69.90736239440633
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tl)
      type: mteb/amazon_massive_scenario
      config: tl
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 60.8843308675185
    - type: f1
      value: 59.30332663713599
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (tr)
      type: mteb/amazon_massive_scenario
      config: tr
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 68.05312710154674
    - type: f1
      value: 67.44024062594775
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (ur)
      type: mteb/amazon_massive_scenario
      config: ur
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 62.111634162743776
    - type: f1
      value: 60.89083013084519
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (vi)
      type: mteb/amazon_massive_scenario
      config: vi
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 67.44115669132482
    - type: f1
      value: 67.92227541674552
  - 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: 74.4687289845326
    - type: f1
      value: 74.16376793486025
  - 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: 68.31876260928043
    - type: f1
      value: 68.5246745215607
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 30.90431696479766
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 27.259158476693774
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 30.28445330838555
    - type: mrr
      value: 31.15758529581164
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: nfcorpus
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 5.353
    - type: map_at_10
      value: 11.565
    - type: map_at_100
      value: 14.097000000000001
    - type: map_at_1000
      value: 15.354999999999999
    - type: map_at_3
      value: 8.749
    - type: map_at_5
      value: 9.974
    - type: mrr_at_1
      value: 42.105
    - type: mrr_at_10
      value: 50.589
    - type: mrr_at_100
      value: 51.187000000000005
    - type: mrr_at_1000
      value: 51.233
    - type: mrr_at_3
      value: 48.246
    - type: mrr_at_5
      value: 49.546
    - type: ndcg_at_1
      value: 40.402
    - type: ndcg_at_10
      value: 31.009999999999998
    - type: ndcg_at_100
      value: 28.026
    - type: ndcg_at_1000
      value: 36.905
    - type: ndcg_at_3
      value: 35.983
    - type: ndcg_at_5
      value: 33.764
    - type: precision_at_1
      value: 42.105
    - type: precision_at_10
      value: 22.786
    - type: precision_at_100
      value: 6.916
    - type: precision_at_1000
      value: 1.981
    - type: precision_at_3
      value: 33.333
    - type: precision_at_5
      value: 28.731
    - type: recall_at_1
      value: 5.353
    - type: recall_at_10
      value: 15.039
    - type: recall_at_100
      value: 27.348
    - type: recall_at_1000
      value: 59.453
    - type: recall_at_3
      value: 9.792
    - type: recall_at_5
      value: 11.882
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: nq
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 33.852
    - type: map_at_10
      value: 48.924
    - type: map_at_100
      value: 49.854
    - type: map_at_1000
      value: 49.886
    - type: map_at_3
      value: 44.9
    - type: map_at_5
      value: 47.387
    - type: mrr_at_1
      value: 38.035999999999994
    - type: mrr_at_10
      value: 51.644
    - type: mrr_at_100
      value: 52.339
    - type: mrr_at_1000
      value: 52.35999999999999
    - type: mrr_at_3
      value: 48.421
    - type: mrr_at_5
      value: 50.468999999999994
    - type: ndcg_at_1
      value: 38.007000000000005
    - type: ndcg_at_10
      value: 56.293000000000006
    - type: ndcg_at_100
      value: 60.167
    - type: ndcg_at_1000
      value: 60.916000000000004
    - type: ndcg_at_3
      value: 48.903999999999996
    - type: ndcg_at_5
      value: 52.978
    - type: precision_at_1
      value: 38.007000000000005
    - type: precision_at_10
      value: 9.041
    - type: precision_at_100
      value: 1.1199999999999999
    - type: precision_at_1000
      value: 0.11900000000000001
    - type: precision_at_3
      value: 22.084
    - type: precision_at_5
      value: 15.608
    - type: recall_at_1
      value: 33.852
    - type: recall_at_10
      value: 75.893
    - type: recall_at_100
      value: 92.589
    - type: recall_at_1000
      value: 98.153
    - type: recall_at_3
      value: 56.969
    - type: recall_at_5
      value: 66.283
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: quora
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 69.174
    - type: map_at_10
      value: 82.891
    - type: map_at_100
      value: 83.545
    - type: map_at_1000
      value: 83.56700000000001
    - type: map_at_3
      value: 79.944
    - type: map_at_5
      value: 81.812
    - type: mrr_at_1
      value: 79.67999999999999
    - type: mrr_at_10
      value: 86.279
    - type: mrr_at_100
      value: 86.39
    - type: mrr_at_1000
      value: 86.392
    - type: mrr_at_3
      value: 85.21
    - type: mrr_at_5
      value: 85.92999999999999
    - type: ndcg_at_1
      value: 79.69000000000001
    - type: ndcg_at_10
      value: 86.929
    - type: ndcg_at_100
      value: 88.266
    - type: ndcg_at_1000
      value: 88.428
    - type: ndcg_at_3
      value: 83.899
    - type: ndcg_at_5
      value: 85.56700000000001
    - type: precision_at_1
      value: 79.69000000000001
    - type: precision_at_10
      value: 13.161000000000001
    - type: precision_at_100
      value: 1.513
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 36.603
    - type: precision_at_5
      value: 24.138
    - type: recall_at_1
      value: 69.174
    - type: recall_at_10
      value: 94.529
    - type: recall_at_100
      value: 99.15
    - type: recall_at_1000
      value: 99.925
    - type: recall_at_3
      value: 85.86200000000001
    - type: recall_at_5
      value: 90.501
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 39.13064340585255
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 282350215ef01743dc01b456c7f5241fa8937f16
    metrics:
    - type: v_measure
      value: 58.97884249325877
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: scidocs
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 3.4680000000000004
    - type: map_at_10
      value: 7.865
    - type: map_at_100
      value: 9.332
    - type: map_at_1000
      value: 9.587
    - type: map_at_3
      value: 5.800000000000001
    - type: map_at_5
      value: 6.8790000000000004
    - type: mrr_at_1
      value: 17.0
    - type: mrr_at_10
      value: 25.629
    - type: mrr_at_100
      value: 26.806
    - type: mrr_at_1000
      value: 26.889000000000003
    - type: mrr_at_3
      value: 22.8
    - type: mrr_at_5
      value: 24.26
    - type: ndcg_at_1
      value: 17.0
    - type: ndcg_at_10
      value: 13.895
    - type: ndcg_at_100
      value: 20.491999999999997
    - type: ndcg_at_1000
      value: 25.759999999999998
    - type: ndcg_at_3
      value: 13.347999999999999
    - type: ndcg_at_5
      value: 11.61
    - type: precision_at_1
      value: 17.0
    - type: precision_at_10
      value: 7.090000000000001
    - type: precision_at_100
      value: 1.669
    - type: precision_at_1000
      value: 0.294
    - type: precision_at_3
      value: 12.3
    - type: precision_at_5
      value: 10.02
    - type: recall_at_1
      value: 3.4680000000000004
    - type: recall_at_10
      value: 14.363000000000001
    - type: recall_at_100
      value: 33.875
    - type: recall_at_1000
      value: 59.711999999999996
    - type: recall_at_3
      value: 7.483
    - type: recall_at_5
      value: 10.173
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
    metrics:
    - type: cos_sim_pearson
      value: 83.04084311714061
    - type: cos_sim_spearman
      value: 77.51342467443078
    - type: euclidean_pearson
      value: 80.0321166028479
    - type: euclidean_spearman
      value: 77.29249114733226
    - type: manhattan_pearson
      value: 80.03105964262431
    - type: manhattan_spearman
      value: 77.22373689514794
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 84.1680158034387
    - type: cos_sim_spearman
      value: 76.55983344071117
    - type: euclidean_pearson
      value: 79.75266678300143
    - type: euclidean_spearman
      value: 75.34516823467025
    - type: manhattan_pearson
      value: 79.75959151517357
    - type: manhattan_spearman
      value: 75.42330344141912
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 76.48898993209346
    - type: cos_sim_spearman
      value: 76.96954120323366
    - type: euclidean_pearson
      value: 76.94139109279668
    - type: euclidean_spearman
      value: 76.85860283201711
    - type: manhattan_pearson
      value: 76.6944095091912
    - type: manhattan_spearman
      value: 76.61096912972553
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 77.85082366246944
    - type: cos_sim_spearman
      value: 75.52053350101731
    - type: euclidean_pearson
      value: 77.1165845070926
    - type: euclidean_spearman
      value: 75.31216065884388
    - type: manhattan_pearson
      value: 77.06193941833494
    - type: manhattan_spearman
      value: 75.31003701700112
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 86.36305246526497
    - type: cos_sim_spearman
      value: 87.11704613927415
    - type: euclidean_pearson
      value: 86.04199125810939
    - type: euclidean_spearman
      value: 86.51117572414263
    - type: manhattan_pearson
      value: 86.0805106816633
    - type: manhattan_spearman
      value: 86.52798366512229
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 82.18536255599724
    - type: cos_sim_spearman
      value: 83.63377151025418
    - type: euclidean_pearson
      value: 83.24657467993141
    - type: euclidean_spearman
      value: 84.02751481993825
    - type: manhattan_pearson
      value: 83.11941806582371
    - type: manhattan_spearman
      value: 83.84251281019304
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ko-ko)
      type: mteb/sts17-crosslingual-sts
      config: ko-ko
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 78.95816528475514
    - type: cos_sim_spearman
      value: 78.86607380120462
    - type: euclidean_pearson
      value: 78.51268699230545
    - type: euclidean_spearman
      value: 79.11649316502229
    - type: manhattan_pearson
      value: 78.32367302808157
    - type: manhattan_spearman
      value: 78.90277699624637
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (ar-ar)
      type: mteb/sts17-crosslingual-sts
      config: ar-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 72.89126914997624
    - type: cos_sim_spearman
      value: 73.0296921832678
    - type: euclidean_pearson
      value: 71.50385903677738
    - type: euclidean_spearman
      value: 73.13368899716289
    - type: manhattan_pearson
      value: 71.47421463379519
    - type: manhattan_spearman
      value: 73.03383242946575
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 59.22923684492637
    - type: cos_sim_spearman
      value: 57.41013211368396
    - type: euclidean_pearson
      value: 61.21107388080905
    - type: euclidean_spearman
      value: 60.07620768697254
    - type: manhattan_pearson
      value: 59.60157142786555
    - type: manhattan_spearman
      value: 59.14069604103739
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 76.24345978774299
    - type: cos_sim_spearman
      value: 77.24225743830719
    - type: euclidean_pearson
      value: 76.66226095469165
    - type: euclidean_spearman
      value: 77.60708820493146
    - type: manhattan_pearson
      value: 76.05303324760429
    - type: manhattan_spearman
      value: 76.96353149912348
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 85.50879160160852
    - type: cos_sim_spearman
      value: 86.43594662965224
    - type: euclidean_pearson
      value: 86.06846012826577
    - type: euclidean_spearman
      value: 86.02041395794136
    - type: manhattan_pearson
      value: 86.10916255616904
    - type: manhattan_spearman
      value: 86.07346068198953
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 58.39803698977196
    - type: cos_sim_spearman
      value: 55.96910950423142
    - type: euclidean_pearson
      value: 58.17941175613059
    - type: euclidean_spearman
      value: 55.03019330522745
    - type: manhattan_pearson
      value: 57.333358138183286
    - type: manhattan_spearman
      value: 54.04614023149965
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 70.98304089637197
    - type: cos_sim_spearman
      value: 72.44071656215888
    - type: euclidean_pearson
      value: 72.19224359033983
    - type: euclidean_spearman
      value: 73.89871188913025
    - type: manhattan_pearson
      value: 71.21098311547406
    - type: manhattan_spearman
      value: 72.93405764824821
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-es)
      type: mteb/sts17-crosslingual-sts
      config: es-es
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 85.99792397466308
    - type: cos_sim_spearman
      value: 84.83824377879495
    - type: euclidean_pearson
      value: 85.70043288694438
    - type: euclidean_spearman
      value: 84.70627558703686
    - type: manhattan_pearson
      value: 85.89570850150801
    - type: manhattan_spearman
      value: 84.95806105313007
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 72.21850322994712
    - type: cos_sim_spearman
      value: 72.28669398117248
    - type: euclidean_pearson
      value: 73.40082510412948
    - type: euclidean_spearman
      value: 73.0326539281865
    - type: manhattan_pearson
      value: 71.8659633964841
    - type: manhattan_spearman
      value: 71.57817425823303
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 75.80921368595645
    - type: cos_sim_spearman
      value: 77.33209091229315
    - type: euclidean_pearson
      value: 76.53159540154829
    - type: euclidean_spearman
      value: 78.17960842810093
    - type: manhattan_pearson
      value: 76.13530186637601
    - type: manhattan_spearman
      value: 78.00701437666875
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
    metrics:
    - type: cos_sim_pearson
      value: 74.74980608267349
    - type: cos_sim_spearman
      value: 75.37597374318821
    - type: euclidean_pearson
      value: 74.90506081911661
    - type: euclidean_spearman
      value: 75.30151613124521
    - type: manhattan_pearson
      value: 74.62642745918002
    - type: manhattan_spearman
      value: 75.18619716592303
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 59.632662289205584
    - type: cos_sim_spearman
      value: 60.938543391610914
    - type: euclidean_pearson
      value: 62.113200529767056
    - type: euclidean_spearman
      value: 61.410312633261164
    - type: manhattan_pearson
      value: 61.75494698945686
    - type: manhattan_spearman
      value: 60.92726195322362
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de)
      type: mteb/sts22-crosslingual-sts
      config: de
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 45.283470551557244
    - type: cos_sim_spearman
      value: 53.44833015864201
    - type: euclidean_pearson
      value: 41.17892011120893
    - type: euclidean_spearman
      value: 53.81441383126767
    - type: manhattan_pearson
      value: 41.17482200420659
    - type: manhattan_spearman
      value: 53.82180269276363
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es)
      type: mteb/sts22-crosslingual-sts
      config: es
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 60.5069165306236
    - type: cos_sim_spearman
      value: 66.87803259033826
    - type: euclidean_pearson
      value: 63.5428979418236
    - type: euclidean_spearman
      value: 66.9293576586897
    - type: manhattan_pearson
      value: 63.59789526178922
    - type: manhattan_spearman
      value: 66.86555009875066
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl)
      type: mteb/sts22-crosslingual-sts
      config: pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 28.23026196280264
    - type: cos_sim_spearman
      value: 35.79397812652861
    - type: euclidean_pearson
      value: 17.828102102767353
    - type: euclidean_spearman
      value: 35.721501145568894
    - type: manhattan_pearson
      value: 17.77134274219677
    - type: manhattan_spearman
      value: 35.98107902846267
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (tr)
      type: mteb/sts22-crosslingual-sts
      config: tr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 56.51946541393812
    - type: cos_sim_spearman
      value: 63.714686006214485
    - type: euclidean_pearson
      value: 58.32104651305898
    - type: euclidean_spearman
      value: 62.237110895702216
    - type: manhattan_pearson
      value: 58.579416468759185
    - type: manhattan_spearman
      value: 62.459738981727
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ar)
      type: mteb/sts22-crosslingual-sts
      config: ar
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 48.76009839569795
    - type: cos_sim_spearman
      value: 56.65188431953149
    - type: euclidean_pearson
      value: 50.997682160915595
    - type: euclidean_spearman
      value: 55.99910008818135
    - type: manhattan_pearson
      value: 50.76220659606342
    - type: manhattan_spearman
      value: 55.517347595391456
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cosine_pearson
      value: 50.724322379215934
    - type: cosine_spearman
      value: 59.90449732164651
    - type: euclidean_pearson
      value: 50.227545226784024
    - type: euclidean_spearman
      value: 59.898906527601085
    - type: main_score
      value: 59.90449732164651
    - type: manhattan_pearson
      value: 50.21762139819405
    - type: manhattan_spearman
      value: 59.761039813759
    - type: pearson
      value: 50.724322379215934
    - type: spearman
      value: 59.90449732164651
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh)
      type: mteb/sts22-crosslingual-sts
      config: zh
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 54.717524559088005
    - type: cos_sim_spearman
      value: 66.83570886252286
    - type: euclidean_pearson
      value: 58.41338625505467
    - type: euclidean_spearman
      value: 66.68991427704938
    - type: manhattan_pearson
      value: 58.78638572916807
    - type: manhattan_spearman
      value: 66.58684161046335
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr)
      type: mteb/sts22-crosslingual-sts
      config: fr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 73.2962042954962
    - type: cos_sim_spearman
      value: 76.58255504852025
    - type: euclidean_pearson
      value: 75.70983192778257
    - type: euclidean_spearman
      value: 77.4547684870542
    - type: manhattan_pearson
      value: 75.75565853870485
    - type: manhattan_spearman
      value: 76.90208974949428
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 54.47396266924846
    - type: cos_sim_spearman
      value: 56.492267162048606
    - type: euclidean_pearson
      value: 55.998505203070195
    - type: euclidean_spearman
      value: 56.46447012960222
    - type: manhattan_pearson
      value: 54.873172394430995
    - type: manhattan_spearman
      value: 56.58111534551218
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 69.87177267688686
    - type: cos_sim_spearman
      value: 74.57160943395763
    - type: euclidean_pearson
      value: 70.88330406826788
    - type: euclidean_spearman
      value: 74.29767636038422
    - type: manhattan_pearson
      value: 71.38245248369536
    - type: manhattan_spearman
      value: 74.53102232732175
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (it)
      type: mteb/sts22-crosslingual-sts
      config: it
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 72.80225656959544
    - type: cos_sim_spearman
      value: 76.52646173725735
    - type: euclidean_pearson
      value: 73.95710720200799
    - type: euclidean_spearman
      value: 76.54040031984111
    - type: manhattan_pearson
      value: 73.89679971946774
    - type: manhattan_spearman
      value: 76.60886958161574
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 70.70844249898789
    - type: cos_sim_spearman
      value: 72.68571783670241
    - type: euclidean_pearson
      value: 72.38800772441031
    - type: euclidean_spearman
      value: 72.86804422703312
    - type: manhattan_pearson
      value: 71.29840508203515
    - type: manhattan_spearman
      value: 71.86264441749513
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 58.647478923935694
    - type: cos_sim_spearman
      value: 63.74453623540931
    - type: euclidean_pearson
      value: 59.60138032437505
    - type: euclidean_spearman
      value: 63.947930832166065
    - type: manhattan_pearson
      value: 58.59735509491861
    - type: manhattan_spearman
      value: 62.082503844627404
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-it)
      type: mteb/sts22-crosslingual-sts
      config: es-it
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 65.8722516867162
    - type: cos_sim_spearman
      value: 71.81208592523012
    - type: euclidean_pearson
      value: 67.95315252165956
    - type: euclidean_spearman
      value: 73.00749822046009
    - type: manhattan_pearson
      value: 68.07884688638924
    - type: manhattan_spearman
      value: 72.34210325803069
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-fr)
      type: mteb/sts22-crosslingual-sts
      config: de-fr
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 54.5405814240949
    - type: cos_sim_spearman
      value: 60.56838649023775
    - type: euclidean_pearson
      value: 53.011731611314104
    - type: euclidean_spearman
      value: 58.533194841668426
    - type: manhattan_pearson
      value: 53.623067729338494
    - type: manhattan_spearman
      value: 58.018756154446926
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-pl)
      type: mteb/sts22-crosslingual-sts
      config: de-pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 13.611046866216112
    - type: cos_sim_spearman
      value: 28.238192909158492
    - type: euclidean_pearson
      value: 22.16189199885129
    - type: euclidean_spearman
      value: 35.012895679076564
    - type: manhattan_pearson
      value: 21.969771178698387
    - type: manhattan_spearman
      value: 32.456985088607475
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (fr-pl)
      type: mteb/sts22-crosslingual-sts
      config: fr-pl
      split: test
      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
    metrics:
    - type: cos_sim_pearson
      value: 74.58077407011655
    - type: cos_sim_spearman
      value: 84.51542547285167
    - type: euclidean_pearson
      value: 74.64613843596234
    - type: euclidean_spearman
      value: 84.51542547285167
    - type: manhattan_pearson
      value: 75.15335973101396
    - type: manhattan_spearman
      value: 84.51542547285167
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 82.0739825531578
    - type: cos_sim_spearman
      value: 84.01057479311115
    - type: euclidean_pearson
      value: 83.85453227433344
    - type: euclidean_spearman
      value: 84.01630226898655
    - type: manhattan_pearson
      value: 83.75323603028978
    - type: manhattan_spearman
      value: 83.89677983727685
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 78.12945623123957
    - type: mrr
      value: 93.87738713719106
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: scifact
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 52.983000000000004
    - type: map_at_10
      value: 62.946000000000005
    - type: map_at_100
      value: 63.514
    - type: map_at_1000
      value: 63.554
    - type: map_at_3
      value: 60.183
    - type: map_at_5
      value: 61.672000000000004
    - type: mrr_at_1
      value: 55.667
    - type: mrr_at_10
      value: 64.522
    - type: mrr_at_100
      value: 64.957
    - type: mrr_at_1000
      value: 64.995
    - type: mrr_at_3
      value: 62.388999999999996
    - type: mrr_at_5
      value: 63.639
    - type: ndcg_at_1
      value: 55.667
    - type: ndcg_at_10
      value: 67.704
    - type: ndcg_at_100
      value: 70.299
    - type: ndcg_at_1000
      value: 71.241
    - type: ndcg_at_3
      value: 62.866
    - type: ndcg_at_5
      value: 65.16999999999999
    - type: precision_at_1
      value: 55.667
    - type: precision_at_10
      value: 9.033
    - type: precision_at_100
      value: 1.053
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 24.444
    - type: precision_at_5
      value: 16.133
    - type: recall_at_1
      value: 52.983000000000004
    - type: recall_at_10
      value: 80.656
    - type: recall_at_100
      value: 92.5
    - type: recall_at_1000
      value: 99.667
    - type: recall_at_3
      value: 67.744
    - type: recall_at_5
      value: 73.433
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.72772277227723
    - type: cos_sim_ap
      value: 92.17845897992215
    - type: cos_sim_f1
      value: 85.9746835443038
    - type: cos_sim_precision
      value: 87.07692307692308
    - type: cos_sim_recall
      value: 84.89999999999999
    - type: dot_accuracy
      value: 99.3039603960396
    - type: dot_ap
      value: 60.70244020124878
    - type: dot_f1
      value: 59.92742353551063
    - type: dot_precision
      value: 62.21743810548978
    - type: dot_recall
      value: 57.8
    - type: euclidean_accuracy
      value: 99.71683168316832
    - type: euclidean_ap
      value: 91.53997039964659
    - type: euclidean_f1
      value: 84.88372093023257
    - type: euclidean_precision
      value: 90.02242152466367
    - type: euclidean_recall
      value: 80.30000000000001
    - type: manhattan_accuracy
      value: 99.72376237623763
    - type: manhattan_ap
      value: 91.80756777790289
    - type: manhattan_f1
      value: 85.48468106479157
    - type: manhattan_precision
      value: 85.8728557013118
    - type: manhattan_recall
      value: 85.1
    - type: max_accuracy
      value: 99.72772277227723
    - type: max_ap
      value: 92.17845897992215
    - type: max_f1
      value: 85.9746835443038
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 53.52464042600003
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.071631948736
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 49.19552407604654
    - type: mrr
      value: 49.95269130379425
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 29.345293033095427
    - type: cos_sim_spearman
      value: 29.976931423258403
    - type: dot_pearson
      value: 27.047078008958408
    - type: dot_spearman
      value: 27.75894368380218
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: trec-covid
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 0.22
    - type: map_at_10
      value: 1.706
    - type: map_at_100
      value: 9.634
    - type: map_at_1000
      value: 23.665
    - type: map_at_3
      value: 0.5950000000000001
    - type: map_at_5
      value: 0.95
    - type: mrr_at_1
      value: 86.0
    - type: mrr_at_10
      value: 91.8
    - type: mrr_at_100
      value: 91.8
    - type: mrr_at_1000
      value: 91.8
    - type: mrr_at_3
      value: 91.0
    - type: mrr_at_5
      value: 91.8
    - type: ndcg_at_1
      value: 80.0
    - type: ndcg_at_10
      value: 72.573
    - type: ndcg_at_100
      value: 53.954
    - type: ndcg_at_1000
      value: 47.760999999999996
    - type: ndcg_at_3
      value: 76.173
    - type: ndcg_at_5
      value: 75.264
    - type: precision_at_1
      value: 86.0
    - type: precision_at_10
      value: 76.4
    - type: precision_at_100
      value: 55.50000000000001
    - type: precision_at_1000
      value: 21.802
    - type: precision_at_3
      value: 81.333
    - type: precision_at_5
      value: 80.4
    - type: recall_at_1
      value: 0.22
    - type: recall_at_10
      value: 1.925
    - type: recall_at_100
      value: 12.762
    - type: recall_at_1000
      value: 44.946000000000005
    - type: recall_at_3
      value: 0.634
    - type: recall_at_5
      value: 1.051
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (sqi-eng)
      type: mteb/tatoeba-bitext-mining
      config: sqi-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 91.0
    - type: f1
      value: 88.55666666666666
    - type: precision
      value: 87.46166666666667
    - type: recall
      value: 91.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fry-eng)
      type: mteb/tatoeba-bitext-mining
      config: fry-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 57.22543352601156
    - type: f1
      value: 51.03220478943021
    - type: precision
      value: 48.8150289017341
    - type: recall
      value: 57.22543352601156
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kur-eng)
      type: mteb/tatoeba-bitext-mining
      config: kur-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 46.58536585365854
    - type: f1
      value: 39.66870798578116
    - type: precision
      value: 37.416085946573745
    - type: recall
      value: 46.58536585365854
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tur-eng)
      type: mteb/tatoeba-bitext-mining
      config: tur-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 89.7
    - type: f1
      value: 86.77999999999999
    - type: precision
      value: 85.45333333333332
    - type: recall
      value: 89.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (deu-eng)
      type: mteb/tatoeba-bitext-mining
      config: deu-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 97.39999999999999
    - type: f1
      value: 96.58333333333331
    - type: precision
      value: 96.2
    - type: recall
      value: 97.39999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nld-eng)
      type: mteb/tatoeba-bitext-mining
      config: nld-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 92.4
    - type: f1
      value: 90.3
    - type: precision
      value: 89.31666666666668
    - type: recall
      value: 92.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ron-eng)
      type: mteb/tatoeba-bitext-mining
      config: ron-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 86.9
    - type: f1
      value: 83.67190476190476
    - type: precision
      value: 82.23333333333332
    - type: recall
      value: 86.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ang-eng)
      type: mteb/tatoeba-bitext-mining
      config: ang-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 50.0
    - type: f1
      value: 42.23229092632078
    - type: precision
      value: 39.851634683724235
    - type: recall
      value: 50.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ido-eng)
      type: mteb/tatoeba-bitext-mining
      config: ido-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 76.3
    - type: f1
      value: 70.86190476190477
    - type: precision
      value: 68.68777777777777
    - type: recall
      value: 76.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (jav-eng)
      type: mteb/tatoeba-bitext-mining
      config: jav-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 57.073170731707314
    - type: f1
      value: 50.658958927251604
    - type: precision
      value: 48.26480836236933
    - type: recall
      value: 57.073170731707314
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (isl-eng)
      type: mteb/tatoeba-bitext-mining
      config: isl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 68.2
    - type: f1
      value: 62.156507936507936
    - type: precision
      value: 59.84964285714286
    - type: recall
      value: 68.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (slv-eng)
      type: mteb/tatoeba-bitext-mining
      config: slv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 77.52126366950182
    - type: f1
      value: 72.8496210148701
    - type: precision
      value: 70.92171498003819
    - type: recall
      value: 77.52126366950182
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cym-eng)
      type: mteb/tatoeba-bitext-mining
      config: cym-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 70.78260869565217
    - type: f1
      value: 65.32422360248447
    - type: precision
      value: 63.063067367415194
    - type: recall
      value: 70.78260869565217
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kaz-eng)
      type: mteb/tatoeba-bitext-mining
      config: kaz-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 78.43478260869566
    - type: f1
      value: 73.02608695652172
    - type: precision
      value: 70.63768115942028
    - type: recall
      value: 78.43478260869566
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (est-eng)
      type: mteb/tatoeba-bitext-mining
      config: est-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 60.9
    - type: f1
      value: 55.309753694581275
    - type: precision
      value: 53.130476190476195
    - type: recall
      value: 60.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (heb-eng)
      type: mteb/tatoeba-bitext-mining
      config: heb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 72.89999999999999
    - type: f1
      value: 67.92023809523809
    - type: precision
      value: 65.82595238095237
    - type: recall
      value: 72.89999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gla-eng)
      type: mteb/tatoeba-bitext-mining
      config: gla-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 46.80337756332931
    - type: f1
      value: 39.42174900558496
    - type: precision
      value: 36.97101116280851
    - type: recall
      value: 46.80337756332931
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mar-eng)
      type: mteb/tatoeba-bitext-mining
      config: mar-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 89.8
    - type: f1
      value: 86.79
    - type: precision
      value: 85.375
    - type: recall
      value: 89.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lat-eng)
      type: mteb/tatoeba-bitext-mining
      config: lat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 47.199999999999996
    - type: f1
      value: 39.95484348984349
    - type: precision
      value: 37.561071428571424
    - type: recall
      value: 47.199999999999996
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bel-eng)
      type: mteb/tatoeba-bitext-mining
      config: bel-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 87.8
    - type: f1
      value: 84.68190476190475
    - type: precision
      value: 83.275
    - type: recall
      value: 87.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pms-eng)
      type: mteb/tatoeba-bitext-mining
      config: pms-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 48.76190476190476
    - type: f1
      value: 42.14965986394558
    - type: precision
      value: 39.96743626743626
    - type: recall
      value: 48.76190476190476
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gle-eng)
      type: mteb/tatoeba-bitext-mining
      config: gle-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 66.10000000000001
    - type: f1
      value: 59.58580086580086
    - type: precision
      value: 57.150238095238095
    - type: recall
      value: 66.10000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pes-eng)
      type: mteb/tatoeba-bitext-mining
      config: pes-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 87.3
    - type: f1
      value: 84.0
    - type: precision
      value: 82.48666666666666
    - type: recall
      value: 87.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nob-eng)
      type: mteb/tatoeba-bitext-mining
      config: nob-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 90.4
    - type: f1
      value: 87.79523809523809
    - type: precision
      value: 86.6
    - type: recall
      value: 90.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bul-eng)
      type: mteb/tatoeba-bitext-mining
      config: bul-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 87.0
    - type: f1
      value: 83.81
    - type: precision
      value: 82.36666666666666
    - type: recall
      value: 87.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cbk-eng)
      type: mteb/tatoeba-bitext-mining
      config: cbk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 63.9
    - type: f1
      value: 57.76533189033189
    - type: precision
      value: 55.50595238095239
    - type: recall
      value: 63.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hun-eng)
      type: mteb/tatoeba-bitext-mining
      config: hun-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 76.1
    - type: f1
      value: 71.83690476190478
    - type: precision
      value: 70.04928571428573
    - type: recall
      value: 76.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (uig-eng)
      type: mteb/tatoeba-bitext-mining
      config: uig-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 66.3
    - type: f1
      value: 59.32626984126984
    - type: precision
      value: 56.62535714285713
    - type: recall
      value: 66.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (rus-eng)
      type: mteb/tatoeba-bitext-mining
      config: rus-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 92.10000000000001
    - type: f1
      value: 89.76666666666667
    - type: main_score
      value: 89.76666666666667
    - type: precision
      value: 88.64999999999999
    - type: recall
      value: 92.10000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (spa-eng)
      type: mteb/tatoeba-bitext-mining
      config: spa-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 93.10000000000001
    - type: f1
      value: 91.10000000000001
    - type: precision
      value: 90.16666666666666
    - type: recall
      value: 93.10000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hye-eng)
      type: mteb/tatoeba-bitext-mining
      config: hye-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 85.71428571428571
    - type: f1
      value: 82.29142600436403
    - type: precision
      value: 80.8076626877166
    - type: recall
      value: 85.71428571428571
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tel-eng)
      type: mteb/tatoeba-bitext-mining
      config: tel-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.88888888888889
    - type: f1
      value: 85.7834757834758
    - type: precision
      value: 84.43732193732193
    - type: recall
      value: 88.88888888888889
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (afr-eng)
      type: mteb/tatoeba-bitext-mining
      config: afr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.5
    - type: f1
      value: 85.67190476190476
    - type: precision
      value: 84.43333333333332
    - type: recall
      value: 88.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mon-eng)
      type: mteb/tatoeba-bitext-mining
      config: mon-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 82.72727272727273
    - type: f1
      value: 78.21969696969695
    - type: precision
      value: 76.18181818181819
    - type: recall
      value: 82.72727272727273
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (arz-eng)
      type: mteb/tatoeba-bitext-mining
      config: arz-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 61.0062893081761
    - type: f1
      value: 55.13976240391334
    - type: precision
      value: 52.92112499659669
    - type: recall
      value: 61.0062893081761
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hrv-eng)
      type: mteb/tatoeba-bitext-mining
      config: hrv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 89.5
    - type: f1
      value: 86.86666666666666
    - type: precision
      value: 85.69166666666668
    - type: recall
      value: 89.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nov-eng)
      type: mteb/tatoeba-bitext-mining
      config: nov-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 73.54085603112841
    - type: f1
      value: 68.56031128404669
    - type: precision
      value: 66.53047989623866
    - type: recall
      value: 73.54085603112841
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (gsw-eng)
      type: mteb/tatoeba-bitext-mining
      config: gsw-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 43.58974358974359
    - type: f1
      value: 36.45299145299145
    - type: precision
      value: 33.81155881155882
    - type: recall
      value: 43.58974358974359
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nds-eng)
      type: mteb/tatoeba-bitext-mining
      config: nds-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 59.599999999999994
    - type: f1
      value: 53.264689754689755
    - type: precision
      value: 50.869166666666665
    - type: recall
      value: 59.599999999999994
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ukr-eng)
      type: mteb/tatoeba-bitext-mining
      config: ukr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 85.2
    - type: f1
      value: 81.61666666666665
    - type: precision
      value: 80.02833333333335
    - type: recall
      value: 85.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (uzb-eng)
      type: mteb/tatoeba-bitext-mining
      config: uzb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 63.78504672897196
    - type: f1
      value: 58.00029669188548
    - type: precision
      value: 55.815809968847354
    - type: recall
      value: 63.78504672897196
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lit-eng)
      type: mteb/tatoeba-bitext-mining
      config: lit-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 66.5
    - type: f1
      value: 61.518333333333345
    - type: precision
      value: 59.622363699102834
    - type: recall
      value: 66.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ina-eng)
      type: mteb/tatoeba-bitext-mining
      config: ina-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.6
    - type: f1
      value: 85.60222222222221
    - type: precision
      value: 84.27916666666665
    - type: recall
      value: 88.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lfn-eng)
      type: mteb/tatoeba-bitext-mining
      config: lfn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 58.699999999999996
    - type: f1
      value: 52.732375957375965
    - type: precision
      value: 50.63214035964035
    - type: recall
      value: 58.699999999999996
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (zsm-eng)
      type: mteb/tatoeba-bitext-mining
      config: zsm-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 92.10000000000001
    - type: f1
      value: 89.99666666666667
    - type: precision
      value: 89.03333333333333
    - type: recall
      value: 92.10000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ita-eng)
      type: mteb/tatoeba-bitext-mining
      config: ita-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 90.10000000000001
    - type: f1
      value: 87.55666666666667
    - type: precision
      value: 86.36166666666668
    - type: recall
      value: 90.10000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cmn-eng)
      type: mteb/tatoeba-bitext-mining
      config: cmn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 91.4
    - type: f1
      value: 88.89000000000001
