intfloat_multilingual-e5-small

Name: intfloat/multilingual-e5-small
License: mit

intfloat · View on Hugging Face ↗

Get this model

Download Torrent Magnet Link

Seeders: — · Leechers: —

—

Model card

The complete upstream card, rendered from this payload's README.md — the same hash-verified bytes the torrent distributes. Images and off-site links are removed; the original card on Hugging Face carries them.

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 model-index:
name: intfloat/multilingual-e5-small results:
- dataset: config: en name: MTEB AmazonCounterfactualClassification (en) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:
  - type: accuracy value: 73.79104477611939
  - type: ap value: 36.9996434842022
  - type: f1 value: 67.95453679103099 task: type: Classification
- dataset: config: de name: MTEB AmazonCounterfactualClassification (de) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:
  - type: accuracy value: 71.64882226980728
  - type: ap value: 82.11942130026586
  - type: f1 value: 69.87963421606715 task: type: Classification
- dataset: config: en-ext name: MTEB AmazonCounterfactualClassification (en-ext) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:
  - type: accuracy value: 75.8095952023988
  - type: ap value: 24.46869495579561
  - type: f1 value: 63.00108480037597 task: type: Classification
- dataset: config: ja name: MTEB AmazonCounterfactualClassification (ja) revision: e8379541af4e31359cca9fbcf4b00f2671dba205 split: test type: mteb/amazon_counterfactual metrics:
  - type: accuracy value: 64.186295503212
  - type: ap value: 15.496804690197042
  - type: f1 value: 52.07153895475031 task: type: Classification
- dataset: config: default name: MTEB AmazonPolarityClassification revision: e2d317d38cd51312af73b3d32a06d1a08b442046 split: test type: mteb/amazon_polarity metrics:
  - type: accuracy value: 88.699325
  - type: ap value: 85.27039559917269
  - type: f1 value: 88.65556295032513 task: type: Classification
- dataset: config: en name: MTEB AmazonReviewsClassification (en) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 44.69799999999999
  - type: f1 value: 43.73187348654165 task: type: Classification
- dataset: config: de name: MTEB AmazonReviewsClassification (de) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 40.245999999999995
  - type: f1 value: 39.3863530637684 task: type: Classification
- dataset: config: es name: MTEB AmazonReviewsClassification (es) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 40.394
  - type: f1 value: 39.301223469483446 task: type: Classification
- dataset: config: fr name: MTEB AmazonReviewsClassification (fr) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 38.864
  - type: f1 value: 37.97974261868003 task: type: Classification
- dataset: config: ja name: MTEB AmazonReviewsClassification (ja) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 37.682
  - type: f1 value: 37.07399369768313 task: type: Classification
- dataset: config: zh name: MTEB AmazonReviewsClassification (zh) revision: 1399c76144fd37290681b995c656ef9b2e06e26d split: test type: mteb/amazon_reviews_multi metrics:
  - type: accuracy value: 37.504
  - type: f1 value: 36.62317273874278 task: type: Classification
- dataset: config: default name: MTEB ArguAna revision: None split: test type: arguana 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: Retrieval
- dataset: config: default name: MTEB ArxivClusteringP2P revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d split: test type: mteb/arxiv-clustering-p2p metrics:
  - type: v_measure value: 39.22266660528253 task: type: Clustering
- dataset: config: default name: MTEB ArxivClusteringS2S revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 split: test type: mteb/arxiv-clustering-s2s metrics:
  - type: v_measure value: 30.79980849482483 task: type: Clustering
- dataset: config: default name: MTEB AskUbuntuDupQuestions revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 split: test type: mteb/askubuntudupquestions-reranking metrics:
  - type: map value: 57.8790068352054
  - type: mrr value: 71.78791276436706 task: type: Reranking
- dataset: config: default name: MTEB BIOSSES revision: d3fb88f8f02e40887cd149695127462bbcf29b4a split: test type: mteb/biosses-sts 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: STS
- dataset: config: de-en name: MTEB BUCC (de-en) revision: d51519689f32196a32af33b075a01d0e7c51e252 split: test type: mteb/bucc-bitext-mining 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: config: fr-en name: MTEB BUCC (fr-en) revision: d51519689f32196a32af33b075a01d0e7c51e252 split: test type: mteb/bucc-bitext-mining 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: config: ru-en name: MTEB BUCC (ru-en) revision: d51519689f32196a32af33b075a01d0e7c51e252 split: test type: mteb/bucc-bitext-mining 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: config: zh-en name: MTEB BUCC (zh-en) revision: d51519689f32196a32af33b075a01d0e7c51e252 split: test type: mteb/bucc-bitext-mining metrics:
  - type: accuracy value: 89.25750394944708
  - type: f1 value: 88.79234684921889
  - type: precision value: 88.57293312269616
  - type: recall value: 89.25750394944708 task: type: BitextMining
- dataset: config: default name: MTEB Banking77Classification revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 split: test type: mteb/banking77 metrics:
  - type: accuracy value: 79.41558441558442
  - type: f1 value: 79.25886487487219 task: type: Classification
- dataset: config: default name: MTEB BiorxivClusteringP2P revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 split: test type: mteb/biorxiv-clustering-p2p metrics:
  - type: v_measure value: 35.747820820329736 task: type: Clustering
- dataset: config: default name: MTEB BiorxivClusteringS2S revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 split: test type: mteb/biorxiv-clustering-s2s metrics:
  - type: v_measure value: 27.045143830596146 task: type: Clustering
- dataset: config: default name: MTEB CQADupstackRetrieval revision: None split: test type: BeIR/cqadupstack 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: config: default name: MTEB ClimateFEVER revision: None split: test type: climate-fever 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: config: default name: MTEB DBPedia revision: None split: test type: dbpedia-entity 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: Retrieval
- dataset: config: default name: MTEB EmotionClassification revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 split: test type: mteb/emotion metrics:
  - type: accuracy value: 42.455
  - type: f1 value: 37.59462649781862 task: type: Classification
- dataset: config: default name: MTEB FEVER revision: None split: test type: fever 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: config: default name: MTEB FiQA2018 revision: None split: test type: fiqa 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: config: default name: MTEB HotpotQA revision: None split: test type: hotpotqa 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: Retrieval
- dataset: config: default name: MTEB ImdbClassification revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 split: test type: mteb/imdb metrics:
  - type: accuracy value: 80.82239999999999
  - type: ap value: 75.65895781725314
  - type: f1 value: 80.75880969095746 task: type: Classification
- dataset: config: default name: MTEB MSMARCO revision: None split: dev type: msmarco 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: Retrieval
- dataset: config: en name: MTEB MTOPDomainClassification (en) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 91.06703146374831
  - type: f1 value: 90.86867815863172 task: type: Classification
- dataset: config: de name: MTEB MTOPDomainClassification (de) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 87.46970977740209
  - type: f1 value: 86.36832872036588 task: type: Classification
- dataset: config: es name: MTEB MTOPDomainClassification (es) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 89.26951300867245
  - type: f1 value: 88.93561193959502 task: type: Classification
- dataset: config: fr name: MTEB MTOPDomainClassification (fr) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 84.22799874725963
  - type: f1 value: 84.30490069236556 task: type: Classification
- dataset: config: hi name: MTEB MTOPDomainClassification (hi) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 86.02007888131948
  - type: f1 value: 85.39376041027991 task: type: Classification
- dataset: config: th name: MTEB MTOPDomainClassification (th) revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf split: test type: mteb/mtop_domain metrics:
  - type: accuracy value: 85.34900542495481
  - type: f1 value: 85.39859673336713 task: type: Classification
- dataset: config: en name: MTEB MTOPIntentClassification (en) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 71.078431372549
  - type: f1 value: 53.45071102002276 task: type: Classification
- dataset: config: de name: MTEB MTOPIntentClassification (de) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 65.85798816568047
  - type: f1 value: 46.53112748993529 task: type: Classification
- dataset: config: es name: MTEB MTOPIntentClassification (es) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 67.96864576384256
  - type: f1 value: 45.966703022829506 task: type: Classification
- dataset: config: fr name: MTEB MTOPIntentClassification (fr) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 61.31537738803633
  - type: f1 value: 45.52601712835461 task: type: Classification
- dataset: config: hi name: MTEB MTOPIntentClassification (hi) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 66.29616349946218
  - type: f1 value: 47.24166485726613 task: type: Classification
- dataset: config: th name: MTEB MTOPIntentClassification (th) revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba split: test type: mteb/mtop_intent metrics:
  - type: accuracy value: 67.51537070524412
  - type: f1 value: 49.463476319014276 task: type: Classification
- dataset: config: af name: MTEB MassiveIntentClassification (af) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.06792199058508
  - type: f1 value: 54.094921857502285 task: type: Classification
- dataset: config: am name: MTEB MassiveIntentClassification (am) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 51.960322797579025
  - type: f1 value: 48.547371223370945 task: type: Classification
- dataset: config: ar name: MTEB MassiveIntentClassification (ar) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 54.425016812373904
  - type: f1 value: 50.47069202054312 task: type: Classification
- dataset: config: az name: MTEB MassiveIntentClassification (az) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 59.798251513113655
  - type: f1 value: 57.05013069086648 task: type: Classification
- dataset: config: bn name: MTEB MassiveIntentClassification (bn) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 59.37794216543376
  - type: f1 value: 56.3607992649805 task: type: Classification
- dataset: config: cy name: MTEB MassiveIntentClassification (cy) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 46.56018829858777
  - type: f1 value: 43.87319715715134 task: type: Classification
- dataset: config: da name: MTEB MassiveIntentClassification (da) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 62.9724277067922
  - type: f1 value: 59.36480066245562 task: type: Classification
- dataset: config: de name: MTEB MassiveIntentClassification (de) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 62.72696704774715
  - type: f1 value: 59.143595966615855 task: type: Classification
- dataset: config: el name: MTEB MassiveIntentClassification (el) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 61.5971755211836
  - type: f1 value: 59.169445724946726 task: type: Classification
- dataset: config: en name: MTEB MassiveIntentClassification (en) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 70.29589778076665
  - type: f1 value: 67.7577001808977 task: type: Classification
- dataset: config: es name: MTEB MassiveIntentClassification (es) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 66.31136516476126
  - type: f1 value: 64.52032955983242 task: type: Classification
- dataset: config: fa name: MTEB MassiveIntentClassification (fa) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 65.54472091459314
  - type: f1 value: 61.47903120066317 task: type: Classification
- dataset: config: fi name: MTEB MassiveIntentClassification (fi) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 61.45595158036314
  - type: f1 value: 58.0891846024637 task: type: Classification
- dataset: config: fr name: MTEB MassiveIntentClassification (fr) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 65.47074646940149
  - type: f1 value: 62.84830858877575 task: type: Classification
- dataset: config: he name: MTEB MassiveIntentClassification (he) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 58.046402151983855
  - type: f1 value: 55.269074430533195 task: type: Classification
- dataset: config: hi name: MTEB MassiveIntentClassification (hi) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 64.06523201075991
  - type: f1 value: 61.35339643021369 task: type: Classification
- dataset: config: hu name: MTEB MassiveIntentClassification (hu) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 60.954942837928726
  - type: f1 value: 57.07035922704846 task: type: Classification
- dataset: config: hy name: MTEB MassiveIntentClassification (hy) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.404169468728995
  - type: f1 value: 53.94259011839138 task: type: Classification
- dataset: config: id name: MTEB MassiveIntentClassification (id) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 64.16610625420309
  - type: f1 value: 61.337103431499365 task: type: Classification
- dataset: config: is name: MTEB MassiveIntentClassification (is) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 52.262945527908535
  - type: f1 value: 49.7610691598921 task: type: Classification
- dataset: config: it name: MTEB MassiveIntentClassification (it) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 65.54472091459314
  - type: f1 value: 63.469099018440154 task: type: Classification
- dataset: config: ja name: MTEB MassiveIntentClassification (ja) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 68.22797579018157
  - type: f1 value: 64.89098471083001 task: type: Classification
- dataset: config: jv name: MTEB MassiveIntentClassification (jv) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 50.847343644922674
  - type: f1 value: 47.8536963168393 task: type: Classification
- dataset: config: ka name: MTEB MassiveIntentClassification (ka) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 48.45326160053799
  - type: f1 value: 46.370078045805556 task: type: Classification
- dataset: config: km name: MTEB MassiveIntentClassification (km) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 42.83120376597175
  - type: f1 value: 39.68948521599982 task: type: Classification
- dataset: config: kn name: MTEB MassiveIntentClassification (kn) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.5084061869536
  - type: f1 value: 53.961876160401545 task: type: Classification
- dataset: config: ko name: MTEB MassiveIntentClassification (ko) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 63.7895090786819
  - type: f1 value: 61.134223684676 task: type: Classification
- dataset: config: lv name: MTEB MassiveIntentClassification (lv) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 54.98991257565569
  - type: f1 value: 52.579862862826296 task: type: Classification
- dataset: config: ml name: MTEB MassiveIntentClassification (ml) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 61.90316072629456
  - type: f1 value: 58.203024538290336 task: type: Classification
- dataset: config: mn name: MTEB MassiveIntentClassification (mn) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.09818426361802
  - type: f1 value: 54.22718458445455 task: type: Classification
- dataset: config: ms name: MTEB MassiveIntentClassification (ms) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 58.991257565568255
  - type: f1 value: 55.84892781767421 task: type: Classification
- dataset: config: my name: MTEB MassiveIntentClassification (my) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 55.901143241425686
  - type: f1 value: 52.25264332199797 task: type: Classification
- dataset: config: nb name: MTEB MassiveIntentClassification (nb) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 61.96368527236047
  - type: f1 value: 58.927243876153454 task: type: Classification
- dataset: config: nl name: MTEB MassiveIntentClassification (nl) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 65.64223268325489
  - type: f1 value: 62.340453718379706 task: type: Classification
- dataset: config: pl name: MTEB MassiveIntentClassification (pl) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 64.52589105581708
  - type: f1 value: 61.661113187022174 task: type: Classification
- dataset: config: pt name: MTEB MassiveIntentClassification (pt) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 66.84599865501009
  - type: f1 value: 64.59342572873005 task: type: Classification
- dataset: config: ro name: MTEB MassiveIntentClassification (ro) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 60.81035642232684
  - type: f1 value: 57.5169089806797 task: type: Classification
- dataset: config: ru name: MTEB MassiveIntentClassification (ru) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 58.652238071815056
  - type: f1 value: 53.22732406426353
  - type: f1_weighted value: 57.585586737209546
  - type: main_score value: 58.652238071815056 task: type: Classification
- dataset: config: sl name: MTEB MassiveIntentClassification (sl) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 56.51647612642906
  - type: f1 value: 54.33154780100043 task: type: Classification
- dataset: config: sq name: MTEB MassiveIntentClassification (sq) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.985877605917956
  - type: f1 value: 54.46187524463802 task: type: Classification
- dataset: config: sv name: MTEB MassiveIntentClassification (sv) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 65.03026227303296
  - type: f1 value: 62.34377392877748 task: type: Classification
- dataset: config: sw name: MTEB MassiveIntentClassification (sw) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 53.567585743106925
  - type: f1 value: 50.73770655983206 task: type: Classification
- dataset: config: ta name: MTEB MassiveIntentClassification (ta) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.2595830531271
  - type: f1 value: 53.657327291708626 task: type: Classification
- dataset: config: te name: MTEB MassiveIntentClassification (te) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 57.82784129119032
  - type: f1 value: 54.82518072665301 task: type: Classification
- dataset: config: th name: MTEB MassiveIntentClassification (th) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 64.06859448554137
  - type: f1 value: 63.00185280500495 task: type: Classification
- dataset: config: tl name: MTEB MassiveIntentClassification (tl) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 58.91055817081371
  - type: f1 value: 55.54116301224262 task: type: Classification
- dataset: config: tr name: MTEB MassiveIntentClassification (tr) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 63.54404841963686
  - type: f1 value: 59.57650946030184 task: type: Classification
- dataset: config: ur name: MTEB MassiveIntentClassification (ur) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 59.27706792199059
  - type: f1 value: 56.50010066083435 task: type: Classification
- dataset: config: vi name: MTEB MassiveIntentClassification (vi) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 64.0719569603228
  - type: f1 value: 61.817075925647956 task: type: Classification
- dataset: config: zh-CN name: MTEB MassiveIntentClassification (zh-CN) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 68.23806321452591
  - type: f1 value: 65.24917026029749 task: type: Classification
- dataset: config: zh-TW name: MTEB MassiveIntentClassification (zh-TW) revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 split: test type: mteb/amazon_massive_intent metrics:
  - type: accuracy value: 62.53530598520511
  - type: f1 value: 61.71131132295768 task: type: Classification
- dataset: config: af name: MTEB MassiveScenarioClassification (af) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 63.04303967720243
  - type: f1 value: 60.3950085685985 task: type: Classification
- dataset: config: am name: MTEB MassiveScenarioClassification (am) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 56.83591123066578
  - type: f1 value: 54.95059828830849 task: type: Classification
- dataset: config: ar name: MTEB MassiveScenarioClassification (ar) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 59.62340282447881
  - type: f1 value: 59.525159996498225 task: type: Classification
- dataset: config: az name: MTEB MassiveScenarioClassification (az) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 60.85406859448555
  - type: f1 value: 59.129299095681276 task: type: Classification
- dataset: config: bn name: MTEB MassiveScenarioClassification (bn) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 62.76731674512441
  - type: f1 value: 61.159560612627715 task: type: Classification
- dataset: config: cy name: MTEB MassiveScenarioClassification (cy) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 50.181573638197705
  - type: f1 value: 46.98422176289957 task: type: Classification
- dataset: config: da name: MTEB MassiveScenarioClassification (da) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.92737054472092
  - type: f1 value: 67.69135611952979 task: type: Classification
- dataset: config: de name: MTEB MassiveScenarioClassification (de) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 69.18964357767318
  - type: f1 value: 68.46106138186214 task: type: Classification
- dataset: config: el name: MTEB MassiveScenarioClassification (el) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 67.0712844653665
  - type: f1 value: 66.75545422473901 task: type: Classification
- dataset: config: en name: MTEB MassiveScenarioClassification (en) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 74.4754539340955
  - type: f1 value: 74.38427146553252 task: type: Classification
- dataset: config: es name: MTEB MassiveScenarioClassification (es) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 69.82515131136518
  - type: f1 value: 69.63516462173847 task: type: Classification
- dataset: config: fa name: MTEB MassiveScenarioClassification (fa) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.70880968392737
  - type: f1 value: 67.45420662567926 task: type: Classification
- dataset: config: fi name: MTEB MassiveScenarioClassification (fi) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 65.95494283792871
  - type: f1 value: 65.06191009049222 task: type: Classification
- dataset: config: fr name: MTEB MassiveScenarioClassification (fr) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.75924680564896
  - type: f1 value: 68.30833379585945 task: type: Classification
- dataset: config: he name: MTEB MassiveScenarioClassification (he) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 63.806321452589096
  - type: f1 value: 63.273048243765054 task: type: Classification
- dataset: config: hi name: MTEB MassiveScenarioClassification (hi) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 67.68997982515133
  - type: f1 value: 66.54703855381324 task: type: Classification
- dataset: config: hu name: MTEB MassiveScenarioClassification (hu) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 66.46940147948891
  - type: f1 value: 65.91017343463396 task: type: Classification
- dataset: config: hy name: MTEB MassiveScenarioClassification (hy) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 59.49899125756556
  - type: f1 value: 57.90333469917769 task: type: Classification
- dataset: config: id name: MTEB MassiveScenarioClassification (id) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 67.9219905850706
  - type: f1 value: 67.23169403762938 task: type: Classification
- dataset: config: is name: MTEB MassiveScenarioClassification (is) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 56.486213853396094
  - type: f1 value: 54.85282355583758 task: type: Classification
- dataset: config: it name: MTEB MassiveScenarioClassification (it) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 69.04169468728985
  - type: f1 value: 68.83833333320462 task: type: Classification
- dataset: config: ja name: MTEB MassiveScenarioClassification (ja) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 73.88702084734365
  - type: f1 value: 74.04474735232299 task: type: Classification
- dataset: config: jv name: MTEB MassiveScenarioClassification (jv) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 56.63416274377943
  - type: f1 value: 55.11332211687954 task: type: Classification
- dataset: config: ka name: MTEB MassiveScenarioClassification (ka) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 52.23604572965702
  - type: f1 value: 50.86529813991055 task: type: Classification
- dataset: config: km name: MTEB MassiveScenarioClassification (km) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 46.62407531943511
  - type: f1 value: 43.63485467164535 task: type: Classification
- dataset: config: kn name: MTEB MassiveScenarioClassification (kn) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 59.15601882985878
  - type: f1 value: 57.522837510959924 task: type: Classification
- dataset: config: ko name: MTEB MassiveScenarioClassification (ko) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 69.84532616005382
  - type: f1 value: 69.60021127179697 task: type: Classification
- dataset: config: lv name: MTEB MassiveScenarioClassification (lv) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 56.65770006724949
  - type: f1 value: 55.84219135523227 task: type: Classification
- dataset: config: ml name: MTEB MassiveScenarioClassification (ml) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 66.53665097511768
  - type: f1 value: 65.09087787792639 task: type: Classification
- dataset: config: mn name: MTEB MassiveScenarioClassification (mn) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 59.31405514458642
  - type: f1 value: 58.06135303831491 task: type: Classification
- dataset: config: ms name: MTEB MassiveScenarioClassification (ms) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 64.88231338264964
  - type: f1 value: 62.751099407787926 task: type: Classification
- dataset: config: my name: MTEB MassiveScenarioClassification (my) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 58.86012104909213
  - type: f1 value: 56.29118323058282 task: type: Classification
- dataset: config: nb name: MTEB MassiveScenarioClassification (nb) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 67.37390719569602
  - type: f1 value: 66.27922244885102 task: type: Classification
- dataset: config: nl name: MTEB MassiveScenarioClassification (nl) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 70.8675184936113
  - type: f1 value: 70.22146529932019 task: type: Classification
- dataset: config: pl name: MTEB MassiveScenarioClassification (pl) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.2212508406187
  - type: f1 value: 67.77454802056282 task: type: Classification
- dataset: config: pt name: MTEB MassiveScenarioClassification (pt) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.18090114324143
  - type: f1 value: 68.03737625431621 task: type: Classification
- dataset: config: ro name: MTEB MassiveScenarioClassification (ro) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 64.65030262273034
  - type: f1 value: 63.792945486912856 task: type: Classification
- dataset: config: ru name: MTEB MassiveScenarioClassification (ru) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 63.772749631087066
  - type: f1 value: 63.4539101720024
  - type: f1_weighted value: 62.778603897469566
  - type: main_score value: 63.772749631087066 task: type: Classification
- dataset: config: sl name: MTEB MassiveScenarioClassification (sl) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 60.17821116341627
  - type: f1 value: 59.3935969827171 task: type: Classification
- dataset: config: sq name: MTEB MassiveScenarioClassification (sq) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 62.86146603900471
  - type: f1 value: 60.133692735032376 task: type: Classification
- dataset: config: sv name: MTEB MassiveScenarioClassification (sv) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 70.89441829186282
  - type: f1 value: 70.03064076194089 task: type: Classification
- dataset: config: sw name: MTEB MassiveScenarioClassification (sw) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 58.15063887020847
  - type: f1 value: 56.23326278499678 task: type: Classification
- dataset: config: ta name: MTEB MassiveScenarioClassification (ta) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 59.43846671149966
  - type: f1 value: 57.70440450281974 task: type: Classification
- dataset: config: te name: MTEB MassiveScenarioClassification (te) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 60.8507061197041
  - type: f1 value: 59.22916396061171 task: type: Classification
- dataset: config: th name: MTEB MassiveScenarioClassification (th) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 70.65568258238063
  - type: f1 value: 69.90736239440633 task: type: Classification
- dataset: config: tl name: MTEB MassiveScenarioClassification (tl) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 60.8843308675185
  - type: f1 value: 59.30332663713599 task: type: Classification
- dataset: config: tr name: MTEB MassiveScenarioClassification (tr) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.05312710154674
  - type: f1 value: 67.44024062594775 task: type: Classification
- dataset: config: ur name: MTEB MassiveScenarioClassification (ur) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 62.111634162743776
  - type: f1 value: 60.89083013084519 task: type: Classification
- dataset: config: vi name: MTEB MassiveScenarioClassification (vi) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 67.44115669132482
  - type: f1 value: 67.92227541674552 task: type: Classification
- dataset: config: zh-CN name: MTEB MassiveScenarioClassification (zh-CN) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 74.4687289845326
  - type: f1 value: 74.16376793486025 task: type: Classification
- dataset: config: zh-TW name: MTEB MassiveScenarioClassification (zh-TW) revision: 7d571f92784cd94a019292a1f45445077d0ef634 split: test type: mteb/amazon_massive_scenario metrics:
  - type: accuracy value: 68.31876260928043
  - type: f1 value: 68.5246745215607 task: type: Classification
- dataset: config: default name: MTEB MedrxivClusteringP2P revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 split: test type: mteb/medrxiv-clustering-p2p metrics:
  - type: v_measure value: 30.90431696479766 task: type: Clustering
- dataset: config: default name: MTEB MedrxivClusteringS2S revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 split: test type: mteb/medrxiv-clustering-s2s metrics:
  - type: v_measure value: 27.259158476693774 task: type: Clustering
- dataset: config: default name: MTEB MindSmallReranking revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 split: test type: mteb/mind_small metrics:
  - type: map value: 30.28445330838555
  - type: mrr value: 31.15758529581164 task: type: Reranking
- dataset: config: default name: MTEB NFCorpus revision: None split: test type: nfcorpus 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: config: default name: MTEB NQ revision: None split: test type: nq 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: config: default name: MTEB QuoraRetrieval revision: None split: test type: quora 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: Retrieval
- dataset: config: default name: MTEB RedditClustering revision: 24640382cdbf8abc73003fb0fa6d111a705499eb split: test type: mteb/reddit-clustering metrics:
  - type: v_measure value: 39.13064340585255 task: type: Clustering
- dataset: config: default name: MTEB RedditClusteringP2P revision: 282350215ef01743dc01b456c7f5241fa8937f16 split: test type: mteb/reddit-clustering-p2p metrics:
  - type: v_measure value: 58.97884249325877 task: type: Clustering
- dataset: config: default name: MTEB SCIDOCS revision: None split: test type: scidocs 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: Retrieval