    - type: precision
      value: 87.71166666666666
    - type: recall
      value: 91.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (lvs-eng)
      type: mteb/tatoeba-bitext-mining
      config: lvs-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 65.7
    - type: f1
      value: 60.67427750410509
    - type: precision
      value: 58.71785714285714
    - type: recall
      value: 65.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (glg-eng)
      type: mteb/tatoeba-bitext-mining
      config: glg-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 85.39999999999999
    - type: f1
      value: 81.93190476190475
    - type: precision
      value: 80.37833333333333
    - type: recall
      value: 85.39999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ceb-eng)
      type: mteb/tatoeba-bitext-mining
      config: ceb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 47.833333333333336
    - type: f1
      value: 42.006625781625786
    - type: precision
      value: 40.077380952380956
    - type: recall
      value: 47.833333333333336
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bre-eng)
      type: mteb/tatoeba-bitext-mining
      config: bre-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 10.4
    - type: f1
      value: 8.24465007215007
    - type: precision
      value: 7.664597069597071
    - type: recall
      value: 10.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ben-eng)
      type: mteb/tatoeba-bitext-mining
      config: ben-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 82.6
    - type: f1
      value: 77.76333333333334
    - type: precision
      value: 75.57833333333332
    - type: recall
      value: 82.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swg-eng)
      type: mteb/tatoeba-bitext-mining
      config: swg-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 52.67857142857143
    - type: f1
      value: 44.302721088435376
    - type: precision
      value: 41.49801587301587
    - type: recall
      value: 52.67857142857143
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (arq-eng)
      type: mteb/tatoeba-bitext-mining
      config: arq-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 28.3205268935236
    - type: f1
      value: 22.426666605171157
    - type: precision
      value: 20.685900116470915
    - type: recall
      value: 28.3205268935236
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kab-eng)
      type: mteb/tatoeba-bitext-mining
      config: kab-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 22.7
    - type: f1
      value: 17.833970473970474
    - type: precision
      value: 16.407335164835164
    - type: recall
      value: 22.7
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fra-eng)
      type: mteb/tatoeba-bitext-mining
      config: fra-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 92.2
    - type: f1
      value: 89.92999999999999
    - type: precision
      value: 88.87
    - type: recall
      value: 92.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (por-eng)
      type: mteb/tatoeba-bitext-mining
      config: por-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 91.4
    - type: f1
      value: 89.25
    - type: precision
      value: 88.21666666666667
    - type: recall
      value: 91.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tat-eng)
      type: mteb/tatoeba-bitext-mining
      config: tat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 69.19999999999999
    - type: f1
      value: 63.38269841269841
    - type: precision
      value: 61.14773809523809
    - type: recall
      value: 69.19999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (oci-eng)
      type: mteb/tatoeba-bitext-mining
      config: oci-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 48.8
    - type: f1
      value: 42.839915639915645
    - type: precision
      value: 40.770287114845935
    - type: recall
      value: 48.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pol-eng)
      type: mteb/tatoeba-bitext-mining
      config: pol-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.8
    - type: f1
      value: 85.90666666666668
    - type: precision
      value: 84.54166666666666
    - type: recall
      value: 88.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (war-eng)
      type: mteb/tatoeba-bitext-mining
      config: war-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 46.6
    - type: f1
      value: 40.85892920804686
    - type: precision
      value: 38.838223114604695
    - type: recall
      value: 46.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (aze-eng)
      type: mteb/tatoeba-bitext-mining
      config: aze-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 84.0
    - type: f1
      value: 80.14190476190475
    - type: precision
      value: 78.45333333333333
    - type: recall
      value: 84.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (vie-eng)
      type: mteb/tatoeba-bitext-mining
      config: vie-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 90.5
    - type: f1
      value: 87.78333333333333
    - type: precision
      value: 86.5
    - type: recall
      value: 90.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (nno-eng)
      type: mteb/tatoeba-bitext-mining
      config: nno-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 74.5
    - type: f1
      value: 69.48397546897547
    - type: precision
      value: 67.51869047619049
    - type: recall
      value: 74.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cha-eng)
      type: mteb/tatoeba-bitext-mining
      config: cha-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 32.846715328467155
    - type: f1
      value: 27.828177499710343
    - type: precision
      value: 26.63451511991658
    - type: recall
      value: 32.846715328467155
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mhr-eng)
      type: mteb/tatoeba-bitext-mining
      config: mhr-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.0
    - type: f1
      value: 6.07664116764988
    - type: precision
      value: 5.544177607179943
    - type: recall
      value: 8.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dan-eng)
      type: mteb/tatoeba-bitext-mining
      config: dan-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 87.6
    - type: f1
      value: 84.38555555555554
    - type: precision
      value: 82.91583333333334
    - type: recall
      value: 87.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ell-eng)
      type: mteb/tatoeba-bitext-mining
      config: ell-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 87.5
    - type: f1
      value: 84.08333333333331
    - type: precision
      value: 82.47333333333333
    - type: recall
      value: 87.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (amh-eng)
      type: mteb/tatoeba-bitext-mining
      config: amh-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 80.95238095238095
    - type: f1
      value: 76.13095238095238
    - type: precision
      value: 74.05753968253967
    - type: recall
      value: 80.95238095238095
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (pam-eng)
      type: mteb/tatoeba-bitext-mining
      config: pam-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.799999999999999
    - type: f1
      value: 6.971422975172975
    - type: precision
      value: 6.557814916172301
    - type: recall
      value: 8.799999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hsb-eng)
      type: mteb/tatoeba-bitext-mining
      config: hsb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 44.099378881987576
    - type: f1
      value: 37.01649742022413
    - type: precision
      value: 34.69420618488942
    - type: recall
      value: 44.099378881987576
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (srp-eng)
      type: mteb/tatoeba-bitext-mining
      config: srp-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 84.3
    - type: f1
      value: 80.32666666666667
    - type: precision
      value: 78.60666666666665
    - type: recall
      value: 84.3
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (epo-eng)
      type: mteb/tatoeba-bitext-mining
      config: epo-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 92.5
    - type: f1
      value: 90.49666666666666
    - type: precision
      value: 89.56666666666668
    - type: recall
      value: 92.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kzj-eng)
      type: mteb/tatoeba-bitext-mining
      config: kzj-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 10.0
    - type: f1
      value: 8.268423529875141
    - type: precision
      value: 7.878118605532398
    - type: recall
      value: 10.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (awa-eng)
      type: mteb/tatoeba-bitext-mining
      config: awa-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 79.22077922077922
    - type: f1
      value: 74.27128427128426
    - type: precision
      value: 72.28715728715729
    - type: recall
      value: 79.22077922077922
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fao-eng)
      type: mteb/tatoeba-bitext-mining
      config: fao-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 65.64885496183206
    - type: f1
      value: 58.87495456197747
    - type: precision
      value: 55.992366412213734
    - type: recall
      value: 65.64885496183206
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mal-eng)
      type: mteb/tatoeba-bitext-mining
      config: mal-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 96.06986899563319
    - type: f1
      value: 94.78408539543909
    - type: precision
      value: 94.15332362930616
    - type: recall
      value: 96.06986899563319
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ile-eng)
      type: mteb/tatoeba-bitext-mining
      config: ile-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 77.2
    - type: f1
      value: 71.72571428571428
    - type: precision
      value: 69.41000000000001
    - type: recall
      value: 77.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (bos-eng)
      type: mteb/tatoeba-bitext-mining
      config: bos-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 86.4406779661017
    - type: f1
      value: 83.2391713747646
    - type: precision
      value: 81.74199623352166
    - type: recall
      value: 86.4406779661017
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cor-eng)
      type: mteb/tatoeba-bitext-mining
      config: cor-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 8.4
    - type: f1
      value: 6.017828743398003
    - type: precision
      value: 5.4829865484756795
    - type: recall
      value: 8.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (cat-eng)
      type: mteb/tatoeba-bitext-mining
      config: cat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 83.5
    - type: f1
      value: 79.74833333333333
    - type: precision
      value: 78.04837662337664
    - type: recall
      value: 83.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (eus-eng)
      type: mteb/tatoeba-bitext-mining
      config: eus-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 60.4
    - type: f1
      value: 54.467301587301584
    - type: precision
      value: 52.23242424242424
    - type: recall
      value: 60.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (yue-eng)
      type: mteb/tatoeba-bitext-mining
      config: yue-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 74.9
    - type: f1
      value: 69.68699134199134
    - type: precision
      value: 67.59873015873016
    - type: recall
      value: 74.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swe-eng)
      type: mteb/tatoeba-bitext-mining
      config: swe-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.0
    - type: f1
      value: 84.9652380952381
    - type: precision
      value: 83.66166666666666
    - type: recall
      value: 88.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dtp-eng)
      type: mteb/tatoeba-bitext-mining
      config: dtp-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 9.1
    - type: f1
      value: 7.681244588744588
    - type: precision
      value: 7.370043290043291
    - type: recall
      value: 9.1
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kat-eng)
      type: mteb/tatoeba-bitext-mining
      config: kat-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 80.9651474530831
    - type: f1
      value: 76.84220605132133
    - type: precision
      value: 75.19606398962966
    - type: recall
      value: 80.9651474530831
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (jpn-eng)
      type: mteb/tatoeba-bitext-mining
      config: jpn-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 86.9
    - type: f1
      value: 83.705
    - type: precision
      value: 82.3120634920635
    - type: recall
      value: 86.9
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (csb-eng)
      type: mteb/tatoeba-bitext-mining
      config: csb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 29.64426877470356
    - type: f1
      value: 23.98763072676116
    - type: precision
      value: 22.506399397703746
    - type: recall
      value: 29.64426877470356
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (xho-eng)
      type: mteb/tatoeba-bitext-mining
      config: xho-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 70.4225352112676
    - type: f1
      value: 62.84037558685445
    - type: precision
      value: 59.56572769953053
    - type: recall
      value: 70.4225352112676
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (orv-eng)
      type: mteb/tatoeba-bitext-mining
      config: orv-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 19.64071856287425
    - type: f1
      value: 15.125271011207756
    - type: precision
      value: 13.865019261197494
    - type: recall
      value: 19.64071856287425
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ind-eng)
      type: mteb/tatoeba-bitext-mining
      config: ind-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 90.2
    - type: f1
      value: 87.80666666666666
    - type: precision
      value: 86.70833333333331
    - type: recall
      value: 90.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tuk-eng)
      type: mteb/tatoeba-bitext-mining
      config: tuk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 23.15270935960591
    - type: f1
      value: 18.407224958949097
    - type: precision
      value: 16.982385430661292
    - type: recall
      value: 23.15270935960591
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (max-eng)
      type: mteb/tatoeba-bitext-mining
      config: max-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 55.98591549295775
    - type: f1
      value: 49.94718309859154
    - type: precision
      value: 47.77864154624717
    - type: recall
      value: 55.98591549295775
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (swh-eng)
      type: mteb/tatoeba-bitext-mining
      config: swh-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 73.07692307692307
    - type: f1
      value: 66.74358974358974
    - type: precision
      value: 64.06837606837607
    - type: recall
      value: 73.07692307692307
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (hin-eng)
      type: mteb/tatoeba-bitext-mining
      config: hin-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 94.89999999999999
    - type: f1
      value: 93.25
    - type: precision
      value: 92.43333333333332
    - type: recall
      value: 94.89999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (dsb-eng)
      type: mteb/tatoeba-bitext-mining
      config: dsb-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 37.78705636743215
    - type: f1
      value: 31.63899658680452
    - type: precision
      value: 29.72264397629742
    - type: recall
      value: 37.78705636743215
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ber-eng)
      type: mteb/tatoeba-bitext-mining
      config: ber-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 21.6
    - type: f1
      value: 16.91697302697303
    - type: precision
      value: 15.71225147075147
    - type: recall
      value: 21.6
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tam-eng)
      type: mteb/tatoeba-bitext-mining
      config: tam-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 85.01628664495115
    - type: f1
      value: 81.38514037536838
    - type: precision
      value: 79.83170466883823
    - type: recall
      value: 85.01628664495115
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (slk-eng)
      type: mteb/tatoeba-bitext-mining
      config: slk-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 83.39999999999999
    - type: f1
      value: 79.96380952380952
    - type: precision
      value: 78.48333333333333
    - type: recall
      value: 83.39999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tgl-eng)
      type: mteb/tatoeba-bitext-mining
      config: tgl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 83.2
    - type: f1
      value: 79.26190476190476
    - type: precision
      value: 77.58833333333334
    - type: recall
      value: 83.2
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ast-eng)
      type: mteb/tatoeba-bitext-mining
      config: ast-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 75.59055118110236
    - type: f1
      value: 71.66854143232096
    - type: precision
      value: 70.30183727034121
    - type: recall
      value: 75.59055118110236
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (mkd-eng)
      type: mteb/tatoeba-bitext-mining
      config: mkd-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 65.5
    - type: f1
      value: 59.26095238095238
    - type: precision
      value: 56.81909090909092
    - type: recall
      value: 65.5
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (khm-eng)
      type: mteb/tatoeba-bitext-mining
      config: khm-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 55.26315789473685
    - type: f1
      value: 47.986523325858506
    - type: precision
      value: 45.33950006595436
    - type: recall
      value: 55.26315789473685
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ces-eng)
      type: mteb/tatoeba-bitext-mining
      config: ces-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 82.89999999999999
    - type: f1
      value: 78.835
    - type: precision
      value: 77.04761904761905
    - type: recall
      value: 82.89999999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tzl-eng)
      type: mteb/tatoeba-bitext-mining
      config: tzl-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 43.269230769230774
    - type: f1
      value: 36.20421245421245
    - type: precision
      value: 33.57371794871795
    - type: recall
      value: 43.269230769230774
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (urd-eng)
      type: mteb/tatoeba-bitext-mining
      config: urd-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 88.0
    - type: f1
      value: 84.70666666666666
    - type: precision
      value: 83.23166666666665
    - type: recall
      value: 88.0
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (ara-eng)
      type: mteb/tatoeba-bitext-mining
      config: ara-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 77.4
    - type: f1
      value: 72.54666666666667
    - type: precision
      value: 70.54318181818181
    - type: recall
      value: 77.4
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (kor-eng)
      type: mteb/tatoeba-bitext-mining
      config: kor-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 78.60000000000001
    - type: f1
      value: 74.1588888888889
    - type: precision
      value: 72.30250000000001
    - type: recall
      value: 78.60000000000001
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (yid-eng)
      type: mteb/tatoeba-bitext-mining
      config: yid-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 72.40566037735849
    - type: f1
      value: 66.82587328813744
    - type: precision
      value: 64.75039308176099
    - type: recall
      value: 72.40566037735849
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (fin-eng)
      type: mteb/tatoeba-bitext-mining
      config: fin-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 73.8
    - type: f1
      value: 68.56357142857144
    - type: precision
      value: 66.3178822055138
    - type: recall
      value: 73.8
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (tha-eng)
      type: mteb/tatoeba-bitext-mining
      config: tha-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 91.78832116788321
    - type: f1
      value: 89.3552311435523
    - type: precision
      value: 88.20559610705597
    - type: recall
      value: 91.78832116788321
  - task:
      type: BitextMining
    dataset:
      name: MTEB Tatoeba (wuu-eng)
      type: mteb/tatoeba-bitext-mining
      config: wuu-eng
      split: test
      revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
    metrics:
    - type: accuracy
      value: 74.3
    - type: f1
      value: 69.05085581085581
    - type: precision
      value: 66.955
    - type: recall
      value: 74.3
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: webis-touche2020
      config: default
      split: test
      revision: None
    metrics:
    - type: map_at_1
      value: 2.896
    - type: map_at_10
      value: 8.993
    - type: map_at_100
      value: 14.133999999999999
    - type: map_at_1000
      value: 15.668000000000001
    - type: map_at_3
      value: 5.862
    - type: map_at_5
      value: 7.17
    - type: mrr_at_1
      value: 34.694
    - type: mrr_at_10
      value: 42.931000000000004
    - type: mrr_at_100
      value: 44.81
    - type: mrr_at_1000
      value: 44.81
    - type: mrr_at_3
      value: 38.435
    - type: mrr_at_5
      value: 41.701
    - type: ndcg_at_1
      value: 31.633
    - type: ndcg_at_10
      value: 21.163
    - type: ndcg_at_100
      value: 33.306000000000004
    - type: ndcg_at_1000
      value: 45.275999999999996
    - type: ndcg_at_3
      value: 25.685999999999996
    - type: ndcg_at_5
      value: 23.732
    - type: precision_at_1
      value: 34.694
    - type: precision_at_10
      value: 17.755000000000003
    - type: precision_at_100
      value: 6.938999999999999
    - type: precision_at_1000
      value: 1.48
    - type: precision_at_3
      value: 25.85
    - type: precision_at_5
      value: 23.265
    - type: recall_at_1
      value: 2.896
    - type: recall_at_10
      value: 13.333999999999998
    - type: recall_at_100
      value: 43.517
    - type: recall_at_1000
      value: 79.836
    - type: recall_at_3
      value: 6.306000000000001
    - type: recall_at_5
      value: 8.825
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
    metrics:
    - type: accuracy
      value: 69.3874
    - type: ap
      value: 13.829909072469423
    - type: f1
      value: 53.54534203543492
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 62.62026032823995
    - type: f1
      value: 62.85251350485221
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 33.21527881409797
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 84.97943613280086
    - type: cos_sim_ap
      value: 70.75454316885921
    - type: cos_sim_f1
      value: 65.38274012676743
    - type: cos_sim_precision
      value: 60.761214318078835
    - type: cos_sim_recall
      value: 70.76517150395777
    - type: dot_accuracy
      value: 79.0546581629612
    - type: dot_ap
      value: 47.3197121792147
    - type: dot_f1
      value: 49.20106524633821
    - type: dot_precision
      value: 42.45499808502489
    - type: dot_recall
      value: 58.49604221635884
    - type: euclidean_accuracy
      value: 85.08076533349228
    - type: euclidean_ap
      value: 70.95016106374474
    - type: euclidean_f1
      value: 65.43987900176455
    - type: euclidean_precision
      value: 62.64478764478765
    - type: euclidean_recall
      value: 68.49604221635884
    - type: manhattan_accuracy
      value: 84.93771234428085
    - type: manhattan_ap
      value: 70.63668388755362
    - type: manhattan_f1
      value: 65.23895401262398
    - type: manhattan_precision
      value: 56.946084218811485
    - type: manhattan_recall
      value: 76.35883905013192
    - type: max_accuracy
      value: 85.08076533349228
    - type: max_ap
      value: 70.95016106374474
    - type: max_f1
      value: 65.43987900176455
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.69096130709822
    - type: cos_sim_ap
      value: 84.82526278228542
    - type: cos_sim_f1
      value: 77.65485060585536
    - type: cos_sim_precision
      value: 75.94582658619167
    - type: cos_sim_recall
      value: 79.44256236526024
    - type: dot_accuracy
      value: 80.97954748321496
    - type: dot_ap
      value: 64.81642914145866
    - type: dot_f1
      value: 60.631996987229975
    - type: dot_precision
      value: 54.5897293631712
    - type: dot_recall
      value: 68.17831844779796
    - type: euclidean_accuracy
      value: 88.6987231730508
    - type: euclidean_ap
      value: 84.80003825477253
    - type: euclidean_f1
      value: 77.67194179854496
    - type: euclidean_precision
      value: 75.7128235122094
    - type: euclidean_recall
      value: 79.73514012935017
    - type: manhattan_accuracy
      value: 88.62692591298949
    - type: manhattan_ap
      value: 84.80451408255276
    - type: manhattan_f1
      value: 77.69888949572183
    - type: manhattan_precision
      value: 73.70311528631622
    - type: manhattan_recall
      value: 82.15275639051433
    - type: max_accuracy
      value: 88.6987231730508
    - type: max_ap
      value: 84.82526278228542
    - type: max_f1
      value: 77.69888949572183
  - task:
      type: BitextMining
    dataset:
      name: MTEB BUCC.v2 (ru-en)
      type: mteb/bucc-bitext-mining
      config: ru-en
      split: test
      revision: 1739dc11ffe9b7bfccd7f3d585aeb4c544fc6677
    metrics:
    - type: accuracy
      value: 95.72566678212678
    - type: f1
      value: 94.42443135896548
    - type: main_score
      value: 94.42443135896548
    - type: precision
      value: 93.80868260016165
    - type: recall
      value: 95.72566678212678
  - task:
      type: Retrieval
    dataset:
      name: MTEB BelebeleRetrieval (rus_Cyrl-rus_Cyrl)
      type: facebook/belebele
      config: rus_Cyrl-rus_Cyrl
      split: test
      revision: 75b399394a9803252cfec289d103de462763db7c
    metrics:
    - type: main_score
      value: 92.23599999999999
    - type: map_at_1
      value: 87.111
    - type: map_at_10
      value: 90.717
    - type: map_at_100
      value: 90.879
    - type: map_at_1000
      value: 90.881
    - type: map_at_20
      value: 90.849
    - type: map_at_3
      value: 90.074
    - type: map_at_5
      value: 90.535
    - type: mrr_at_1
      value: 87.1111111111111
    - type: mrr_at_10
      value: 90.7173721340388
    - type: mrr_at_100
      value: 90.87859682638407
    - type: mrr_at_1000
      value: 90.88093553612326
    - type: mrr_at_20
      value: 90.84863516113515
    - type: mrr_at_3
      value: 90.07407407407409
    - type: mrr_at_5
      value: 90.53518518518521
    - type: nauc_map_at_1000_diff1
      value: 92.37373187280554
    - type: nauc_map_at_1000_max
      value: 79.90465445423249
    - type: nauc_map_at_1000_std
      value: -0.6220290556185463
    - type: nauc_map_at_100_diff1
      value: 92.37386697345335
    - type: nauc_map_at_100_max
      value: 79.90991577223959
    - type: nauc_map_at_100_std
      value: -0.602247514642845
    - type: nauc_map_at_10_diff1
      value: 92.30907447072467
    - type: nauc_map_at_10_max
      value: 79.86831935337598
    - type: nauc_map_at_10_std
      value: -0.7455191860719699
    - type: nauc_map_at_1_diff1
      value: 93.29828518358822
    - type: nauc_map_at_1_max
      value: 78.69539619887887
    - type: nauc_map_at_1_std
      value: -4.097150817605763
    - type: nauc_map_at_20_diff1
      value: 92.38414149703077
    - type: nauc_map_at_20_max
      value: 79.94789814504661
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      value: -0.3928031130400773
    - type: nauc_map_at_3_diff1
      value: 92.21688899306734
    - type: nauc_map_at_3_max
      value: 80.34586671780885
    - type: nauc_map_at_3_std
      value: 0.24088319695435909
    - type: nauc_map_at_5_diff1
      value: 92.27931726042982
    - type: nauc_map_at_5_max
      value: 79.99198834003367
    - type: nauc_map_at_5_std
      value: -0.6296366922840796
    - type: nauc_mrr_at_1000_diff1
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    - type: nauc_mrr_at_1000_max
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    - type: nauc_mrr_at_1000_std
      value: -0.6220290556185463
    - type: nauc_mrr_at_100_diff1
      value: 92.37386697345335
    - type: nauc_mrr_at_100_max
      value: 79.90991577223959
    - type: nauc_mrr_at_100_std
      value: -0.602247514642845
    - type: nauc_mrr_at_10_diff1
      value: 92.30907447072467
    - type: nauc_mrr_at_10_max
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    - type: nauc_mrr_at_10_std
      value: -0.7455191860719699
    - type: nauc_mrr_at_1_diff1
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    - type: nauc_mrr_at_1_max
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    - type: nauc_mrr_at_1_std
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    - type: nauc_mrr_at_20_diff1
      value: 92.38414149703077
    - type: nauc_mrr_at_20_max
      value: 79.94789814504661
    - type: nauc_mrr_at_20_std
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    - type: nauc_mrr_at_3_diff1
      value: 92.21688899306734
    - type: nauc_mrr_at_3_max
      value: 80.34586671780885
    - type: nauc_mrr_at_3_std
      value: 0.24088319695435909
    - type: nauc_mrr_at_5_diff1
      value: 92.27931726042982
    - type: nauc_mrr_at_5_max
      value: 79.99198834003367
    - type: nauc_mrr_at_5_std
      value: -0.6296366922840796
    - type: nauc_ndcg_at_1000_diff1
      value: 92.30526497646306
    - type: nauc_ndcg_at_1000_max
      value: 80.12734537480418
    - type: nauc_ndcg_at_1000_std
      value: 0.22849408935578744
    - type: nauc_ndcg_at_100_diff1
      value: 92.31347123202318
    - type: nauc_ndcg_at_100_max
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    - type: nauc_ndcg_at_100_std
      value: 0.816825944406239
    - type: nauc_ndcg_at_10_diff1
      value: 92.05430189845808
    - type: nauc_ndcg_at_10_max
      value: 80.16515667442968
    - type: nauc_ndcg_at_10_std
      value: 0.7486447532544893
    - type: nauc_ndcg_at_1_diff1
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    - type: nauc_ndcg_at_1_max
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    - type: nauc_ndcg_at_20_diff1
      value: 92.40147868825079
    - type: nauc_ndcg_at_20_max
      value: 80.5117307181802
    - type: nauc_ndcg_at_20_std
      value: 2.0431351539517033
    - type: nauc_ndcg_at_3_diff1
      value: 91.88894444422789
    - type: nauc_ndcg_at_3_max
      value: 81.09256084196045
    - type: nauc_ndcg_at_3_std
      value: 2.422705909643621
    - type: nauc_ndcg_at_5_diff1
      value: 91.99711052955728
    - type: nauc_ndcg_at_5_max
      value: 80.46996334573979
    - type: nauc_ndcg_at_5_std
      value: 0.9086986899040708
    - type: nauc_precision_at_1000_diff1
      value: .nan
    - type: nauc_precision_at_1000_max
      value: .nan
    - type: nauc_precision_at_1000_std
      value: .nan
    - type: nauc_precision_at_100_diff1
      value: 93.46405228758012
    - type: nauc_precision_at_100_max
      value: 100.0
    - type: nauc_precision_at_100_std
      value: 70.71661998132774
    - type: nauc_precision_at_10_diff1
      value: 90.13938908896874
    - type: nauc_precision_at_10_max
      value: 82.21121782046167
    - type: nauc_precision_at_10_std
      value: 13.075230092036083
    - type: nauc_precision_at_1_diff1
      value: 93.29828518358822
    - type: nauc_precision_at_1_max
      value: 78.69539619887887
    - type: nauc_precision_at_1_std
      value: -4.097150817605763
    - type: nauc_precision_at_20_diff1
      value: 94.9723479135242
    - type: nauc_precision_at_20_max
      value: 91.04000574588684
    - type: nauc_precision_at_20_std
      value: 48.764634058749586
    - type: nauc_precision_at_3_diff1
      value: 90.52690041533852
    - type: nauc_precision_at_3_max
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  - task:
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      value: .nan
    - type: nauc_recall_at_100_diff1
      value: 60.93103908229921
    - type: nauc_recall_at_100_max
      value: 52.62104841936668
    - type: nauc_recall_at_100_std
      value: 85.60090702947748
    - type: nauc_recall_at_10_diff1
      value: 76.26517273576097
    - type: nauc_recall_at_10_max
      value: 65.20136943666347
    - type: nauc_recall_at_10_std
      value: 26.50357920946174
    - type: nauc_recall_at_1_diff1
      value: 86.37079221403225
    - type: nauc_recall_at_1_max
      value: 61.856861655370686
    - type: nauc_recall_at_1_std
      value: 4.708911881992707
    - type: nauc_recall_at_20_diff1
      value: 73.47946930710269
    - type: nauc_recall_at_20_max
      value: 70.19520986689254
    - type: nauc_recall_at_20_std
      value: 45.93186111653943
    - type: nauc_recall_at_3_diff1
      value: 79.02026879450173
    - type: nauc_recall_at_3_max
      value: 58.750746246923924
    - type: nauc_recall_at_3_std
      value: 16.740684654251076
    - type: nauc_recall_at_5_diff1
      value: 76.4758566228162
    - type: nauc_recall_at_5_max
      value: 61.862709220131386
    - type: nauc_recall_at_5_std
      value: 20.18336254550361
    - type: ndcg_at_1
      value: 73.444
    - type: ndcg_at_10
      value: 82.748
    - type: ndcg_at_100
      value: 84.416
    - type: ndcg_at_1000
      value: 84.52300000000001
    - type: ndcg_at_20
      value: 83.646
    - type: ndcg_at_3
      value: 80.267
    - type: ndcg_at_5
      value: 81.922
    - type: precision_at_1
      value: 73.444
    - type: precision_at_10
      value: 9.167
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.761
    - type: precision_at_3
      value: 28.37
    - type: precision_at_5
      value: 17.822
    - type: recall_at_1
      value: 73.444
    - type: recall_at_10
      value: 91.667
    - type: recall_at_100
      value: 99.222
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 95.222
    - type: recall_at_3
      value: 85.111
    - type: recall_at_5
      value: 89.11099999999999
  - task:
      type: BitextMining
    dataset:
      name: MTEB BibleNLPBitextMining (eng_Latn-rus_Cyrl)
      type: davidstap/biblenlp-corpus-mmteb
      config: eng_Latn-rus_Cyrl
      split: train
      revision: 264a18480c529d9e922483839b4b9758e690b762
    metrics:
    - type: accuracy
      value: 96.875
    - type: f1
      value: 95.83333333333333
    - type: main_score
      value: 95.83333333333333
    - type: precision
      value: 95.3125
    - type: recall
      value: 96.875
  - task:
      type: BitextMining
    dataset:
      name: MTEB BibleNLPBitextMining (rus_Cyrl-eng_Latn)
      type: davidstap/biblenlp-corpus-mmteb
      config: rus_Cyrl-eng_Latn
      split: train
      revision: 264a18480c529d9e922483839b4b9758e690b762
    metrics:
    - type: accuracy
      value: 88.671875
    - type: f1
      value: 85.3515625
    - type: main_score
      value: 85.3515625
    - type: precision
      value: 83.85416666666667
    - type: recall
      value: 88.671875
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB CEDRClassification (default)
      type: ai-forever/cedr-classification
      config: default
      split: test
      revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4
    metrics:
    - type: accuracy
      value: 40.06907545164719
    - type: f1
      value: 26.285000550712407
    - type: lrap
      value: 64.4280021253997
    - type: main_score
      value: 40.06907545164719
  - task:
      type: Classification
    dataset:
      name: MTEB CyrillicTurkicLangClassification (default)
      type: tatiana-merz/cyrillic_turkic_langs
      config: default
      split: test
      revision: e42d330f33d65b7b72dfd408883daf1661f06f18
    metrics:
    - type: accuracy
      value: 43.3447265625
    - type: f1
      value: 40.08400146827895
    - type: f1_weighted
      value: 40.08499428040896
    - type: main_score
      value: 43.3447265625
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ace_Arab-rus_Cyrl)
      type: mteb/flores
      config: ace_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 6.225296442687747
    - type: f1
      value: 5.5190958860075
    - type: main_score
      value: 5.5190958860075
    - type: precision
      value: 5.3752643758000005
    - type: recall
      value: 6.225296442687747
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bam_Latn-rus_Cyrl)
      type: mteb/flores
      config: bam_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.37944664031622
    - type: f1
      value: 64.54819836666252
    - type: main_score
      value: 64.54819836666252
    - type: precision
      value: 63.07479233454916
    - type: recall
      value: 68.37944664031622
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (dzo_Tibt-rus_Cyrl)
      type: mteb/flores
      config: dzo_Tibt-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 0.09881422924901186
    - type: f1
      value: 0.00019509225912934226
    - type: main_score
      value: 0.00019509225912934226
    - type: precision
      value: 9.76425190207627e-05
    - type: recall
      value: 0.09881422924901186
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hin_Deva-rus_Cyrl)
      type: mteb/flores
      config: hin_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.47299077733861
    - type: main_score
      value: 99.47299077733861
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (khm_Khmr-rus_Cyrl)
      type: mteb/flores
      config: khm_Khmr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.83399209486166
    - type: f1
      value: 87.71151056318254
    - type: main_score
      value: 87.71151056318254
    - type: precision
      value: 87.32012500709193
    - type: recall
      value: 88.83399209486166
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mag_Deva-rus_Cyrl)
      type: mteb/flores
      config: mag_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.7239789196311
    - type: main_score
      value: 97.7239789196311
    - type: precision
      value: 97.61904761904762
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pap_Latn-rus_Cyrl)
      type: mteb/flores
      config: pap_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.0711462450593
    - type: f1
      value: 93.68187806922984
    - type: main_score
      value: 93.68187806922984
    - type: precision
      value: 93.58925452707051
    - type: recall
      value: 94.0711462450593
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sot_Latn-rus_Cyrl)
      type: mteb/flores
      config: sot_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 90.9090909090909
    - type: f1
      value: 89.23171936758892
    - type: main_score
      value: 89.23171936758892
    - type: precision
      value: 88.51790014083866
    - type: recall
      value: 90.9090909090909
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tur_Latn-rus_Cyrl)
      type: mteb/flores
      config: tur_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ace_Latn-rus_Cyrl)
      type: mteb/flores
      config: ace_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 66.10671936758892
    - type: f1
      value: 63.81888256297873
    - type: main_score
      value: 63.81888256297873
    - type: precision
      value: 63.01614067933451
    - type: recall
      value: 66.10671936758892
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ban_Latn-rus_Cyrl)
      type: mteb/flores
      config: ban_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 79.44664031620553
    - type: f1
      value: 77.6311962082713
    - type: main_score
      value: 77.6311962082713
    - type: precision
      value: 76.93977931929739
    - type: recall
      value: 79.44664031620553
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ell_Grek-rus_Cyrl)
      type: mteb/flores
      config: ell_Grek-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hne_Deva-rus_Cyrl)
      type: mteb/flores
      config: hne_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.83794466403161
    - type: f1
      value: 96.25352907961603
    - type: main_score
      value: 96.25352907961603
    - type: precision
      value: 96.02155091285526
    - type: recall
      value: 96.83794466403161
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kik_Latn-rus_Cyrl)
      type: mteb/flores
      config: kik_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 76.28458498023716
    - type: f1
      value: 73.5596919895859
    - type: main_score
      value: 73.5596919895859
    - type: precision
      value: 72.40900759055246
    - type: recall
      value: 76.28458498023716
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mai_Deva-rus_Cyrl)
      type: mteb/flores
      config: mai_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.72727272727273
    - type: f1
      value: 97.37812911725956
    - type: main_score
      value: 97.37812911725956
    - type: precision
      value: 97.26002258610953
    - type: recall
      value: 97.72727272727273
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pbt_Arab-rus_Cyrl)
      type: mteb/flores
      config: pbt_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.0711462450593
    - type: f1
      value: 93.34700387331966
    - type: main_score
      value: 93.34700387331966
    - type: precision
      value: 93.06920556920556
    - type: recall
      value: 94.0711462450593
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (spa_Latn-rus_Cyrl)
      type: mteb/flores
      config: spa_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (twi_Latn-rus_Cyrl)
      type: mteb/flores
      config: twi_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.73122529644269
    - type: f1
      value: 77.77434363246721
    - type: main_score
      value: 77.77434363246721
    - type: precision
      value: 76.54444287596462
    - type: recall
      value: 80.73122529644269
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (acm_Arab-rus_Cyrl)
      type: mteb/flores
      config: acm_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.56521739130434
    - type: f1
      value: 92.92490118577075
    - type: main_score
      value: 92.92490118577075
    - type: precision
      value: 92.16897233201581
    - type: recall
      value: 94.56521739130434
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bel_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: bel_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.98550724637681
    - type: main_score
      value: 98.98550724637681
    - type: precision
      value: 98.88833992094862
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (eng_Latn-rus_Cyrl)