- dataset: config: default name: MTEB SICK-R revision: a6ea5a8cab320b040a23452cc28066d9beae2cee split: test type: mteb/sickr-sts 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: config: default name: MTEB STS12 revision: a0d554a64d88156834ff5ae9920b964011b16384 split: test type: mteb/sts12-sts 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: config: default name: MTEB STS13 revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca split: test type: mteb/sts13-sts 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: config: default name: MTEB STS14 revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 split: test type: mteb/sts14-sts 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: config: default name: MTEB STS15 revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 split: test type: mteb/sts15-sts 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: config: default name: MTEB STS16 revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 split: test type: mteb/sts16-sts 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: config: ko-ko name: MTEB STS17 (ko-ko) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: ar-ar name: MTEB STS17 (ar-ar) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: en-ar name: MTEB STS17 (en-ar) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: en-de name: MTEB STS17 (en-de) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: en-en name: MTEB STS17 (en-en) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: en-tr name: MTEB STS17 (en-tr) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: es-en name: MTEB STS17 (es-en) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: es-es name: MTEB STS17 (es-es) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: fr-en name: MTEB STS17 (fr-en) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: it-en name: MTEB STS17 (it-en) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: nl-en name: MTEB STS17 (nl-en) revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d split: test type: mteb/sts17-crosslingual-sts 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: config: en name: MTEB STS22 (en) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: de name: MTEB STS22 (de) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: es name: MTEB STS22 (es) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: pl name: MTEB STS22 (pl) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: tr name: MTEB STS22 (tr) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: ar name: MTEB STS22 (ar) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: ru name: MTEB STS22 (ru) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: zh name: MTEB STS22 (zh) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: fr name: MTEB STS22 (fr) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: de-en name: MTEB STS22 (de-en) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: es-en name: MTEB STS22 (es-en) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: it name: MTEB STS22 (it) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: pl-en name: MTEB STS22 (pl-en) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: zh-en name: MTEB STS22 (zh-en) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: es-it name: MTEB STS22 (es-it) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: de-fr name: MTEB STS22 (de-fr) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: de-pl name: MTEB STS22 (de-pl) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: fr-pl name: MTEB STS22 (fr-pl) revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 split: test type: mteb/sts22-crosslingual-sts 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: config: default name: MTEB STSBenchmark revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 split: test type: mteb/stsbenchmark-sts 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: STS
- dataset: config: default name: MTEB SciDocsRR revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab split: test type: mteb/scidocs-reranking metrics:
  - type: map value: 78.12945623123957
  - type: mrr value: 93.87738713719106 task: type: Reranking
- dataset: config: default name: MTEB SciFact revision: None split: test type: scifact 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: Retrieval
- dataset: config: default name: MTEB SprintDuplicateQuestions revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 split: test type: mteb/sprintduplicatequestions-pairclassification 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: PairClassification
- dataset: config: default name: MTEB StackExchangeClustering revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 split: test type: mteb/stackexchange-clustering metrics:
  - type: v_measure value: 53.52464042600003 task: type: Clustering
- dataset: config: default name: MTEB StackExchangeClusteringP2P revision: 815ca46b2622cec33ccafc3735d572c266efdb44 split: test type: mteb/stackexchange-clustering-p2p metrics:
  - type: v_measure value: 32.071631948736 task: type: Clustering
- dataset: config: default name: MTEB StackOverflowDupQuestions revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 split: test type: mteb/stackoverflowdupquestions-reranking metrics:
  - type: map value: 49.19552407604654
  - type: mrr value: 49.95269130379425 task: type: Reranking
- dataset: config: default name: MTEB SummEval revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c split: test type: mteb/summeval 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: Summarization
- dataset: config: default name: MTEB TRECCOVID revision: None split: test type: trec-covid 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: Retrieval
- dataset: config: sqi-eng name: MTEB Tatoeba (sqi-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: fry-eng name: MTEB Tatoeba (fry-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kur-eng name: MTEB Tatoeba (kur-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tur-eng name: MTEB Tatoeba (tur-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: deu-eng name: MTEB Tatoeba (deu-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: nld-eng name: MTEB Tatoeba (nld-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ron-eng name: MTEB Tatoeba (ron-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ang-eng name: MTEB Tatoeba (ang-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ido-eng name: MTEB Tatoeba (ido-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: jav-eng name: MTEB Tatoeba (jav-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: isl-eng name: MTEB Tatoeba (isl-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: slv-eng name: MTEB Tatoeba (slv-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cym-eng name: MTEB Tatoeba (cym-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kaz-eng name: MTEB Tatoeba (kaz-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: est-eng name: MTEB Tatoeba (est-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: heb-eng name: MTEB Tatoeba (heb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: gla-eng name: MTEB Tatoeba (gla-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: mar-eng name: MTEB Tatoeba (mar-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: lat-eng name: MTEB Tatoeba (lat-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: bel-eng name: MTEB Tatoeba (bel-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: pms-eng name: MTEB Tatoeba (pms-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: gle-eng name: MTEB Tatoeba (gle-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: pes-eng name: MTEB Tatoeba (pes-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: nob-eng name: MTEB Tatoeba (nob-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: bul-eng name: MTEB Tatoeba (bul-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cbk-eng name: MTEB Tatoeba (cbk-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: hun-eng name: MTEB Tatoeba (hun-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: uig-eng name: MTEB Tatoeba (uig-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: rus-eng name: MTEB Tatoeba (rus-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: spa-eng name: MTEB Tatoeba (spa-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: hye-eng name: MTEB Tatoeba (hye-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tel-eng name: MTEB Tatoeba (tel-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: afr-eng name: MTEB Tatoeba (afr-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: mon-eng name: MTEB Tatoeba (mon-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: arz-eng name: MTEB Tatoeba (arz-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: hrv-eng name: MTEB Tatoeba (hrv-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: nov-eng name: MTEB Tatoeba (nov-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: gsw-eng name: MTEB Tatoeba (gsw-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: nds-eng name: MTEB Tatoeba (nds-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ukr-eng name: MTEB Tatoeba (ukr-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: uzb-eng name: MTEB Tatoeba (uzb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: lit-eng name: MTEB Tatoeba (lit-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ina-eng name: MTEB Tatoeba (ina-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: lfn-eng name: MTEB Tatoeba (lfn-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: zsm-eng name: MTEB Tatoeba (zsm-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ita-eng name: MTEB Tatoeba (ita-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cmn-eng name: MTEB Tatoeba (cmn-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: lvs-eng name: MTEB Tatoeba (lvs-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: glg-eng name: MTEB Tatoeba (glg-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ceb-eng name: MTEB Tatoeba (ceb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: bre-eng name: MTEB Tatoeba (bre-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ben-eng name: MTEB Tatoeba (ben-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: swg-eng name: MTEB Tatoeba (swg-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: arq-eng name: MTEB Tatoeba (arq-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kab-eng name: MTEB Tatoeba (kab-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: fra-eng name: MTEB Tatoeba (fra-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: por-eng name: MTEB Tatoeba (por-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tat-eng name: MTEB Tatoeba (tat-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: oci-eng name: MTEB Tatoeba (oci-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: pol-eng name: MTEB Tatoeba (pol-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: war-eng name: MTEB Tatoeba (war-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: aze-eng name: MTEB Tatoeba (aze-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: vie-eng name: MTEB Tatoeba (vie-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: nno-eng name: MTEB Tatoeba (nno-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cha-eng name: MTEB Tatoeba (cha-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: mhr-eng name: MTEB Tatoeba (mhr-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: dan-eng name: MTEB Tatoeba (dan-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ell-eng name: MTEB Tatoeba (ell-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: amh-eng name: MTEB Tatoeba (amh-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: pam-eng name: MTEB Tatoeba (pam-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: hsb-eng name: MTEB Tatoeba (hsb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: srp-eng name: MTEB Tatoeba (srp-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: epo-eng name: MTEB Tatoeba (epo-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kzj-eng name: MTEB Tatoeba (kzj-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: awa-eng name: MTEB Tatoeba (awa-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: fao-eng name: MTEB Tatoeba (fao-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: mal-eng name: MTEB Tatoeba (mal-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ile-eng name: MTEB Tatoeba (ile-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: bos-eng name: MTEB Tatoeba (bos-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cor-eng name: MTEB Tatoeba (cor-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: cat-eng name: MTEB Tatoeba (cat-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: eus-eng name: MTEB Tatoeba (eus-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: yue-eng name: MTEB Tatoeba (yue-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: swe-eng name: MTEB Tatoeba (swe-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: dtp-eng name: MTEB Tatoeba (dtp-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kat-eng name: MTEB Tatoeba (kat-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: jpn-eng name: MTEB Tatoeba (jpn-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: csb-eng name: MTEB Tatoeba (csb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: xho-eng name: MTEB Tatoeba (xho-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: orv-eng name: MTEB Tatoeba (orv-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ind-eng name: MTEB Tatoeba (ind-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tuk-eng name: MTEB Tatoeba (tuk-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: max-eng name: MTEB Tatoeba (max-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: swh-eng name: MTEB Tatoeba (swh-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: hin-eng name: MTEB Tatoeba (hin-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: dsb-eng name: MTEB Tatoeba (dsb-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ber-eng name: MTEB Tatoeba (ber-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tam-eng name: MTEB Tatoeba (tam-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: slk-eng name: MTEB Tatoeba (slk-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tgl-eng name: MTEB Tatoeba (tgl-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ast-eng name: MTEB Tatoeba (ast-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: mkd-eng name: MTEB Tatoeba (mkd-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: khm-eng name: MTEB Tatoeba (khm-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ces-eng name: MTEB Tatoeba (ces-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tzl-eng name: MTEB Tatoeba (tzl-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: urd-eng name: MTEB Tatoeba (urd-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: ara-eng name: MTEB Tatoeba (ara-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: kor-eng name: MTEB Tatoeba (kor-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: yid-eng name: MTEB Tatoeba (yid-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: fin-eng name: MTEB Tatoeba (fin-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: tha-eng name: MTEB Tatoeba (tha-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining 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: config: wuu-eng name: MTEB Tatoeba (wuu-eng) revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 split: test type: mteb/tatoeba-bitext-mining metrics:
  - type: accuracy value: 74.3
  - type: f1 value: 69.05085581085581
  - type: precision value: 66.955
  - type: recall value: 74.3 task: type: BitextMining
- dataset: config: default name: MTEB Touche2020 revision: None split: test type: webis-touche2020 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: Retrieval
- dataset: config: default name: MTEB ToxicConversationsClassification revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c split: test type: mteb/toxic_conversations_50k metrics:
  - type: accuracy value: 69.3874
  - type: ap value: 13.829909072469423
  - type: f1 value: 53.54534203543492 task: type: Classification
- dataset: config: default name: MTEB TweetSentimentExtractionClassification revision: d604517c81ca91fe16a244d1248fc021f9ecee7a split: test type: mteb/tweet_sentiment_extraction metrics:
  - type: accuracy value: 62.62026032823995
  - type: f1 value: 62.85251350485221 task: type: Classification
- dataset: config: default name: MTEB TwentyNewsgroupsClustering revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 split: test type: mteb/twentynewsgroups-clustering metrics:
  - type: v_measure value: 33.21527881409797 task: type: Clustering
- dataset: config: default name: MTEB TwitterSemEval2015 revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 split: test type: mteb/twittersemeval2015-pairclassification 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: config: default name: MTEB TwitterURLCorpus revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf split: test type: mteb/twitterurlcorpus-pairclassification 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: PairClassification
- dataset: config: ru-en name: MTEB BUCC.v2 (ru-en) revision: 1739dc11ffe9b7bfccd7f3d585aeb4c544fc6677 split: test type: mteb/bucc-bitext-mining 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: BitextMining
- dataset: config: rus_Cyrl-rus_Cyrl name: MTEB BelebeleRetrieval (rus_Cyrl-rus_Cyrl) revision: 75b399394a9803252cfec289d103de462763db7c split: test type: facebook/belebele 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
  - type: nauc_map_at_20_std 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 value: 92.37373187280554
  - type: nauc_mrr_at_1000_max value: 79.90465445423249
  - 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 value: 79.86831935337598
  - type: nauc_mrr_at_10_std value: -0.7455191860719699
  - type: nauc_mrr_at_1_diff1 value: 93.29828518358822
  - type: nauc_mrr_at_1_max value: 78.69539619887887
  - type: nauc_mrr_at_1_std value: -4.097150817605763
  - type: nauc_mrr_at_20_diff1 value: 92.38414149703077
  - type: nauc_mrr_at_20_max value: 79.94789814504661
  - type: nauc_mrr_at_20_std value: -0.3928031130400773
  - 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 value: 80.29207038703142
  - 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 value: 93.29828518358822
  - type: nauc_ndcg_at_1_max value: 78.69539619887887
  - type: nauc_ndcg_at_1_std value: -4.097150817605763
  - 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 value: 84.35075179497126
  - type: nauc_precision_at_3_std value: 12.036768730480507
  - type: nauc_precision_at_5_diff1 value: 90.44234360410769
  - type: nauc_precision_at_5_max value: 83.21895424836558
  - type: nauc_precision_at_5_std value: 9.974323062558037
  - 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: 93.46405228758294
  - type: nauc_recall_at_100_max value: 100.0
  - type: nauc_recall_at_100_std value: 70.71661998132666
  - type: nauc_recall_at_10_diff1 value: 90.13938908896864
  - type: nauc_recall_at_10_max value: 82.21121782046124
  - type: nauc_recall_at_10_std value: 13.075230092036506
  - type: nauc_recall_at_1_diff1 value: 93.29828518358822
  - type: nauc_recall_at_1_max value: 78.69539619887887