      type: mteb/flores
      config: eng_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.4729907773386
    - type: main_score
      value: 99.4729907773386
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hrv_Latn-rus_Cyrl)
      type: mteb/flores
      config: hrv_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 99.05138339920948
    - type: main_score
      value: 99.05138339920948
    - type: precision
      value: 99.00691699604744
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kin_Latn-rus_Cyrl)
      type: mteb/flores
      config: kin_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.2411067193676
    - type: f1
      value: 86.5485246227658
    - type: main_score
      value: 86.5485246227658
    - type: precision
      value: 85.90652101521667
    - type: recall
      value: 88.2411067193676
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mal_Mlym-rus_Cyrl)
      type: mteb/flores
      config: mal_Mlym-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.51778656126481
    - type: f1
      value: 98.07971014492753
    - type: main_score
      value: 98.07971014492753
    - type: precision
      value: 97.88372859025033
    - type: recall
      value: 98.51778656126481
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pes_Arab-rus_Cyrl)
      type: mteb/flores
      config: pes_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.51778656126481
    - type: f1
      value: 98.0566534914361
    - type: main_score
      value: 98.0566534914361
    - type: precision
      value: 97.82608695652173
    - type: recall
      value: 98.51778656126481
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (srd_Latn-rus_Cyrl)
      type: mteb/flores
      config: srd_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.6086956521739
    - type: f1
      value: 80.9173470979821
    - type: main_score
      value: 80.9173470979821
    - type: precision
      value: 80.24468672882627
    - type: recall
      value: 82.6086956521739
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tzm_Tfng-rus_Cyrl)
      type: mteb/flores
      config: tzm_Tfng-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 7.41106719367589
    - type: f1
      value: 6.363562740945329
    - type: main_score
      value: 6.363562740945329
    - type: precision
      value: 6.090373175353411
    - type: recall
      value: 7.41106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (acq_Arab-rus_Cyrl)
      type: mteb/flores
      config: acq_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.25691699604744
    - type: f1
      value: 93.81422924901187
    - type: main_score
      value: 93.81422924901187
    - type: precision
      value: 93.14064558629775
    - type: recall
      value: 95.25691699604744
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bem_Latn-rus_Cyrl)
      type: mteb/flores
      config: bem_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.08300395256917
    - type: f1
      value: 65.01368772860867
    - type: main_score
      value: 65.01368772860867
    - type: precision
      value: 63.91052337510628
    - type: recall
      value: 68.08300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (epo_Latn-rus_Cyrl)
      type: mteb/flores
      config: epo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.41897233201581
    - type: f1
      value: 98.17193675889328
    - type: main_score
      value: 98.17193675889328
    - type: precision
      value: 98.08210564139418
    - type: recall
      value: 98.41897233201581
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hun_Latn-rus_Cyrl)
      type: mteb/flores
      config: hun_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.1106719367589
    - type: main_score
      value: 99.1106719367589
    - type: precision
      value: 99.01185770750988
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kir_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: kir_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.5296442687747
    - type: f1
      value: 97.07549806364035
    - type: main_score
      value: 97.07549806364035
    - type: precision
      value: 96.90958498023716
    - type: recall
      value: 97.5296442687747
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mar_Deva-rus_Cyrl)
      type: mteb/flores
      config: mar_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.44400527009222
    - type: main_score
      value: 97.44400527009222
    - type: precision
      value: 97.28966685488425
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (plt_Latn-rus_Cyrl)
      type: mteb/flores
      config: plt_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 79.9407114624506
    - type: f1
      value: 78.3154177760691
    - type: main_score
      value: 78.3154177760691
    - type: precision
      value: 77.69877344877344
    - type: recall
      value: 79.9407114624506
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (srp_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: srp_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.70355731225297
    - type: f1
      value: 99.60474308300395
    - type: main_score
      value: 99.60474308300395
    - type: precision
      value: 99.55533596837944
    - type: recall
      value: 99.70355731225297
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (uig_Arab-rus_Cyrl)
      type: mteb/flores
      config: uig_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.20158102766798
    - type: f1
      value: 81.44381923034585
    - type: main_score
      value: 81.44381923034585
    - type: precision
      value: 80.78813411582477
    - type: recall
      value: 83.20158102766798
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (aeb_Arab-rus_Cyrl)
      type: mteb/flores
      config: aeb_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.20553359683794
    - type: f1
      value: 88.75352907961603
    - type: main_score
      value: 88.75352907961603
    - type: precision
      value: 87.64328063241106
    - type: recall
      value: 91.20553359683794
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ben_Beng-rus_Cyrl)
      type: mteb/flores
      config: ben_Beng-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.60671936758894
    - type: main_score
      value: 98.60671936758894
    - type: precision
      value: 98.4766139657444
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (est_Latn-rus_Cyrl)
      type: mteb/flores
      config: est_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.24505928853755
    - type: f1
      value: 95.27417027417027
    - type: main_score
      value: 95.27417027417027
    - type: precision
      value: 94.84107378129117
    - type: recall
      value: 96.24505928853755
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hye_Armn-rus_Cyrl)
      type: mteb/flores
      config: hye_Armn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.67786561264822
    - type: main_score
      value: 97.67786561264822
    - type: precision
      value: 97.55839022637441
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kmb_Latn-rus_Cyrl)
      type: mteb/flores
      config: kmb_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 46.047430830039524
    - type: f1
      value: 42.94464804804471
    - type: main_score
      value: 42.94464804804471
    - type: precision
      value: 41.9851895607238
    - type: recall
      value: 46.047430830039524
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (min_Arab-rus_Cyrl)
      type: mteb/flores
      config: min_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 3.9525691699604746
    - type: f1
      value: 3.402665192725756
    - type: main_score
      value: 3.402665192725756
    - type: precision
      value: 3.303787557740127
    - type: recall
      value: 3.9525691699604746
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pol_Latn-rus_Cyrl)
      type: mteb/flores
      config: pol_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.4729907773386
    - type: main_score
      value: 99.4729907773386
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ssw_Latn-rus_Cyrl)
      type: mteb/flores
      config: ssw_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 73.22134387351778
    - type: f1
      value: 70.43086049508975
    - type: main_score
      value: 70.43086049508975
    - type: precision
      value: 69.35312022355656
    - type: recall
      value: 73.22134387351778
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ukr_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: ukr_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.90118577075098
    - type: f1
      value: 99.86824769433464
    - type: main_score
      value: 99.86824769433464
    - type: precision
      value: 99.85177865612648
    - type: recall
      value: 99.90118577075098
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (afr_Latn-rus_Cyrl)
      type: mteb/flores
      config: afr_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bho_Deva-rus_Cyrl)
      type: mteb/flores
      config: bho_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.0711462450593
    - type: f1
      value: 93.12182382834557
    - type: main_score
      value: 93.12182382834557
    - type: precision
      value: 92.7523453232338
    - type: recall
      value: 94.0711462450593
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (eus_Latn-rus_Cyrl)
      type: mteb/flores
      config: eus_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.19367588932806
    - type: f1
      value: 91.23604975587072
    - type: main_score
      value: 91.23604975587072
    - type: precision
      value: 90.86697443588663
    - type: recall
      value: 92.19367588932806
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ibo_Latn-rus_Cyrl)
      type: mteb/flores
      config: ibo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.21343873517787
    - type: f1
      value: 80.17901604858126
    - type: main_score
      value: 80.17901604858126
    - type: precision
      value: 79.3792284780028
    - type: recall
      value: 82.21343873517787
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kmr_Latn-rus_Cyrl)
      type: mteb/flores
      config: kmr_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.67588932806325
    - type: f1
      value: 66.72311714750278
    - type: main_score
      value: 66.72311714750278
    - type: precision
      value: 66.00178401554004
    - type: recall
      value: 68.67588932806325
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (min_Latn-rus_Cyrl)
      type: mteb/flores
      config: min_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 78.65612648221344
    - type: f1
      value: 76.26592719972166
    - type: main_score
      value: 76.26592719972166
    - type: precision
      value: 75.39980459997484
    - type: recall
      value: 78.65612648221344
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (por_Latn-rus_Cyrl)
      type: mteb/flores
      config: por_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.83794466403161
    - type: f1
      value: 95.9669678147939
    - type: main_score
      value: 95.9669678147939
    - type: precision
      value: 95.59453227931488
    - type: recall
      value: 96.83794466403161
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sun_Latn-rus_Cyrl)
      type: mteb/flores
      config: sun_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.4901185770751
    - type: f1
      value: 91.66553983773662
    - type: main_score
      value: 91.66553983773662
    - type: precision
      value: 91.34530928009188
    - type: recall
      value: 92.4901185770751
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (umb_Latn-rus_Cyrl)
      type: mteb/flores
      config: umb_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 41.00790513833992
    - type: f1
      value: 38.21319326004483
    - type: main_score
      value: 38.21319326004483
    - type: precision
      value: 37.200655467675546
    - type: recall
      value: 41.00790513833992
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ajp_Arab-rus_Cyrl)
      type: mteb/flores
      config: ajp_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.35573122529645
    - type: f1
      value: 93.97233201581028
    - type: main_score
      value: 93.97233201581028
    - type: precision
      value: 93.33333333333333
    - type: recall
      value: 95.35573122529645
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bjn_Arab-rus_Cyrl)
      type: mteb/flores
      config: bjn_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 3.6561264822134385
    - type: f1
      value: 3.1071978056336484
    - type: main_score
      value: 3.1071978056336484
    - type: precision
      value: 3.0039741229718215
    - type: recall
      value: 3.6561264822134385
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ewe_Latn-rus_Cyrl)
      type: mteb/flores
      config: ewe_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 62.845849802371546
    - type: f1
      value: 59.82201175670472
    - type: main_score
      value: 59.82201175670472
    - type: precision
      value: 58.72629236362003
    - type: recall
      value: 62.845849802371546
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ilo_Latn-rus_Cyrl)
      type: mteb/flores
      config: ilo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.10276679841897
    - type: f1
      value: 80.75065288987582
    - type: main_score
      value: 80.75065288987582
    - type: precision
      value: 79.80726451662179
    - type: recall
      value: 83.10276679841897
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (knc_Arab-rus_Cyrl)
      type: mteb/flores
      config: knc_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 10.079051383399209
    - type: f1
      value: 8.759282456080921
    - type: main_score
      value: 8.759282456080921
    - type: precision
      value: 8.474735138956142
    - type: recall
      value: 10.079051383399209
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mkd_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: mkd_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.55072463768116
    - type: main_score
      value: 98.55072463768116
    - type: precision
      value: 98.36956521739131
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (prs_Arab-rus_Cyrl)
      type: mteb/flores
      config: prs_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (swe_Latn-rus_Cyrl)
      type: mteb/flores
      config: swe_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.22595520421606
    - type: main_score
      value: 99.22595520421606
    - type: precision
      value: 99.14361001317523
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (urd_Arab-rus_Cyrl)
      type: mteb/flores
      config: urd_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.25625823451911
    - type: main_score
      value: 97.25625823451911
    - type: precision
      value: 97.03063241106719
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (aka_Latn-rus_Cyrl)
      type: mteb/flores
      config: aka_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.22529644268775
    - type: f1
      value: 77.94307687941227
    - type: main_score
      value: 77.94307687941227
    - type: precision
      value: 76.58782793293665
    - type: recall
      value: 81.22529644268775
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bjn_Latn-rus_Cyrl)
      type: mteb/flores
      config: bjn_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.27667984189723
    - type: f1
      value: 83.6869192829922
    - type: main_score
      value: 83.6869192829922
    - type: precision
      value: 83.08670670691656
    - type: recall
      value: 85.27667984189723
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fao_Latn-rus_Cyrl)
      type: mteb/flores
      config: fao_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.9288537549407
    - type: f1
      value: 79.29806087454745
    - type: main_score
      value: 79.29806087454745
    - type: precision
      value: 78.71445871526987
    - type: recall
      value: 80.9288537549407
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ind_Latn-rus_Cyrl)
      type: mteb/flores
      config: ind_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.5296442687747
    - type: main_score
      value: 97.5296442687747
    - type: precision
      value: 97.23320158102767
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (knc_Latn-rus_Cyrl)
      type: mteb/flores
      config: knc_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 33.49802371541502
    - type: f1
      value: 32.02378215033989
    - type: main_score
      value: 32.02378215033989
    - type: precision
      value: 31.511356103747406
    - type: recall
      value: 33.49802371541502
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mlt_Latn-rus_Cyrl)
      type: mteb/flores
      config: mlt_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.40316205533597
    - type: f1
      value: 90.35317684386006
    - type: main_score
      value: 90.35317684386006
    - type: precision
      value: 89.94845939633488
    - type: recall
      value: 91.40316205533597
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (quy_Latn-rus_Cyrl)
      type: mteb/flores
      config: quy_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 40.612648221343875
    - type: f1
      value: 38.74337544712602
    - type: main_score
      value: 38.74337544712602
    - type: precision
      value: 38.133716022178575
    - type: recall
      value: 40.612648221343875
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (swh_Latn-rus_Cyrl)
      type: mteb/flores
      config: swh_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.13438735177866
    - type: f1
      value: 96.47435897435898
    - type: main_score
      value: 96.47435897435898
    - type: precision
      value: 96.18741765480895
    - type: recall
      value: 97.13438735177866
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (uzn_Latn-rus_Cyrl)
      type: mteb/flores
      config: uzn_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.83794466403161
    - type: f1
      value: 96.26355528529442
    - type: main_score
      value: 96.26355528529442
    - type: precision
      value: 96.0501756697409
    - type: recall
      value: 96.83794466403161
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (als_Latn-rus_Cyrl)
      type: mteb/flores
      config: als_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.6907114624506
    - type: main_score
      value: 98.6907114624506
    - type: precision
      value: 98.6142480707698
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bod_Tibt-rus_Cyrl)
      type: mteb/flores
      config: bod_Tibt-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 1.0869565217391304
    - type: f1
      value: 0.9224649610442628
    - type: main_score
      value: 0.9224649610442628
    - type: precision
      value: 0.8894275740459898
    - type: recall
      value: 1.0869565217391304
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fij_Latn-rus_Cyrl)
      type: mteb/flores
      config: fij_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 63.24110671936759
    - type: f1
      value: 60.373189068189525
    - type: main_score
      value: 60.373189068189525
    - type: precision
      value: 59.32326368115546
    - type: recall
      value: 63.24110671936759
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (isl_Latn-rus_Cyrl)
      type: mteb/flores
      config: isl_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.03162055335969
    - type: f1
      value: 87.3102634715907
    - type: main_score
      value: 87.3102634715907
    - type: precision
      value: 86.65991814698712
    - type: recall
      value: 89.03162055335969
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kon_Latn-rus_Cyrl)
      type: mteb/flores
      config: kon_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 73.91304347826086
    - type: f1
      value: 71.518235523573
    - type: main_score
      value: 71.518235523573
    - type: precision
      value: 70.58714102449801
    - type: recall
      value: 73.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mni_Beng-rus_Cyrl)
      type: mteb/flores
      config: mni_Beng-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 29.545454545454547
    - type: f1
      value: 27.59513619889114
    - type: main_score
      value: 27.59513619889114
    - type: precision
      value: 26.983849851025344
    - type: recall
      value: 29.545454545454547
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ron_Latn-rus_Cyrl)
      type: mteb/flores
      config: ron_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (szl_Latn-rus_Cyrl)
      type: mteb/flores
      config: szl_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.26482213438736
    - type: f1
      value: 85.18912031587512
    - type: main_score
      value: 85.18912031587512
    - type: precision
      value: 84.77199409959775
    - type: recall
      value: 86.26482213438736
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (vec_Latn-rus_Cyrl)
      type: mteb/flores
      config: vec_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.67193675889328
    - type: f1
      value: 84.62529734716581
    - type: main_score
      value: 84.62529734716581
    - type: precision
      value: 84.2611422440705
    - type: recall
      value: 85.67193675889328
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (amh_Ethi-rus_Cyrl)
      type: mteb/flores
      config: amh_Ethi-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.76284584980237
    - type: f1
      value: 93.91735076517685
    - type: main_score
      value: 93.91735076517685
    - type: precision
      value: 93.57553798858147
    - type: recall
      value: 94.76284584980237
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bos_Latn-rus_Cyrl)
      type: mteb/flores
      config: bos_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 99.05655938264634
    - type: main_score
      value: 99.05655938264634
    - type: precision
      value: 99.01185770750988
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fin_Latn-rus_Cyrl)
      type: mteb/flores
      config: fin_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.43741765480895
    - type: main_score
      value: 97.43741765480895
    - type: precision
      value: 97.1590909090909
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ita_Latn-rus_Cyrl)
      type: mteb/flores
      config: ita_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.70355731225297
    - type: f1
      value: 99.60474308300395
    - type: main_score
      value: 99.60474308300395
    - type: precision
      value: 99.55533596837944
    - type: recall
      value: 99.70355731225297
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kor_Hang-rus_Cyrl)
      type: mteb/flores
      config: kor_Hang-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.33201581027669
    - type: f1
      value: 96.49868247694334
    - type: main_score
      value: 96.49868247694334
    - type: precision
      value: 96.10507246376811
    - type: recall
      value: 97.33201581027669
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mos_Latn-rus_Cyrl)
      type: mteb/flores
      config: mos_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 34.683794466403164
    - type: f1
      value: 32.766819308009076
    - type: main_score
      value: 32.766819308009076
    - type: precision
      value: 32.1637493670237
    - type: recall
      value: 34.683794466403164
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (run_Latn-rus_Cyrl)
      type: mteb/flores
      config: run_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.399209486166
    - type: f1
      value: 81.10578750604326
    - type: main_score
      value: 81.10578750604326
    - type: precision
      value: 80.16763162673529
    - type: recall
      value: 83.399209486166
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tam_Taml-rus_Cyrl)
      type: mteb/flores
      config: tam_Taml-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.41897233201581
    - type: f1
      value: 98.01548089591567
    - type: main_score
      value: 98.01548089591567
    - type: precision
      value: 97.84020327498588
    - type: recall
      value: 98.41897233201581
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (vie_Latn-rus_Cyrl)
      type: mteb/flores
      config: vie_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.81422924901186
    - type: main_score
      value: 98.81422924901186
    - type: precision
      value: 98.66600790513834
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (apc_Arab-rus_Cyrl)
      type: mteb/flores
      config: apc_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.87351778656127
    - type: f1
      value: 92.10803689064558
    - type: main_score
      value: 92.10803689064558
    - type: precision
      value: 91.30434782608695
    - type: recall
      value: 93.87351778656127
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bug_Latn-rus_Cyrl)
      type: mteb/flores
      config: bug_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 57.608695652173914
    - type: f1
      value: 54.95878654927162
    - type: main_score
      value: 54.95878654927162
    - type: precision
      value: 54.067987427805654
    - type: recall
      value: 57.608695652173914
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fon_Latn-rus_Cyrl)
      type: mteb/flores
      config: fon_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 61.95652173913043
    - type: f1
      value: 58.06537275812945
    - type: main_score
      value: 58.06537275812945
    - type: precision
      value: 56.554057596959204
    - type: recall
      value: 61.95652173913043
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (jav_Latn-rus_Cyrl)
      type: mteb/flores
      config: jav_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.47826086956522
    - type: f1
      value: 92.4784405318002
    - type: main_score
      value: 92.4784405318002
    - type: precision
      value: 92.09168143201127
    - type: recall
      value: 93.47826086956522
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lao_Laoo-rus_Cyrl)
      type: mteb/flores
      config: lao_Laoo-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.10671936758892
    - type: f1
      value: 89.76104922745239
    - type: main_score
      value: 89.76104922745239
    - type: precision
      value: 89.24754593232855
    - type: recall
      value: 91.10671936758892
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mri_Latn-rus_Cyrl)
      type: mteb/flores
      config: mri_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 71.14624505928853
    - type: f1
      value: 68.26947125119062
    - type: main_score
      value: 68.26947125119062
    - type: precision
      value: 67.15942311051006
    - type: recall
      value: 71.14624505928853
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ace_Arab)
      type: mteb/flores
      config: rus_Cyrl-ace_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 19.565217391304348
    - type: f1
      value: 16.321465000323805
    - type: main_score
      value: 16.321465000323805
    - type: precision
      value: 15.478527409347508
    - type: recall
      value: 19.565217391304348
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bam_Latn)
      type: mteb/flores
      config: rus_Cyrl-bam_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 73.41897233201581
    - type: f1
      value: 68.77366228182746
    - type: main_score
      value: 68.77366228182746
    - type: precision
      value: 66.96012924273795
    - type: recall
      value: 73.41897233201581
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-dzo_Tibt)
      type: mteb/flores
      config: rus_Cyrl-dzo_Tibt
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 0.592885375494071
    - type: f1
      value: 0.02458062426370458
    - type: main_score
      value: 0.02458062426370458
    - type: precision
      value: 0.012824114724683876
    - type: recall
      value: 0.592885375494071
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hin_Deva)
      type: mteb/flores
      config: rus_Cyrl-hin_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.90118577075098
    - type: f1
      value: 99.86824769433464
    - type: main_score
      value: 99.86824769433464
    - type: precision
      value: 99.85177865612648
    - type: recall
      value: 99.90118577075098
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-khm_Khmr)
      type: mteb/flores
      config: rus_Cyrl-khm_Khmr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.13438735177866
    - type: f1
      value: 96.24505928853755
    - type: main_score
      value: 96.24505928853755
    - type: precision
      value: 95.81686429512516
    - type: recall
      value: 97.13438735177866
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mag_Deva)
      type: mteb/flores
      config: rus_Cyrl-mag_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.50592885375494
    - type: f1
      value: 99.35770750988142
    - type: main_score
      value: 99.35770750988142
    - type: precision
      value: 99.29183135704875
    - type: recall
      value: 99.50592885375494
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pap_Latn)
      type: mteb/flores
      config: rus_Cyrl-pap_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.93675889328063
    - type: f1
      value: 96.05072463768116
    - type: main_score
      value: 96.05072463768116
    - type: precision
      value: 95.66040843214758
    - type: recall
      value: 96.93675889328063
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sot_Latn)
      type: mteb/flores
      config: rus_Cyrl-sot_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.67588932806325
    - type: f1
      value: 91.7786561264822
    - type: main_score
      value: 91.7786561264822
    - type: precision
      value: 90.91238471673255
    - type: recall
      value: 93.67588932806325
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tur_Latn)
      type: mteb/flores
      config: rus_Cyrl-tur_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ace_Latn)
      type: mteb/flores
      config: rus_Cyrl-ace_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 74.1106719367589
    - type: f1
      value: 70.21737923911836
    - type: main_score
      value: 70.21737923911836
    - type: precision
      value: 68.7068791410511
    - type: recall
      value: 74.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ban_Latn)
      type: mteb/flores
      config: rus_Cyrl-ban_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.7193675889328
    - type: f1
      value: 78.76470334510617
    - type: main_score
      value: 78.76470334510617
    - type: precision
      value: 77.76208475761422
    - type: recall
      value: 81.7193675889328
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ell_Grek)
      type: mteb/flores
      config: rus_Cyrl-ell_Grek
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.3201581027668
    - type: f1
      value: 97.76021080368908
    - type: main_score
      value: 97.76021080368908
    - type: precision
      value: 97.48023715415019
    - type: recall
      value: 98.3201581027668
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hne_Deva)
      type: mteb/flores
      config: rus_Cyrl-hne_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.51778656126481
    - type: f1
      value: 98.0566534914361
    - type: main_score
      value: 98.0566534914361
    - type: precision
      value: 97.82608695652173
    - type: recall
      value: 98.51778656126481
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kik_Latn)
      type: mteb/flores
      config: rus_Cyrl-kik_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.73122529644269
    - type: f1
      value: 76.42689244220864
    - type: main_score
      value: 76.42689244220864
    - type: precision
      value: 74.63877909530083
    - type: recall
      value: 80.73122529644269
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mai_Deva)
      type: mteb/flores
      config: rus_Cyrl-mai_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.56719367588933
    - type: main_score
      value: 98.56719367588933
    - type: precision
      value: 98.40250329380763
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pbt_Arab)
      type: mteb/flores
      config: rus_Cyrl-pbt_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.5296442687747
    - type: f1
      value: 96.73913043478261
    - type: main_score
      value: 96.73913043478261
    - type: precision
      value: 96.36034255599473
    - type: recall
      value: 97.5296442687747
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-spa_Latn)
      type: mteb/flores
      config: rus_Cyrl-spa_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.20948616600789
    - type: main_score
      value: 99.20948616600789
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-twi_Latn)
      type: mteb/flores
      config: rus_Cyrl-twi_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.01581027667984
    - type: f1
      value: 78.064787822953
    - type: main_score
      value: 78.064787822953
    - type: precision
      value: 76.43272186750448
    - type: recall
      value: 82.01581027667984
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-acm_Arab)
      type: mteb/flores
      config: rus_Cyrl-acm_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.3201581027668
    - type: f1
      value: 97.76021080368908
    - type: main_score
      value: 97.76021080368908
    - type: precision
      value: 97.48023715415019
    - type: recall
      value: 98.3201581027668
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bel_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-bel_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.22134387351778
    - type: f1
      value: 97.67786561264822
    - type: main_score
      value: 97.67786561264822
    - type: precision
      value: 97.4308300395257
    - type: recall
      value: 98.22134387351778
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-eng_Latn)
      type: mteb/flores
      config: rus_Cyrl-eng_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.70355731225297
    - type: f1
      value: 99.60474308300395
    - type: main_score
      value: 99.60474308300395
    - type: precision
      value: 99.55533596837944
    - type: recall
      value: 99.70355731225297
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hrv_Latn)
      type: mteb/flores
      config: rus_Cyrl-hrv_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.83069828722002
    - type: main_score
      value: 98.83069828722002
    - type: precision
      value: 98.69894598155466
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kin_Latn)
      type: mteb/flores
      config: rus_Cyrl-kin_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.37944664031622
    - type: f1
      value: 91.53162055335969
    - type: main_score
      value: 91.53162055335969
    - type: precision
      value: 90.71475625823452
    - type: recall
      value: 93.37944664031622
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mal_Mlym)
      type: mteb/flores
      config: rus_Cyrl-mal_Mlym
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.07773386034255
    - type: main_score
      value: 99.07773386034255
    - type: precision
      value: 98.96245059288538
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pes_Arab)
      type: mteb/flores
      config: rus_Cyrl-pes_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.30368906455863
    - type: main_score
      value: 98.30368906455863
    - type: precision
      value: 98.10606060606061
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-srd_Latn)
      type: mteb/flores
      config: rus_Cyrl-srd_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.03162055335969
    - type: f1
      value: 86.11048371917937
    - type: main_score
      value: 86.11048371917937
    - type: precision
      value: 84.86001317523056
    - type: recall
      value: 89.03162055335969
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tzm_Tfng)
      type: mteb/flores
      config: rus_Cyrl-tzm_Tfng
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 12.351778656126482
    - type: f1
      value: 10.112177999067715
    - type: main_score
      value: 10.112177999067715
    - type: precision
      value: 9.53495885438645
    - type: recall
      value: 12.351778656126482
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-acq_Arab)
      type: mteb/flores
      config: rus_Cyrl-acq_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.55072463768116
    - type: main_score
      value: 98.55072463768116
    - type: precision
      value: 98.36956521739131
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bem_Latn)
      type: mteb/flores
      config: rus_Cyrl-bem_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 73.22134387351778
    - type: f1
      value: 68.30479412989295
    - type: main_score
      value: 68.30479412989295
    - type: precision
      value: 66.40073447632736
    - type: recall
      value: 73.22134387351778
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-epo_Latn)
      type: mteb/flores
      config: rus_Cyrl-epo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.81422924901186
    - type: main_score
      value: 98.81422924901186
    - type: precision
      value: 98.66600790513834
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hun_Latn)
      type: mteb/flores
      config: rus_Cyrl-hun_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.83794466403161
    - type: f1
      value: 95.88274044795784
    - type: main_score
      value: 95.88274044795784
    - type: precision
      value: 95.45454545454545
    - type: recall
      value: 96.83794466403161
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kir_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-kir_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.34387351778656
    - type: f1
      value: 95.49280429715212
    - type: main_score
      value: 95.49280429715212
    - type: precision
      value: 95.14163372859026
    - type: recall
      value: 96.34387351778656
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mar_Deva)
      type: mteb/flores
      config: rus_Cyrl-mar_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.28722002635047
    - type: main_score
      value: 98.28722002635047
    - type: precision
      value: 98.07312252964427
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-plt_Latn)
      type: mteb/flores
      config: rus_Cyrl-plt_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.04347826086956
    - type: f1
      value: 85.14328063241106
    - type: main_score
      value: 85.14328063241106
    - type: precision
      value: 83.96339168078298
    - type: recall
      value: 88.04347826086956
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-srp_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-srp_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-uig_Arab)
      type: mteb/flores
      config: rus_Cyrl-uig_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.19367588932806
    - type: f1
      value: 89.98541313758706
    - type: main_score
      value: 89.98541313758706
    - type: precision
      value: 89.01021080368906
    - type: recall
      value: 92.19367588932806
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-aeb_Arab)
      type: mteb/flores
      config: rus_Cyrl-aeb_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.8498023715415
    - type: f1
      value: 94.63109354413703
    - type: main_score
      value: 94.63109354413703
    - type: precision
      value: 94.05467720685111
    - type: recall
      value: 95.8498023715415
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ben_Beng)
      type: mteb/flores
      config: rus_Cyrl-ben_Beng
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-est_Latn)
      type: mteb/flores
      config: rus_Cyrl-est_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.55335968379447
    - type: f1
      value: 94.2588932806324
    - type: main_score
      value: 94.2588932806324
    - type: precision
      value: 93.65118577075098
    - type: recall
      value: 95.55335968379447
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hye_Armn)
      type: mteb/flores
      config: rus_Cyrl-hye_Armn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.28722002635045
    - type: main_score
      value: 98.28722002635045
    - type: precision
      value: 98.07312252964427
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kmb_Latn)
      type: mteb/flores
      config: rus_Cyrl-kmb_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 54.24901185770751
    - type: f1
      value: 49.46146674116913
    - type: main_score
      value: 49.46146674116913
    - type: precision
      value: 47.81033799314432
    - type: recall
      value: 54.24901185770751
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-min_Arab)
      type: mteb/flores
      config: rus_Cyrl-min_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 15.810276679841898
    - type: f1
      value: 13.271207641419332
    - type: main_score
      value: 13.271207641419332
    - type: precision
      value: 12.510673148766033
    - type: recall
      value: 15.810276679841898
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pol_Latn)
      type: mteb/flores
      config: rus_Cyrl-pol_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.32674571805006
    - type: main_score
      value: 98.32674571805006
    - type: precision
      value: 98.14723320158103
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ssw_Latn)
      type: mteb/flores
      config: rus_Cyrl-ssw_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.8300395256917
    - type: f1
      value: 76.51717847370023
    - type: main_score
      value: 76.51717847370023
    - type: precision
      value: 74.74143610013175
    - type: recall
      value: 80.8300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ukr_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-ukr_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.4729907773386
    - type: main_score
      value: 99.4729907773386
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-afr_Latn)
      type: mteb/flores
      config: rus_Cyrl-afr_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.81422924901186
    - type: main_score
      value: 98.81422924901186
    - type: precision
      value: 98.66600790513834
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bho_Deva)
      type: mteb/flores
      config: rus_Cyrl-bho_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.6403162055336
    - type: f1
      value: 95.56982872200265
    - type: main_score
      value: 95.56982872200265
    - type: precision
      value: 95.0592885375494
    - type: recall
      value: 96.6403162055336
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-eus_Latn)
      type: mteb/flores
      config: rus_Cyrl-eus_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.62845849802372