  - type: nauc_recall_at_1_std value: -4.097150817605763
  - type: nauc_recall_at_20_diff1 value: 94.97234791352489
  - type: nauc_recall_at_20_max value: 91.04000574588774
  - type: nauc_recall_at_20_std value: 48.764634058752065
  - type: nauc_recall_at_3_diff1 value: 90.52690041533845
  - type: nauc_recall_at_3_max value: 84.35075179497079
  - type: nauc_recall_at_3_std value: 12.036768730480583
  - type: nauc_recall_at_5_diff1 value: 90.44234360410861
  - type: nauc_recall_at_5_max value: 83.21895424836595
  - type: nauc_recall_at_5_std value: 9.974323062558147
  - type: ndcg_at_1 value: 87.111
  - type: ndcg_at_10 value: 92.23599999999999
  - type: ndcg_at_100 value: 92.87100000000001
  - type: ndcg_at_1000 value: 92.928
  - type: ndcg_at_20 value: 92.67699999999999
  - type: ndcg_at_3 value: 90.973
  - type: ndcg_at_5 value: 91.801
  - type: precision_at_1 value: 87.111
  - type: precision_at_10 value: 9.689
  - type: precision_at_100 value: 0.996
  - type: precision_at_1000 value: 0.1
  - type: precision_at_20 value: 4.928
  - type: precision_at_3 value: 31.185000000000002
  - type: precision_at_5 value: 19.111
  - type: recall_at_1 value: 87.111
  - type: recall_at_10 value: 96.88900000000001
  - type: recall_at_100 value: 99.556
  - type: recall_at_1000 value: 100.0
  - type: recall_at_20 value: 98.556
  - type: recall_at_3 value: 93.556
  - type: recall_at_5 value: 95.556 task: type: Retrieval
- dataset: config: rus_Cyrl-eng_Latn name: MTEB BelebeleRetrieval (rus_Cyrl-eng_Latn) revision: 75b399394a9803252cfec289d103de462763db7c split: test type: facebook/belebele metrics:
  - type: main_score value: 86.615
  - type: map_at_1 value: 78.0
  - type: map_at_10 value: 83.822
  - type: map_at_100 value: 84.033
  - type: map_at_1000 value: 84.03500000000001
  - type: map_at_20 value: 83.967
  - type: map_at_3 value: 82.315
  - type: map_at_5 value: 83.337
  - type: mrr_at_1 value: 78.0
  - type: mrr_at_10 value: 83.82213403880073
  - type: mrr_at_100 value: 84.03281327810801
  - type: mrr_at_1000 value: 84.03460051000452
  - type: mrr_at_20 value: 83.9673773122303
  - type: mrr_at_3 value: 82.31481481481484
  - type: mrr_at_5 value: 83.33703703703708
  - type: nauc_map_at_1000_diff1 value: 80.78467576987832
  - type: nauc_map_at_1000_max value: 51.41718334647604
  - type: nauc_map_at_1000_std value: -16.23873782768812
  - type: nauc_map_at_100_diff1 value: 80.78490931240695
  - type: nauc_map_at_100_max value: 51.41504597713061
  - type: nauc_map_at_100_std value: -16.23538559475366
  - type: nauc_map_at_10_diff1 value: 80.73989245374868
  - type: nauc_map_at_10_max value: 51.43026079433827
  - type: nauc_map_at_10_std value: -16.13414330905897
  - type: nauc_map_at_1_diff1 value: 82.36966971144186
  - type: nauc_map_at_1_max value: 52.988877039509916
  - type: nauc_map_at_1_std value: -15.145824639495546
  - type: nauc_map_at_20_diff1 value: 80.75923781626145
  - type: nauc_map_at_20_max value: 51.40181079374639
  - type: nauc_map_at_20_std value: -16.260566097377165
  - type: nauc_map_at_3_diff1 value: 80.65242627065471
  - type: nauc_map_at_3_max value: 50.623980338841214
  - type: nauc_map_at_3_std value: -16.818343442794294
  - type: nauc_map_at_5_diff1 value: 80.45976387021862
  - type: nauc_map_at_5_max value: 51.533621728445866
  - type: nauc_map_at_5_std value: -16.279891536945815
  - type: nauc_mrr_at_1000_diff1 value: 80.78467576987832
  - type: nauc_mrr_at_1000_max value: 51.41718334647604
  - type: nauc_mrr_at_1000_std value: -16.23873782768812
  - type: nauc_mrr_at_100_diff1 value: 80.78490931240695
  - type: nauc_mrr_at_100_max value: 51.41504597713061
  - type: nauc_mrr_at_100_std value: -16.23538559475366
  - type: nauc_mrr_at_10_diff1 value: 80.73989245374868
  - type: nauc_mrr_at_10_max value: 51.43026079433827
  - type: nauc_mrr_at_10_std value: -16.13414330905897
  - type: nauc_mrr_at_1_diff1 value: 82.36966971144186
  - type: nauc_mrr_at_1_max value: 52.988877039509916
  - type: nauc_mrr_at_1_std value: -15.145824639495546
  - type: nauc_mrr_at_20_diff1 value: 80.75923781626145
  - type: nauc_mrr_at_20_max value: 51.40181079374639
  - type: nauc_mrr_at_20_std value: -16.260566097377165
  - type: nauc_mrr_at_3_diff1 value: 80.65242627065471
  - type: nauc_mrr_at_3_max value: 50.623980338841214
  - type: nauc_mrr_at_3_std value: -16.818343442794294
  - type: nauc_mrr_at_5_diff1 value: 80.45976387021862
  - type: nauc_mrr_at_5_max value: 51.533621728445866
  - type: nauc_mrr_at_5_std value: -16.279891536945815
  - type: nauc_ndcg_at_1000_diff1 value: 80.60009446938174
  - type: nauc_ndcg_at_1000_max value: 51.381708043594166
  - type: nauc_ndcg_at_1000_std value: -16.054256944160848
  - type: nauc_ndcg_at_100_diff1 value: 80.58971462930421
  - type: nauc_ndcg_at_100_max value: 51.25436917735444
  - type: nauc_ndcg_at_100_std value: -15.862944972269894
  - type: nauc_ndcg_at_10_diff1 value: 80.37967179454489
  - type: nauc_ndcg_at_10_max value: 51.590394257251006
  - type: nauc_ndcg_at_10_std value: -15.489799384799591
  - type: nauc_ndcg_at_1_diff1 value: 82.36966971144186
  - type: nauc_ndcg_at_1_max value: 52.988877039509916
  - type: nauc_ndcg_at_1_std value: -15.145824639495546
  - type: nauc_ndcg_at_20_diff1 value: 80.40299527470081
  - type: nauc_ndcg_at_20_max value: 51.395132284307074
  - type: nauc_ndcg_at_20_std value: -15.906165526937203
  - type: nauc_ndcg_at_3_diff1 value: 80.10347913649302
  - type: nauc_ndcg_at_3_max value: 50.018431855573844
  - type: nauc_ndcg_at_3_std value: -17.12743750163884
  - type: nauc_ndcg_at_5_diff1 value: 79.65918647776613
  - type: nauc_ndcg_at_5_max value: 51.76710880330806
  - type: nauc_ndcg_at_5_std value: -16.071901882035945
  - 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: 77.41596638655459
  - type: nauc_precision_at_100_max value: 22.572362278246565
  - type: nauc_precision_at_100_std value: 26.890756302525716
  - type: nauc_precision_at_10_diff1 value: 77.82112845138009
  - type: nauc_precision_at_10_max value: 54.2550353474723
  - type: nauc_precision_at_10_std value: -7.492997198879646
  - type: nauc_precision_at_1_diff1 value: 82.36966971144186
  - type: nauc_precision_at_1_max value: 52.988877039509916
  - type: nauc_precision_at_1_std value: -15.145824639495546
  - type: nauc_precision_at_20_diff1 value: 75.89091192032318
  - type: nauc_precision_at_20_max value: 52.03275754746293
  - type: nauc_precision_at_20_std value: -7.8411920323686175
  - type: nauc_precision_at_3_diff1 value: 78.0256020644638
  - type: nauc_precision_at_3_max value: 47.80353641248523
  - type: nauc_precision_at_3_std value: -18.181625255723503
  - type: nauc_precision_at_5_diff1 value: 75.21583976056174
  - type: nauc_precision_at_5_max value: 53.716281032960765
  - type: nauc_precision_at_5_std value: -14.411700753360812
  - 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: 77.4159663865523
  - type: nauc_recall_at_100_max value: 22.57236227824646
  - type: nauc_recall_at_100_std value: 26.89075630252133
  - type: nauc_recall_at_10_diff1 value: 77.82112845138037
  - type: nauc_recall_at_10_max value: 54.25503534747204
  - type: nauc_recall_at_10_std value: -7.492997198879666
  - type: nauc_recall_at_1_diff1 value: 82.36966971144186
  - type: nauc_recall_at_1_max value: 52.988877039509916
  - type: nauc_recall_at_1_std value: -15.145824639495546
  - type: nauc_recall_at_20_diff1 value: 75.89091192032362
  - type: nauc_recall_at_20_max value: 52.032757547463184
  - type: nauc_recall_at_20_std value: -7.84119203236888
  - type: nauc_recall_at_3_diff1 value: 78.02560206446354
  - type: nauc_recall_at_3_max value: 47.80353641248526
  - type: nauc_recall_at_3_std value: -18.181625255723656
  - type: nauc_recall_at_5_diff1 value: 75.21583976056185
  - type: nauc_recall_at_5_max value: 53.71628103296118
  - type: nauc_recall_at_5_std value: -14.411700753360634
  - type: ndcg_at_1 value: 78.0
  - type: ndcg_at_10 value: 86.615
  - type: ndcg_at_100 value: 87.558
  - type: ndcg_at_1000 value: 87.613
  - type: ndcg_at_20 value: 87.128
  - type: ndcg_at_3 value: 83.639
  - type: ndcg_at_5 value: 85.475
  - type: precision_at_1 value: 78.0
  - type: precision_at_10 value: 9.533
  - type: precision_at_100 value: 0.996
  - type: precision_at_1000 value: 0.1
  - type: precision_at_20 value: 4.867
  - type: precision_at_3 value: 29.148000000000003
  - type: precision_at_5 value: 18.378
  - type: recall_at_1 value: 78.0
  - type: recall_at_10 value: 95.333
  - type: recall_at_100 value: 99.556
  - type: recall_at_1000 value: 100.0
  - type: recall_at_20 value: 97.333
  - type: recall_at_3 value: 87.444
  - type: recall_at_5 value: 91.889 task: type: Retrieval
- dataset: config: eng_Latn-rus_Cyrl name: MTEB BelebeleRetrieval (eng_Latn-rus_Cyrl) revision: 75b399394a9803252cfec289d103de462763db7c split: test type: facebook/belebele metrics:
  - type: main_score value: 82.748
  - type: map_at_1 value: 73.444
  - type: map_at_10 value: 79.857
  - type: map_at_100 value: 80.219
  - type: map_at_1000 value: 80.22500000000001
  - type: map_at_20 value: 80.10300000000001
  - type: map_at_3 value: 78.593
  - type: map_at_5 value: 79.515
  - type: mrr_at_1 value: 73.44444444444444
  - type: mrr_at_10 value: 79.85705467372136
  - type: mrr_at_100 value: 80.21942320422542
  - type: mrr_at_1000 value: 80.2245364027152
  - type: mrr_at_20 value: 80.10273201266493
  - type: mrr_at_3 value: 78.59259259259258
  - type: mrr_at_5 value: 79.51481481481483
  - type: nauc_map_at_1000_diff1 value: 83.69682652271125
  - type: nauc_map_at_1000_max value: 61.70131708044767
  - type: nauc_map_at_1000_std value: 9.345825405274955
  - type: nauc_map_at_100_diff1 value: 83.68924820523492
  - type: nauc_map_at_100_max value: 61.6965735573098
  - type: nauc_map_at_100_std value: 9.366132859525775
  - type: nauc_map_at_10_diff1 value: 83.61802964269985
  - type: nauc_map_at_10_max value: 61.74274476167882
  - type: nauc_map_at_10_std value: 9.504060995819101
  - type: nauc_map_at_1_diff1 value: 86.37079221403225
  - type: nauc_map_at_1_max value: 61.856861655370686
  - type: nauc_map_at_1_std value: 4.708911881992707
  - type: nauc_map_at_20_diff1 value: 83.62920965453047
  - type: nauc_map_at_20_max value: 61.761029350326965
  - type: nauc_map_at_20_std value: 9.572978651118351
  - type: nauc_map_at_3_diff1 value: 83.66665673154306
  - type: nauc_map_at_3_max value: 61.13597610587937
  - type: nauc_map_at_3_std value: 9.309596395240598
  - type: nauc_map_at_5_diff1 value: 83.52307226455358
  - type: nauc_map_at_5_max value: 61.59405758027573
  - type: nauc_map_at_5_std value: 9.320025423287671
  - type: nauc_mrr_at_1000_diff1 value: 83.69682652271125
  - type: nauc_mrr_at_1000_max value: 61.70131708044767
  - type: nauc_mrr_at_1000_std value: 9.345825405274955
  - type: nauc_mrr_at_100_diff1 value: 83.68924820523492
  - type: nauc_mrr_at_100_max value: 61.6965735573098
  - type: nauc_mrr_at_100_std value: 9.366132859525775
  - type: nauc_mrr_at_10_diff1 value: 83.61802964269985
  - type: nauc_mrr_at_10_max value: 61.74274476167882
  - type: nauc_mrr_at_10_std value: 9.504060995819101
  - type: nauc_mrr_at_1_diff1 value: 86.37079221403225
  - type: nauc_mrr_at_1_max value: 61.856861655370686
  - type: nauc_mrr_at_1_std value: 4.708911881992707
  - type: nauc_mrr_at_20_diff1 value: 83.62920965453047
  - type: nauc_mrr_at_20_max value: 61.761029350326965
  - type: nauc_mrr_at_20_std value: 9.572978651118351
  - type: nauc_mrr_at_3_diff1 value: 83.66665673154306
  - type: nauc_mrr_at_3_max value: 61.13597610587937
  - type: nauc_mrr_at_3_std value: 9.309596395240598
  - type: nauc_mrr_at_5_diff1 value: 83.52307226455358
  - type: nauc_mrr_at_5_max value: 61.59405758027573
  - type: nauc_mrr_at_5_std value: 9.320025423287671
  - type: nauc_ndcg_at_1000_diff1 value: 83.24213186482201
  - type: nauc_ndcg_at_1000_max value: 61.77629841787496
  - type: nauc_ndcg_at_1000_std value: 10.332527869705851
  - type: nauc_ndcg_at_100_diff1 value: 83.06815820441027
  - type: nauc_ndcg_at_100_max value: 61.6947181864579
  - type: nauc_ndcg_at_100_std value: 10.888922975877316
  - type: nauc_ndcg_at_10_diff1 value: 82.58238431386295
  - type: nauc_ndcg_at_10_max value: 62.10333663935709
  - type: nauc_ndcg_at_10_std value: 11.746030330958174
  - type: nauc_ndcg_at_1_diff1 value: 86.37079221403225
  - type: nauc_ndcg_at_1_max value: 61.856861655370686
  - type: nauc_ndcg_at_1_std value: 4.708911881992707
  - type: nauc_ndcg_at_20_diff1 value: 82.67888324480154
  - type: nauc_ndcg_at_20_max value: 62.28124917486516
  - type: nauc_ndcg_at_20_std value: 12.343058917563914
  - type: nauc_ndcg_at_3_diff1 value: 82.71277373710663
  - type: nauc_ndcg_at_3_max value: 60.66677922989939
  - type: nauc_ndcg_at_3_std value: 10.843633736296528
  - type: nauc_ndcg_at_5_diff1 value: 82.34691124846786
  - type: nauc_ndcg_at_5_max value: 61.605961382062716
  - type: nauc_ndcg_at_5_std value: 11.129011077702602
  - 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: 60.93103908230194
  - type: nauc_precision_at_100_max value: 52.621048419370695
  - type: nauc_precision_at_100_std value: 85.60090702947922
  - type: nauc_precision_at_10_diff1 value: 76.26517273576093
  - type: nauc_precision_at_10_max value: 65.2013694366636
  - type: nauc_precision_at_10_std value: 26.50357920946173
  - type: nauc_precision_at_1_diff1 value: 86.37079221403225
  - type: nauc_precision_at_1_max value: 61.856861655370686
  - type: nauc_precision_at_1_std value: 4.708911881992707
  - type: nauc_precision_at_20_diff1 value: 73.47946930710295
  - type: nauc_precision_at_20_max value: 70.19520986689217
  - type: nauc_precision_at_20_std value: 45.93186111653967
  - type: nauc_precision_at_3_diff1 value: 79.02026879450186
  - type: nauc_precision_at_3_max value: 58.75074624692399
  - type: nauc_precision_at_3_std value: 16.740684654251037
  - type: nauc_precision_at_5_diff1 value: 76.47585662281637
  - type: nauc_precision_at_5_max value: 61.86270922013127
  - type: nauc_precision_at_5_std value: 20.1833625455035
  - 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: 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: Retrieval
- dataset: config: eng_Latn-rus_Cyrl name: MTEB BibleNLPBitextMining (eng_Latn-rus_Cyrl) revision: 264a18480c529d9e922483839b4b9758e690b762 split: train type: davidstap/biblenlp-corpus-mmteb 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: config: rus_Cyrl-eng_Latn name: MTEB BibleNLPBitextMining (rus_Cyrl-eng_Latn) revision: 264a18480c529d9e922483839b4b9758e690b762 split: train type: davidstap/biblenlp-corpus-mmteb 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: BitextMining
- dataset: config: default name: MTEB CEDRClassification (default) revision: c0ba03d058e3e1b2f3fd20518875a4563dd12db4 split: test type: ai-forever/cedr-classification metrics:
  - type: accuracy value: 40.06907545164719
  - type: f1 value: 26.285000550712407
  - type: lrap value: 64.4280021253997
  - type: main_score value: 40.06907545164719 task: type: MultilabelClassification
- dataset: config: default name: MTEB CyrillicTurkicLangClassification (default) revision: e42d330f33d65b7b72dfd408883daf1661f06f18 split: test type: tatiana-merz/cyrillic_turkic_langs 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: Classification