    - type: f1
      value: 96.9038208168643
    - type: main_score
      value: 96.9038208168643
    - type: precision
      value: 96.55797101449275
    - type: recall
      value: 97.62845849802372
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ibo_Latn)
      type: mteb/flores
      config: rus_Cyrl-ibo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.2292490118577
    - type: f1
      value: 86.35234330886506
    - type: main_score
      value: 86.35234330886506
    - type: precision
      value: 85.09881422924902
    - type: recall
      value: 89.2292490118577
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kmr_Latn)
      type: mteb/flores
      config: rus_Cyrl-kmr_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.49802371541502
    - type: f1
      value: 79.23630717108978
    - type: main_score
      value: 79.23630717108978
    - type: precision
      value: 77.48188405797102
    - type: recall
      value: 83.49802371541502
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-min_Latn)
      type: mteb/flores
      config: rus_Cyrl-min_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 79.34782608695652
    - type: f1
      value: 75.31689928429059
    - type: main_score
      value: 75.31689928429059
    - type: precision
      value: 73.91519410541149
    - type: recall
      value: 79.34782608695652
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-por_Latn)
      type: mteb/flores
      config: rus_Cyrl-por_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.54150197628458
    - type: f1
      value: 95.53218520609825
    - type: main_score
      value: 95.53218520609825
    - type: precision
      value: 95.07575757575756
    - type: recall
      value: 96.54150197628458
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sun_Latn)
      type: mteb/flores
      config: rus_Cyrl-sun_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.2806324110672
    - type: f1
      value: 91.56973461321287
    - type: main_score
      value: 91.56973461321287
    - type: precision
      value: 90.84396334890405
    - type: recall
      value: 93.2806324110672
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-umb_Latn)
      type: mteb/flores
      config: rus_Cyrl-umb_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 51.87747035573123
    - type: f1
      value: 46.36591778884269
    - type: main_score
      value: 46.36591778884269
    - type: precision
      value: 44.57730391234227
    - type: recall
      value: 51.87747035573123
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ajp_Arab)
      type: mteb/flores
      config: rus_Cyrl-ajp_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.30368906455863
    - type: main_score
      value: 98.30368906455863
    - type: precision
      value: 98.10606060606061
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bjn_Arab)
      type: mteb/flores
      config: rus_Cyrl-bjn_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 14.82213438735178
    - type: f1
      value: 12.365434276616856
    - type: main_score
      value: 12.365434276616856
    - type: precision
      value: 11.802079517180589
    - type: recall
      value: 14.82213438735178
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ewe_Latn)
      type: mteb/flores
      config: rus_Cyrl-ewe_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 71.44268774703558
    - type: f1
      value: 66.74603174603175
    - type: main_score
      value: 66.74603174603175
    - type: precision
      value: 64.99933339607253
    - type: recall
      value: 71.44268774703558
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ilo_Latn)
      type: mteb/flores
      config: rus_Cyrl-ilo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.86956521739131
    - type: f1
      value: 83.00139015960917
    - type: main_score
      value: 83.00139015960917
    - type: precision
      value: 81.91411396574439
    - type: recall
      value: 85.86956521739131
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-knc_Arab)
      type: mteb/flores
      config: rus_Cyrl-knc_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 14.525691699604742
    - type: f1
      value: 12.618283715726806
    - type: main_score
      value: 12.618283715726806
    - type: precision
      value: 12.048458493742352
    - type: recall
      value: 14.525691699604742
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mkd_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-mkd_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.22595520421606
    - type: main_score
      value: 99.22595520421606
    - type: precision
      value: 99.14361001317523
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-prs_Arab)
      type: mteb/flores
      config: rus_Cyrl-prs_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.07773386034255
    - type: main_score
      value: 99.07773386034255
    - type: precision
      value: 98.96245059288538
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-swe_Latn)
      type: mteb/flores
      config: rus_Cyrl-swe_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.07773386034256
    - type: main_score
      value: 99.07773386034256
    - type: precision
      value: 98.96245059288538
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-urd_Arab)
      type: mteb/flores
      config: rus_Cyrl-urd_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.61660079051383
    - type: f1
      value: 98.15546772068511
    - type: main_score
      value: 98.15546772068511
    - type: precision
      value: 97.92490118577075
    - type: recall
      value: 98.61660079051383
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-aka_Latn)
      type: mteb/flores
      config: rus_Cyrl-aka_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.02766798418972
    - type: f1
      value: 76.73277809147375
    - type: main_score
      value: 76.73277809147375
    - type: precision
      value: 74.97404165882426
    - type: recall
      value: 81.02766798418972
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bjn_Latn)
      type: mteb/flores
      config: rus_Cyrl-bjn_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.7588932806324
    - type: f1
      value: 83.92064566965753
    - type: main_score
      value: 83.92064566965753
    - type: precision
      value: 82.83734079929732
    - type: recall
      value: 86.7588932806324
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fao_Latn)
      type: mteb/flores
      config: rus_Cyrl-fao_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.43873517786561
    - type: f1
      value: 85.48136645962732
    - type: main_score
      value: 85.48136645962732
    - type: precision
      value: 84.23418972332016
    - type: recall
      value: 88.43873517786561
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ind_Latn)
      type: mteb/flores
      config: rus_Cyrl-ind_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-knc_Latn)
      type: mteb/flores
      config: rus_Cyrl-knc_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 45.8498023715415
    - type: f1
      value: 40.112030865489366
    - type: main_score
      value: 40.112030865489366
    - type: precision
      value: 38.28262440050776
    - type: recall
      value: 45.8498023715415
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mlt_Latn)
      type: mteb/flores
      config: rus_Cyrl-mlt_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.18181818181817
    - type: f1
      value: 91.30787690570298
    - type: main_score
      value: 91.30787690570298
    - type: precision
      value: 90.4983060417843
    - type: recall
      value: 93.18181818181817
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-quy_Latn)
      type: mteb/flores
      config: rus_Cyrl-quy_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 62.450592885375485
    - type: f1
      value: 57.28742975628178
    - type: main_score
      value: 57.28742975628178
    - type: precision
      value: 55.56854987623269
    - type: recall
      value: 62.450592885375485
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-swh_Latn)
      type: mteb/flores
      config: rus_Cyrl-swh_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.3201581027668
    - type: f1
      value: 97.77667984189723
    - type: main_score
      value: 97.77667984189723
    - type: precision
      value: 97.51317523056655
    - type: recall
      value: 98.3201581027668
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-uzn_Latn)
      type: mteb/flores
      config: rus_Cyrl-uzn_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.59081498211933
    - type: main_score
      value: 97.59081498211933
    - type: precision
      value: 97.34848484848484
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-als_Latn)
      type: mteb/flores
      config: rus_Cyrl-als_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.09420289855073
    - type: main_score
      value: 99.09420289855073
    - type: precision
      value: 98.99538866930172
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bod_Tibt)
      type: mteb/flores
      config: rus_Cyrl-bod_Tibt
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 11.561264822134387
    - type: f1
      value: 8.121312045385636
    - type: main_score
      value: 8.121312045385636
    - type: precision
      value: 7.350577020893972
    - type: recall
      value: 11.561264822134387
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fij_Latn)
      type: mteb/flores
      config: rus_Cyrl-fij_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 72.23320158102767
    - type: f1
      value: 67.21000233846082
    - type: main_score
      value: 67.21000233846082
    - type: precision
      value: 65.3869439739005
    - type: recall
      value: 72.23320158102767
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-isl_Latn)
      type: mteb/flores
      config: rus_Cyrl-isl_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.99604743083005
    - type: f1
      value: 89.75955204216073
    - type: main_score
      value: 89.75955204216073
    - type: precision
      value: 88.7598814229249
    - type: recall
      value: 91.99604743083005
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kon_Latn)
      type: mteb/flores
      config: rus_Cyrl-kon_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.81818181818183
    - type: f1
      value: 77.77800098452272
    - type: main_score
      value: 77.77800098452272
    - type: precision
      value: 76.1521268586486
    - type: recall
      value: 81.81818181818183
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mni_Beng)
      type: mteb/flores
      config: rus_Cyrl-mni_Beng
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 54.74308300395256
    - type: f1
      value: 48.97285299254615
    - type: main_score
      value: 48.97285299254615
    - type: precision
      value: 46.95125742968299
    - type: recall
      value: 54.74308300395256
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ron_Latn)
      type: mteb/flores
      config: rus_Cyrl-ron_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.22134387351778
    - type: f1
      value: 97.64492753623189
    - type: main_score
      value: 97.64492753623189
    - type: precision
      value: 97.36495388669302
    - type: recall
      value: 98.22134387351778
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-szl_Latn)
      type: mteb/flores
      config: rus_Cyrl-szl_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.09486166007905
    - type: f1
      value: 90.10375494071147
    - type: main_score
      value: 90.10375494071147
    - type: precision
      value: 89.29606625258798
    - type: recall
      value: 92.09486166007905
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-vec_Latn)
      type: mteb/flores
      config: rus_Cyrl-vec_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.4901185770751
    - type: f1
      value: 90.51430453604365
    - type: main_score
      value: 90.51430453604365
    - type: precision
      value: 89.69367588932808
    - type: recall
      value: 92.4901185770751
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-amh_Ethi)
      type: mteb/flores
      config: rus_Cyrl-amh_Ethi
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.11791831357048
    - type: main_score
      value: 97.11791831357048
    - type: precision
      value: 96.77206851119894
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bos_Latn)
      type: mteb/flores
      config: rus_Cyrl-bos_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.55072463768116
    - type: main_score
      value: 98.55072463768116
    - type: precision
      value: 98.36956521739131
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fin_Latn)
      type: mteb/flores
      config: rus_Cyrl-fin_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.65217391304348
    - type: f1
      value: 94.4235836627141
    - type: main_score
      value: 94.4235836627141
    - type: precision
      value: 93.84881422924902
    - type: recall
      value: 95.65217391304348
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ita_Latn)
      type: mteb/flores
      config: rus_Cyrl-ita_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.55072463768117
    - type: main_score
      value: 98.55072463768117
    - type: precision
      value: 98.36956521739131
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kor_Hang)
      type: mteb/flores
      config: rus_Cyrl-kor_Hang
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.55335968379447
    - type: f1
      value: 94.15349143610013
    - type: main_score
      value: 94.15349143610013
    - type: precision
      value: 93.49472990777339
    - type: recall
      value: 95.55335968379447
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mos_Latn)
      type: mteb/flores
      config: rus_Cyrl-mos_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 43.67588932806324
    - type: f1
      value: 38.84849721190082
    - type: main_score
      value: 38.84849721190082
    - type: precision
      value: 37.43294462099682
    - type: recall
      value: 43.67588932806324
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-run_Latn)
      type: mteb/flores
      config: rus_Cyrl-run_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 90.21739130434783
    - type: f1
      value: 87.37483530961792
    - type: main_score
      value: 87.37483530961792
    - type: precision
      value: 86.07872200263506
    - type: recall
      value: 90.21739130434783
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tam_Taml)
      type: mteb/flores
      config: rus_Cyrl-tam_Taml
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-vie_Latn)
      type: mteb/flores
      config: rus_Cyrl-vie_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.03557312252964
    - type: f1
      value: 96.13636363636364
    - type: main_score
      value: 96.13636363636364
    - type: precision
      value: 95.70981554677206
    - type: recall
      value: 97.03557312252964
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-apc_Arab)
      type: mteb/flores
      config: rus_Cyrl-apc_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.49670619235836
    - type: main_score
      value: 97.49670619235836
    - type: precision
      value: 97.18379446640316
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bug_Latn)
      type: mteb/flores
      config: rus_Cyrl-bug_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 67.29249011857708
    - type: f1
      value: 62.09268717667927
    - type: main_score
      value: 62.09268717667927
    - type: precision
      value: 60.28554009748714
    - type: recall
      value: 67.29249011857708
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fon_Latn)
      type: mteb/flores
      config: rus_Cyrl-fon_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 63.43873517786561
    - type: f1
      value: 57.66660107569199
    - type: main_score
      value: 57.66660107569199
    - type: precision
      value: 55.66676396919363
    - type: recall
      value: 63.43873517786561
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-jav_Latn)
      type: mteb/flores
      config: rus_Cyrl-jav_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.46640316205533
    - type: f1
      value: 92.89384528514964
    - type: main_score
      value: 92.89384528514964
    - type: precision
      value: 92.19367588932806
    - type: recall
      value: 94.46640316205533
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lao_Laoo)
      type: mteb/flores
      config: rus_Cyrl-lao_Laoo
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.23320158102767
    - type: f1
      value: 96.40974967061922
    - type: main_score
      value: 96.40974967061922
    - type: precision
      value: 96.034255599473
    - type: recall
      value: 97.23320158102767
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mri_Latn)
      type: mteb/flores
      config: rus_Cyrl-mri_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 76.77865612648222
    - type: f1
      value: 73.11286539547409
    - type: main_score
      value: 73.11286539547409
    - type: precision
      value: 71.78177214337046
    - type: recall
      value: 76.77865612648222
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-taq_Latn)
      type: mteb/flores
      config: rus_Cyrl-taq_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 41.99604743083004
    - type: f1
      value: 37.25127063318763
    - type: main_score
      value: 37.25127063318763
    - type: precision
      value: 35.718929186985726
    - type: recall
      value: 41.99604743083004
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-war_Latn)
      type: mteb/flores
      config: rus_Cyrl-war_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.55335968379447
    - type: f1
      value: 94.1699604743083
    - type: main_score
      value: 94.1699604743083
    - type: precision
      value: 93.52766798418972
    - type: recall
      value: 95.55335968379447
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-arb_Arab)
      type: mteb/flores
      config: rus_Cyrl-arb_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.4729907773386
    - type: main_score
      value: 99.4729907773386
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bul_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-bul_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.70355731225297
    - type: f1
      value: 99.60474308300395
    - type: main_score
      value: 99.60474308300395
    - type: precision
      value: 99.55533596837944
    - type: recall
      value: 99.70355731225297
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fra_Latn)
      type: mteb/flores
      config: rus_Cyrl-fra_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.47299077733861
    - type: main_score
      value: 99.47299077733861
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-jpn_Jpan)
      type: mteb/flores
      config: rus_Cyrl-jpn_Jpan
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.44268774703558
    - type: f1
      value: 95.30632411067194
    - type: main_score
      value: 95.30632411067194
    - type: precision
      value: 94.76284584980237
    - type: recall
      value: 96.44268774703558
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lij_Latn)
      type: mteb/flores
      config: rus_Cyrl-lij_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 90.21739130434783
    - type: f1
      value: 87.4703557312253
    - type: main_score
      value: 87.4703557312253
    - type: precision
      value: 86.29611330698287
    - type: recall
      value: 90.21739130434783
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-mya_Mymr)
      type: mteb/flores
      config: rus_Cyrl-mya_Mymr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.364953886693
    - type: main_score
      value: 97.364953886693
    - type: precision
      value: 97.03557312252964
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sag_Latn)
      type: mteb/flores
      config: rus_Cyrl-sag_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 54.841897233201585
    - type: f1
      value: 49.61882037503349
    - type: main_score
      value: 49.61882037503349
    - type: precision
      value: 47.831968755881796
    - type: recall
      value: 54.841897233201585
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-taq_Tfng)
      type: mteb/flores
      config: rus_Cyrl-taq_Tfng
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 15.316205533596838
    - type: f1
      value: 11.614836360389717
    - type: main_score
      value: 11.614836360389717
    - type: precision
      value: 10.741446193235223
    - type: recall
      value: 15.316205533596838
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-wol_Latn)
      type: mteb/flores
      config: rus_Cyrl-wol_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 67.88537549407114
    - type: f1
      value: 62.2536417249856
    - type: main_score
      value: 62.2536417249856
    - type: precision
      value: 60.27629128666678
    - type: recall
      value: 67.88537549407114
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-arb_Latn)
      type: mteb/flores
      config: rus_Cyrl-arb_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 27.766798418972332
    - type: f1
      value: 23.39674889624077
    - type: main_score
      value: 23.39674889624077
    - type: precision
      value: 22.28521155585345
    - type: recall
      value: 27.766798418972332
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-cat_Latn)
      type: mteb/flores
      config: rus_Cyrl-cat_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.23320158102767
    - type: f1
      value: 96.42151326933936
    - type: main_score
      value: 96.42151326933936
    - type: precision
      value: 96.04743083003953
    - type: recall
      value: 97.23320158102767
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fur_Latn)
      type: mteb/flores
      config: rus_Cyrl-fur_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.63636363636364
    - type: f1
      value: 85.80792396009788
    - type: main_score
      value: 85.80792396009788
    - type: precision
      value: 84.61508901726293
    - type: recall
      value: 88.63636363636364
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kab_Latn)
      type: mteb/flores
      config: rus_Cyrl-kab_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 48.12252964426877
    - type: f1
      value: 43.05387582971066
    - type: main_score
      value: 43.05387582971066
    - type: precision
      value: 41.44165117538212
    - type: recall
      value: 48.12252964426877
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lim_Latn)
      type: mteb/flores
      config: rus_Cyrl-lim_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.81818181818183
    - type: f1
      value: 77.81676163099087
    - type: main_score
      value: 77.81676163099087
    - type: precision
      value: 76.19565217391305
    - type: recall
      value: 81.81818181818183
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nld_Latn)
      type: mteb/flores
      config: rus_Cyrl-nld_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.33201581027669
    - type: f1
      value: 96.4756258234519
    - type: main_score
      value: 96.4756258234519
    - type: precision
      value: 96.06389986824769
    - type: recall
      value: 97.33201581027669
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-san_Deva)
      type: mteb/flores
      config: rus_Cyrl-san_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.47826086956522
    - type: f1
      value: 91.70289855072463
    - type: main_score
      value: 91.70289855072463
    - type: precision
      value: 90.9370882740448
    - type: recall
      value: 93.47826086956522
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tat_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-tat_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.72727272727273
    - type: f1
      value: 97.00263504611331
    - type: main_score
      value: 97.00263504611331
    - type: precision
      value: 96.65678524374177
    - type: recall
      value: 97.72727272727273
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-xho_Latn)
      type: mteb/flores
      config: rus_Cyrl-xho_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.08300395256917
    - type: f1
      value: 91.12977602108036
    - type: main_score
      value: 91.12977602108036
    - type: precision
      value: 90.22562582345192
    - type: recall
      value: 93.08300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ars_Arab)
      type: mteb/flores
      config: rus_Cyrl-ars_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.40711462450594
    - type: f1
      value: 99.2094861660079
    - type: main_score
      value: 99.2094861660079
    - type: precision
      value: 99.1106719367589
    - type: recall
      value: 99.40711462450594
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ceb_Latn)
      type: mteb/flores
      config: rus_Cyrl-ceb_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.65217391304348
    - type: f1
      value: 94.3544137022398
    - type: main_score
      value: 94.3544137022398
    - type: precision
      value: 93.76646903820817
    - type: recall
      value: 95.65217391304348
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-fuv_Latn)
      type: mteb/flores
      config: rus_Cyrl-fuv_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 51.18577075098815
    - type: f1
      value: 44.5990252610806
    - type: main_score
      value: 44.5990252610806
    - type: precision
      value: 42.34331599450177
    - type: recall
      value: 51.18577075098815
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kac_Latn)
      type: mteb/flores
      config: rus_Cyrl-kac_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 46.93675889328063
    - type: f1
      value: 41.79004018701787
    - type: main_score
      value: 41.79004018701787
    - type: precision
      value: 40.243355662392624
    - type: recall
      value: 46.93675889328063
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lin_Latn)
      type: mteb/flores
      config: rus_Cyrl-lin_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.50197628458498
    - type: f1
      value: 89.1205533596838
    - type: main_score
      value: 89.1205533596838
    - type: precision
      value: 88.07147562582345
    - type: recall
      value: 91.50197628458498
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nno_Latn)
      type: mteb/flores
      config: rus_Cyrl-nno_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.81422924901186
    - type: f1
      value: 98.41897233201581
    - type: main_score
      value: 98.41897233201581
    - type: precision
      value: 98.22134387351778
    - type: recall
      value: 98.81422924901186
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sat_Olck)
      type: mteb/flores
      config: rus_Cyrl-sat_Olck
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 2.371541501976284
    - type: f1
      value: 1.0726274943087382
    - type: main_score
      value: 1.0726274943087382
    - type: precision
      value: 0.875279634748803
    - type: recall
      value: 2.371541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tel_Telu)
      type: mteb/flores
      config: rus_Cyrl-tel_Telu
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ydd_Hebr)
      type: mteb/flores
      config: rus_Cyrl-ydd_Hebr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.42687747035573
    - type: f1
      value: 86.47609636740073
    - type: main_score
      value: 86.47609636740073
    - type: precision
      value: 85.13669301712781
    - type: recall
      value: 89.42687747035573
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ary_Arab)
      type: mteb/flores
      config: rus_Cyrl-ary_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.82213438735178
    - type: f1
      value: 87.04545454545456
    - type: main_score
      value: 87.04545454545456
    - type: precision
      value: 85.76910408432148
    - type: recall
      value: 89.82213438735178
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ces_Latn)
      type: mteb/flores
      config: rus_Cyrl-ces_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-gaz_Latn)
      type: mteb/flores
      config: rus_Cyrl-gaz_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 64.9209486166008
    - type: f1
      value: 58.697458119394874
    - type: main_score
      value: 58.697458119394874
    - type: precision
      value: 56.43402189597842
    - type: recall
      value: 64.9209486166008
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kam_Latn)
      type: mteb/flores
      config: rus_Cyrl-kam_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 59.18972332015811
    - type: f1
      value: 53.19031511966295
    - type: main_score
      value: 53.19031511966295
    - type: precision
      value: 51.08128357343655
    - type: recall
      value: 59.18972332015811
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lit_Latn)
      type: mteb/flores
      config: rus_Cyrl-lit_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.54150197628458
    - type: f1
      value: 95.5368906455863
    - type: main_score
      value: 95.5368906455863
    - type: precision
      value: 95.0592885375494
    - type: recall
      value: 96.54150197628458
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nob_Latn)
      type: mteb/flores
      config: rus_Cyrl-nob_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.51317523056655
    - type: main_score
      value: 97.51317523056655
    - type: precision
      value: 97.2167325428195
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-scn_Latn)
      type: mteb/flores
      config: rus_Cyrl-scn_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 84.0909090909091
    - type: f1
      value: 80.37000439174352
    - type: main_score
      value: 80.37000439174352
    - type: precision
      value: 78.83994628559846
    - type: recall
      value: 84.0909090909091
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tgk_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-tgk_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.68774703557312
    - type: f1
      value: 90.86344814605684
    - type: main_score
      value: 90.86344814605684
    - type: precision
      value: 90.12516469038208
    - type: recall
      value: 92.68774703557312
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-yor_Latn)
      type: mteb/flores
      config: rus_Cyrl-yor_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 72.13438735177866
    - type: f1
      value: 66.78759646150951
    - type: main_score
      value: 66.78759646150951
    - type: precision
      value: 64.85080192096002
    - type: recall
      value: 72.13438735177866
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-arz_Arab)
      type: mteb/flores
      config: rus_Cyrl-arz_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.364953886693
    - type: main_score
      value: 97.364953886693
    - type: precision
      value: 97.03557312252964
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-cjk_Latn)
      type: mteb/flores
      config: rus_Cyrl-cjk_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 51.976284584980235
    - type: f1
      value: 46.468762353149714
    - type: main_score
      value: 46.468762353149714
    - type: precision
      value: 44.64073366247278
    - type: recall
      value: 51.976284584980235
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-gla_Latn)
      type: mteb/flores
      config: rus_Cyrl-gla_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 79.74308300395256
    - type: f1
      value: 75.55611165294958
    - type: main_score
      value: 75.55611165294958
    - type: precision
      value: 73.95033408620365
    - type: recall
      value: 79.74308300395256
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kan_Knda)
      type: mteb/flores
      config: rus_Cyrl-kan_Knda
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.96245059288538
    - type: main_score
      value: 98.96245059288538
    - type: precision
      value: 98.84716732542819
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lmo_Latn)
      type: mteb/flores
      config: rus_Cyrl-lmo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.41106719367589
    - type: f1
      value: 78.56413514022209
    - type: main_score
      value: 78.56413514022209
    - type: precision
      value: 77.15313068573938
    - type: recall
      value: 82.41106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-npi_Deva)
      type: mteb/flores
      config: rus_Cyrl-npi_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.3201581027668
    - type: main_score
      value: 98.3201581027668
    - type: precision
      value: 98.12252964426878
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-shn_Mymr)
      type: mteb/flores
      config: rus_Cyrl-shn_Mymr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 57.11462450592886
    - type: f1
      value: 51.51361369197337
    - type: main_score
      value: 51.51361369197337
    - type: precision
      value: 49.71860043649573
    - type: recall
      value: 57.11462450592886
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tgl_Latn)
      type: mteb/flores
      config: rus_Cyrl-tgl_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.18379446640316
    - type: main_score
      value: 97.18379446640316
    - type: precision
      value: 96.88735177865613
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-yue_Hant)
      type: mteb/flores
      config: rus_Cyrl-yue_Hant
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.09420289855072
    - type: main_score
      value: 99.09420289855072
    - type: precision
      value: 98.9953886693017
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-asm_Beng)
      type: mteb/flores
      config: rus_Cyrl-asm_Beng
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.55335968379447
    - type: f1
      value: 94.16007905138339
    - type: main_score
      value: 94.16007905138339
    - type: precision
      value: 93.50296442687747
    - type: recall
      value: 95.55335968379447
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ckb_Arab)
      type: mteb/flores
      config: rus_Cyrl-ckb_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.88537549407114
    - type: f1
      value: 90.76745718050066
    - type: main_score
      value: 90.76745718050066
    - type: precision
      value: 89.80072463768116
    - type: recall
      value: 92.88537549407114
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-gle_Latn)
      type: mteb/flores
      config: rus_Cyrl-gle_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.699604743083
    - type: f1
      value: 89.40899680030115
    - type: main_score
      value: 89.40899680030115
    - type: precision
      value: 88.40085638998683
    - type: recall
      value: 91.699604743083
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kas_Arab)
      type: mteb/flores
      config: rus_Cyrl-kas_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 88.3399209486166
    - type: f1
      value: 85.14351590438548
    - type: main_score
      value: 85.14351590438548
    - type: precision
      value: 83.72364953886692
    - type: recall
      value: 88.3399209486166
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ltg_Latn)
      type: mteb/flores
      config: rus_Cyrl-ltg_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.399209486166
    - type: f1
      value: 79.88408934061107
    - type: main_score
      value: 79.88408934061107
    - type: precision
      value: 78.53794509179885
    - type: recall
      value: 83.399209486166
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nso_Latn)
      type: mteb/flores
      config: rus_Cyrl-nso_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.20553359683794
    - type: f1
      value: 88.95406635525212
    - type: main_score
      value: 88.95406635525212
    - type: precision
      value: 88.01548089591567
    - type: recall
      value: 91.20553359683794
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sin_Sinh)
      type: mteb/flores
      config: rus_Cyrl-sin_Sinh
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.56719367588933
    - type: main_score
      value: 98.56719367588933
    - type: precision
      value: 98.40250329380763
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tha_Thai)
      type: mteb/flores
      config: rus_Cyrl-tha_Thai
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.94861660079052
    - type: f1
      value: 94.66403162055336
    - type: main_score
      value: 94.66403162055336
    - type: precision
      value: 94.03820816864295
    - type: recall
      value: 95.94861660079052
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-zho_Hans)
      type: mteb/flores
      config: rus_Cyrl-zho_Hans
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.4308300395257
    - type: f1
      value: 96.5909090909091
    - type: main_score
      value: 96.5909090909091
    - type: precision
      value: 96.17918313570487
    - type: recall
      value: 97.4308300395257
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ast_Latn)
      type: mteb/flores
      config: rus_Cyrl-ast_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.46640316205533
    - type: f1
      value: 92.86890645586297
    - type: main_score
      value: 92.86890645586297
    - type: precision
      value: 92.14756258234519
    - type: recall
      value: 94.46640316205533
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-crh_Latn)
      type: mteb/flores
      config: rus_Cyrl-crh_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.66403162055336
    - type: f1
      value: 93.2663592446201
    - type: main_score
      value: 93.2663592446201
    - type: precision
      value: 92.66716073781292
    - type: recall
      value: 94.66403162055336
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-glg_Latn)
      type: mteb/flores
      config: rus_Cyrl-glg_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.81422924901186
    - type: f1
      value: 98.46837944664031
    - type: main_score
      value: 98.46837944664031
    - type: precision
      value: 98.3201581027668
    - type: recall
      value: 98.81422924901186
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kas_Deva)
      type: mteb/flores
      config: rus_Cyrl-kas_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 69.1699604743083
    - type: f1
      value: 63.05505292906477
    - type: main_score
      value: 63.05505292906477
    - type: precision
      value: 60.62594108789761
    - type: recall
      value: 69.1699604743083
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ltz_Latn)
      type: mteb/flores
      config: rus_Cyrl-ltz_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.40316205533597
    - type: f1
      value: 89.26571616789009
    - type: main_score
      value: 89.26571616789009
    - type: precision
      value: 88.40179747788443
    - type: recall
      value: 91.40316205533597
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nus_Latn)
      type: mteb/flores
      config: rus_Cyrl-nus_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 38.93280632411067
    - type: f1
      value: 33.98513032905371
    - type: main_score
      value: 33.98513032905371
    - type: precision
      value: 32.56257884802308
    - type: recall
      value: 38.93280632411067
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-slk_Latn)
      type: mteb/flores
      config: rus_Cyrl-slk_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.42094861660078
    - type: main_score
      value: 97.42094861660078
    - type: precision
      value: 97.14262187088273
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tir_Ethi)
      type: mteb/flores
      config: rus_Cyrl-tir_Ethi
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.30434782608695
    - type: f1
      value: 88.78129117259552
    - type: main_score
      value: 88.78129117259552
    - type: precision
      value: 87.61528326745717
    - type: recall
      value: 91.30434782608695
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-zho_Hant)
      type: mteb/flores
      config: rus_Cyrl-zho_Hant
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.81422924901186
    - type: main_score
      value: 98.81422924901186
    - type: precision
      value: 98.66600790513834
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-awa_Deva)
      type: mteb/flores
      config: rus_Cyrl-awa_Deva
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.70092226613966
    - type: main_score
      value: 97.70092226613966
    - type: precision
      value: 97.50494071146245
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-cym_Latn)
      type: mteb/flores
      config: rus_Cyrl-cym_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.94861660079052
    - type: f1
      value: 94.74308300395256
    - type: main_score
      value: 94.74308300395256
    - type: precision
      value: 94.20289855072464
    - type: recall
      value: 95.94861660079052
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-grn_Latn)
      type: mteb/flores
      config: rus_Cyrl-grn_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 77.96442687747036
    - type: f1
      value: 73.64286789187975
    - type: main_score
      value: 73.64286789187975
    - type: precision
      value: 71.99324893260821
    - type: recall
      value: 77.96442687747036
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kat_Geor)
      type: mteb/flores
      config: rus_Cyrl-kat_Geor
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.56719367588933
    - type: main_score
      value: 98.56719367588933
    - type: precision
      value: 98.40250329380764
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lua_Latn)
      type: mteb/flores
      config: rus_Cyrl-lua_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 72.03557312252964
    - type: f1
      value: 67.23928163404449
    - type: main_score
      value: 67.23928163404449
    - type: precision
      value: 65.30797101449275
    - type: recall
      value: 72.03557312252964
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-nya_Latn)
      type: mteb/flores
      config: rus_Cyrl-nya_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.29249011857708
    - type: f1
      value: 90.0494071146245
    - type: main_score
      value: 90.0494071146245
    - type: precision
      value: 89.04808959156786
    - type: recall
      value: 92.29249011857708
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-slv_Latn)
      type: mteb/flores
      config: rus_Cyrl-slv_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.30368906455863
    - type: main_score
      value: 98.30368906455863
    - type: precision
      value: 98.10606060606061
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tpi_Latn)
      type: mteb/flores
      config: rus_Cyrl-tpi_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.53359683794467
    - type: f1
      value: 76.59481822525301
    - type: main_score
      value: 76.59481822525301
    - type: precision
      value: 75.12913223140497
    - type: recall
      value: 80.53359683794467
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-zsm_Latn)
      type: mteb/flores
      config: rus_Cyrl-zsm_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.33201581027669
    - type: f1
      value: 96.58620365142104
    - type: main_score
      value: 96.58620365142104
    - type: precision
      value: 96.26152832674572
    - type: recall
      value: 97.33201581027669
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ayr_Latn)
      type: mteb/flores
      config: rus_Cyrl-ayr_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 45.55335968379446
    - type: f1
      value: 40.13076578531388
    - type: main_score
      value: 40.13076578531388
    - type: precision
      value: 38.398064362362355
    - type: recall
      value: 45.55335968379446
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-dan_Latn)
      type: mteb/flores
      config: rus_Cyrl-dan_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-guj_Gujr)
      type: mteb/flores
      config: rus_Cyrl-guj_Gujr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kaz_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-kaz_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.81422924901186
    - type: f1
      value: 98.43544137022398
    - type: main_score
      value: 98.43544137022398
    - type: precision
      value: 98.25428194993412
    - type: recall
      value: 98.81422924901186
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lug_Latn)
      type: mteb/flores
      config: rus_Cyrl-lug_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.21343873517787
    - type: f1
      value: 77.97485726833554
    - type: main_score
      value: 77.97485726833554
    - type: precision
      value: 76.22376717485415
    - type: recall
      value: 82.21343873517787
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-oci_Latn)
      type: mteb/flores
      config: rus_Cyrl-oci_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.87351778656127
    - type: f1
      value: 92.25319969885187
    - type: main_score
      value: 92.25319969885187
    - type: precision
      value: 91.5638528138528
    - type: recall
      value: 93.87351778656127
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-smo_Latn)
      type: mteb/flores
      config: rus_Cyrl-smo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 84.88142292490119
    - type: f1
      value: 81.24364765669114
    - type: main_score
      value: 81.24364765669114
    - type: precision
      value: 79.69991416137661
    - type: recall
      value: 84.88142292490119
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tsn_Latn)
      type: mteb/flores
      config: rus_Cyrl-tsn_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.05533596837944
    - type: f1
      value: 83.90645586297761
    - type: main_score
      value: 83.90645586297761
    - type: precision
      value: 82.56752305665349
    - type: recall
      value: 87.05533596837944
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-zul_Latn)
      type: mteb/flores
      config: rus_Cyrl-zul_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.15810276679841
    - type: f1
      value: 93.77140974967062
    - type: main_score
      value: 93.77140974967062
    - type: precision
      value: 93.16534914361002
    - type: recall
      value: 95.15810276679841
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-azb_Arab)
      type: mteb/flores
      config: rus_Cyrl-azb_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.91699604743083
    - type: f1
      value: 77.18050065876152
    - type: main_score
      value: 77.18050065876152
    - type: precision
      value: 75.21519543258673
    - type: recall
      value: 81.91699604743083
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-deu_Latn)
      type: mteb/flores
      config: rus_Cyrl-deu_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.50592885375494
    - type: f1
      value: 99.34123847167325
    - type: main_score
      value: 99.34123847167325
    - type: precision
      value: 99.2588932806324
    - type: recall
      value: 99.50592885375494
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hat_Latn)
      type: mteb/flores
      config: rus_Cyrl-hat_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.00790513833992
    - type: f1
      value: 88.69126043039086
    - type: main_score
      value: 88.69126043039086
    - type: precision
      value: 87.75774044795784
    - type: recall
      value: 91.00790513833992
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kbp_Latn)
      type: mteb/flores
      config: rus_Cyrl-kbp_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 47.233201581027664
    - type: f1
      value: 43.01118618096943
    - type: main_score
      value: 43.01118618096943
    - type: precision
      value: 41.739069205043556
    - type: recall
      value: 47.233201581027664
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-luo_Latn)
      type: mteb/flores
      config: rus_Cyrl-luo_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 60.47430830039525
    - type: f1
      value: 54.83210565429816
    - type: main_score
      value: 54.83210565429816
    - type: precision
      value: 52.81630744284779
    - type: recall
      value: 60.47430830039525
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-ory_Orya)
      type: mteb/flores
      config: rus_Cyrl-ory_Orya
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.1106719367589
    - type: f1
      value: 98.83069828722003
    - type: main_score
      value: 98.83069828722003
    - type: precision
      value: 98.69894598155467
    - type: recall
      value: 99.1106719367589
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-sna_Latn)
      type: mteb/flores
      config: rus_Cyrl-sna_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.72332015810277
    - type: f1
      value: 87.30013645774514
    - type: main_score
      value: 87.30013645774514
    - type: precision
      value: 86.25329380764163
    - type: recall
      value: 89.72332015810277
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tso_Latn)
      type: mteb/flores
      config: rus_Cyrl-tso_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 84.38735177865613
    - type: f1
      value: 80.70424744337788
    - type: main_score
      value: 80.70424744337788
    - type: precision
      value: 79.18560606060606
    - type: recall
      value: 84.38735177865613
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-azj_Latn)
      type: mteb/flores
      config: rus_Cyrl-azj_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.33201581027669
    - type: f1
      value: 96.56455862977602
    - type: main_score
      value: 96.56455862977602
    - type: precision
      value: 96.23682476943345
    - type: recall
      value: 97.33201581027669
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-dik_Latn)
      type: mteb/flores
      config: rus_Cyrl-dik_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 46.047430830039524
    - type: f1
      value: 40.05513069495283
    - type: main_score
      value: 40.05513069495283
    - type: precision
      value: 38.072590197096126
    - type: recall
      value: 46.047430830039524
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-hau_Latn)
      type: mteb/flores
      config: rus_Cyrl-hau_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.94466403162056
    - type: f1
      value: 84.76943346508563
    - type: main_score
      value: 84.76943346508563
    - type: precision
      value: 83.34486166007905
    - type: recall
      value: 87.94466403162056
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-kea_Latn)
      type: mteb/flores
      config: rus_Cyrl-kea_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.42687747035573
    - type: f1
      value: 86.83803021747684
    - type: main_score
      value: 86.83803021747684
    - type: precision
      value: 85.78416149068323
    - type: recall
      value: 89.42687747035573
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lus_Latn)
      type: mteb/flores
      config: rus_Cyrl-lus_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.97233201581028
    - type: f1
      value: 64.05480726292745
    - type: main_score
      value: 64.05480726292745
    - type: precision
      value: 62.42670749487858
    - type: recall
      value: 68.97233201581028
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pag_Latn)
      type: mteb/flores
      config: rus_Cyrl-pag_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 78.75494071146245
    - type: f1
      value: 74.58573558401933
    - type: main_score
      value: 74.58573558401933
    - type: precision
      value: 73.05532028358115
    - type: recall
      value: 78.75494071146245
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-snd_Arab)
      type: mteb/flores
      config: rus_Cyrl-snd_Arab
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.8498023715415
    - type: f1
      value: 94.56521739130434
    - type: main_score
      value: 94.56521739130434
    - type: precision
      value: 93.97233201581028
    - type: recall
      value: 95.8498023715415
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tuk_Latn)
      type: mteb/flores
      config: rus_Cyrl-tuk_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.08300395256917
    - type: f1
      value: 62.93565240205557
    - type: main_score
      value: 62.93565240205557
    - type: precision
      value: 61.191590257043934
    - type: recall
      value: 68.08300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-bak_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-bak_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.04743083003953
    - type: f1
      value: 94.86824769433464
    - type: main_score
      value: 94.86824769433464
    - type: precision
      value: 94.34288537549406
    - type: recall
      value: 96.04743083003953
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-dyu_Latn)
      type: mteb/flores
      config: rus_Cyrl-dyu_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 37.45059288537549
    - type: f1
      value: 31.670482312800807
    - type: main_score
      value: 31.670482312800807
    - type: precision
      value: 29.99928568357422
    - type: recall
      value: 37.45059288537549
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-heb_Hebr)
      type: mteb/flores
      config: rus_Cyrl-heb_Hebr
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.23320158102767
    - type: f1
      value: 96.38998682476942
    - type: main_score
      value: 96.38998682476942
    - type: precision
      value: 95.99802371541502
    - type: recall
      value: 97.23320158102767
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-khk_Cyrl)
      type: mteb/flores
      config: rus_Cyrl-khk_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.41897233201581
    - type: f1
      value: 98.00724637681158
    - type: main_score
      value: 98.00724637681158
    - type: precision
      value: 97.82938076416336
    - type: recall
      value: 98.41897233201581
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-lvs_Latn)
      type: mteb/flores
      config: rus_Cyrl-lvs_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.4308300395257
    - type: f1
      value: 96.61396574440053
    - type: main_score
      value: 96.61396574440053
    - type: precision
      value: 96.2203557312253
    - type: recall
      value: 97.4308300395257
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-pan_Guru)
      type: mteb/flores
      config: rus_Cyrl-pan_Guru
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.07773386034256
    - type: main_score
      value: 99.07773386034256
    - type: precision
      value: 98.96245059288538
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-som_Latn)
      type: mteb/flores
      config: rus_Cyrl-som_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.74703557312253
    - type: f1
      value: 84.52898550724638
    - type: main_score
      value: 84.52898550724638
    - type: precision
      value: 83.09288537549409
    - type: recall
      value: 87.74703557312253
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (rus_Cyrl-tum_Latn)
      type: mteb/flores
      config: rus_Cyrl-tum_Latn
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.15415019762845
    - type: f1
      value: 83.85069640504425
    - type: main_score
      value: 83.85069640504425
    - type: precision
      value: 82.43671183888576
    - type: recall
      value: 87.15415019762845
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (taq_Latn-rus_Cyrl)
      type: mteb/flores
      config: taq_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 28.55731225296443
    - type: f1
      value: 26.810726360049568
    - type: main_score
      value: 26.810726360049568
    - type: precision
      value: 26.260342858265577
    - type: recall
      value: 28.55731225296443
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (war_Latn-rus_Cyrl)
      type: mteb/flores
      config: war_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.86166007905138
    - type: f1
      value: 94.03147083483051
    - type: main_score
      value: 94.03147083483051
    - type: precision
      value: 93.70653606003322
    - type: recall
      value: 94.86166007905138
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (arb_Arab-rus_Cyrl)
      type: mteb/flores
      config: arb_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.34387351778656
    - type: f1
      value: 95.23056653491436
    - type: main_score
      value: 95.23056653491436
    - type: precision
      value: 94.70520421607378
    - type: recall
      value: 96.34387351778656
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bul_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: bul_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.90118577075098
    - type: f1
      value: 99.86824769433464
    - type: main_score
      value: 99.86824769433464
    - type: precision
      value: 99.85177865612648
    - type: recall
      value: 99.90118577075098
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fra_Latn-rus_Cyrl)
      type: mteb/flores
      config: fra_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (jpn_Jpan-rus_Cyrl)
      type: mteb/flores
      config: jpn_Jpan-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.3201581027668
    - type: f1
      value: 97.76021080368905
    - type: main_score
      value: 97.76021080368905
    - type: precision
      value: 97.48023715415019
    - type: recall
      value: 98.3201581027668
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lij_Latn-rus_Cyrl)
      type: mteb/flores
      config: lij_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 83.49802371541502
    - type: f1
      value: 81.64800059239636
    - type: main_score
      value: 81.64800059239636
    - type: precision
      value: 80.9443055878478
    - type: recall
      value: 83.49802371541502
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (mya_Mymr-rus_Cyrl)
      type: mteb/flores
      config: mya_Mymr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 90.21739130434783
    - type: f1
      value: 88.76776366313682
    - type: main_score
      value: 88.76776366313682
    - type: precision
      value: 88.18370446119435
    - type: recall
      value: 90.21739130434783
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sag_Latn-rus_Cyrl)
      type: mteb/flores
      config: sag_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 41.699604743083
    - type: f1
      value: 39.53066322643847
    - type: main_score
      value: 39.53066322643847
    - type: precision
      value: 38.822876239229274
    - type: recall
      value: 41.699604743083
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (taq_Tfng-rus_Cyrl)
      type: mteb/flores
      config: taq_Tfng-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 10.67193675889328
    - type: f1
      value: 9.205744965817951
    - type: main_score
      value: 9.205744965817951
    - type: precision
      value: 8.85195219073817
    - type: recall
      value: 10.67193675889328
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (wol_Latn-rus_Cyrl)
      type: mteb/flores
      config: wol_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 63.537549407114625
    - type: f1
      value: 60.65190727391827
    - type: main_score
      value: 60.65190727391827
    - type: precision
      value: 59.61144833427442
    - type: recall
      value: 63.537549407114625
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (arb_Latn-rus_Cyrl)
      type: mteb/flores
      config: arb_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 13.142292490118576
    - type: f1
      value: 12.372910318176764
    - type: main_score
      value: 12.372910318176764
    - type: precision
      value: 12.197580895919188
    - type: recall
      value: 13.142292490118576
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (cat_Latn-rus_Cyrl)
      type: mteb/flores
      config: cat_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.80599472990777
    - type: main_score
      value: 98.80599472990777
    - type: precision
      value: 98.72953133822698
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fur_Latn-rus_Cyrl)
      type: mteb/flores
      config: fur_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.02766798418972
    - type: f1
      value: 79.36184294084613
    - type: main_score
      value: 79.36184294084613
    - type: precision
      value: 78.69187826527705
    - type: recall
      value: 81.02766798418972
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kab_Latn-rus_Cyrl)
      type: mteb/flores
      config: kab_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 34.387351778656125
    - type: f1
      value: 32.02306921576947
    - type: main_score
      value: 32.02306921576947
    - type: precision
      value: 31.246670347137467
    - type: recall
      value: 34.387351778656125
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lim_Latn-rus_Cyrl)
      type: mteb/flores
      config: lim_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 78.26086956521739
    - type: f1
      value: 75.90239449214359
    - type: main_score
      value: 75.90239449214359
    - type: precision
      value: 75.02211430745493
    - type: recall
      value: 78.26086956521739
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nld_Latn-rus_Cyrl)
      type: mteb/flores
      config: nld_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.9459815546772
    - type: main_score
      value: 98.9459815546772
    - type: precision
      value: 98.81422924901186
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (san_Deva-rus_Cyrl)
      type: mteb/flores
      config: san_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.94466403162056
    - type: f1
      value: 86.68928897189767
    - type: main_score
      value: 86.68928897189767
    - type: precision
      value: 86.23822997079216
    - type: recall
      value: 87.94466403162056
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tat_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: tat_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.03557312252964
    - type: f1
      value: 96.4167365353136
    - type: main_score
      value: 96.4167365353136
    - type: precision
      value: 96.16847826086958
    - type: recall
      value: 97.03557312252964
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (xho_Latn-rus_Cyrl)
      type: mteb/flores
      config: xho_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.95652173913044
    - type: f1
      value: 85.5506497283435
    - type: main_score
      value: 85.5506497283435
    - type: precision
      value: 84.95270479733395
    - type: recall
      value: 86.95652173913044
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ars_Arab-rus_Cyrl)
      type: mteb/flores
      config: ars_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 96.6403162055336
    - type: f1
      value: 95.60935441370223
    - type: main_score
      value: 95.60935441370223
    - type: precision
      value: 95.13339920948617
    - type: recall
      value: 96.6403162055336
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ceb_Latn-rus_Cyrl)
      type: mteb/flores
      config: ceb_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.7509881422925
    - type: f1
      value: 95.05209198303827
    - type: main_score
      value: 95.05209198303827
    - type: precision
      value: 94.77662283368805
    - type: recall
      value: 95.7509881422925
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (fuv_Latn-rus_Cyrl)
      type: mteb/flores
      config: fuv_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 45.25691699604743
    - type: f1
      value: 42.285666666742365
    - type: main_score
      value: 42.285666666742365
    - type: precision
      value: 41.21979853402283
    - type: recall
      value: 45.25691699604743
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kac_Latn-rus_Cyrl)
      type: mteb/flores
      config: kac_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 34.683794466403164
    - type: f1
      value: 33.3235346229031
    - type: main_score
      value: 33.3235346229031
    - type: precision
      value: 32.94673924616852
    - type: recall
      value: 34.683794466403164
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lin_Latn-rus_Cyrl)
      type: mteb/flores
      config: lin_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.85770750988142
    - type: f1
      value: 85.1867110799439
    - type: main_score
      value: 85.1867110799439
    - type: precision
      value: 84.53038212173273
    - type: recall
      value: 86.85770750988142
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nno_Latn-rus_Cyrl)
      type: mteb/flores
      config: nno_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.4308300395257
    - type: f1
      value: 96.78383210991906
    - type: main_score
      value: 96.78383210991906
    - type: precision
      value: 96.51185770750989
    - type: recall
      value: 97.4308300395257
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sat_Olck-rus_Cyrl)
      type: mteb/flores
      config: sat_Olck-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 1.185770750988142
    - type: f1
      value: 1.0279253129117258
    - type: main_score
      value: 1.0279253129117258
    - type: precision
      value: 1.0129746819135175
    - type: recall
      value: 1.185770750988142
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tel_Telu-rus_Cyrl)
      type: mteb/flores
      config: tel_Telu-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.12252964426878
    - type: f1
      value: 97.61198945981555
    - type: main_score
      value: 97.61198945981555
    - type: precision
      value: 97.401185770751
    - type: recall
      value: 98.12252964426878
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ydd_Hebr-rus_Cyrl)
      type: mteb/flores
      config: ydd_Hebr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 75.8893280632411
    - type: f1
      value: 74.00244008018511
    - type: main_score
      value: 74.00244008018511
    - type: precision
      value: 73.25683020960382
    - type: recall
      value: 75.8893280632411
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ary_Arab-rus_Cyrl)
      type: mteb/flores
      config: ary_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.56126482213439
    - type: f1
      value: 83.72796285839765
    - type: main_score
      value: 83.72796285839765
    - type: precision
      value: 82.65014273166447
    - type: recall
      value: 86.56126482213439
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ces_Latn-rus_Cyrl)
      type: mteb/flores
      config: ces_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.60474308300395
    - type: f1
      value: 99.4729907773386
    - type: main_score
      value: 99.4729907773386
    - type: precision
      value: 99.40711462450594
    - type: recall
      value: 99.60474308300395
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (gaz_Latn-rus_Cyrl)
      type: mteb/flores
      config: gaz_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 42.58893280632411
    - type: f1
      value: 40.75832866805978
    - type: main_score
      value: 40.75832866805978
    - type: precision
      value: 40.14285046917723
    - type: recall
      value: 42.58893280632411
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kam_Latn-rus_Cyrl)
      type: mteb/flores
      config: kam_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 45.25691699604743
    - type: f1
      value: 42.6975518029456
    - type: main_score
      value: 42.6975518029456
    - type: precision
      value: 41.87472710984596
    - type: recall
      value: 45.25691699604743
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lit_Latn-rus_Cyrl)
      type: mteb/flores
      config: lit_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.33201581027669
    - type: f1
      value: 96.62384716732542
    - type: main_score
      value: 96.62384716732542
    - type: precision
      value: 96.3175230566535
    - type: recall
      value: 97.33201581027669
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nob_Latn-rus_Cyrl)
      type: mteb/flores
      config: nob_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.30368906455863
    - type: main_score
      value: 98.30368906455863
    - type: precision
      value: 98.10606060606061
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (scn_Latn-rus_Cyrl)
      type: mteb/flores
      config: scn_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 70.45454545454545
    - type: f1
      value: 68.62561022640075
    - type: main_score
      value: 68.62561022640075
    - type: precision
      value: 67.95229103411222
    - type: recall
      value: 70.45454545454545
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tgk_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: tgk_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.4901185770751
    - type: f1
      value: 91.58514492753623
    - type: main_score
      value: 91.58514492753623
    - type: precision
      value: 91.24759298672342
    - type: recall
      value: 92.4901185770751
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (yor_Latn-rus_Cyrl)
      type: mteb/flores
      config: yor_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 67.98418972332016
    - type: f1
      value: 64.72874247330768
    - type: main_score
      value: 64.72874247330768
    - type: precision
      value: 63.450823399938685
    - type: recall
      value: 67.98418972332016
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (arz_Arab-rus_Cyrl)
      type: mteb/flores
      config: arz_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 94.56521739130434
    - type: f1
      value: 93.07971014492755
    - type: main_score
      value: 93.07971014492755
    - type: precision
      value: 92.42753623188406
    - type: recall
      value: 94.56521739130434
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (cjk_Latn-rus_Cyrl)
      type: mteb/flores
      config: cjk_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 38.63636363636363
    - type: f1
      value: 36.25747140862938
    - type: main_score
      value: 36.25747140862938
    - type: precision
      value: 35.49101355074723
    - type: recall
      value: 38.63636363636363
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (gla_Latn-rus_Cyrl)
      type: mteb/flores
      config: gla_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 69.26877470355731
    - type: f1
      value: 66.11797423328613
    - type: main_score
      value: 66.11797423328613
    - type: precision
      value: 64.89369649409694
    - type: recall
      value: 69.26877470355731
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kan_Knda-rus_Cyrl)
      type: mteb/flores
      config: kan_Knda-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.51505740636176
    - type: main_score
      value: 97.51505740636176
    - type: precision
      value: 97.30731225296442
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lmo_Latn-rus_Cyrl)
      type: mteb/flores
      config: lmo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 73.3201581027668
    - type: f1
      value: 71.06371608677273
    - type: main_score
      value: 71.06371608677273
    - type: precision
      value: 70.26320288266223
    - type: recall
      value: 73.3201581027668
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (npi_Deva-rus_Cyrl)
      type: mteb/flores
      config: npi_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.36645107198466
    - type: main_score
      value: 97.36645107198466
    - type: precision
      value: 97.1772068511199
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (shn_Mymr-rus_Cyrl)
      type: mteb/flores
      config: shn_Mymr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 39.426877470355734
    - type: f1
      value: 37.16728785513024
    - type: main_score
      value: 37.16728785513024
    - type: precision
      value: 36.56918548278505
    - type: recall
      value: 39.426877470355734
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tgl_Latn-rus_Cyrl)
      type: mteb/flores
      config: tgl_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.92490118577075
    - type: f1
      value: 97.6378693769998
    - type: main_score
      value: 97.6378693769998
    - type: precision
      value: 97.55371440154047
    - type: recall
      value: 97.92490118577075
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (yue_Hant-rus_Cyrl)
      type: mteb/flores
      config: yue_Hant-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.92490118577075
    - type: f1
      value: 97.3833051006964
    - type: main_score
      value: 97.3833051006964
    - type: precision
      value: 97.1590909090909
    - type: recall
      value: 97.92490118577075
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (asm_Beng-rus_Cyrl)
      type: mteb/flores
      config: asm_Beng-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.78656126482213
    - type: f1
      value: 91.76917395296842
    - type: main_score
      value: 91.76917395296842
    - type: precision
      value: 91.38292866553736
    - type: recall
      value: 92.78656126482213
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ckb_Arab-rus_Cyrl)
      type: mteb/flores
      config: ckb_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.8300395256917
    - type: f1
      value: 79.17664345468799
    - type: main_score
      value: 79.17664345468799
    - type: precision
      value: 78.5622171683459
    - type: recall
      value: 80.8300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (gle_Latn-rus_Cyrl)
      type: mteb/flores
      config: gle_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.86956521739131
    - type: f1
      value: 84.45408265372492
    - type: main_score
      value: 84.45408265372492
    - type: precision
      value: 83.8774340026703
    - type: recall
      value: 85.86956521739131
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kas_Arab-rus_Cyrl)
      type: mteb/flores
      config: kas_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 76.28458498023716
    - type: f1
      value: 74.11216313578267
    - type: main_score
      value: 74.11216313578267
    - type: precision
      value: 73.2491277759584
    - type: recall
      value: 76.28458498023716
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ltg_Latn-rus_Cyrl)
      type: mteb/flores
      config: ltg_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 71.14624505928853
    - type: f1
      value: 68.69245357723618
    - type: main_score
      value: 68.69245357723618
    - type: precision
      value: 67.8135329666459
    - type: recall
      value: 71.14624505928853
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nso_Latn-rus_Cyrl)
      type: mteb/flores
      config: nso_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.64822134387352
    - type: f1
      value: 85.98419219986725
    - type: main_score
      value: 85.98419219986725
    - type: precision
      value: 85.32513873917036
    - type: recall
      value: 87.64822134387352
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sin_Sinh-rus_Cyrl)
      type: mteb/flores
      config: sin_Sinh-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.62845849802372
    - type: f1
      value: 97.10144927536231
    - type: main_score
      value: 97.10144927536231
    - type: precision
      value: 96.87986585219788
    - type: recall
      value: 97.62845849802372
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tha_Thai-rus_Cyrl)
      type: mteb/flores
      config: tha_Thai-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.71541501976284
    - type: f1
      value: 98.28722002635045
    - type: main_score
      value: 98.28722002635045
    - type: precision
      value: 98.07312252964427
    - type: recall
      value: 98.71541501976284
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (zho_Hans-rus_Cyrl)
      type: mteb/flores
      config: zho_Hans-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.68247694334651
    - type: main_score
      value: 98.68247694334651
    - type: precision
      value: 98.51778656126481
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ast_Latn-rus_Cyrl)
      type: mteb/flores
      config: ast_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.65217391304348
    - type: f1
      value: 94.90649683857505
    - type: main_score
      value: 94.90649683857505
    - type: precision
      value: 94.61352657004831
    - type: recall
      value: 95.65217391304348
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (crh_Latn-rus_Cyrl)
      type: mteb/flores
      config: crh_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 93.08300395256917
    - type: f1
      value: 92.20988998886428
    - type: main_score
      value: 92.20988998886428
    - type: precision
      value: 91.85631013694254
    - type: recall
      value: 93.08300395256917
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (glg_Latn-rus_Cyrl)
      type: mteb/flores
      config: glg_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.55335968379447
    - type: f1
      value: 95.18006148440931
    - type: main_score
      value: 95.18006148440931
    - type: precision
      value: 95.06540560888386
    - type: recall
      value: 95.55335968379447
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kas_Deva-rus_Cyrl)
      type: mteb/flores
      config: kas_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 55.03952569169961
    - type: f1
      value: 52.19871938895554
    - type: main_score
      value: 52.19871938895554
    - type: precision
      value: 51.17660971469557
    - type: recall
      value: 55.03952569169961
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ltz_Latn-rus_Cyrl)
      type: mteb/flores
      config: ltz_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 87.64822134387352
    - type: f1
      value: 86.64179841897234
    - type: main_score
      value: 86.64179841897234
    - type: precision
      value: 86.30023235431587
    - type: recall
      value: 87.64822134387352
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nus_Latn-rus_Cyrl)
      type: mteb/flores
      config: nus_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 27.4703557312253
    - type: f1
      value: 25.703014277858088
    - type: main_score
      value: 25.703014277858088
    - type: precision
      value: 25.194105476917315
    - type: recall
      value: 27.4703557312253
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (slk_Latn-rus_Cyrl)
      type: mteb/flores
      config: slk_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.1106719367589
    - type: main_score
      value: 99.1106719367589
    - type: precision
      value: 99.02832674571805
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tir_Ethi-rus_Cyrl)
      type: mteb/flores
      config: tir_Ethi-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 80.73122529644269
    - type: f1
      value: 78.66903754775608
    - type: main_score
      value: 78.66903754775608
    - type: precision
      value: 77.86431694163612
    - type: recall
      value: 80.73122529644269
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (zho_Hant-rus_Cyrl)
      type: mteb/flores
      config: zho_Hant-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.22134387351778
    - type: f1
      value: 97.66798418972333
    - type: main_score
      value: 97.66798418972333
    - type: precision
      value: 97.40612648221344
    - type: recall
      value: 98.22134387351778
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (awa_Deva-rus_Cyrl)
      type: mteb/flores
      config: awa_Deva-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.5296442687747
    - type: f1
      value: 96.94224857268335
    - type: main_score
      value: 96.94224857268335
    - type: precision
      value: 96.68560606060606
    - type: recall
      value: 97.5296442687747
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (cym_Latn-rus_Cyrl)
      type: mteb/flores
      config: cym_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 92.68774703557312
    - type: f1
      value: 91.69854302097961
    - type: main_score
      value: 91.69854302097961
    - type: precision
      value: 91.31236846157795
    - type: recall
      value: 92.68774703557312
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (grn_Latn-rus_Cyrl)
      type: mteb/flores
      config: grn_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 64.13043478260869
    - type: f1
      value: 61.850586118740004
    - type: main_score
      value: 61.850586118740004
    - type: precision
      value: 61.0049495186209
    - type: recall
      value: 64.13043478260869
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kat_Geor-rus_Cyrl)
      type: mteb/flores
      config: kat_Geor-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.59881422924902
    - type: main_score
      value: 97.59881422924902
    - type: precision
      value: 97.42534036012296
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lua_Latn-rus_Cyrl)
      type: mteb/flores
      config: lua_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 63.63636363636363
    - type: f1
      value: 60.9709122526128
    - type: main_score
      value: 60.9709122526128
    - type: precision
      value: 60.03915902282226
    - type: recall
      value: 63.63636363636363
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (nya_Latn-rus_Cyrl)
      type: mteb/flores
      config: nya_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 89.2292490118577
    - type: f1
      value: 87.59723824473149
    - type: main_score
      value: 87.59723824473149
    - type: precision
      value: 86.90172707867349
    - type: recall
      value: 89.2292490118577
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (slv_Latn-rus_Cyrl)
      type: mteb/flores
      config: slv_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.01185770750988
    - type: f1
      value: 98.74835309617917
    - type: main_score
      value: 98.74835309617917
    - type: precision
      value: 98.63636363636364
    - type: recall
      value: 99.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tpi_Latn-rus_Cyrl)
      type: mteb/flores
      config: tpi_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 77.37154150197628
    - type: f1
      value: 75.44251611276084
    - type: main_score
      value: 75.44251611276084
    - type: precision
      value: 74.78103665109595
    - type: recall
      value: 77.37154150197628
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (zsm_Latn-rus_Cyrl)
      type: mteb/flores
      config: zsm_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.2094861660079
    - type: f1
      value: 98.96245059288538
    - type: main_score
      value: 98.96245059288538
    - type: precision
      value: 98.8471673254282
    - type: recall
      value: 99.2094861660079
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ayr_Latn-rus_Cyrl)
      type: mteb/flores
      config: ayr_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 27.766798418972332
    - type: f1
      value: 26.439103195281312
    - type: main_score
      value: 26.439103195281312
    - type: precision
      value: 26.052655604573964
    - type: recall
      value: 27.766798418972332
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (dan_Latn-rus_Cyrl)
      type: mteb/flores
      config: dan_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.30830039525692
    - type: f1
      value: 99.07773386034255
    - type: main_score
      value: 99.07773386034255
    - type: precision
      value: 98.96245059288538
    - type: recall
      value: 99.30830039525692
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (guj_Gujr-rus_Cyrl)
      type: mteb/flores
      config: guj_Gujr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.26449275362317
    - type: main_score
      value: 97.26449275362317
    - type: precision
      value: 97.02498588368154
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kaz_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: kaz_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.5296442687747
    - type: f1
      value: 97.03557312252964
    - type: main_score
      value: 97.03557312252964
    - type: precision
      value: 96.85022158342316
    - type: recall
      value: 97.5296442687747
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lug_Latn-rus_Cyrl)
      type: mteb/flores
      config: lug_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 68.57707509881423
    - type: f1
      value: 65.93361605820395
    - type: main_score
      value: 65.93361605820395
    - type: precision
      value: 64.90348248593789
    - type: recall
      value: 68.57707509881423
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (oci_Latn-rus_Cyrl)
      type: mteb/flores
      config: oci_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.26482213438736
    - type: f1
      value: 85.33176417155623
    - type: main_score
      value: 85.33176417155623
    - type: precision
      value: 85.00208833384637
    - type: recall
      value: 86.26482213438736
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (smo_Latn-rus_Cyrl)
      type: mteb/flores
      config: smo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 77.96442687747036
    - type: f1
      value: 75.70960450188885
    - type: main_score
      value: 75.70960450188885
    - type: precision
      value: 74.8312632736777
    - type: recall
      value: 77.96442687747036
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tsn_Latn-rus_Cyrl)
      type: mteb/flores
      config: tsn_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 84.38735177865613
    - type: f1
      value: 82.13656376349225
    - type: main_score
      value: 82.13656376349225
    - type: precision
      value: 81.16794543904518
    - type: recall
      value: 84.38735177865613
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (zul_Latn-rus_Cyrl)
      type: mteb/flores
      config: zul_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 90.21739130434783
    - type: f1
      value: 88.77570602050753
    - type: main_score
      value: 88.77570602050753
    - type: precision
      value: 88.15978104021582
    - type: recall
      value: 90.21739130434783
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (azb_Arab-rus_Cyrl)
      type: mteb/flores
      config: azb_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 65.71146245059289
    - type: f1
      value: 64.18825390221271
    - type: main_score
      value: 64.18825390221271
    - type: precision
      value: 63.66811154793568
    - type: recall
      value: 65.71146245059289
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (deu_Latn-rus_Cyrl)
      type: mteb/flores
      config: deu_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 99.70355731225297
    - type: f1
      value: 99.60474308300395
    - type: main_score
      value: 99.60474308300395
    - type: precision
      value: 99.55533596837944
    - type: recall
      value: 99.70355731225297
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hat_Latn-rus_Cyrl)
      type: mteb/flores
      config: hat_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 86.7588932806324
    - type: f1
      value: 85.86738623695146
    - type: main_score
      value: 85.86738623695146
    - type: precision
      value: 85.55235467420822
    - type: recall
      value: 86.7588932806324
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kbp_Latn-rus_Cyrl)
      type: mteb/flores
      config: kbp_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 34.88142292490119
    - type: f1
      value: 32.16511669463015
    - type: main_score
      value: 32.16511669463015
    - type: precision
      value: 31.432098549546318
    - type: recall
      value: 34.88142292490119
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (luo_Latn-rus_Cyrl)
      type: mteb/flores
      config: luo_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 52.27272727272727
    - type: f1
      value: 49.60489626836975
    - type: main_score
      value: 49.60489626836975
    - type: precision
      value: 48.69639631803339
    - type: recall
      value: 52.27272727272727
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (ory_Orya-rus_Cyrl)
      type: mteb/flores
      config: ory_Orya-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.82608695652173
    - type: f1
      value: 97.27437417654808
    - type: main_score
      value: 97.27437417654808
    - type: precision
      value: 97.04968944099377
    - type: recall
      value: 97.82608695652173
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (sna_Latn-rus_Cyrl)
      type: mteb/flores
      config: sna_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.37549407114624
    - type: f1
      value: 83.09911316305177
    - type: main_score
      value: 83.09911316305177
    - type: precision
      value: 82.1284950958864
    - type: recall
      value: 85.37549407114624
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tso_Latn-rus_Cyrl)
      type: mteb/flores
      config: tso_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 82.90513833992095
    - type: f1
      value: 80.28290385503824
    - type: main_score
      value: 80.28290385503824
    - type: precision
      value: 79.23672543237761
    - type: recall
      value: 82.90513833992095
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (azj_Latn-rus_Cyrl)
      type: mteb/flores
      config: azj_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.02371541501977
    - type: f1
      value: 97.49200075287031
    - type: main_score
      value: 97.49200075287031
    - type: precision
      value: 97.266139657444
    - type: recall
      value: 98.02371541501977
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (dik_Latn-rus_Cyrl)
      type: mteb/flores
      config: dik_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 38.43873517786561
    - type: f1
      value: 35.78152442955223
    - type: main_score
      value: 35.78152442955223
    - type: precision
      value: 34.82424325078237
    - type: recall
      value: 38.43873517786561
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (hau_Latn-rus_Cyrl)
      type: mteb/flores
      config: hau_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.42292490118577
    - type: f1
      value: 79.24612283124593
    - type: main_score
      value: 79.24612283124593
    - type: precision
      value: 78.34736070751448
    - type: recall
      value: 81.42292490118577
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (kea_Latn-rus_Cyrl)
      type: mteb/flores
      config: kea_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 81.62055335968378
    - type: f1
      value: 80.47015182884748
    - type: main_score
      value: 80.47015182884748
    - type: precision
      value: 80.02671028885862
    - type: recall
      value: 81.62055335968378
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lus_Latn-rus_Cyrl)
      type: mteb/flores
      config: lus_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 62.74703557312253
    - type: f1
      value: 60.53900079111122
    - type: main_score
      value: 60.53900079111122
    - type: precision
      value: 59.80024202850289
    - type: recall
      value: 62.74703557312253
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pag_Latn-rus_Cyrl)
      type: mteb/flores
      config: pag_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 74.01185770750988
    - type: f1
      value: 72.57280648279529
    - type: main_score
      value: 72.57280648279529
    - type: precision
      value: 71.99952968456789
    - type: recall
      value: 74.01185770750988
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (snd_Arab-rus_Cyrl)
      type: mteb/flores
      config: snd_Arab-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 91.30434782608695
    - type: f1
      value: 90.24653499445358
    - type: main_score
      value: 90.24653499445358
    - type: precision
      value: 89.83134068200232
    - type: recall
      value: 91.30434782608695
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tuk_Latn-rus_Cyrl)
      type: mteb/flores
      config: tuk_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 47.62845849802372
    - type: f1
      value: 45.812928836644254
    - type: main_score
      value: 45.812928836644254
    - type: precision
      value: 45.23713833170355
    - type: recall
      value: 47.62845849802372
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (bak_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: bak_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.8498023715415
    - type: f1
      value: 95.18904459615922
    - type: main_score
      value: 95.18904459615922
    - type: precision
      value: 94.92812441182006
    - type: recall
      value: 95.8498023715415
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (dyu_Latn-rus_Cyrl)
      type: mteb/flores
      config: dyu_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 29.64426877470356
    - type: f1
      value: 27.287335193938166
    - type: main_score
      value: 27.287335193938166
    - type: precision
      value: 26.583996026587492
    - type: recall
      value: 29.64426877470356
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (heb_Hebr-rus_Cyrl)
      type: mteb/flores
      config: heb_Hebr-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 98.91304347826086
    - type: f1
      value: 98.55072463768116
    - type: main_score
      value: 98.55072463768116
    - type: precision
      value: 98.36956521739131
    - type: recall
      value: 98.91304347826086
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (khk_Cyrl-rus_Cyrl)
      type: mteb/flores
      config: khk_Cyrl-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 95.15810276679841
    - type: f1
      value: 94.44009547764487
    - type: main_score
      value: 94.44009547764487
    - type: precision
      value: 94.16579797014579
    - type: recall
      value: 95.15810276679841
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (lvs_Latn-rus_Cyrl)
      type: mteb/flores
      config: lvs_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.92490118577075
    - type: f1
      value: 97.51467241585817
    - type: main_score
      value: 97.51467241585817
    - type: precision
      value: 97.36166007905138
    - type: recall
      value: 97.92490118577075
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (pan_Guru-rus_Cyrl)
      type: mteb/flores
      config: pan_Guru-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 97.92490118577075
    - type: f1
      value: 97.42918313570486
    - type: main_score
      value: 97.42918313570486
    - type: precision
      value: 97.22261434217955
    - type: recall
      value: 97.92490118577075
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (som_Latn-rus_Cyrl)
      type: mteb/flores
      config: som_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 75.69169960474308
    - type: f1
      value: 73.7211667065916
    - type: main_score
      value: 73.7211667065916
    - type: precision
      value: 72.95842401892384
    - type: recall
      value: 75.69169960474308
  - task:
      type: BitextMining
    dataset:
      name: MTEB FloresBitextMining (tum_Latn-rus_Cyrl)
      type: mteb/flores
      config: tum_Latn-rus_Cyrl
      split: devtest
      revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e
    metrics:
    - type: accuracy
      value: 85.67193675889328
    - type: f1
      value: 82.9296066252588
    - type: main_score
      value: 82.9296066252588
    - type: precision
      value: 81.77330225447936
    - type: recall
      value: 85.67193675889328
  - task:
      type: Classification
    dataset:
      name: MTEB GeoreviewClassification (default)
      type: ai-forever/georeview-classification
      config: default
      split: test
      revision: 3765c0d1de6b7d264bc459433c45e5a75513839c
    metrics:
    - type: accuracy
      value: 44.6630859375
    - type: f1
      value: 42.607425073610536
    - type: f1_weighted
      value: 42.60639474586065
    - type: main_score
      value: 44.6630859375
  - task:
      type: Clustering
    dataset:
      name: MTEB GeoreviewClusteringP2P (default)
      type: ai-forever/georeview-clustering-p2p
      config: default
      split: test
      revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec
    metrics:
    - type: main_score
      value: 58.15951247070825
    - type: v_measure
      value: 58.15951247070825
    - type: v_measure_std
      value: 0.6739615788288809
  - task:
      type: Classification
    dataset:
      name: MTEB HeadlineClassification (default)
      type: ai-forever/headline-classification
      config: default
      split: test
      revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb
    metrics:
    - type: accuracy
      value: 73.935546875
    - type: f1
      value: 73.8654872186846
    - type: f1_weighted
      value: 73.86733122685095
    - type: main_score
      value: 73.935546875
  - task:
      type: Classification
    dataset:
      name: MTEB InappropriatenessClassification (default)
      type: ai-forever/inappropriateness-classification
      config: default
      split: test
      revision: 601651fdc45ef243751676e62dd7a19f491c0285
    metrics:
    - type: accuracy
      value: 59.16015624999999
    - type: ap
      value: 55.52276605836938
    - type: ap_weighted
      value: 55.52276605836938
    - type: f1
      value: 58.614248199637956
    - type: f1_weighted
      value: 58.614248199637956
    - type: main_score
      value: 59.16015624999999
  - task:
      type: Classification
    dataset:
      name: MTEB KinopoiskClassification (default)
      type: ai-forever/kinopoisk-sentiment-classification
      config: default
      split: test
      revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
    metrics:
    - type: accuracy
      value: 49.959999999999994
    - type: f1
      value: 48.4900332316098
    - type: f1_weighted
      value: 48.4900332316098
    - type: main_score
      value: 49.959999999999994
  - task:
      type: Classification
    dataset:
      name: MTEB LanguageClassification (default)
      type: papluca/language-identification
      config: default
      split: test
      revision: aa56583bf2bc52b0565770607d6fc3faebecf9e2
    metrics:
    - type: accuracy
      value: 71.005859375
    - type: f1
      value: 69.63481100303348
    - type: f1_weighted
      value: 69.64640413409529
    - type: main_score
      value: 71.005859375
  - task:
      type: Clustering
    dataset:
      name: MTEB MLSUMClusteringP2P (ru)
      type: reciTAL/mlsum
      config: ru
      split: test
      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
    metrics:
    - type: main_score
      value: 42.11280087032343
    - type: v_measure
      value: 42.11280087032343
    - type: v_measure_std
      value: 6.7619971723605135
    - type: main_score
      value: 43.00112546945811
    - type: v_measure
      value: 43.00112546945811
    - type: v_measure_std
      value: 1.4740560414835675
    - type: main_score
      value: 39.81446080575161
    - type: v_measure
      value: 39.81446080575161
    - type: v_measure_std
      value: 7.125661320308298
    - type: main_score
      value: 39.29659668980239
    - type: v_measure
      value: 39.29659668980239
    - type: v_measure_std
      value: 2.6570502923023094
  - task:
      type: Retrieval
    dataset:
      name: MTEB MultiLongDocRetrieval (ru)
      type: Shitao/MLDR
      config: ru
      split: dev
      revision: d67138e705d963e346253a80e59676ddb418810a
    metrics:
    - type: main_score
      value: 38.671
    - type: map_at_1
      value: 30.0
    - type: map_at_10
      value: 36.123
    - type: map_at_100
      value: 36.754999999999995
    - type: map_at_1000
      value: 36.806
    - type: map_at_20
      value: 36.464
    - type: map_at_3
      value: 35.25
    - type: map_at_5
      value: 35.8
    - type: mrr_at_1
      value: 30.0
    - type: mrr_at_10
      value: 36.122817460317464
    - type: mrr_at_100
      value: 36.75467016625293
    - type: mrr_at_1000
      value: 36.80612724920882
    - type: mrr_at_20
      value: 36.46359681984682
    - type: mrr_at_3
      value: 35.25
    - type: mrr_at_5
      value: 35.800000000000004
    - type: nauc_map_at_1000_diff1
      value: 55.61987610843598
    - type: nauc_map_at_1000_max
      value: 52.506795017152186
    - type: nauc_map_at_1000_std
      value: 2.95487192066911
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    - type: nauc_map_at_100_max
      value: 52.48192017040307
    - type: nauc_map_at_100_std
      value: 2.930120252521189
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    - type: nauc_map_at_10_max
      value: 52.739573233234424
    - type: nauc_map_at_10_std
      value: 2.4073432421641545
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      value: 52.57059856776112
    - type: nauc_map_at_1_max
      value: 50.55668152952304
    - type: nauc_map_at_1_std
      value: 1.6572084853398048
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    - type: nauc_map_at_20_max
      value: 52.53663737242853
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      value: 2.8489192879814
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      value: 56.90294128342709
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      value: 53.10608389782041
    - type: nauc_map_at_3_std
      value: 1.4909731657889491
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      value: 52.398078357541564
    - type: nauc_map_at_5_std
      value: 1.8256862015101467
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    - type: nauc_mrr_at_1000_max
      value: 52.506795017152186
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      value: 52.739573233234424
    - type: nauc_mrr_at_10_std
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    - type: nauc_mrr_at_1_max
      value: 50.55668152952304
    - type: nauc_mrr_at_1_std
      value: 1.6572084853398048
    - type: nauc_mrr_at_20_diff1
      value: 55.75769029917031
    - type: nauc_mrr_at_20_max
      value: 52.53663737242853
    - type: nauc_mrr_at_20_std
      value: 2.8489192879814
    - type: nauc_mrr_at_3_diff1
      value: 56.90294128342709
    - type: nauc_mrr_at_3_max
      value: 53.10608389782041
    - type: nauc_mrr_at_3_std
      value: 1.4909731657889491
    - type: nauc_mrr_at_5_diff1
      value: 56.1258315436073
    - type: nauc_mrr_at_5_max
      value: 52.398078357541564
    - type: nauc_mrr_at_5_std
      value: 1.8256862015101467
    - type: nauc_ndcg_at_1000_diff1
      value: 55.30733548408918
    - type: nauc_ndcg_at_1000_max
      value: 53.51143366189318
    - type: nauc_ndcg_at_1000_std
      value: 7.133789405525702
    - type: nauc_ndcg_at_100_diff1
      value: 54.32209039488095
    - type: nauc_ndcg_at_100_max
      value: 52.67499334461009
    - type: nauc_ndcg_at_100_std
      value: 6.878823275077807
    - type: nauc_ndcg_at_10_diff1
      value: 56.266780806997716
    - type: nauc_ndcg_at_10_max
      value: 53.52837255793743
    - type: nauc_ndcg_at_10_std
      value: 3.756832592964262
    - type: nauc_ndcg_at_1_diff1
      value: 52.57059856776112
    - type: nauc_ndcg_at_1_max
      value: 50.55668152952304
    - type: nauc_ndcg_at_1_std
      value: 1.6572084853398048
    - type: nauc_ndcg_at_20_diff1
      value: 55.39255420432796
    - type: nauc_ndcg_at_20_max
      value: 52.946114684072235
    - type: nauc_ndcg_at_20_std
      value: 5.414933414031693
    - type: nauc_ndcg_at_3_diff1
      value: 57.92826624996289
    - type: nauc_ndcg_at_3_max
      value: 53.89907760306972
    - type: nauc_ndcg_at_3_std
      value: 1.6661401245309218
    - type: nauc_ndcg_at_5_diff1
      value: 56.47508936029308
    - type: nauc_ndcg_at_5_max
      value: 52.66800998045517
    - type: nauc_ndcg_at_5_std
      value: 2.4127296184140423
    - type: nauc_precision_at_1000_diff1
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    - type: nauc_precision_at_1000_max
      value: 65.1132590931922
    - type: nauc_precision_at_1000_std
      value: 40.60788709618145
    - type: nauc_precision_at_100_diff1
      value: 46.49620002554606
    - type: nauc_precision_at_100_max
      value: 53.02960148167071
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      value: 28.206028867032863
    - type: nauc_precision_at_10_diff1
      value: 56.562744749606765
    - type: nauc_precision_at_10_max
      value: 56.00594967783547
    - type: nauc_precision_at_10_std
      value: 8.368379831645163
    - type: nauc_precision_at_1_diff1
      value: 52.57059856776112
    - type: nauc_precision_at_1_max
      value: 50.55668152952304
    - type: nauc_precision_at_1_std
      value: 1.6572084853398048
    - type: nauc_precision_at_20_diff1
      value: 53.25915754614111
    - type: nauc_precision_at_20_max
      value: 54.03255118937036
    - type: nauc_precision_at_20_std
      value: 15.161611674272718
    - type: nauc_precision_at_3_diff1
      value: 60.726785748943854
    - type: nauc_precision_at_3_max
      value: 56.139896875869354
    - type: nauc_precision_at_3_std
      value: 2.2306901035769893
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      value: 57.1201127525187
    - type: nauc_precision_at_5_max
      value: 53.28665761862506
    - type: nauc_precision_at_5_std
      value: 4.358720050112237
    - type: nauc_recall_at_1000_diff1
      value: 57.259240202383964
    - type: nauc_recall_at_1000_max
      value: 65.11325909319218
    - type: nauc_recall_at_1000_std
      value: 40.60788709618142
    - type: nauc_recall_at_100_diff1
      value: 46.49620002554603
    - type: nauc_recall_at_100_max
      value: 53.02960148167071
    - type: nauc_recall_at_100_std
      value: 28.206028867032835
    - type: nauc_recall_at_10_diff1
      value: 56.562744749606765
    - type: nauc_recall_at_10_max
      value: 56.00594967783549
    - type: nauc_recall_at_10_std
      value: 8.368379831645147
    - type: nauc_recall_at_1_diff1
      value: 52.57059856776112
    - type: nauc_recall_at_1_max
      value: 50.55668152952304
    - type: nauc_recall_at_1_std
      value: 1.6572084853398048
    - type: nauc_recall_at_20_diff1
      value: 53.259157546141154
    - type: nauc_recall_at_20_max
      value: 54.03255118937038
    - type: nauc_recall_at_20_std
      value: 15.16161167427274
    - type: nauc_recall_at_3_diff1
      value: 60.72678574894387
    - type: nauc_recall_at_3_max
      value: 56.13989687586933
    - type: nauc_recall_at_3_std
      value: 2.2306901035770066
    - type: nauc_recall_at_5_diff1
      value: 57.12011275251864
    - type: nauc_recall_at_5_max
      value: 53.28665761862502
    - type: nauc_recall_at_5_std
      value: 4.3587200501122245
    - type: ndcg_at_1
      value: 30.0
    - type: ndcg_at_10
      value: 38.671
    - type: ndcg_at_100
      value: 42.173
    - type: ndcg_at_1000
      value: 44.016
    - type: ndcg_at_20
      value: 39.845000000000006
    - type: ndcg_at_3
      value: 36.863
    - type: ndcg_at_5
      value: 37.874
    - type: precision_at_1
      value: 30.0
    - type: precision_at_10
      value: 4.65
    - type: precision_at_100
      value: 0.64
    - type: precision_at_1000
      value: 0.08
    - type: precision_at_20
      value: 2.55
    - type: precision_at_3
      value: 13.833
    - type: precision_at_5
      value: 8.799999999999999
    - type: recall_at_1
      value: 30.0
    - type: recall_at_10
      value: 46.5
    - type: recall_at_100
      value: 64.0
    - type: recall_at_1000
      value: 79.5
    - type: recall_at_20
      value: 51.0
    - type: recall_at_3
      value: 41.5
    - type: recall_at_5
      value: 44.0
  - task:
      type: Classification
    dataset:
      name: MTEB MultilingualSentimentClassification (rus)
      type: mteb/multilingual-sentiment-classification
      config: rus
      split: test
      revision: 2b9b4d10fc589af67794141fe8cbd3739de1eb33
    metrics:
    - type: accuracy
      value: 79.52710495963092
    - type: ap
      value: 84.5713457178972
    - type: ap_weighted
      value: 84.5713457178972
    - type: f1
      value: 77.88661181524105
    - type: f1_weighted
      value: 79.87563079922718
    - type: main_score
      value: 79.52710495963092
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (arb_Arab-rus_Cyrl)
      type: mteb/NTREX
      config: arb_Arab-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 86.47971957936905
    - type: f1
      value: 82.79864240805654
    - type: main_score
      value: 82.79864240805654
    - type: precision
      value: 81.21485800128767
    - type: recall
      value: 86.47971957936905
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (bel_Cyrl-rus_Cyrl)
      type: mteb/NTREX
      config: bel_Cyrl-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.84226339509264
    - type: f1
      value: 93.56399067465667
    - type: main_score
      value: 93.56399067465667
    - type: precision
      value: 93.01619095309631
    - type: recall
      value: 94.84226339509264
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (ben_Beng-rus_Cyrl)
      type: mteb/NTREX
      config: ben_Beng-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.18828242363544
    - type: f1
      value: 90.42393889620612
    - type: main_score
      value: 90.42393889620612
    - type: precision
      value: 89.67904925153297
    - type: recall
      value: 92.18828242363544
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (bos_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: bos_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.69203805708563
    - type: f1
      value: 93.37172425304624
    - type: main_score
      value: 93.37172425304624
    - type: precision
      value: 92.79204521067315
    - type: recall
      value: 94.69203805708563
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (bul_Cyrl-rus_Cyrl)
      type: mteb/NTREX
      config: bul_Cyrl-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.99549323985978
    - type: f1
      value: 96.13086296110833
    - type: main_score
      value: 96.13086296110833
    - type: precision
      value: 95.72441996327827
    - type: recall
      value: 96.99549323985978
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (ces_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: ces_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.94391587381071
    - type: f1
      value: 94.90680465142157
    - type: main_score
      value: 94.90680465142157
    - type: precision
      value: 94.44541812719079
    - type: recall
      value: 95.94391587381071
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (deu_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: deu_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.09414121181773
    - type: f1
      value: 94.94408279085295
    - type: main_score
      value: 94.94408279085295
    - type: precision
      value: 94.41245201135037
    - type: recall
      value: 96.09414121181773
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (ell_Grek-rus_Cyrl)
      type: mteb/NTREX
      config: ell_Grek-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.19429143715573
    - type: f1
      value: 95.12101485561676
    - type: main_score
      value: 95.12101485561676
    - type: precision
      value: 94.60440660991488
    - type: recall
      value: 96.19429143715573
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (eng_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: eng_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.49474211316975
    - type: f1
      value: 95.46581777428045
    - type: main_score
      value: 95.46581777428045
    - type: precision
      value: 94.98414288098814
    - type: recall
      value: 96.49474211316975
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (fas_Arab-rus_Cyrl)
      type: mteb/NTREX
      config: fas_Arab-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.44166249374061
    - type: f1
      value: 92.92383018972905
    - type: main_score
      value: 92.92383018972905
    - type: precision
      value: 92.21957936905358
    - type: recall
      value: 94.44166249374061
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (fin_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: fin_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.18828242363544
    - type: f1
      value: 90.2980661468393
    - type: main_score
      value: 90.2980661468393
    - type: precision
      value: 89.42580537472877
    - type: recall
      value: 92.18828242363544
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (fra_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: fra_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.84376564847271
    - type: f1
      value: 94.81054915706895
    - type: main_score
      value: 94.81054915706895
    - type: precision
      value: 94.31369276136427
    - type: recall
      value: 95.84376564847271
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (heb_Hebr-rus_Cyrl)
      type: mteb/NTREX
      config: heb_Hebr-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.89233850776164
    - type: f1
      value: 93.42513770655985
    - type: main_score
      value: 93.42513770655985
    - type: precision
      value: 92.73493573693875
    - type: recall
      value: 94.89233850776164
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (hin_Deva-rus_Cyrl)
      type: mteb/NTREX
      config: hin_Deva-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.23985978968453
    - type: f1
      value: 91.52816526376867
    - type: main_score
      value: 91.52816526376867
    - type: precision
      value: 90.76745946425466
    - type: recall
      value: 93.23985978968453
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (hrv_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: hrv_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.99098647971958
    - type: f1
      value: 92.36354531797697
    - type: main_score
      value: 92.36354531797697
    - type: precision
      value: 91.63228970439788
    - type: recall
      value: 93.99098647971958
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (hun_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: hun_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.64046069103655
    - type: f1
      value: 92.05224503421799
    - type: main_score
      value: 92.05224503421799
    - type: precision
      value: 91.33998616973079
    - type: recall
      value: 93.64046069103655
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (ind_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: ind_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 91.68753129694541
    - type: f1
      value: 89.26222667334335
    - type: main_score
      value: 89.26222667334335
    - type: precision
      value: 88.14638624603572
    - type: recall
      value: 91.68753129694541
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (jpn_Jpan-rus_Cyrl)
      type: mteb/NTREX
      config: jpn_Jpan-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 91.28693039559339
    - type: f1
      value: 89.21161763348957
    - type: main_score
      value: 89.21161763348957
    - type: precision
      value: 88.31188340952988
    - type: recall
      value: 91.28693039559339
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (kor_Hang-rus_Cyrl)
      type: mteb/NTREX
      config: kor_Hang-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 89.53430145217827
    - type: f1
      value: 86.88322165788365
    - type: main_score
      value: 86.88322165788365
    - type: precision
      value: 85.73950211030831
    - type: recall
      value: 89.53430145217827
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (lit_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: lit_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 90.28542814221332
    - type: f1
      value: 88.10249103814452
    - type: main_score
      value: 88.10249103814452
    - type: precision
      value: 87.17689323973752
    - type: recall
      value: 90.28542814221332
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (mkd_Cyrl-rus_Cyrl)
      type: mteb/NTREX
      config: mkd_Cyrl-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.04256384576865
    - type: f1
      value: 93.65643703650713
    - type: main_score
      value: 93.65643703650713
    - type: precision
      value: 93.02036387915207
    - type: recall
      value: 95.04256384576865
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (nld_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: nld_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.39308963445168
    - type: f1
      value: 94.16207644800535
    - type: main_score
      value: 94.16207644800535
    - type: precision
      value: 93.582516632091
    - type: recall
      value: 95.39308963445168
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (pol_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: pol_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.7436154231347
    - type: f1
      value: 94.5067601402103
    - type: main_score
      value: 94.5067601402103
    - type: precision
      value: 93.91587381071608
    - type: recall
      value: 95.7436154231347
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (por_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: por_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 65.89884827240861
    - type: f1
      value: 64.61805459419219
    - type: main_score
      value: 64.61805459419219
    - type: precision
      value: 64.07119451106485
    - type: recall
      value: 65.89884827240861
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-arb_Arab)
      type: mteb/NTREX
      config: rus_Cyrl-arb_Arab
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.2413620430646
    - type: f1
      value: 92.67663399861698
    - type: main_score
      value: 92.67663399861698
    - type: precision
      value: 91.94625271240193
    - type: recall
      value: 94.2413620430646
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-bel_Cyrl)
      type: mteb/NTREX
      config: rus_Cyrl-bel_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.89233850776164
    - type: f1
      value: 93.40343849106993
    - type: main_score
      value: 93.40343849106993
    - type: precision
      value: 92.74077783341679
    - type: recall
      value: 94.89233850776164
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-ben_Beng)
      type: mteb/NTREX
      config: rus_Cyrl-ben_Beng
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.2914371557336
    - type: f1
      value: 92.62226673343348
    - type: main_score
      value: 92.62226673343348
    - type: precision
      value: 91.84610248706393
    - type: recall
      value: 94.2914371557336
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-bos_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-bos_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.69354031046569
    - type: f1
      value: 94.50418051319403
    - type: main_score
      value: 94.50418051319403
    - type: precision
      value: 93.95843765648473
    - type: recall
      value: 95.69354031046569
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-bul_Cyrl)
      type: mteb/NTREX
      config: rus_Cyrl-bul_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.89384076114172
    - type: f1
      value: 94.66199298948423
    - type: main_score
      value: 94.66199298948423
    - type: precision
      value: 94.08028709731263
    - type: recall
      value: 95.89384076114172
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-ces_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-ces_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.94091136705057
    - type: f1
      value: 92.3746731207923
    - type: main_score
      value: 92.3746731207923
    - type: precision
      value: 91.66207644800535
    - type: recall
      value: 93.94091136705057
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-deu_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-deu_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.94391587381071
    - type: f1
      value: 94.76214321482223
    - type: main_score
      value: 94.76214321482223
    - type: precision
      value: 94.20380570856285
    - type: recall
      value: 95.94391587381071
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-ell_Grek)
      type: mteb/NTREX
      config: rus_Cyrl-ell_Grek
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.44316474712068
    - type: f1
      value: 94.14788849941579
    - type: main_score
      value: 94.14788849941579
    - type: precision
      value: 93.54197963612084
    - type: recall
      value: 95.44316474712068
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-eng_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-eng_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 98.14722083124687
    - type: f1
      value: 97.57135703555333
    - type: main_score
      value: 97.57135703555333
    - type: precision
      value: 97.2959439158738
    - type: recall
      value: 98.14722083124687
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-fas_Arab)
      type: mteb/NTREX
      config: rus_Cyrl-fas_Arab
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.64196294441662
    - type: f1
      value: 93.24653647137372
    - type: main_score
      value: 93.24653647137372
    - type: precision
      value: 92.60724419963279
    - type: recall
      value: 94.64196294441662
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-fin_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-fin_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 87.98197295943916
    - type: f1
      value: 85.23368385912201
    - type: main_score
      value: 85.23368385912201
    - type: precision
      value: 84.08159858835873
    - type: recall
      value: 87.98197295943916
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-fra_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-fra_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.24436654982473
    - type: f1
      value: 95.07093974294774
    - type: main_score
      value: 95.07093974294774
    - type: precision
      value: 94.49591053246536
    - type: recall
      value: 96.24436654982473
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-heb_Hebr)
      type: mteb/NTREX
      config: rus_Cyrl-heb_Hebr
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 91.08662994491738
    - type: f1
      value: 88.5161074945752
    - type: main_score
      value: 88.5161074945752
    - type: precision
      value: 87.36187614755467
    - type: recall
      value: 91.08662994491738
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-hin_Deva)
      type: mteb/NTREX
      config: rus_Cyrl-hin_Deva
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.04256384576865
    - type: f1
      value: 93.66382907694876
    - type: main_score
      value: 93.66382907694876
    - type: precision
      value: 93.05291270238692
    - type: recall
      value: 95.04256384576865
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-hrv_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-hrv_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.14271407110667
    - type: f1
      value: 93.7481221832749
    - type: main_score
      value: 93.7481221832749
    - type: precision
      value: 93.10930681736892
    - type: recall
      value: 95.14271407110667
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-hun_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-hun_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 90.18527791687532
    - type: f1
      value: 87.61415933423946
    - type: main_score
      value: 87.61415933423946
    - type: precision
      value: 86.5166400394242
    - type: recall
      value: 90.18527791687532
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-ind_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-ind_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.69053580370556
    - type: f1
      value: 91.83608746453012
    - type: main_score
      value: 91.83608746453012
    - type: precision
      value: 90.97145718577868
    - type: recall
      value: 93.69053580370556
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-jpn_Jpan)
      type: mteb/NTREX
      config: rus_Cyrl-jpn_Jpan
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 89.48422633950926
    - type: f1
      value: 86.91271033534429
    - type: main_score
      value: 86.91271033534429
    - type: precision
      value: 85.82671626487351
    - type: recall
      value: 89.48422633950926
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-kor_Hang)
      type: mteb/NTREX
      config: rus_Cyrl-kor_Hang
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 88.4827240861292
    - type: f1
      value: 85.35080398375342
    - type: main_score
      value: 85.35080398375342
    - type: precision
      value: 83.9588549490903
    - type: recall
      value: 88.4827240861292
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-lit_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-lit_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 90.33550325488233
    - type: f1
      value: 87.68831819157307
    - type: main_score
      value: 87.68831819157307
    - type: precision
      value: 86.51524906407231
    - type: recall
      value: 90.33550325488233
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-mkd_Cyrl)
      type: mteb/NTREX
      config: rus_Cyrl-mkd_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.94391587381071
    - type: f1
      value: 94.90402270071775
    - type: main_score
      value: 94.90402270071775
    - type: precision
      value: 94.43915873810715
    - type: recall
      value: 95.94391587381071
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-nld_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-nld_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.98948422633951
    - type: f1
      value: 91.04323151393756
    - type: main_score
      value: 91.04323151393756
    - type: precision
      value: 90.14688699716241
    - type: recall
      value: 92.98948422633951
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-pol_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-pol_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.34151226840261
    - type: f1
      value: 92.8726422967785
    - type: main_score
      value: 92.8726422967785
    - type: precision
      value: 92.19829744616925
    - type: recall
      value: 94.34151226840261
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-por_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-por_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 86.17926890335504
    - type: f1
      value: 82.7304882287356
    - type: main_score
      value: 82.7304882287356
    - type: precision
      value: 81.28162481817964
    - type: recall
      value: 86.17926890335504
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-slk_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-slk_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.7391086629945
    - type: f1
      value: 90.75112669003506
    - type: main_score
      value: 90.75112669003506
    - type: precision
      value: 89.8564513436822
    - type: recall
      value: 92.7391086629945
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-slv_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-slv_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.8893340010015
    - type: f1
      value: 91.05992321816058
    - type: main_score
      value: 91.05992321816058
    - type: precision
      value: 90.22589439715128
    - type: recall
      value: 92.8893340010015
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-spa_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-spa_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.49474211316975
    - type: f1
      value: 95.4715406442998
    - type: main_score
      value: 95.4715406442998
    - type: precision
      value: 94.9799699549324
    - type: recall
      value: 96.49474211316975
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-srp_Cyrl)
      type: mteb/NTREX
      config: rus_Cyrl-srp_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 81.07160741111667
    - type: f1
      value: 76.55687285507015
    - type: main_score
      value: 76.55687285507015
    - type: precision
      value: 74.71886401030116
    - type: recall
      value: 81.07160741111667
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-srp_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-srp_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.14271407110667
    - type: f1
      value: 93.73302377809138
    - type: main_score
      value: 93.73302377809138
    - type: precision
      value: 93.06960440660991
    - type: recall
      value: 95.14271407110667
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-swa_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-swa_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.79218828242364
    - type: f1
      value: 93.25988983475212
    - type: main_score
      value: 93.25988983475212
    - type: precision
      value: 92.53463528626273
    - type: recall
      value: 94.79218828242364
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-swe_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-swe_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.04256384576865
    - type: f1
      value: 93.58704723752295
    - type: main_score
      value: 93.58704723752295
    - type: precision
      value: 92.91437155733601
    - type: recall
      value: 95.04256384576865
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-tam_Taml)
      type: mteb/NTREX
      config: rus_Cyrl-tam_Taml
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.28993490235354
    - type: f1
      value: 91.63912535469872
    - type: main_score
      value: 91.63912535469872
    - type: precision
      value: 90.87738750983617
    - type: recall
      value: 93.28993490235354
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-tur_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-tur_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.74061091637456
    - type: f1
      value: 91.96628275746953
    - type: main_score
      value: 91.96628275746953
    - type: precision
      value: 91.15923885828742
    - type: recall
      value: 93.74061091637456
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-ukr_Cyrl)
      type: mteb/NTREX
      config: rus_Cyrl-ukr_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.99399098647972
    - type: f1
      value: 94.89567684860624
    - type: main_score
      value: 94.89567684860624
    - type: precision
      value: 94.37072275079286
    - type: recall
      value: 95.99399098647972
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-vie_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-vie_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 91.4371557336004
    - type: f1
      value: 88.98681355366382
    - type: main_score
      value: 88.98681355366382
    - type: precision
      value: 87.89183775663496
    - type: recall
      value: 91.4371557336004
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-zho_Hant)
      type: mteb/NTREX
      config: rus_Cyrl-zho_Hant
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.7891837756635
    - type: f1
      value: 90.79047142141783
    - type: main_score
      value: 90.79047142141783
    - type: precision
      value: 89.86980470706058
    - type: recall
      value: 92.7891837756635
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (rus_Cyrl-zul_Latn)
      type: mteb/NTREX
      config: rus_Cyrl-zul_Latn
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 87.43114672008012
    - type: f1
      value: 84.04618833011422
    - type: main_score
      value: 84.04618833011422
    - type: precision
      value: 82.52259341393041
    - type: recall
      value: 87.43114672008012
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (slk_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: slk_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.34301452178268
    - type: f1
      value: 94.20392493502158
    - type: main_score
      value: 94.20392493502158
    - type: precision
      value: 93.67384409948257
    - type: recall
      value: 95.34301452178268
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (slv_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: slv_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 92.23835753630446
    - type: f1
      value: 90.5061759305625
    - type: main_score
      value: 90.5061759305625
    - type: precision
      value: 89.74231188051918
    - type: recall
      value: 92.23835753630446
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (spa_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: spa_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.54481722583876
    - type: f1
      value: 95.54665331330328
    - type: main_score
      value: 95.54665331330328
    - type: precision
      value: 95.06342847604739
    - type: recall
      value: 96.54481722583876
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (srp_Cyrl-rus_Cyrl)
      type: mteb/NTREX
      config: srp_Cyrl-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 83.62543815723585
    - type: f1
      value: 80.77095672699816
    - type: main_score
      value: 80.77095672699816
    - type: precision
      value: 79.74674313056886
    - type: recall
      value: 83.62543815723585
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (srp_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: srp_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 94.44166249374061
    - type: f1
      value: 93.00733206591994
    - type: main_score
      value: 93.00733206591994
    - type: precision
      value: 92.37203026762366
    - type: recall
      value: 94.44166249374061
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (swa_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: swa_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 90.23535302954431
    - type: f1
      value: 87.89596482636041
    - type: main_score
      value: 87.89596482636041
    - type: precision
      value: 86.87060227370694
    - type: recall
      value: 90.23535302954431
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (swe_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: swe_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 95.44316474712068
    - type: f1
      value: 94.1896177599733
    - type: main_score
      value: 94.1896177599733
    - type: precision
      value: 93.61542313470206
    - type: recall
      value: 95.44316474712068
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (tam_Taml-rus_Cyrl)
      type: mteb/NTREX
      config: tam_Taml-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 89.68452679018529
    - type: f1
      value: 87.37341160650037
    - type: main_score
      value: 87.37341160650037
    - type: precision
      value: 86.38389402285247
    - type: recall
      value: 89.68452679018529
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (tur_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: tur_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.89083625438157
    - type: f1
      value: 92.33892505424804
    - type: main_score
      value: 92.33892505424804
    - type: precision
      value: 91.63125640842216
    - type: recall
      value: 93.89083625438157
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (ukr_Cyrl-rus_Cyrl)
      type: mteb/NTREX
      config: ukr_Cyrl-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 96.14421632448673
    - type: f1
      value: 95.11028447433054
    - type: main_score
      value: 95.11028447433054
    - type: precision
      value: 94.62944416624937
    - type: recall
      value: 96.14421632448673
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (vie_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: vie_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 93.79068602904357
    - type: f1
      value: 92.14989150392256
    - type: main_score
      value: 92.14989150392256
    - type: precision
      value: 91.39292271740945
    - type: recall
      value: 93.79068602904357
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (zho_Hant-rus_Cyrl)
      type: mteb/NTREX
      config: zho_Hant-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 89.13370055082625
    - type: f1
      value: 86.51514618639217
    - type: main_score
      value: 86.51514618639217
    - type: precision
      value: 85.383920035898
    - type: recall
      value: 89.13370055082625
  - task:
      type: BitextMining
    dataset:
      name: MTEB NTREXBitextMining (zul_Latn-rus_Cyrl)
      type: mteb/NTREX
      config: zul_Latn-rus_Cyrl
      split: test
      revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33
    metrics:
    - type: accuracy
      value: 81.17175763645467
    - type: f1
      value: 77.72331766047338
    - type: main_score
      value: 77.72331766047338
    - type: precision
      value: 76.24629555848075
    - type: recall
      value: 81.17175763645467
  - task:
      type: PairClassification
    dataset:
      name: MTEB OpusparcusPC (ru)
      type: GEM/opusparcus
      config: ru
      split: test.full
      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
    metrics:
    - type: cosine_accuracy
      value: 73.09136420525657
    - type: cosine_accuracy_threshold
      value: 87.70400881767273
    - type: cosine_ap
      value: 86.51938550599533
    - type: cosine_f1
      value: 80.84358523725834
    - type: cosine_f1_threshold
      value: 86.90648078918457
    - type: cosine_precision
      value: 73.24840764331209
    - type: cosine_recall
      value: 90.19607843137256
    - type: dot_accuracy
      value: 73.09136420525657
    - type: dot_accuracy_threshold
      value: 87.7040147781372
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    dataset:
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      type: xhluca/publichealth-qa
      config: russian
      split: test
      revision: main
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  - task:
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      type: merionum/ru_paraphraser
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      revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4
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  - task:
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      revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7
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    - type: nauc_recall_at_10_std
      value: -6.62483991471789
    - type: nauc_recall_at_1_diff1
      value: 69.31275711813979
    - type: nauc_recall_at_1_max
      value: 26.386708520283758
    - type: nauc_recall_at_1_std
      value: -14.434616447245464
    - type: nauc_recall_at_20_diff1
      value: 55.93570036001682
    - type: nauc_recall_at_20_max
      value: 34.986401733887554
    - type: nauc_recall_at_20_std
      value: -0.3651846515931506
    - type: nauc_recall_at_3_diff1
      value: 60.94100093991499
    - type: nauc_recall_at_3_max
      value: 31.422239034357606
    - type: nauc_recall_at_3_std
      value: -12.725765565378966
    - type: nauc_recall_at_5_diff1
      value: 59.450505195434125
    - type: nauc_recall_at_5_max
      value: 32.07638712418387
    - type: nauc_recall_at_5_std
      value: -10.024459103498472
    - type: ndcg_at_1
      value: 55.97
    - type: ndcg_at_10
      value: 70.00999999999999
    - type: ndcg_at_100
      value: 72.20100000000001
    - type: ndcg_at_1000
      value: 72.65599999999999
    - type: ndcg_at_20
      value: 71.068
    - type: ndcg_at_3
      value: 66.228
    - type: ndcg_at_5
      value: 68.191
    - type: precision_at_1
      value: 55.97
    - type: precision_at_10
      value: 8.373999999999999
    - type: precision_at_100
      value: 0.9390000000000001
    - type: precision_at_1000
      value: 0.097
    - type: precision_at_20
      value: 4.3950000000000005
    - type: precision_at_3
      value: 24.46
    - type: precision_at_5
      value: 15.626000000000001
    - type: recall_at_1
      value: 55.97
    - type: recall_at_10
      value: 83.74000000000001
    - type: recall_at_100
      value: 93.87
    - type: recall_at_1000
      value: 97.49
    - type: recall_at_20
      value: 87.89
    - type: recall_at_3
      value: 73.38
    - type: recall_at_5
      value: 78.13
  - task:
      type: Reranking
    dataset:
      name: MTEB RuBQReranking (default)
      type: ai-forever/rubq-reranking
      config: default
      split: test
      revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
    metrics:
    - type: main_score
      value: 71.44929565043827
    - type: map
      value: 71.44929565043827
    - type: mrr
      value: 77.78391820945014
    - type: nAUC_map_diff1
      value: 38.140840668080244
    - type: nAUC_map_max
      value: 27.54328688105381
    - type: nAUC_map_std
      value: 16.81572082284672
    - type: nAUC_mrr_diff1
      value: 44.51350415961509
    - type: nAUC_mrr_max
      value: 36.491182016669754
    - type: nAUC_mrr_std
      value: 22.47139593052269
  - task:
      type: Retrieval
    dataset:
      name: MTEB RuBQRetrieval (default)
      type: ai-forever/rubq-retrieval
      config: default
      split: test
      revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
    metrics:
    - type: main_score
      value: 68.529
    - type: map_at_1
      value: 42.529
    - type: map_at_10
      value: 60.864
    - type: map_at_100
      value: 61.868
    - type: map_at_1000
      value: 61.907000000000004
    - type: map_at_20
      value: 61.596
    - type: map_at_3
      value: 55.701
    - type: map_at_5
      value: 58.78
    - type: mrr_at_1
      value: 60.57919621749409
    - type: mrr_at_10
      value: 70.55614188149649
    - type: mrr_at_100
      value: 70.88383816664494
    - type: mrr_at_1000
      value: 70.89719252668833
    - type: mrr_at_20
      value: 70.79839750105347
    - type: mrr_at_3
      value: 68.4594168636722
    - type: mrr_at_5
      value: 69.67100078802214
    - type: nauc_map_at_1000_diff1
      value: 40.67438785660885
    - type: nauc_map_at_1000_max
      value: 32.79981738507424
    - type: nauc_map_at_1000_std
      value: -6.873402600044831
    - type: nauc_map_at_100_diff1
      value: 40.65643664443284
    - type: nauc_map_at_100_max
      value: 32.81594799919249
    - type: nauc_map_at_100_std
      value: -6.8473246794498195
    - type: nauc_map_at_10_diff1
      value: 40.39048268484908
    - type: nauc_map_at_10_max
      value: 32.403242161479525
    - type: nauc_map_at_10_std
      value: -7.344413799841244
    - type: nauc_map_at_1_diff1
      value: 44.36306892906905
    - type: nauc_map_at_1_max
      value: 25.61348630699028
    - type: nauc_map_at_1_std
      value: -8.713074613333902
    - type: nauc_map_at_20_diff1
      value: 40.530326570124615
    - type: nauc_map_at_20_max
      value: 32.74028319323205
    - type: nauc_map_at_20_std
      value: -7.008180779820569
    - type: nauc_map_at_3_diff1
      value: 40.764924859364044
    - type: nauc_map_at_3_max
      value: 29.809671682025336
    - type: nauc_map_at_3_std
      value: -9.205620202725564
    - type: nauc_map_at_5_diff1
      value: 40.88599496021476
    - type: nauc_map_at_5_max
      value: 32.1701894666848
    - type: nauc_map_at_5_std
      value: -7.801251849010623
    - type: nauc_mrr_at_1000_diff1
      value: 48.64181373540728
    - type: nauc_mrr_at_1000_max
      value: 40.136947990653546
    - type: nauc_mrr_at_1000_std
      value: -7.250260497468805
    - type: nauc_mrr_at_100_diff1
      value: 48.63349902496212
    - type: nauc_mrr_at_100_max
      value: 40.14510559704008
    - type: nauc_mrr_at_100_std
      value: -7.228702374801103
    - type: nauc_mrr_at_10_diff1
      value: 48.58580560194813
    - type: nauc_mrr_at_10_max
      value: 40.15075599433366
    - type: nauc_mrr_at_10_std
      value: -7.267928771548688
    - type: nauc_mrr_at_1_diff1
      value: 51.47535097164919
    - type: nauc_mrr_at_1_max
      value: 38.23579750430856
    - type: nauc_mrr_at_1_std
      value: -9.187785187137633
    - type: nauc_mrr_at_20_diff1
      value: 48.58688378336222
    - type: nauc_mrr_at_20_max
      value: 40.13408744088299
    - type: nauc_mrr_at_20_std
      value: -7.283132775160146
    - type: nauc_mrr_at_3_diff1
      value: 48.66833005454742
    - type: nauc_mrr_at_3_max
      value: 40.07987333638038
    - type: nauc_mrr_at_3_std
      value: -7.738819947521418
    - type: nauc_mrr_at_5_diff1
      value: 48.76536305941537
    - type: nauc_mrr_at_5_max
      value: 40.381929739522185
    - type: nauc_mrr_at_5_std
      value: -7.592858318378928
    - type: nauc_ndcg_at_1000_diff1
      value: 41.67304442004693
    - type: nauc_ndcg_at_1000_max
      value: 35.84126926253235
    - type: nauc_ndcg_at_1000_std
      value: -4.78971011604655
    - type: nauc_ndcg_at_100_diff1
      value: 41.16918850185783
    - type: nauc_ndcg_at_100_max
      value: 36.082461962326505
    - type: nauc_ndcg_at_100_std
      value: -4.092442251697269
    - type: nauc_ndcg_at_10_diff1
      value: 40.300065598615205
    - type: nauc_ndcg_at_10_max
      value: 34.87866296788365
    - type: nauc_ndcg_at_10_std
      value: -5.866529277842453
    - type: nauc_ndcg_at_1_diff1
      value: 51.74612915209495
    - type: nauc_ndcg_at_1_max
      value: 37.71907067970078
    - type: nauc_ndcg_at_1_std
      value: -9.064124266098696
    - type: nauc_ndcg_at_20_diff1
      value: 40.493949850214584
    - type: nauc_ndcg_at_20_max
      value: 35.69331503650286
    - type: nauc_ndcg_at_20_std
      value: -4.995310342975443
    - type: nauc_ndcg_at_3_diff1
      value: 41.269443212112364
    - type: nauc_ndcg_at_3_max
      value: 32.572844460953334
    - type: nauc_ndcg_at_3_std
      value: -9.063015396458791
    - type: nauc_ndcg_at_5_diff1
      value: 41.37039652522888
    - type: nauc_ndcg_at_5_max
      value: 34.67416011393571
    - type: nauc_ndcg_at_5_std
      value: -7.106845569862319
    - type: nauc_precision_at_1000_diff1
      value: -9.571769961090155
    - type: nauc_precision_at_1000_max
      value: 5.574782583417188
    - type: nauc_precision_at_1000_std
      value: 7.28333847923847
    - type: nauc_precision_at_100_diff1
      value: -7.7405012003383735
    - type: nauc_precision_at_100_max
      value: 9.67745355070353
    - type: nauc_precision_at_100_std
      value: 9.327890294080992
    - type: nauc_precision_at_10_diff1
      value: -1.006879647532931
    - type: nauc_precision_at_10_max
      value: 15.899825481231064
    - type: nauc_precision_at_10_std
      value: 4.2284084852153105
    - type: nauc_precision_at_1_diff1
      value: 51.74612915209495
    - type: nauc_precision_at_1_max
      value: 37.71907067970078
    - type: nauc_precision_at_1_std
      value: -9.064124266098696
    - type: nauc_precision_at_20_diff1
      value: -4.982301544401409
    - type: nauc_precision_at_20_max
      value: 13.241674471380568
    - type: nauc_precision_at_20_std
      value: 7.052280133821539
    - type: nauc_precision_at_3_diff1
      value: 15.442614376387374
    - type: nauc_precision_at_3_max
      value: 25.12695418083
    - type: nauc_precision_at_3_std
      value: -3.1150066697920638
    - type: nauc_precision_at_5_diff1
      value: 8.381026072692444
    - type: nauc_precision_at_5_max
      value: 22.839056540604822
    - type: nauc_precision_at_5_std
      value: 1.5126905486524331
    - type: nauc_recall_at_1000_diff1
      value: -0.8869709920433502
    - type: nauc_recall_at_1000_max
      value: 45.092324433377264
    - type: nauc_recall_at_1000_std
      value: 62.21264093315108
    - type: nauc_recall_at_100_diff1
      value: 16.036715011075714
    - type: nauc_recall_at_100_max
      value: 39.79963411771158
    - type: nauc_recall_at_100_std
      value: 28.41850069503361
    - type: nauc_recall_at_10_diff1
      value: 25.189622794479998
    - type: nauc_recall_at_10_max
      value: 30.82355277039427
    - type: nauc_recall_at_10_std
      value: 0.0964544736531047
    - type: nauc_recall_at_1_diff1
      value: 44.36306892906905
    - type: nauc_recall_at_1_max
      value: 25.61348630699028
    - type: nauc_recall_at_1_std
      value: -8.713074613333902
    - type: nauc_recall_at_20_diff1
      value: 20.43424504746087
    - type: nauc_recall_at_20_max
      value: 33.96010554649377
    - type: nauc_recall_at_20_std
      value: 6.900984030301936
    - type: nauc_recall_at_3_diff1
      value: 33.86531858793492
    - type: nauc_recall_at_3_max
      value: 27.725692256711188
    - type: nauc_recall_at_3_std
      value: -8.533124289305709
    - type: nauc_recall_at_5_diff1
      value: 32.006964557701686
    - type: nauc_recall_at_5_max
      value: 31.493370659289806
    - type: nauc_recall_at_5_std
      value: -4.8639793547793255
    - type: ndcg_at_1
      value: 60.461
    - type: ndcg_at_10
      value: 68.529
    - type: ndcg_at_100
      value: 71.664
    - type: ndcg_at_1000
      value: 72.396
    - type: ndcg_at_20
      value: 70.344
    - type: ndcg_at_3
      value: 61.550000000000004
    - type: ndcg_at_5
      value: 64.948
    - type: precision_at_1
      value: 60.461
    - type: precision_at_10
      value: 13.28
    - type: precision_at_100
      value: 1.555
    - type: precision_at_1000
      value: 0.164
    - type: precision_at_20
      value: 7.216
    - type: precision_at_3
      value: 33.077
    - type: precision_at_5
      value: 23.014000000000003
    - type: recall_at_1
      value: 42.529
    - type: recall_at_10
      value: 81.169
    - type: recall_at_100
      value: 93.154
    - type: recall_at_1000
      value: 98.18299999999999
    - type: recall_at_20
      value: 87.132
    - type: recall_at_3
      value: 63.905
    - type: recall_at_5
      value: 71.967
  - task:
      type: Classification
    dataset:
      name: MTEB RuReviewsClassification (default)
      type: ai-forever/ru-reviews-classification
      config: default
      split: test
      revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
    metrics:
    - type: accuracy
      value: 61.17675781250001
    - type: f1
      value: 60.354535346041374
    - type: f1_weighted
      value: 60.35437313166116
    - type: main_score
      value: 61.17675781250001
  - task:
      type: STS
    dataset:
      name: MTEB RuSTSBenchmarkSTS (default)
      type: ai-forever/ru-stsbenchmark-sts
      config: default
      split: test
      revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
    metrics:
    - type: cosine_pearson
      value: 78.1301041727274
    - type: cosine_spearman
      value: 78.08238025421747
    - type: euclidean_pearson
      value: 77.35224254583635
    - type: euclidean_spearman
      value: 78.08235336582496
    - type: main_score
      value: 78.08238025421747
    - type: manhattan_pearson
      value: 77.24138550052075
    - type: manhattan_spearman
      value: 77.98199107904142
    - type: pearson
      value: 78.1301041727274
    - type: spearman
      value: 78.08238025421747
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchGRNTIClassification (default)
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: accuracy
      value: 54.990234375
    - type: f1
      value: 53.537019057131374
    - type: f1_weighted
      value: 53.552745354520766
    - type: main_score
      value: 54.990234375
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchGRNTIClusteringP2P (default)
      type: ai-forever/ru-scibench-grnti-classification
      config: default
      split: test
      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
    metrics:
    - type: main_score
      value: 50.775228895355106
    - type: v_measure
      value: 50.775228895355106
    - type: v_measure_std
      value: 0.9533571150165796
  - task:
      type: Classification
    dataset:
      name: MTEB RuSciBenchOECDClassification (default)
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: accuracy
      value: 41.71875
    - type: f1
      value: 39.289100975858304
    - type: f1_weighted
      value: 39.29257829217775
    - type: main_score
      value: 41.71875
  - task:
      type: Clustering
    dataset:
      name: MTEB RuSciBenchOECDClusteringP2P (default)
      type: ai-forever/ru-scibench-oecd-classification
      config: default
      split: test
      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
    metrics:
    - type: main_score
      value: 45.10904808834516
    - type: v_measure
      value: 45.10904808834516
    - type: v_measure_std
      value: 1.0572643410157534
  - task:
      type: Classification
    dataset:
      name: MTEB SIB200Classification (rus_Cyrl)
      type: mteb/sib200
      config: rus_Cyrl
      split: test
      revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
    metrics:
    - type: accuracy
      value: 66.36363636363637
    - type: f1
      value: 64.6940336621617
    - type: f1_weighted
      value: 66.43317771876966
    - type: main_score
      value: 66.36363636363637
  - task:
      type: Clustering
    dataset:
      name: MTEB SIB200ClusteringS2S (rus_Cyrl)
      type: mteb/sib200
      config: rus_Cyrl
      split: test
      revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b
    metrics:
    - type: main_score
      value: 33.99178497314711
    - type: v_measure
      value: 33.99178497314711
    - type: v_measure_std
      value: 4.036337464043786
  - task:
      type: STS
    dataset:
      name: MTEB STS22.v2 (ru)
      type: mteb/sts22-crosslingual-sts
      config: ru
      split: test
      revision: d31f33a128469b20e357535c39b82fb3c3f6f2bd
    metrics:
    - type: cosine_pearson
      value: 50.724322379215934
    - type: cosine_spearman
      value: 59.90449732164651
    - type: euclidean_pearson
      value: 50.227545226784024
    - type: euclidean_spearman
      value: 59.898906527601085
    - type: main_score
      value: 59.90449732164651
    - type: manhattan_pearson
      value: 50.21762139819405
    - type: manhattan_spearman
      value: 59.761039813759
    - type: pearson
      value: 50.724322379215934
    - type: spearman
      value: 59.90449732164651
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmarkMultilingualSTS (ru)
      type: mteb/stsb_multi_mt
      config: ru
      split: dev
      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
    metrics:
    - type: cosine_pearson
      value: 78.43928769569945
    - type: cosine_spearman
      value: 78.23961768018884
    - type: euclidean_pearson
      value: 77.4718694027985
    - type: euclidean_spearman
      value: 78.23887044760475
    - type: main_score
      value: 78.23961768018884
    - type: manhattan_pearson
      value: 77.34517128089547
    - type: manhattan_spearman
      value: 78.1146477340426
    - type: pearson
      value: 78.43928769569945
    - type: spearman
      value: 78.23961768018884
  - task:
      type: MultilabelClassification
    dataset:
      name: MTEB SensitiveTopicsClassification (default)
      type: ai-forever/sensitive-topics-classification
      config: default
      split: test
      revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2
    metrics:
    - type: accuracy
      value: 22.8125
    - type: f1
      value: 17.31969589593409
    - type: lrap
      value: 33.82412380642287
    - type: main_score
      value: 22.8125
  - task:
      type: PairClassification
    dataset:
      name: MTEB TERRa (default)
      type: ai-forever/terra-pairclassification
      config: default
      split: dev
      revision: 7b58f24536063837d644aab9a023c62199b2a612
    metrics:
    - type: cosine_accuracy
      value: 57.32899022801303
    - type: cosine_accuracy_threshold
      value: 85.32201051712036
    - type: cosine_ap
      value: 55.14264553720072
    - type: cosine_f1
      value: 66.83544303797468
    - type: cosine_f1_threshold
      value: 85.32201051712036
    - type: cosine_precision
      value: 54.54545454545454
    - type: cosine_recall
      value: 86.27450980392157
    - type: dot_accuracy
      value: 57.32899022801303
    - type: dot_accuracy_threshold
      value: 85.32201051712036
    - type: dot_ap
      value: 55.14264553720072
    - type: dot_f1
      value: 66.83544303797468
    - type: dot_f1_threshold
      value: 85.32201051712036
    - type: dot_precision
      value: 54.54545454545454
    - type: dot_recall
      value: 86.27450980392157
    - type: euclidean_accuracy
      value: 57.32899022801303
    - type: euclidean_accuracy_threshold
      value: 54.18117046356201
    - type: euclidean_ap
      value: 55.14264553720072
    - type: euclidean_f1
      value: 66.83544303797468
    - type: euclidean_f1_threshold
      value: 54.18117046356201
    - type: euclidean_precision
      value: 54.54545454545454
    - type: euclidean_recall
      value: 86.27450980392157
    - type: main_score
      value: 55.14264553720072
    - type: manhattan_accuracy
      value: 57.32899022801303
    - type: manhattan_accuracy_threshold
      value: 828.8480758666992
    - type: manhattan_ap
      value: 55.077974053622555
    - type: manhattan_f1
      value: 66.82352941176471
    - type: manhattan_f1_threshold
      value: 885.6784820556641
    - type: manhattan_precision
      value: 52.20588235294118
    - type: manhattan_recall
      value: 92.81045751633987
    - type: max_ap
      value: 55.14264553720072
    - type: max_f1
      value: 66.83544303797468
    - type: max_precision
      value: 54.54545454545454
    - type: max_recall
      value: 92.81045751633987
    - type: similarity_accuracy
      value: 57.32899022801303
    - type: similarity_accuracy_threshold
      value: 85.32201051712036
    - type: similarity_ap
      value: 55.14264553720072
    - type: similarity_f1
      value: 66.83544303797468
    - type: similarity_f1_threshold
      value: 85.32201051712036
    - type: similarity_precision
      value: 54.54545454545454
    - type: similarity_recall
      value: 86.27450980392157
  - task:
      type: PairClassification
    dataset:
      name: MTEB XNLI (ru)
      type: mteb/xnli
      config: ru
      split: test
      revision: 09698e0180d87dc247ca447d3a1248b931ac0cdb
    metrics:
    - type: cosine_accuracy
      value: 67.6923076923077
    - type: cosine_accuracy_threshold
      value: 87.6681923866272
    - type: cosine_ap
      value: 73.18693800863593
    - type: cosine_f1
      value: 70.40641099026904
    - type: cosine_f1_threshold
      value: 85.09706258773804
    - type: cosine_precision
      value: 57.74647887323944
    - type: cosine_recall
      value: 90.17595307917888
    - type: dot_accuracy
      value: 67.6923076923077
    - type: dot_accuracy_threshold
      value: 87.66818642616272
    - type: dot_ap
      value: 73.18693800863593
    - type: dot_f1
      value: 70.40641099026904
    - type: dot_f1_threshold
      value: 85.09706258773804
    - type: dot_precision
      value: 57.74647887323944
    - type: dot_recall
      value: 90.17595307917888
    - type: euclidean_accuracy
      value: 67.6923076923077
    - type: euclidean_accuracy_threshold
      value: 49.662476778030396
    - type: euclidean_ap
      value: 73.18693800863593
    - type: euclidean_f1
      value: 70.40641099026904
    - type: euclidean_f1_threshold
      value: 54.59475517272949
    - type: euclidean_precision
      value: 57.74647887323944
    - type: euclidean_recall
      value: 90.17595307917888
    - type: main_score
      value: 73.18693800863593
    - type: manhattan_accuracy
      value: 67.54578754578755
    - type: manhattan_accuracy_threshold
      value: 777.1001815795898
    - type: manhattan_ap
      value: 72.98861474758783
    - type: manhattan_f1
      value: 70.6842435655995
    - type: manhattan_f1_threshold
      value: 810.3782653808594
    - type: manhattan_precision
      value: 61.80021953896817
    - type: manhattan_recall
      value: 82.55131964809385
    - type: max_ap
      value: 73.18693800863593
    - type: max_f1
      value: 70.6842435655995
    - type: max_precision
      value: 61.80021953896817
    - type: max_recall
      value: 90.17595307917888
    - type: similarity_accuracy
      value: 67.6923076923077
    - type: similarity_accuracy_threshold
      value: 87.6681923866272
    - type: similarity_ap
      value: 73.18693800863593
    - type: similarity_f1
      value: 70.40641099026904
    - type: similarity_f1_threshold
      value: 85.09706258773804
    - type: similarity_precision
      value: 57.74647887323944
    - type: similarity_recall
      value: 90.17595307917888
  - task:
      type: PairClassification
    dataset:
      name: MTEB XNLIV2 (russian)
      type: mteb/xnli2.0-multi-pair
      config: russian
      split: test
      revision: 5b7d477a8c62cdd18e2fed7e015497c20b4371ad
    metrics:
    - type: cosine_accuracy
      value: 68.35164835164835
    - type: cosine_accuracy_threshold
      value: 88.48621845245361
    - type: cosine_ap
      value: 73.10205506215699
    - type: cosine_f1
      value: 71.28712871287128
    - type: cosine_f1_threshold
      value: 87.00399398803711
    - type: cosine_precision
      value: 61.67023554603854
    - type: cosine_recall
      value: 84.4574780058651
    - type: dot_accuracy
      value: 68.35164835164835
    - type: dot_accuracy_threshold
      value: 88.48622441291809
    - type: dot_ap
      value: 73.10191110714706
    - type: dot_f1
      value: 71.28712871287128
    - type: dot_f1_threshold
      value: 87.00399398803711
    - type: dot_precision
      value: 61.67023554603854
    - type: dot_recall
      value: 84.4574780058651
    - type: euclidean_accuracy
      value: 68.35164835164835
    - type: euclidean_accuracy_threshold
      value: 47.98704385757446
    - type: euclidean_ap
      value: 73.10205506215699
    - type: euclidean_f1
      value: 71.28712871287128
    - type: euclidean_f1_threshold
      value: 50.982362031936646
    - type: euclidean_precision
      value: 61.67023554603854
    - type: euclidean_recall
      value: 84.4574780058651
    - type: main_score
      value: 73.10205506215699
    - type: manhattan_accuracy
      value: 67.91208791208791
    - type: manhattan_accuracy_threshold
      value: 746.1360931396484
    - type: manhattan_ap
      value: 72.8954736175069
    - type: manhattan_f1
      value: 71.1297071129707
    - type: manhattan_f1_threshold
      value: 808.0789566040039
    - type: manhattan_precision
      value: 60.04036326942482
    - type: manhattan_recall
      value: 87.2434017595308
    - type: max_ap
      value: 73.10205506215699
    - type: max_f1
      value: 71.28712871287128
    - type: max_precision
      value: 61.67023554603854
    - type: max_recall
      value: 87.2434017595308
    - type: similarity_accuracy
      value: 68.35164835164835
    - type: similarity_accuracy_threshold
      value: 88.48621845245361
    - type: similarity_ap
      value: 73.10205506215699
    - type: similarity_f1
      value: 71.28712871287128
    - type: similarity_f1_threshold
      value: 87.00399398803711
    - type: similarity_precision
      value: 61.67023554603854
    - type: similarity_recall
      value: 84.4574780058651
  - task:
      type: Retrieval
    dataset:
      name: MTEB XQuADRetrieval (ru)
      type: google/xquad
      config: ru
      split: validation
      revision: 51adfef1c1287aab1d2d91b5bead9bcfb9c68583
    metrics:
    - type: main_score
      value: 95.705
    - type: map_at_1
      value: 90.802
    - type: map_at_10
      value: 94.427
    - type: map_at_100
      value: 94.451
    - type: map_at_1000
      value: 94.451
    - type: map_at_20
      value: 94.446
    - type: map_at_3
      value: 94.121
    - type: map_at_5
      value: 94.34
    - type: mrr_at_1
      value: 90.80168776371308
    - type: mrr_at_10
      value: 94.42659567343111
    - type: mrr_at_100
      value: 94.45099347521871
    - type: mrr_at_1000
      value: 94.45099347521871
    - type: mrr_at_20
      value: 94.44574530017569
    - type: mrr_at_3
      value: 94.12095639943743
    - type: mrr_at_5
      value: 94.34036568213786
    - type: nauc_map_at_1000_diff1
      value: 87.40573202946949
    - type: nauc_map_at_1000_max
      value: 65.56220344468791
    - type: nauc_map_at_1000_std
      value: 8.865583291735863
    - type: nauc_map_at_100_diff1
      value: 87.40573202946949
    - type: nauc_map_at_100_max
      value: 65.56220344468791
    - type: nauc_map_at_100_std
      value: 8.865583291735863
    - type: nauc_map_at_10_diff1
      value: 87.43657080570291
    - type: nauc_map_at_10_max
      value: 65.71295628534446
    - type: nauc_map_at_10_std
      value: 9.055399339099655
    - type: nauc_map_at_1_diff1
      value: 88.08395824560428
    - type: nauc_map_at_1_max
      value: 62.92813192908893
    - type: nauc_map_at_1_std
      value: 6.738987385482432
    - type: nauc_map_at_20_diff1
      value: 87.40979818966589
    - type: nauc_map_at_20_max
      value: 65.59474346926105
    - type: nauc_map_at_20_std
      value: 8.944420599300914
    - type: nauc_map_at_3_diff1
      value: 86.97771892161035
    - type: nauc_map_at_3_max
      value: 66.14330030122467
    - type: nauc_map_at_3_std
      value: 8.62516327793521
    - type: nauc_map_at_5_diff1
      value: 87.30273362211798
    - type: nauc_map_at_5_max
      value: 66.1522476584607
    - type: nauc_map_at_5_std
      value: 9.780940862679724
    - type: nauc_mrr_at_1000_diff1
      value: 87.40573202946949
    - type: nauc_mrr_at_1000_max
      value: 65.56220344468791
    - type: nauc_mrr_at_1000_std
      value: 8.865583291735863
    - type: nauc_mrr_at_100_diff1
      value: 87.40573202946949
    - type: nauc_mrr_at_100_max
      value: 65.56220344468791
    - type: nauc_mrr_at_100_std
      value: 8.865583291735863
    - type: nauc_mrr_at_10_diff1
      value: 87.43657080570291
    - type: nauc_mrr_at_10_max
      value: 65.71295628534446
    - type: nauc_mrr_at_10_std
      value: 9.055399339099655
    - type: nauc_mrr_at_1_diff1
      value: 88.08395824560428
    - type: nauc_mrr_at_1_max
      value: 62.92813192908893
    - type: nauc_mrr_at_1_std
      value: 6.738987385482432
    - type: nauc_mrr_at_20_diff1
      value: 87.40979818966589
    - type: nauc_mrr_at_20_max
      value: 65.59474346926105
    - type: nauc_mrr_at_20_std
      value: 8.944420599300914
    - type: nauc_mrr_at_3_diff1
      value: 86.97771892161035
    - type: nauc_mrr_at_3_max
      value: 66.14330030122467
    - type: nauc_mrr_at_3_std
      value: 8.62516327793521
    - type: nauc_mrr_at_5_diff1
      value: 87.30273362211798
    - type: nauc_mrr_at_5_max
      value: 66.1522476584607
    - type: nauc_mrr_at_5_std
      value: 9.780940862679724
    - type: nauc_ndcg_at_1000_diff1
      value: 87.37823158814116
    - type: nauc_ndcg_at_1000_max
      value: 66.00874244792789
    - type: nauc_ndcg_at_1000_std
      value: 9.479929342875067
    - type: nauc_ndcg_at_100_diff1
      value: 87.37823158814116
    - type: nauc_ndcg_at_100_max
      value: 66.00874244792789
    - type: nauc_ndcg_at_100_std
      value: 9.479929342875067
    - type: nauc_ndcg_at_10_diff1
      value: 87.54508467181488
    - type: nauc_ndcg_at_10_max
      value: 66.88756470312894
    - type: nauc_ndcg_at_10_std
      value: 10.812624405397022
    - type: nauc_ndcg_at_1_diff1
      value: 88.08395824560428
    - type: nauc_ndcg_at_1_max
      value: 62.92813192908893
    - type: nauc_ndcg_at_1_std
      value: 6.738987385482432
    - type: nauc_ndcg_at_20_diff1
      value: 87.42097894104597
    - type: nauc_ndcg_at_20_max
      value: 66.37031898778943
    - type: nauc_ndcg_at_20_std
      value: 10.34862538094813
    - type: nauc_ndcg_at_3_diff1
      value: 86.50039907157999
    - type: nauc_ndcg_at_3_max
      value: 67.97798288917929
    - type: nauc_ndcg_at_3_std
      value: 10.162410286746852
    - type: nauc_ndcg_at_5_diff1
      value: 87.13322094568531
    - type: nauc_ndcg_at_5_max
      value: 68.08576118683821
    - type: nauc_ndcg_at_5_std
      value: 12.639637379592855
    - type: nauc_precision_at_1000_diff1
      value: 100.0
    - type: nauc_precision_at_1000_max
      value: 100.0
    - type: nauc_precision_at_1000_std
      value: 100.0
    - type: nauc_precision_at_100_diff1
      value: 100.0
    - type: nauc_precision_at_100_max
      value: 100.0
    - type: nauc_precision_at_100_std
      value: 100.0
    - type: nauc_precision_at_10_diff1
      value: 93.46711505595813
    - type: nauc_precision_at_10_max
      value: 100.0
    - type: nauc_precision_at_10_std
      value: 65.42573557179935
    - type: nauc_precision_at_1_diff1
      value: 88.08395824560428
    - type: nauc_precision_at_1_max
      value: 62.92813192908893
    - type: nauc_precision_at_1_std
      value: 6.738987385482432
    - type: nauc_precision_at_20_diff1
      value: 91.28948674127133
    - type: nauc_precision_at_20_max
      value: 100.0
    - type: nauc_precision_at_20_std
      value: 90.74278258632364
    - type: nauc_precision_at_3_diff1
      value: 82.64606115071832
    - type: nauc_precision_at_3_max
      value: 83.26201582412921
    - type: nauc_precision_at_3_std
      value: 23.334013491433762
    - type: nauc_precision_at_5_diff1
      value: 85.0867539350284
    - type: nauc_precision_at_5_max
      value: 96.57011448655484
    - type: nauc_precision_at_5_std
      value: 56.46869543426768
    - type: nauc_recall_at_1000_diff1
      value: .nan
    - type: nauc_recall_at_1000_max
      value: .nan
    - type: nauc_recall_at_1000_std
      value: .nan
    - type: nauc_recall_at_100_diff1
      value: .nan
    - type: nauc_recall_at_100_max
      value: .nan
    - type: nauc_recall_at_100_std
      value: .nan
    - type: nauc_recall_at_10_diff1
      value: 93.46711505595623
    - type: nauc_recall_at_10_max
      value: 100.0
    - type: nauc_recall_at_10_std
      value: 65.42573557180279
    - type: nauc_recall_at_1_diff1
      value: 88.08395824560428
    - type: nauc_recall_at_1_max
      value: 62.92813192908893
    - type: nauc_recall_at_1_std
      value: 6.738987385482432
    - type: nauc_recall_at_20_diff1
      value: 91.28948674127474
    - type: nauc_recall_at_20_max
      value: 100.0
    - type: nauc_recall_at_20_std
      value: 90.74278258632704
    - type: nauc_recall_at_3_diff1
      value: 82.64606115071967
    - type: nauc_recall_at_3_max
      value: 83.26201582413023
    - type: nauc_recall_at_3_std
      value: 23.334013491434007
    - type: nauc_recall_at_5_diff1
      value: 85.08675393502854
    - type: nauc_recall_at_5_max
      value: 96.57011448655487
    - type: nauc_recall_at_5_std
      value: 56.46869543426658
    - type: ndcg_at_1
      value: 90.802
    - type: ndcg_at_10
      value: 95.705
    - type: ndcg_at_100
      value: 95.816
    - type: ndcg_at_1000
      value: 95.816
    - type: ndcg_at_20
      value: 95.771
    - type: ndcg_at_3
      value: 95.11699999999999
    - type: ndcg_at_5
      value: 95.506
    - type: precision_at_1
      value: 90.802
    - type: precision_at_10
      value: 9.949
    - type: precision_at_100
      value: 1.0
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_20
      value: 4.987
    - type: precision_at_3
      value: 32.658
    - type: precision_at_5
      value: 19.781000000000002
    - type: recall_at_1
      value: 90.802
    - type: recall_at_10
      value: 99.494
    - type: recall_at_100
      value: 100.0
    - type: recall_at_1000
      value: 100.0
    - type: recall_at_20
      value: 99.747
    - type: recall_at_3
      value: 97.975
    - type: recall_at_5
      value: 98.90299999999999
---


## Multilingual-E5-small
**Disclaimer**: This model is cloned from  [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small). The only difference from the original model is `pad_token_id` in `config.json` which is corrected to `1`.

[Multilingual E5 Text Embeddings: A Technical Report](https://arxiv.org/pdf/2402.05672).
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024

This model has 12 layers and the embedding size is 384.

## Usage

Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.

```python
import torch.nn.functional as F

from torch import Tensor
from transformers import AutoTokenizer, AutoModel


def average_pool(last_hidden_states: Tensor,
                 attention_mask: Tensor) -> Tensor:
    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]


# Each input text should start with "query: " or "passage: ", even for non-English texts.
# For tasks other than retrieval, you can simply use the "query: " prefix.
input_texts = ['query: how much protein should a female eat',
               'query: 南瓜的家常做法',
               "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
               "passage: 1.清炒南瓜丝 原料:嫩南瓜半个 调料:葱、盐、白糖、鸡精 做法: 1、南瓜用刀薄薄的削去表面一层皮,用勺子刮去瓤 2、擦成细丝(没有擦菜板就用刀慢慢切成细丝) 3、锅烧热放油,入葱花煸出香味 4、入南瓜丝快速翻炒一分钟左右,放盐、一点白糖和鸡精调味出锅 2.香葱炒南瓜 原料:南瓜1只 调料:香葱、蒜末、橄榄油、盐 做法: 1、将南瓜去皮,切成片 2、油锅8成热后,将蒜末放入爆香 3、爆香后,将南瓜片放入,翻炒 4、在翻炒的同时,可以不时地往锅里加水,但不要太多 5、放入盐,炒匀 6、南瓜差不多软和绵了之后,就可以关火 7、撒入香葱,即可出锅"]

tokenizer = AutoTokenizer.from_pretrained('intfloat/multilingual-e5-small')
model = AutoModel.from_pretrained('intfloat/multilingual-e5-small')

# Tokenize the input texts
batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')

outputs = model(**batch_dict)
embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])

# normalize embeddings
embeddings = F.normalize(embeddings, p=2, dim=1)
scores = (embeddings[:2] @ embeddings[2:].T) * 100
print(scores.tolist())
```

## Supported Languages

This model is initialized from [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384)
and continually trained on a mixture of multilingual datasets.
It supports 100 languages from xlm-roberta,
but low-resource languages may see performance degradation.

## Training Details

**Initialization**: [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384)

**First stage**: contrastive pre-training with weak supervision

| Dataset                                                                                                | Weak supervision                      | # of text pairs |
|--------------------------------------------------------------------------------------------------------|---------------------------------------|-----------------|
| Filtered [mC4](https://huggingface.co/datasets/mc4)                                                    | (title, page content)                 | 1B              |
| [CC News](https://huggingface.co/datasets/intfloat/multilingual_cc_news)                               | (title, news content)                 | 400M            |
| [NLLB](https://huggingface.co/datasets/allenai/nllb)                                                   | translation pairs                     | 2.4B            |
| [Wikipedia](https://huggingface.co/datasets/intfloat/wikipedia)                                        | (hierarchical section title, passage) | 150M            |
| Filtered [Reddit](https://www.reddit.com/)                                                             | (comment, response)                   | 800M            |
| [S2ORC](https://github.com/allenai/s2orc)                                                              | (title, abstract) and citation pairs  | 100M            |
| [Stackexchange](https://stackexchange.com/)                                                            | (question, answer)                    | 50M             |
| [xP3](https://huggingface.co/datasets/bigscience/xP3)                                                  | (input prompt, response)              | 80M             |
| [Miscellaneous unsupervised SBERT data](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) | -                                     | 10M             |

**Second stage**: supervised fine-tuning

| Dataset                                                                                | Language     | # of text pairs |
|----------------------------------------------------------------------------------------|--------------|-----------------|
| [MS MARCO](https://microsoft.github.io/msmarco/)                                       | English      | 500k            |
| [NQ](https://github.com/facebookresearch/DPR)                                          | English      | 70k             |
| [Trivia QA](https://github.com/facebookresearch/DPR)                                   | English      | 60k             |
| [NLI from SimCSE](https://github.com/princeton-nlp/SimCSE)                             | English      | <300k           |
| [ELI5](https://huggingface.co/datasets/eli5)                                           | English      | 500k            |
| [DuReader Retrieval](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval) | Chinese      | 86k             |
| [KILT Fever](https://huggingface.co/datasets/kilt_tasks)                               | English      | 70k             |
| [KILT HotpotQA](https://huggingface.co/datasets/kilt_tasks)                            | English      | 70k             |
| [SQuAD](https://huggingface.co/datasets/squad)                                         | English      | 87k             |
| [Quora](https://huggingface.co/datasets/quora)                                         | English      | 150k            |
| [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi)                                                                           | 11 languages | 50k             |
| [MIRACL](https://huggingface.co/datasets/miracl/miracl)                                                                             | 16 languages | 40k             |

For all labeled datasets, we only use its training set for fine-tuning.

For other training details, please refer to our paper at [https://arxiv.org/pdf/2402.05672](https://arxiv.org/pdf/2402.05672).

## Benchmark Results on [Mr. TyDi](https://arxiv.org/abs/2108.08787)

| Model                 | Avg MRR@10 |       | ar   | bn | en | fi | id | ja | ko | ru | sw   | te | th |
|-----------------------|------------|-------|------| --- | --- | --- | --- | --- | --- | --- |------| --- | --- |
| BM25                  | 33.3       | | 36.7 | 41.3 | 15.1 | 28.8 | 38.2 | 21.7 | 28.1 | 32.9 | 39.6 | 42.4 | 41.7 |
| mDPR                  | 16.7       | | 26.0 | 25.8  | 16.2 | 11.3 | 14.6 | 18.1 | 21.9 | 18.5 | 7.3 | 10.6 | 13.5 |
| BM25 + mDPR           | 41.7       | | 49.1 | 53.5 | 28.4 | 36.5 | 45.5 | 35.5 | 36.2 | 42.7 | 40.5 | 42.0 | 49.2 |
|                       |            |
| multilingual-e5-small | 64.4       | | 71.5 | 66.3 | 54.5 | 57.7 | 63.2 | 55.4 | 54.3 | 60.8 | 65.4 | 89.1 | 70.1 |
| multilingual-e5-base  | 65.9       | | 72.3 | 65.0 | 58.5 | 60.8 | 64.9 | 56.6 | 55.8 | 62.7 | 69.0 | 86.6 | 72.7 |
| multilingual-e5-large | **70.5**   | | 77.5 | 73.2 | 60.8 | 66.8 | 68.5 | 62.5 | 61.6 | 65.8 | 72.7 | 90.2 | 76.2 |

## MTEB Benchmark Evaluation

Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results
on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).

## Support for Sentence Transformers

Below is an example for usage with sentence_transformers.
```python
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('intfloat/multilingual-e5-small')
input_texts = [
    'query: how much protein should a female eat',
    'query: 南瓜的家常做法',
    "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 i     s 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or traini     ng for a marathon. Check out the chart below to see how much protein you should be eating each day.",
    "passage: 1.清炒南瓜丝 原料:嫩南瓜半个 调料:葱、盐、白糖、鸡精 做法: 1、南瓜用刀薄薄的削去表面一层皮     ,用勺子刮去瓤 2、擦成细丝(没有擦菜板就用刀慢慢切成细丝) 3、锅烧热放油,入葱花煸出香味 4、入南瓜丝快速翻炒一分钟左右,     放盐、一点白糖和鸡精调味出锅 2.香葱炒南瓜 原料:南瓜1只 调料:香葱、蒜末、橄榄油、盐 做法: 1、将南瓜去皮,切成片 2、油     锅8成热后,将蒜末放入爆香 3、爆香后,将南瓜片放入,翻炒 4、在翻炒的同时,可以不时地往锅里加水,但不要太多 5、放入盐,炒匀      6、南瓜差不多软和绵了之后,就可以关火 7、撒入香葱,即可出锅"
]
embeddings = model.encode(input_texts, normalize_embeddings=True)
```

Package requirements

`pip install sentence_transformers~=2.2.2`

Contributors: [michaelfeil](https://huggingface.co/michaelfeil)

## FAQ

**1. Do I need to add the prefix "query: " and "passage: " to input texts?**

Yes, this is how the model is trained, otherwise you will see a performance degradation.

Here are some rules of thumb:
- Use "query: " and "passage: " correspondingly for asymmetric tasks such as passage retrieval in open QA, ad-hoc information retrieval.

- Use "query: " prefix for symmetric tasks such as semantic similarity, bitext mining, paraphrase retrieval.

- Use "query: " prefix if you want to use embeddings as features, such as linear probing classification, clustering.

**2. Why are my reproduced results slightly different from reported in the model card?**

Different versions of `transformers` and `pytorch` could cause negligible but non-zero performance differences.

**3. Why does the cosine similarity scores distribute around 0.7 to 1.0?**

This is a known and expected behavior as we use a low temperature 0.01 for InfoNCE contrastive loss.

For text embedding tasks like text retrieval or semantic similarity,
what matters is the relative order of the scores instead of the absolute values,
so this should not be an issue.

## Citation

If you find our paper or models helpful, please consider cite as follows:

```
@article{wang2024multilingual,
  title={Multilingual E5 Text Embeddings: A Technical Report},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2402.05672},
  year={2024}
}
```

## Limitations

Long texts will be truncated to at most 512 tokens.