- dataset: config: ace_Arab-rus_Cyrl name: MTEB FloresBitextMining (ace_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bam_Latn-rus_Cyrl name: MTEB FloresBitextMining (bam_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: dzo_Tibt-rus_Cyrl name: MTEB FloresBitextMining (dzo_Tibt-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hin_Deva-rus_Cyrl name: MTEB FloresBitextMining (hin_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: khm_Khmr-rus_Cyrl name: MTEB FloresBitextMining (khm_Khmr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mag_Deva-rus_Cyrl name: MTEB FloresBitextMining (mag_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pap_Latn-rus_Cyrl name: MTEB FloresBitextMining (pap_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sot_Latn-rus_Cyrl name: MTEB FloresBitextMining (sot_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tur_Latn-rus_Cyrl name: MTEB FloresBitextMining (tur_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ace_Latn-rus_Cyrl name: MTEB FloresBitextMining (ace_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ban_Latn-rus_Cyrl name: MTEB FloresBitextMining (ban_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ell_Grek-rus_Cyrl name: MTEB FloresBitextMining (ell_Grek-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hne_Deva-rus_Cyrl name: MTEB FloresBitextMining (hne_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kik_Latn-rus_Cyrl name: MTEB FloresBitextMining (kik_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mai_Deva-rus_Cyrl name: MTEB FloresBitextMining (mai_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pbt_Arab-rus_Cyrl name: MTEB FloresBitextMining (pbt_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: spa_Latn-rus_Cyrl name: MTEB FloresBitextMining (spa_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: twi_Latn-rus_Cyrl name: MTEB FloresBitextMining (twi_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: acm_Arab-rus_Cyrl name: MTEB FloresBitextMining (acm_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bel_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (bel_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: eng_Latn-rus_Cyrl name: MTEB FloresBitextMining (eng_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hrv_Latn-rus_Cyrl name: MTEB FloresBitextMining (hrv_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kin_Latn-rus_Cyrl name: MTEB FloresBitextMining (kin_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mal_Mlym-rus_Cyrl name: MTEB FloresBitextMining (mal_Mlym-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pes_Arab-rus_Cyrl name: MTEB FloresBitextMining (pes_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: srd_Latn-rus_Cyrl name: MTEB FloresBitextMining (srd_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tzm_Tfng-rus_Cyrl name: MTEB FloresBitextMining (tzm_Tfng-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: acq_Arab-rus_Cyrl name: MTEB FloresBitextMining (acq_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bem_Latn-rus_Cyrl name: MTEB FloresBitextMining (bem_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: epo_Latn-rus_Cyrl name: MTEB FloresBitextMining (epo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hun_Latn-rus_Cyrl name: MTEB FloresBitextMining (hun_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kir_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (kir_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mar_Deva-rus_Cyrl name: MTEB FloresBitextMining (mar_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: plt_Latn-rus_Cyrl name: MTEB FloresBitextMining (plt_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: srp_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (srp_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: uig_Arab-rus_Cyrl name: MTEB FloresBitextMining (uig_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: aeb_Arab-rus_Cyrl name: MTEB FloresBitextMining (aeb_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ben_Beng-rus_Cyrl name: MTEB FloresBitextMining (ben_Beng-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: est_Latn-rus_Cyrl name: MTEB FloresBitextMining (est_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hye_Armn-rus_Cyrl name: MTEB FloresBitextMining (hye_Armn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kmb_Latn-rus_Cyrl name: MTEB FloresBitextMining (kmb_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: min_Arab-rus_Cyrl name: MTEB FloresBitextMining (min_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pol_Latn-rus_Cyrl name: MTEB FloresBitextMining (pol_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ssw_Latn-rus_Cyrl name: MTEB FloresBitextMining (ssw_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ukr_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (ukr_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: afr_Latn-rus_Cyrl name: MTEB FloresBitextMining (afr_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bho_Deva-rus_Cyrl name: MTEB FloresBitextMining (bho_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: eus_Latn-rus_Cyrl name: MTEB FloresBitextMining (eus_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ibo_Latn-rus_Cyrl name: MTEB FloresBitextMining (ibo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kmr_Latn-rus_Cyrl name: MTEB FloresBitextMining (kmr_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: min_Latn-rus_Cyrl name: MTEB FloresBitextMining (min_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: por_Latn-rus_Cyrl name: MTEB FloresBitextMining (por_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sun_Latn-rus_Cyrl name: MTEB FloresBitextMining (sun_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: umb_Latn-rus_Cyrl name: MTEB FloresBitextMining (umb_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ajp_Arab-rus_Cyrl name: MTEB FloresBitextMining (ajp_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bjn_Arab-rus_Cyrl name: MTEB FloresBitextMining (bjn_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ewe_Latn-rus_Cyrl name: MTEB FloresBitextMining (ewe_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ilo_Latn-rus_Cyrl name: MTEB FloresBitextMining (ilo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: knc_Arab-rus_Cyrl name: MTEB FloresBitextMining (knc_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mkd_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (mkd_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: prs_Arab-rus_Cyrl name: MTEB FloresBitextMining (prs_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: swe_Latn-rus_Cyrl name: MTEB FloresBitextMining (swe_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: urd_Arab-rus_Cyrl name: MTEB FloresBitextMining (urd_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: aka_Latn-rus_Cyrl name: MTEB FloresBitextMining (aka_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bjn_Latn-rus_Cyrl name: MTEB FloresBitextMining (bjn_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fao_Latn-rus_Cyrl name: MTEB FloresBitextMining (fao_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ind_Latn-rus_Cyrl name: MTEB FloresBitextMining (ind_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: knc_Latn-rus_Cyrl name: MTEB FloresBitextMining (knc_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mlt_Latn-rus_Cyrl name: MTEB FloresBitextMining (mlt_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: quy_Latn-rus_Cyrl name: MTEB FloresBitextMining (quy_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: swh_Latn-rus_Cyrl name: MTEB FloresBitextMining (swh_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: uzn_Latn-rus_Cyrl name: MTEB FloresBitextMining (uzn_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: als_Latn-rus_Cyrl name: MTEB FloresBitextMining (als_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bod_Tibt-rus_Cyrl name: MTEB FloresBitextMining (bod_Tibt-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fij_Latn-rus_Cyrl name: MTEB FloresBitextMining (fij_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: isl_Latn-rus_Cyrl name: MTEB FloresBitextMining (isl_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kon_Latn-rus_Cyrl name: MTEB FloresBitextMining (kon_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mni_Beng-rus_Cyrl name: MTEB FloresBitextMining (mni_Beng-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ron_Latn-rus_Cyrl name: MTEB FloresBitextMining (ron_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: szl_Latn-rus_Cyrl name: MTEB FloresBitextMining (szl_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: vec_Latn-rus_Cyrl name: MTEB FloresBitextMining (vec_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: amh_Ethi-rus_Cyrl name: MTEB FloresBitextMining (amh_Ethi-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bos_Latn-rus_Cyrl name: MTEB FloresBitextMining (bos_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fin_Latn-rus_Cyrl name: MTEB FloresBitextMining (fin_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ita_Latn-rus_Cyrl name: MTEB FloresBitextMining (ita_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kor_Hang-rus_Cyrl name: MTEB FloresBitextMining (kor_Hang-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mos_Latn-rus_Cyrl name: MTEB FloresBitextMining (mos_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: run_Latn-rus_Cyrl name: MTEB FloresBitextMining (run_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tam_Taml-rus_Cyrl name: MTEB FloresBitextMining (tam_Taml-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: vie_Latn-rus_Cyrl name: MTEB FloresBitextMining (vie_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: apc_Arab-rus_Cyrl name: MTEB FloresBitextMining (apc_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bug_Latn-rus_Cyrl name: MTEB FloresBitextMining (bug_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fon_Latn-rus_Cyrl name: MTEB FloresBitextMining (fon_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: jav_Latn-rus_Cyrl name: MTEB FloresBitextMining (jav_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lao_Laoo-rus_Cyrl name: MTEB FloresBitextMining (lao_Laoo-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mri_Latn-rus_Cyrl name: MTEB FloresBitextMining (mri_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ace_Arab name: MTEB FloresBitextMining (rus_Cyrl-ace_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bam_Latn name: MTEB FloresBitextMining (rus_Cyrl-bam_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-dzo_Tibt name: MTEB FloresBitextMining (rus_Cyrl-dzo_Tibt) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hin_Deva name: MTEB FloresBitextMining (rus_Cyrl-hin_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-khm_Khmr name: MTEB FloresBitextMining (rus_Cyrl-khm_Khmr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mag_Deva name: MTEB FloresBitextMining (rus_Cyrl-mag_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pap_Latn name: MTEB FloresBitextMining (rus_Cyrl-pap_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sot_Latn name: MTEB FloresBitextMining (rus_Cyrl-sot_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tur_Latn name: MTEB FloresBitextMining (rus_Cyrl-tur_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ace_Latn name: MTEB FloresBitextMining (rus_Cyrl-ace_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ban_Latn name: MTEB FloresBitextMining (rus_Cyrl-ban_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ell_Grek name: MTEB FloresBitextMining (rus_Cyrl-ell_Grek) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hne_Deva name: MTEB FloresBitextMining (rus_Cyrl-hne_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kik_Latn name: MTEB FloresBitextMining (rus_Cyrl-kik_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mai_Deva name: MTEB FloresBitextMining (rus_Cyrl-mai_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pbt_Arab name: MTEB FloresBitextMining (rus_Cyrl-pbt_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-spa_Latn name: MTEB FloresBitextMining (rus_Cyrl-spa_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-twi_Latn name: MTEB FloresBitextMining (rus_Cyrl-twi_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-acm_Arab name: MTEB FloresBitextMining (rus_Cyrl-acm_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bel_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-bel_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-eng_Latn name: MTEB FloresBitextMining (rus_Cyrl-eng_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hrv_Latn name: MTEB FloresBitextMining (rus_Cyrl-hrv_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kin_Latn name: MTEB FloresBitextMining (rus_Cyrl-kin_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mal_Mlym name: MTEB FloresBitextMining (rus_Cyrl-mal_Mlym) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pes_Arab name: MTEB FloresBitextMining (rus_Cyrl-pes_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-srd_Latn name: MTEB FloresBitextMining (rus_Cyrl-srd_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tzm_Tfng name: MTEB FloresBitextMining (rus_Cyrl-tzm_Tfng) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-acq_Arab name: MTEB FloresBitextMining (rus_Cyrl-acq_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bem_Latn name: MTEB FloresBitextMining (rus_Cyrl-bem_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-epo_Latn name: MTEB FloresBitextMining (rus_Cyrl-epo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hun_Latn name: MTEB FloresBitextMining (rus_Cyrl-hun_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kir_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-kir_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mar_Deva name: MTEB FloresBitextMining (rus_Cyrl-mar_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-plt_Latn name: MTEB FloresBitextMining (rus_Cyrl-plt_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-srp_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-srp_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-uig_Arab name: MTEB FloresBitextMining (rus_Cyrl-uig_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-aeb_Arab name: MTEB FloresBitextMining (rus_Cyrl-aeb_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ben_Beng name: MTEB FloresBitextMining (rus_Cyrl-ben_Beng) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-est_Latn name: MTEB FloresBitextMining (rus_Cyrl-est_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hye_Armn name: MTEB FloresBitextMining (rus_Cyrl-hye_Armn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kmb_Latn name: MTEB FloresBitextMining (rus_Cyrl-kmb_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-min_Arab name: MTEB FloresBitextMining (rus_Cyrl-min_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pol_Latn name: MTEB FloresBitextMining (rus_Cyrl-pol_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ssw_Latn name: MTEB FloresBitextMining (rus_Cyrl-ssw_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ukr_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-ukr_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-afr_Latn name: MTEB FloresBitextMining (rus_Cyrl-afr_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bho_Deva name: MTEB FloresBitextMining (rus_Cyrl-bho_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-eus_Latn name: MTEB FloresBitextMining (rus_Cyrl-eus_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ibo_Latn name: MTEB FloresBitextMining (rus_Cyrl-ibo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kmr_Latn name: MTEB FloresBitextMining (rus_Cyrl-kmr_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-min_Latn name: MTEB FloresBitextMining (rus_Cyrl-min_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-por_Latn name: MTEB FloresBitextMining (rus_Cyrl-por_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sun_Latn name: MTEB FloresBitextMining (rus_Cyrl-sun_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-umb_Latn name: MTEB FloresBitextMining (rus_Cyrl-umb_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ajp_Arab name: MTEB FloresBitextMining (rus_Cyrl-ajp_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bjn_Arab name: MTEB FloresBitextMining (rus_Cyrl-bjn_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ewe_Latn name: MTEB FloresBitextMining (rus_Cyrl-ewe_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ilo_Latn name: MTEB FloresBitextMining (rus_Cyrl-ilo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-knc_Arab name: MTEB FloresBitextMining (rus_Cyrl-knc_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mkd_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-mkd_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-prs_Arab name: MTEB FloresBitextMining (rus_Cyrl-prs_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-swe_Latn name: MTEB FloresBitextMining (rus_Cyrl-swe_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-urd_Arab name: MTEB FloresBitextMining (rus_Cyrl-urd_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-aka_Latn name: MTEB FloresBitextMining (rus_Cyrl-aka_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bjn_Latn name: MTEB FloresBitextMining (rus_Cyrl-bjn_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fao_Latn name: MTEB FloresBitextMining (rus_Cyrl-fao_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ind_Latn name: MTEB FloresBitextMining (rus_Cyrl-ind_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-knc_Latn name: MTEB FloresBitextMining (rus_Cyrl-knc_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mlt_Latn name: MTEB FloresBitextMining (rus_Cyrl-mlt_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-quy_Latn name: MTEB FloresBitextMining (rus_Cyrl-quy_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-swh_Latn name: MTEB FloresBitextMining (rus_Cyrl-swh_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-uzn_Latn name: MTEB FloresBitextMining (rus_Cyrl-uzn_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-als_Latn name: MTEB FloresBitextMining (rus_Cyrl-als_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bod_Tibt name: MTEB FloresBitextMining (rus_Cyrl-bod_Tibt) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fij_Latn name: MTEB FloresBitextMining (rus_Cyrl-fij_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-isl_Latn name: MTEB FloresBitextMining (rus_Cyrl-isl_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kon_Latn name: MTEB FloresBitextMining (rus_Cyrl-kon_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mni_Beng name: MTEB FloresBitextMining (rus_Cyrl-mni_Beng) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ron_Latn name: MTEB FloresBitextMining (rus_Cyrl-ron_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-szl_Latn name: MTEB FloresBitextMining (rus_Cyrl-szl_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-vec_Latn name: MTEB FloresBitextMining (rus_Cyrl-vec_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-amh_Ethi name: MTEB FloresBitextMining (rus_Cyrl-amh_Ethi) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bos_Latn name: MTEB FloresBitextMining (rus_Cyrl-bos_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fin_Latn name: MTEB FloresBitextMining (rus_Cyrl-fin_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ita_Latn name: MTEB FloresBitextMining (rus_Cyrl-ita_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kor_Hang name: MTEB FloresBitextMining (rus_Cyrl-kor_Hang) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mos_Latn name: MTEB FloresBitextMining (rus_Cyrl-mos_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-run_Latn name: MTEB FloresBitextMining (rus_Cyrl-run_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tam_Taml name: MTEB FloresBitextMining (rus_Cyrl-tam_Taml) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-vie_Latn name: MTEB FloresBitextMining (rus_Cyrl-vie_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-apc_Arab name: MTEB FloresBitextMining (rus_Cyrl-apc_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bug_Latn name: MTEB FloresBitextMining (rus_Cyrl-bug_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fon_Latn name: MTEB FloresBitextMining (rus_Cyrl-fon_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-jav_Latn name: MTEB FloresBitextMining (rus_Cyrl-jav_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lao_Laoo name: MTEB FloresBitextMining (rus_Cyrl-lao_Laoo) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mri_Latn name: MTEB FloresBitextMining (rus_Cyrl-mri_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-taq_Latn name: MTEB FloresBitextMining (rus_Cyrl-taq_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-war_Latn name: MTEB FloresBitextMining (rus_Cyrl-war_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-arb_Arab name: MTEB FloresBitextMining (rus_Cyrl-arb_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bul_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-bul_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fra_Latn name: MTEB FloresBitextMining (rus_Cyrl-fra_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-jpn_Jpan name: MTEB FloresBitextMining (rus_Cyrl-jpn_Jpan) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lij_Latn name: MTEB FloresBitextMining (rus_Cyrl-lij_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-mya_Mymr name: MTEB FloresBitextMining (rus_Cyrl-mya_Mymr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sag_Latn name: MTEB FloresBitextMining (rus_Cyrl-sag_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-taq_Tfng name: MTEB FloresBitextMining (rus_Cyrl-taq_Tfng) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-wol_Latn name: MTEB FloresBitextMining (rus_Cyrl-wol_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-arb_Latn name: MTEB FloresBitextMining (rus_Cyrl-arb_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-cat_Latn name: MTEB FloresBitextMining (rus_Cyrl-cat_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fur_Latn name: MTEB FloresBitextMining (rus_Cyrl-fur_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kab_Latn name: MTEB FloresBitextMining (rus_Cyrl-kab_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lim_Latn name: MTEB FloresBitextMining (rus_Cyrl-lim_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nld_Latn name: MTEB FloresBitextMining (rus_Cyrl-nld_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-san_Deva name: MTEB FloresBitextMining (rus_Cyrl-san_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tat_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-tat_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-xho_Latn name: MTEB FloresBitextMining (rus_Cyrl-xho_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ars_Arab name: MTEB FloresBitextMining (rus_Cyrl-ars_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ceb_Latn name: MTEB FloresBitextMining (rus_Cyrl-ceb_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-fuv_Latn name: MTEB FloresBitextMining (rus_Cyrl-fuv_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kac_Latn name: MTEB FloresBitextMining (rus_Cyrl-kac_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lin_Latn name: MTEB FloresBitextMining (rus_Cyrl-lin_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nno_Latn name: MTEB FloresBitextMining (rus_Cyrl-nno_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sat_Olck name: MTEB FloresBitextMining (rus_Cyrl-sat_Olck) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tel_Telu name: MTEB FloresBitextMining (rus_Cyrl-tel_Telu) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ydd_Hebr name: MTEB FloresBitextMining (rus_Cyrl-ydd_Hebr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ary_Arab name: MTEB FloresBitextMining (rus_Cyrl-ary_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ces_Latn name: MTEB FloresBitextMining (rus_Cyrl-ces_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-gaz_Latn name: MTEB FloresBitextMining (rus_Cyrl-gaz_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kam_Latn name: MTEB FloresBitextMining (rus_Cyrl-kam_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lit_Latn name: MTEB FloresBitextMining (rus_Cyrl-lit_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nob_Latn name: MTEB FloresBitextMining (rus_Cyrl-nob_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-scn_Latn name: MTEB FloresBitextMining (rus_Cyrl-scn_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tgk_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-tgk_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-yor_Latn name: MTEB FloresBitextMining (rus_Cyrl-yor_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-arz_Arab name: MTEB FloresBitextMining (rus_Cyrl-arz_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-cjk_Latn name: MTEB FloresBitextMining (rus_Cyrl-cjk_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-gla_Latn name: MTEB FloresBitextMining (rus_Cyrl-gla_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kan_Knda name: MTEB FloresBitextMining (rus_Cyrl-kan_Knda) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lmo_Latn name: MTEB FloresBitextMining (rus_Cyrl-lmo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-npi_Deva name: MTEB FloresBitextMining (rus_Cyrl-npi_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-shn_Mymr name: MTEB FloresBitextMining (rus_Cyrl-shn_Mymr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tgl_Latn name: MTEB FloresBitextMining (rus_Cyrl-tgl_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-yue_Hant name: MTEB FloresBitextMining (rus_Cyrl-yue_Hant) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-asm_Beng name: MTEB FloresBitextMining (rus_Cyrl-asm_Beng) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ckb_Arab name: MTEB FloresBitextMining (rus_Cyrl-ckb_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-gle_Latn name: MTEB FloresBitextMining (rus_Cyrl-gle_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kas_Arab name: MTEB FloresBitextMining (rus_Cyrl-kas_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ltg_Latn name: MTEB FloresBitextMining (rus_Cyrl-ltg_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nso_Latn name: MTEB FloresBitextMining (rus_Cyrl-nso_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sin_Sinh name: MTEB FloresBitextMining (rus_Cyrl-sin_Sinh) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tha_Thai name: MTEB FloresBitextMining (rus_Cyrl-tha_Thai) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-zho_Hans name: MTEB FloresBitextMining (rus_Cyrl-zho_Hans) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ast_Latn name: MTEB FloresBitextMining (rus_Cyrl-ast_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-crh_Latn name: MTEB FloresBitextMining (rus_Cyrl-crh_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-glg_Latn name: MTEB FloresBitextMining (rus_Cyrl-glg_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kas_Deva name: MTEB FloresBitextMining (rus_Cyrl-kas_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ltz_Latn name: MTEB FloresBitextMining (rus_Cyrl-ltz_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nus_Latn name: MTEB FloresBitextMining (rus_Cyrl-nus_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-slk_Latn name: MTEB FloresBitextMining (rus_Cyrl-slk_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tir_Ethi name: MTEB FloresBitextMining (rus_Cyrl-tir_Ethi) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-zho_Hant name: MTEB FloresBitextMining (rus_Cyrl-zho_Hant) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-awa_Deva name: MTEB FloresBitextMining (rus_Cyrl-awa_Deva) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-cym_Latn name: MTEB FloresBitextMining (rus_Cyrl-cym_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-grn_Latn name: MTEB FloresBitextMining (rus_Cyrl-grn_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kat_Geor name: MTEB FloresBitextMining (rus_Cyrl-kat_Geor) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lua_Latn name: MTEB FloresBitextMining (rus_Cyrl-lua_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-nya_Latn name: MTEB FloresBitextMining (rus_Cyrl-nya_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-slv_Latn name: MTEB FloresBitextMining (rus_Cyrl-slv_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tpi_Latn name: MTEB FloresBitextMining (rus_Cyrl-tpi_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-zsm_Latn name: MTEB FloresBitextMining (rus_Cyrl-zsm_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ayr_Latn name: MTEB FloresBitextMining (rus_Cyrl-ayr_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-dan_Latn name: MTEB FloresBitextMining (rus_Cyrl-dan_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-guj_Gujr name: MTEB FloresBitextMining (rus_Cyrl-guj_Gujr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kaz_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-kaz_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lug_Latn name: MTEB FloresBitextMining (rus_Cyrl-lug_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-oci_Latn name: MTEB FloresBitextMining (rus_Cyrl-oci_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-smo_Latn name: MTEB FloresBitextMining (rus_Cyrl-smo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tsn_Latn name: MTEB FloresBitextMining (rus_Cyrl-tsn_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-zul_Latn name: MTEB FloresBitextMining (rus_Cyrl-zul_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-azb_Arab name: MTEB FloresBitextMining (rus_Cyrl-azb_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-deu_Latn name: MTEB FloresBitextMining (rus_Cyrl-deu_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hat_Latn name: MTEB FloresBitextMining (rus_Cyrl-hat_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kbp_Latn name: MTEB FloresBitextMining (rus_Cyrl-kbp_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-luo_Latn name: MTEB FloresBitextMining (rus_Cyrl-luo_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-ory_Orya name: MTEB FloresBitextMining (rus_Cyrl-ory_Orya) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-sna_Latn name: MTEB FloresBitextMining (rus_Cyrl-sna_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tso_Latn name: MTEB FloresBitextMining (rus_Cyrl-tso_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-azj_Latn name: MTEB FloresBitextMining (rus_Cyrl-azj_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-dik_Latn name: MTEB FloresBitextMining (rus_Cyrl-dik_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-hau_Latn name: MTEB FloresBitextMining (rus_Cyrl-hau_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-kea_Latn name: MTEB FloresBitextMining (rus_Cyrl-kea_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lus_Latn name: MTEB FloresBitextMining (rus_Cyrl-lus_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pag_Latn name: MTEB FloresBitextMining (rus_Cyrl-pag_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-snd_Arab name: MTEB FloresBitextMining (rus_Cyrl-snd_Arab) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tuk_Latn name: MTEB FloresBitextMining (rus_Cyrl-tuk_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-bak_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-bak_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-dyu_Latn name: MTEB FloresBitextMining (rus_Cyrl-dyu_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-heb_Hebr name: MTEB FloresBitextMining (rus_Cyrl-heb_Hebr) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-khk_Cyrl name: MTEB FloresBitextMining (rus_Cyrl-khk_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-lvs_Latn name: MTEB FloresBitextMining (rus_Cyrl-lvs_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-pan_Guru name: MTEB FloresBitextMining (rus_Cyrl-pan_Guru) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-som_Latn name: MTEB FloresBitextMining (rus_Cyrl-som_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: rus_Cyrl-tum_Latn name: MTEB FloresBitextMining (rus_Cyrl-tum_Latn) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: taq_Latn-rus_Cyrl name: MTEB FloresBitextMining (taq_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: war_Latn-rus_Cyrl name: MTEB FloresBitextMining (war_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: arb_Arab-rus_Cyrl name: MTEB FloresBitextMining (arb_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bul_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (bul_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fra_Latn-rus_Cyrl name: MTEB FloresBitextMining (fra_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: jpn_Jpan-rus_Cyrl name: MTEB FloresBitextMining (jpn_Jpan-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lij_Latn-rus_Cyrl name: MTEB FloresBitextMining (lij_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: mya_Mymr-rus_Cyrl name: MTEB FloresBitextMining (mya_Mymr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sag_Latn-rus_Cyrl name: MTEB FloresBitextMining (sag_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: taq_Tfng-rus_Cyrl name: MTEB FloresBitextMining (taq_Tfng-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: wol_Latn-rus_Cyrl name: MTEB FloresBitextMining (wol_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: arb_Latn-rus_Cyrl name: MTEB FloresBitextMining (arb_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: cat_Latn-rus_Cyrl name: MTEB FloresBitextMining (cat_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fur_Latn-rus_Cyrl name: MTEB FloresBitextMining (fur_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kab_Latn-rus_Cyrl name: MTEB FloresBitextMining (kab_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lim_Latn-rus_Cyrl name: MTEB FloresBitextMining (lim_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nld_Latn-rus_Cyrl name: MTEB FloresBitextMining (nld_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: san_Deva-rus_Cyrl name: MTEB FloresBitextMining (san_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tat_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (tat_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: xho_Latn-rus_Cyrl name: MTEB FloresBitextMining (xho_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ars_Arab-rus_Cyrl name: MTEB FloresBitextMining (ars_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ceb_Latn-rus_Cyrl name: MTEB FloresBitextMining (ceb_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: fuv_Latn-rus_Cyrl name: MTEB FloresBitextMining (fuv_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kac_Latn-rus_Cyrl name: MTEB FloresBitextMining (kac_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lin_Latn-rus_Cyrl name: MTEB FloresBitextMining (lin_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nno_Latn-rus_Cyrl name: MTEB FloresBitextMining (nno_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sat_Olck-rus_Cyrl name: MTEB FloresBitextMining (sat_Olck-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tel_Telu-rus_Cyrl name: MTEB FloresBitextMining (tel_Telu-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ydd_Hebr-rus_Cyrl name: MTEB FloresBitextMining (ydd_Hebr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ary_Arab-rus_Cyrl name: MTEB FloresBitextMining (ary_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ces_Latn-rus_Cyrl name: MTEB FloresBitextMining (ces_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: gaz_Latn-rus_Cyrl name: MTEB FloresBitextMining (gaz_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kam_Latn-rus_Cyrl name: MTEB FloresBitextMining (kam_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lit_Latn-rus_Cyrl name: MTEB FloresBitextMining (lit_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nob_Latn-rus_Cyrl name: MTEB FloresBitextMining (nob_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: scn_Latn-rus_Cyrl name: MTEB FloresBitextMining (scn_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tgk_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (tgk_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: yor_Latn-rus_Cyrl name: MTEB FloresBitextMining (yor_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: arz_Arab-rus_Cyrl name: MTEB FloresBitextMining (arz_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: cjk_Latn-rus_Cyrl name: MTEB FloresBitextMining (cjk_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: gla_Latn-rus_Cyrl name: MTEB FloresBitextMining (gla_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kan_Knda-rus_Cyrl name: MTEB FloresBitextMining (kan_Knda-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lmo_Latn-rus_Cyrl name: MTEB FloresBitextMining (lmo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: npi_Deva-rus_Cyrl name: MTEB FloresBitextMining (npi_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: shn_Mymr-rus_Cyrl name: MTEB FloresBitextMining (shn_Mymr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tgl_Latn-rus_Cyrl name: MTEB FloresBitextMining (tgl_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: yue_Hant-rus_Cyrl name: MTEB FloresBitextMining (yue_Hant-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: asm_Beng-rus_Cyrl name: MTEB FloresBitextMining (asm_Beng-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ckb_Arab-rus_Cyrl name: MTEB FloresBitextMining (ckb_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: gle_Latn-rus_Cyrl name: MTEB FloresBitextMining (gle_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kas_Arab-rus_Cyrl name: MTEB FloresBitextMining (kas_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ltg_Latn-rus_Cyrl name: MTEB FloresBitextMining (ltg_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nso_Latn-rus_Cyrl name: MTEB FloresBitextMining (nso_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sin_Sinh-rus_Cyrl name: MTEB FloresBitextMining (sin_Sinh-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tha_Thai-rus_Cyrl name: MTEB FloresBitextMining (tha_Thai-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: zho_Hans-rus_Cyrl name: MTEB FloresBitextMining (zho_Hans-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ast_Latn-rus_Cyrl name: MTEB FloresBitextMining (ast_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: crh_Latn-rus_Cyrl name: MTEB FloresBitextMining (crh_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: glg_Latn-rus_Cyrl name: MTEB FloresBitextMining (glg_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kas_Deva-rus_Cyrl name: MTEB FloresBitextMining (kas_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ltz_Latn-rus_Cyrl name: MTEB FloresBitextMining (ltz_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nus_Latn-rus_Cyrl name: MTEB FloresBitextMining (nus_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: slk_Latn-rus_Cyrl name: MTEB FloresBitextMining (slk_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tir_Ethi-rus_Cyrl name: MTEB FloresBitextMining (tir_Ethi-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: zho_Hant-rus_Cyrl name: MTEB FloresBitextMining (zho_Hant-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: awa_Deva-rus_Cyrl name: MTEB FloresBitextMining (awa_Deva-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: cym_Latn-rus_Cyrl name: MTEB FloresBitextMining (cym_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: grn_Latn-rus_Cyrl name: MTEB FloresBitextMining (grn_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kat_Geor-rus_Cyrl name: MTEB FloresBitextMining (kat_Geor-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lua_Latn-rus_Cyrl name: MTEB FloresBitextMining (lua_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: nya_Latn-rus_Cyrl name: MTEB FloresBitextMining (nya_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: slv_Latn-rus_Cyrl name: MTEB FloresBitextMining (slv_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tpi_Latn-rus_Cyrl name: MTEB FloresBitextMining (tpi_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: zsm_Latn-rus_Cyrl name: MTEB FloresBitextMining (zsm_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ayr_Latn-rus_Cyrl name: MTEB FloresBitextMining (ayr_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: dan_Latn-rus_Cyrl name: MTEB FloresBitextMining (dan_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: guj_Gujr-rus_Cyrl name: MTEB FloresBitextMining (guj_Gujr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kaz_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (kaz_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lug_Latn-rus_Cyrl name: MTEB FloresBitextMining (lug_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: oci_Latn-rus_Cyrl name: MTEB FloresBitextMining (oci_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: smo_Latn-rus_Cyrl name: MTEB FloresBitextMining (smo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tsn_Latn-rus_Cyrl name: MTEB FloresBitextMining (tsn_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: zul_Latn-rus_Cyrl name: MTEB FloresBitextMining (zul_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: azb_Arab-rus_Cyrl name: MTEB FloresBitextMining (azb_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: deu_Latn-rus_Cyrl name: MTEB FloresBitextMining (deu_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hat_Latn-rus_Cyrl name: MTEB FloresBitextMining (hat_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kbp_Latn-rus_Cyrl name: MTEB FloresBitextMining (kbp_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: luo_Latn-rus_Cyrl name: MTEB FloresBitextMining (luo_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: ory_Orya-rus_Cyrl name: MTEB FloresBitextMining (ory_Orya-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: sna_Latn-rus_Cyrl name: MTEB FloresBitextMining (sna_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tso_Latn-rus_Cyrl name: MTEB FloresBitextMining (tso_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: azj_Latn-rus_Cyrl name: MTEB FloresBitextMining (azj_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: dik_Latn-rus_Cyrl name: MTEB FloresBitextMining (dik_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: hau_Latn-rus_Cyrl name: MTEB FloresBitextMining (hau_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: kea_Latn-rus_Cyrl name: MTEB FloresBitextMining (kea_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lus_Latn-rus_Cyrl name: MTEB FloresBitextMining (lus_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pag_Latn-rus_Cyrl name: MTEB FloresBitextMining (pag_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: snd_Arab-rus_Cyrl name: MTEB FloresBitextMining (snd_Arab-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tuk_Latn-rus_Cyrl name: MTEB FloresBitextMining (tuk_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: bak_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (bak_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: dyu_Latn-rus_Cyrl name: MTEB FloresBitextMining (dyu_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: heb_Hebr-rus_Cyrl name: MTEB FloresBitextMining (heb_Hebr-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: khk_Cyrl-rus_Cyrl name: MTEB FloresBitextMining (khk_Cyrl-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: lvs_Latn-rus_Cyrl name: MTEB FloresBitextMining (lvs_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: pan_Guru-rus_Cyrl name: MTEB FloresBitextMining (pan_Guru-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: som_Latn-rus_Cyrl name: MTEB FloresBitextMining (som_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: config: tum_Latn-rus_Cyrl name: MTEB FloresBitextMining (tum_Latn-rus_Cyrl) revision: e6b647fcb6299a2f686f742f4d4c023e553ea67e split: devtest type: mteb/flores 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: BitextMining
- dataset: config: default name: MTEB GeoreviewClassification (default) revision: 3765c0d1de6b7d264bc459433c45e5a75513839c split: test type: ai-forever/georeview-classification 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: Classification
- dataset: config: default name: MTEB GeoreviewClusteringP2P (default) revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec split: test type: ai-forever/georeview-clustering-p2p metrics:
  - type: main_score value: 58.15951247070825
  - type: v_measure value: 58.15951247070825
  - type: v_measure_std value: 0.6739615788288809 task: type: Clustering
- dataset: config: default name: MTEB HeadlineClassification (default) revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb split: test type: ai-forever/headline-classification 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: config: default name: MTEB InappropriatenessClassification (default) revision: 601651fdc45ef243751676e62dd7a19f491c0285 split: test type: ai-forever/inappropriateness-classification 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: config: default name: MTEB KinopoiskClassification (default) revision: 5911f26666ac11af46cb9c6849d0dc80a378af24 split: test type: ai-forever/kinopoisk-sentiment-classification 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: config: default name: MTEB LanguageClassification (default) revision: aa56583bf2bc52b0565770607d6fc3faebecf9e2 split: test type: papluca/language-identification 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: Classification
- dataset: config: ru name: MTEB MLSUMClusteringP2P (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:
  - type: main_score value: 42.11280087032343
  - type: v_measure value: 42.11280087032343
  - type: v_measure_std value: 6.7619971723605135 task: type: Clustering
- dataset: config: ru name: MTEB MLSUMClusteringP2P.v2 (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:
  - type: main_score value: 43.00112546945811
  - type: v_measure value: 43.00112546945811
  - type: v_measure_std value: 1.4740560414835675 task: type: Clustering
- dataset: config: ru name: MTEB MLSUMClusteringS2S (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:
  - type: main_score value: 39.81446080575161
  - type: v_measure value: 39.81446080575161
  - type: v_measure_std value: 7.125661320308298 task: type: Clustering
- dataset: config: ru name: MTEB MLSUMClusteringS2S.v2 (ru) revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7 split: test type: reciTAL/mlsum metrics:
  - type: main_score value: 39.29659668980239
  - type: v_measure value: 39.29659668980239
  - type: v_measure_std value: 2.6570502923023094 task: type: Clustering
- dataset: config: ru name: MTEB MultiLongDocRetrieval (ru) revision: d67138e705d963e346253a80e59676ddb418810a split: dev type: Shitao/MLDR 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
  - type: nauc_map_at_100_diff1 value: 55.598419532054734
  - type: nauc_map_at_100_max value: 52.48192017040307
  - type: nauc_map_at_100_std value: 2.930120252521189
  - type: nauc_map_at_10_diff1 value: 56.02309155375198
  - type: nauc_map_at_10_max value: 52.739573233234424
  - type: nauc_map_at_10_std value: 2.4073432421641545
  - type: nauc_map_at_1_diff1 value: 52.57059856776112
  - type: nauc_map_at_1_max value: 50.55668152952304
  - type: nauc_map_at_1_std value: 1.6572084853398048
  - type: nauc_map_at_20_diff1 value: 55.75769029917031
  - type: nauc_map_at_20_max value: 52.53663737242853
  - type: nauc_map_at_20_std value: 2.8489192879814
  - type: nauc_map_at_3_diff1 value: 56.90294128342709
  - type: nauc_map_at_3_max value: 53.10608389782041
  - type: nauc_map_at_3_std value: 1.4909731657889491
  - type: nauc_map_at_5_diff1 value: 56.1258315436073
  - type: nauc_map_at_5_max value: 52.398078357541564
  - type: nauc_map_at_5_std value: 1.8256862015101467
  - type: nauc_mrr_at_1000_diff1 value: 55.61987610843598
  - type: nauc_mrr_at_1000_max value: 52.506795017152186
  - type: nauc_mrr_at_1000_std value: 2.95487192066911
  - type: nauc_mrr_at_100_diff1 value: 55.598419532054734
  - type: nauc_mrr_at_100_max value: 52.48192017040307
  - type: nauc_mrr_at_100_std value: 2.930120252521189
  - type: nauc_mrr_at_10_diff1 value: 56.02309155375198
  - type: nauc_mrr_at_10_max value: 52.739573233234424
  - type: nauc_mrr_at_10_std value: 2.4073432421641545
  - type: nauc_mrr_at_1_diff1 value: 52.57059856776112
  - 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 value: 57.25924020238401
  - 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
  - type: nauc_precision_at_100_std 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
  - type: nauc_precision_at_5_diff1 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: Retrieval
- dataset: config: rus name: MTEB MultilingualSentimentClassification (rus) revision: 2b9b4d10fc589af67794141fe8cbd3739de1eb33 split: test type: mteb/multilingual-sentiment-classification 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: Classification
- dataset: config: arb_Arab-rus_Cyrl name: MTEB NTREXBitextMining (arb_Arab-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: bel_Cyrl-rus_Cyrl name: MTEB NTREXBitextMining (bel_Cyrl-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: ben_Beng-rus_Cyrl name: MTEB NTREXBitextMining (ben_Beng-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: bos_Latn-rus_Cyrl name: MTEB NTREXBitextMining (bos_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: bul_Cyrl-rus_Cyrl name: MTEB NTREXBitextMining (bul_Cyrl-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: ces_Latn-rus_Cyrl name: MTEB NTREXBitextMining (ces_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: deu_Latn-rus_Cyrl name: MTEB NTREXBitextMining (deu_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: ell_Grek-rus_Cyrl name: MTEB NTREXBitextMining (ell_Grek-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: eng_Latn-rus_Cyrl name: MTEB NTREXBitextMining (eng_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: fas_Arab-rus_Cyrl name: MTEB NTREXBitextMining (fas_Arab-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: fin_Latn-rus_Cyrl name: MTEB NTREXBitextMining (fin_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: fra_Latn-rus_Cyrl name: MTEB NTREXBitextMining (fra_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: heb_Hebr-rus_Cyrl name: MTEB NTREXBitextMining (heb_Hebr-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: hin_Deva-rus_Cyrl name: MTEB NTREXBitextMining (hin_Deva-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: hrv_Latn-rus_Cyrl name: MTEB NTREXBitextMining (hrv_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: hun_Latn-rus_Cyrl name: MTEB NTREXBitextMining (hun_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: ind_Latn-rus_Cyrl name: MTEB NTREXBitextMining (ind_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: jpn_Jpan-rus_Cyrl name: MTEB NTREXBitextMining (jpn_Jpan-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: kor_Hang-rus_Cyrl name: MTEB NTREXBitextMining (kor_Hang-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: lit_Latn-rus_Cyrl name: MTEB NTREXBitextMining (lit_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: mkd_Cyrl-rus_Cyrl name: MTEB NTREXBitextMining (mkd_Cyrl-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: nld_Latn-rus_Cyrl name: MTEB NTREXBitextMining (nld_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: pol_Latn-rus_Cyrl name: MTEB NTREXBitextMining (pol_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: por_Latn-rus_Cyrl name: MTEB NTREXBitextMining (por_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-arb_Arab name: MTEB NTREXBitextMining (rus_Cyrl-arb_Arab) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-bel_Cyrl name: MTEB NTREXBitextMining (rus_Cyrl-bel_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-ben_Beng name: MTEB NTREXBitextMining (rus_Cyrl-ben_Beng) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-bos_Latn name: MTEB NTREXBitextMining (rus_Cyrl-bos_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-bul_Cyrl name: MTEB NTREXBitextMining (rus_Cyrl-bul_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-ces_Latn name: MTEB NTREXBitextMining (rus_Cyrl-ces_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-deu_Latn name: MTEB NTREXBitextMining (rus_Cyrl-deu_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-ell_Grek name: MTEB NTREXBitextMining (rus_Cyrl-ell_Grek) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-eng_Latn name: MTEB NTREXBitextMining (rus_Cyrl-eng_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-fas_Arab name: MTEB NTREXBitextMining (rus_Cyrl-fas_Arab) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-fin_Latn name: MTEB NTREXBitextMining (rus_Cyrl-fin_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-fra_Latn name: MTEB NTREXBitextMining (rus_Cyrl-fra_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-heb_Hebr name: MTEB NTREXBitextMining (rus_Cyrl-heb_Hebr) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-hin_Deva name: MTEB NTREXBitextMining (rus_Cyrl-hin_Deva) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-hrv_Latn name: MTEB NTREXBitextMining (rus_Cyrl-hrv_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-hun_Latn name: MTEB NTREXBitextMining (rus_Cyrl-hun_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-ind_Latn name: MTEB NTREXBitextMining (rus_Cyrl-ind_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-jpn_Jpan name: MTEB NTREXBitextMining (rus_Cyrl-jpn_Jpan) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-kor_Hang name: MTEB NTREXBitextMining (rus_Cyrl-kor_Hang) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-lit_Latn name: MTEB NTREXBitextMining (rus_Cyrl-lit_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-mkd_Cyrl name: MTEB NTREXBitextMining (rus_Cyrl-mkd_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-nld_Latn name: MTEB NTREXBitextMining (rus_Cyrl-nld_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-pol_Latn name: MTEB NTREXBitextMining (rus_Cyrl-pol_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-por_Latn name: MTEB NTREXBitextMining (rus_Cyrl-por_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-slk_Latn name: MTEB NTREXBitextMining (rus_Cyrl-slk_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-slv_Latn name: MTEB NTREXBitextMining (rus_Cyrl-slv_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-spa_Latn name: MTEB NTREXBitextMining (rus_Cyrl-spa_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-srp_Cyrl name: MTEB NTREXBitextMining (rus_Cyrl-srp_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-srp_Latn name: MTEB NTREXBitextMining (rus_Cyrl-srp_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-swa_Latn name: MTEB NTREXBitextMining (rus_Cyrl-swa_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-swe_Latn name: MTEB NTREXBitextMining (rus_Cyrl-swe_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-tam_Taml name: MTEB NTREXBitextMining (rus_Cyrl-tam_Taml) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-tur_Latn name: MTEB NTREXBitextMining (rus_Cyrl-tur_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-ukr_Cyrl name: MTEB NTREXBitextMining (rus_Cyrl-ukr_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-vie_Latn name: MTEB NTREXBitextMining (rus_Cyrl-vie_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-zho_Hant name: MTEB NTREXBitextMining (rus_Cyrl-zho_Hant) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: rus_Cyrl-zul_Latn name: MTEB NTREXBitextMining (rus_Cyrl-zul_Latn) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: slk_Latn-rus_Cyrl name: MTEB NTREXBitextMining (slk_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: slv_Latn-rus_Cyrl name: MTEB NTREXBitextMining (slv_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: spa_Latn-rus_Cyrl name: MTEB NTREXBitextMining (spa_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: srp_Cyrl-rus_Cyrl name: MTEB NTREXBitextMining (srp_Cyrl-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: srp_Latn-rus_Cyrl name: MTEB NTREXBitextMining (srp_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: swa_Latn-rus_Cyrl name: MTEB NTREXBitextMining (swa_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: swe_Latn-rus_Cyrl name: MTEB NTREXBitextMining (swe_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: tam_Taml-rus_Cyrl name: MTEB NTREXBitextMining (tam_Taml-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: tur_Latn-rus_Cyrl name: MTEB NTREXBitextMining (tur_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: ukr_Cyrl-rus_Cyrl name: MTEB NTREXBitextMining (ukr_Cyrl-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: vie_Latn-rus_Cyrl name: MTEB NTREXBitextMining (vie_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: zho_Hant-rus_Cyrl name: MTEB NTREXBitextMining (zho_Hant-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: config: zul_Latn-rus_Cyrl name: MTEB NTREXBitextMining (zul_Latn-rus_Cyrl) revision: ed9a4403ed4adbfaf4aab56d5b2709e9f6c3ba33 split: test type: mteb/NTREX 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: BitextMining
- dataset: config: ru name: MTEB OpusparcusPC (ru) revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a split: test.full type: GEM/opusparcus 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
  - type: dot_ap value: 86.51934769946833
  - type: dot_f1 value: 80.84358523725834
  - type: dot_f1_threshold value: 86.90648078918457
  - type: dot_precision value: 73.24840764331209
  - type: dot_recall value: 90.19607843137256
  - type: euclidean_accuracy value: 73.09136420525657
  - type: euclidean_accuracy_threshold value: 49.590304493904114
  - type: euclidean_ap value: 86.51934769946833
  - type: euclidean_f1 value: 80.84358523725834
  - type: euclidean_f1_threshold value: 51.173269748687744
  - type: euclidean_precision value: 73.24840764331209
  - type: euclidean_recall value: 90.19607843137256
  - type: main_score value: 86.51976811057995
  - type: manhattan_accuracy value: 73.40425531914893
  - type: manhattan_accuracy_threshold value: 757.8278541564941
  - type: manhattan_ap value: 86.51976811057995
  - type: manhattan_f1 value: 80.92898615453328
  - type: manhattan_f1_threshold value: 778.3821105957031
  - type: manhattan_precision value: 74.32321575061526
  - type: manhattan_recall value: 88.8235294117647
  - type: max_ap value: 86.51976811057995
  - type: max_f1 value: 80.92898615453328
  - type: max_precision value: 74.32321575061526
  - type: max_recall value: 90.19607843137256
  - type: similarity_accuracy value: 73.09136420525657
  - type: similarity_accuracy_threshold value: 87.70400881767273
  - type: similarity_ap value: 86.51938550599533
  - type: similarity_f1 value: 80.84358523725834
  - type: similarity_f1_threshold value: 86.90648078918457
  - type: similarity_precision value: 73.24840764331209
  - type: similarity_recall value: 90.19607843137256 task: type: PairClassification
- dataset: config: russian name: MTEB PublicHealthQA (russian) revision: main split: test type: xhluca/publichealth-qa metrics:
  - type: main_score value: 79.303
  - type: map_at_1 value: 61.538000000000004
  - type: map_at_10 value: 74.449
  - type: map_at_100 value: 74.687
  - type: map_at_1000 value: 74.687
  - type: map_at_20 value: 74.589
  - type: map_at_3 value: 73.333
  - type: map_at_5 value: 74.256
  - type: mrr_at_1 value: 61.53846153846154
  - type: mrr_at_10 value: 74.44871794871794
  - type: mrr_at_100 value: 74.68730304304074
  - type: mrr_at_1000 value: 74.68730304304074
  - type: mrr_at_20 value: 74.58857808857809
  - type: mrr_at_3 value: 73.33333333333333
  - type: mrr_at_5 value: 74.25641025641025
  - type: nauc_map_at_1000_diff1 value: 61.375798048778506
  - type: nauc_map_at_1000_max value: 51.37093181241067
  - type: nauc_map_at_1000_std value: 41.735794471409015
  - type: nauc_map_at_100_diff1 value: 61.375798048778506
  - type: nauc_map_at_100_max value: 51.37093181241067
  - type: nauc_map_at_100_std value: 41.735794471409015
  - type: nauc_map_at_10_diff1 value: 61.12796039757213
  - type: nauc_map_at_10_max value: 51.843445267118014
  - type: nauc_map_at_10_std value: 42.243121474939365
  - type: nauc_map_at_1_diff1 value: 66.39100974909151
  - type: nauc_map_at_1_max value: 44.77165601342703
  - type: nauc_map_at_1_std value: 32.38542979413408
  - type: nauc_map_at_20_diff1 value: 61.16611123434347
  - type: nauc_map_at_20_max value: 51.52605092407306
  - type: nauc_map_at_20_std value: 41.94787773313971
  - type: nauc_map_at_3_diff1 value: 61.40157474408937
  - type: nauc_map_at_3_max value: 51.47230077853947
  - type: nauc_map_at_3_std value: 42.63540269440141
  - type: nauc_map_at_5_diff1 value: 61.07631147583098
  - type: nauc_map_at_5_max value: 52.02626939341523
  - type: nauc_map_at_5_std value: 42.511607332150334
  - type: nauc_mrr_at_1000_diff1 value: 61.375798048778506
  - type: nauc_mrr_at_1000_max value: 51.37093181241067
  - type: nauc_mrr_at_1000_std value: 41.735794471409015
  - type: nauc_mrr_at_100_diff1 value: 61.375798048778506
  - type: nauc_mrr_at_100_max value: 51.37093181241067
  - type: nauc_mrr_at_100_std value: 41.735794471409015
  - type: nauc_mrr_at_10_diff1 value: 61.12796039757213
  - type: nauc_mrr_at_10_max value: 51.843445267118014
  - type: nauc_mrr_at_10_std value: 42.243121474939365
  - type: nauc_mrr_at_1_diff1 value: 66.39100974909151
  - type: nauc_mrr_at_1_max value: 44.77165601342703
  - type: nauc_mrr_at_1_std value: 32.38542979413408
  - type: nauc_mrr_at_20_diff1 value: 61.16611123434347
  - type: nauc_mrr_at_20_max value: 51.52605092407306
  - type: nauc_mrr_at_20_std value: 41.94787773313971
  - type: nauc_mrr_at_3_diff1 value: 61.40157474408937
  - type: nauc_mrr_at_3_max value: 51.47230077853947
  - type: nauc_mrr_at_3_std value: 42.63540269440141
  - type: nauc_mrr_at_5_diff1 value: 61.07631147583098
  - type: nauc_mrr_at_5_max value: 52.02626939341523
  - type: nauc_mrr_at_5_std value: 42.511607332150334
  - type: nauc_ndcg_at_1000_diff1 value: 60.54821630436157
  - type: nauc_ndcg_at_1000_max value: 52.584328363863634
  - type: nauc_ndcg_at_1000_std value: 43.306961101645946
  - type: nauc_ndcg_at_100_diff1 value: 60.54821630436157
  - type: nauc_ndcg_at_100_max value: 52.584328363863634
  - type: nauc_ndcg_at_100_std value: 43.306961101645946
  - type: nauc_ndcg_at_10_diff1 value: 58.800340278109886
  - type: nauc_ndcg_at_10_max value: 55.31050771670664
  - type: nauc_ndcg_at_10_std value: 46.40931672942848
  - type: nauc_ndcg_at_1_diff1 value: 66.39100974909151
  - type: nauc_ndcg_at_1_max value: 44.77165601342703
  - type: nauc_ndcg_at_1_std value: 32.38542979413408
  - type: nauc_ndcg_at_20_diff1 value: 58.88690479697946
  - type: nauc_ndcg_at_20_max value: 54.19269661177923
  - type: nauc_ndcg_at_20_std value: 45.39305589413174
  - type: nauc_ndcg_at_3_diff1 value: 59.61866351451574
  - type: nauc_ndcg_at_3_max value: 54.23992718744033
  - type: nauc_ndcg_at_3_std value: 46.997379274101
  - type: nauc_ndcg_at_5_diff1 value: 58.70739588066225
  - type: nauc_ndcg_at_5_max value: 55.76766902539152
  - type: nauc_ndcg_at_5_std value: 47.10553115762958
  - 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: .nan
  - type: nauc_precision_at_100_max value: .nan
  - type: nauc_precision_at_100_std value: .nan
  - type: nauc_precision_at_10_diff1 value: 35.72622112397501
  - type: nauc_precision_at_10_max value: 89.84297108673948
  - type: nauc_precision_at_10_std value: 86.60269192422707
  - type: nauc_precision_at_1_diff1 value: 66.39100974909151
  - type: nauc_precision_at_1_max value: 44.77165601342703
  - type: nauc_precision_at_1_std value: 32.38542979413408
  - type: nauc_precision_at_20_diff1 value: 29.188449183726433
  - type: nauc_precision_at_20_max value: 86.45729478231968
  - type: nauc_precision_at_20_std value: 86.45729478231968
  - type: nauc_precision_at_3_diff1 value: 50.294126629236224
  - type: nauc_precision_at_3_max value: 68.98223127174579
  - type: nauc_precision_at_3_std value: 70.31195520376356
  - type: nauc_precision_at_5_diff1 value: 39.648884288124385
  - type: nauc_precision_at_5_max value: 86.3409770687935
  - type: nauc_precision_at_5_std value: 83.74875373878356
  - 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: 35.72622112397516
  - type: nauc_recall_at_10_max value: 89.84297108673968
  - type: nauc_recall_at_10_std value: 86.60269192422749
  - type: nauc_recall_at_1_diff1 value: 66.39100974909151
  - type: nauc_recall_at_1_max value: 44.77165601342703
  - type: nauc_recall_at_1_std value: 32.38542979413408
  - type: nauc_recall_at_20_diff1 value: 29.188449183726323
  - type: nauc_recall_at_20_max value: 86.45729478231985
  - type: nauc_recall_at_20_std value: 86.45729478231985
  - type: nauc_recall_at_3_diff1 value: 50.29412662923603
  - type: nauc_recall_at_3_max value: 68.98223127174562
  - type: nauc_recall_at_3_std value: 70.31195520376346
  - type: nauc_recall_at_5_diff1 value: 39.64888428812445
  - type: nauc_recall_at_5_max value: 86.34097706879359
  - type: nauc_recall_at_5_std value: 83.74875373878366
  - type: ndcg_at_1 value: 61.538000000000004
  - type: ndcg_at_10 value: 79.303
  - type: ndcg_at_100 value: 80.557
  - type: ndcg_at_1000 value: 80.557
  - type: ndcg_at_20 value: 79.732
  - type: ndcg_at_3 value: 77.033
  - type: ndcg_at_5 value: 78.818
  - type: precision_at_1 value: 61.538000000000004
  - type: precision_at_10 value: 9.385
  - type: precision_at_100 value: 1.0
  - type: precision_at_1000 value: 0.1
  - type: precision_at_20 value: 4.769
  - type: precision_at_3 value: 29.231
  - type: precision_at_5 value: 18.462
  - type: recall_at_1 value: 61.538000000000004
  - type: recall_at_10 value: 93.84599999999999
  - type: recall_at_100 value: 100.0
  - type: recall_at_1000 value: 100.0
  - type: recall_at_20 value: 95.38499999999999
  - type: recall_at_3 value: 87.69200000000001
  - type: recall_at_5 value: 92.308 task: type: Retrieval
- dataset: config: default name: MTEB RUParaPhraserSTS (default) revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4 split: test type: merionum/ru_paraphraser metrics:
  - type: cosine_pearson value: 64.73554596215753
  - type: cosine_spearman value: 70.45849652271855
  - type: euclidean_pearson value: 68.08069844834267
  - type: euclidean_spearman value: 70.45854872959124
  - type: main_score value: 70.45849652271855
  - type: manhattan_pearson value: 67.88325986519624
  - type: manhattan_spearman value: 70.21131896834542
  - type: pearson value: 64.73554596215753
  - type: spearman value: 70.45849652271855 task: type: STS
- dataset: config: default name: MTEB RiaNewsRetrieval (default) revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7 split: test type: ai-forever/ria-news-retrieval metrics:
  - type: main_score value: 70.00999999999999
  - type: map_at_1 value: 55.97
  - type: map_at_10 value: 65.59700000000001
  - type: map_at_100 value: 66.057
  - type: map_at_1000 value: 66.074
  - type: map_at_20 value: 65.892
  - type: map_at_3 value: 63.74999999999999
  - type: map_at_5 value: 64.84299999999999
  - type: mrr_at_1 value: 55.88999999999999
  - type: mrr_at_10 value: 65.55873015872977
  - type: mrr_at_100 value: 66.01891495129716
  - type: mrr_at_1000 value: 66.03538391493299
  - type: mrr_at_20 value: 65.85351193431555
  - type: mrr_at_3 value: 63.7133333333329
  - type: mrr_at_5 value: 64.80483333333268
  - type: nauc_map_at_1000_diff1 value: 65.95332946436318
  - type: nauc_map_at_1000_max value: 28.21204156197811
  - type: nauc_map_at_1000_std value: -13.139245767083743
  - type: nauc_map_at_100_diff1 value: 65.94763105024367
  - type: nauc_map_at_100_max value: 28.212832170078205
  - type: nauc_map_at_100_std value: -13.131425849370665
  - type: nauc_map_at_10_diff1 value: 65.88455089448388
  - type: nauc_map_at_10_max value: 28.13555838776792
  - type: nauc_map_at_10_std value: -13.326989827081023
  - type: nauc_map_at_1_diff1 value: 69.31275711813979
  - type: nauc_map_at_1_max value: 26.386708520283758
  - type: nauc_map_at_1_std value: -14.434616447245464
  - type: nauc_map_at_20_diff1 value: 65.91227032605677
  - type: nauc_map_at_20_max value: 28.20538655600886
  - type: nauc_map_at_20_std value: -13.191148834410274
  - type: nauc_map_at_3_diff1 value: 66.0051677952641
  - type: nauc_map_at_3_max value: 28.25443420019022
  - type: nauc_map_at_3_std value: -13.893284109029558
  - type: nauc_map_at_5_diff1 value: 65.89784348297898
  - type: nauc_map_at_5_max value: 28.26449765184183
  - type: nauc_map_at_5_std value: -13.506692912805008
  - type: nauc_mrr_at_1000_diff1 value: 66.06599513750889
  - type: nauc_mrr_at_1000_max value: 28.191556650722287
  - type: nauc_mrr_at_1000_std value: -13.098487982930276
  - type: nauc_mrr_at_100_diff1 value: 66.0602307977725
  - type: nauc_mrr_at_100_max value: 28.19235936624514
  - type: nauc_mrr_at_100_std value: -13.09069677716269
  - type: nauc_mrr_at_10_diff1 value: 65.99546819079403
  - type: nauc_mrr_at_10_max value: 28.11556170120022
  - type: nauc_mrr_at_10_std value: -13.286711073897553
  - type: nauc_mrr_at_1_diff1 value: 69.49541040517995
  - type: nauc_mrr_at_1_max value: 26.354622707276153
  - type: nauc_mrr_at_1_std value: -14.358839778104695
  - type: nauc_mrr_at_20_diff1 value: 66.02427154257936
  - type: nauc_mrr_at_20_max value: 28.18509383563462
  - type: nauc_mrr_at_20_std value: -13.150543398429
  - type: nauc_mrr_at_3_diff1 value: 66.11258119082618
  - type: nauc_mrr_at_3_max value: 28.239510722224004
  - type: nauc_mrr_at_3_std value: -13.857249251136269
  - type: nauc_mrr_at_5_diff1 value: 66.00633786765626
  - type: nauc_mrr_at_5_max value: 28.244875152193032
  - type: nauc_mrr_at_5_std value: -13.467206028704434
  - type: nauc_ndcg_at_1000_diff1 value: 65.02876183314446
  - type: nauc_ndcg_at_1000_max value: 29.109368390197194
  - type: nauc_ndcg_at_1000_std value: -11.56514359821697
  - type: nauc_ndcg_at_100_diff1 value: 64.85837726893713
  - type: nauc_ndcg_at_100_max value: 29.19990133137256
  - type: nauc_ndcg_at_100_std value: -11.17450348161257
  - type: nauc_ndcg_at_10_diff1 value: 64.53842705024796
  - type: nauc_ndcg_at_10_max value: 28.748734006088526
  - type: nauc_ndcg_at_10_std value: -12.331395505957063
  - type: nauc_ndcg_at_1_diff1 value: 69.31275711813979
  - type: nauc_ndcg_at_1_max value: 26.386708520283758
  - type: nauc_ndcg_at_1_std value: -14.434616447245464
  - type: nauc_ndcg_at_20_diff1 value: 64.59017606740504
  - type: nauc_ndcg_at_20_max value: 29.047332048898017
  - type: nauc_ndcg_at_20_std value: -11.746548770195954
  - type: nauc_ndcg_at_3_diff1 value: 64.87900935713822
  - type: nauc_ndcg_at_3_max value: 28.953157521204403
  - type: nauc_ndcg_at_3_std value: -13.639947228880942
  - type: nauc_ndcg_at_5_diff1 value: 64.61466953479034
  - type: nauc_ndcg_at_5_max value: 29.01899321868392
  - type: nauc_ndcg_at_5_std value: -12.85356404799802
  - type: nauc_precision_at_1000_diff1 value: 48.85481417002382
  - type: nauc_precision_at_1000_max value: 57.129837326696375
  - type: nauc_precision_at_1000_std value: 37.889524999906435
  - type: nauc_precision_at_100_diff1 value: 53.374672326788264
  - type: nauc_precision_at_100_max value: 43.819333062207974
  - type: nauc_precision_at_100_std value: 21.387064885769362
  - type: nauc_precision_at_10_diff1 value: 57.66571169774445
  - type: nauc_precision_at_10_max value: 31.779694837242033
  - type: nauc_precision_at_10_std value: -6.6248399147180255
  - type: nauc_precision_at_1_diff1 value: 69.31275711813979
  - type: nauc_precision_at_1_max value: 26.386708520283758
  - type: nauc_precision_at_1_std value: -14.434616447245464
  - type: nauc_precision_at_20_diff1 value: 55.93570036001682
  - type: nauc_precision_at_20_max value: 34.98640173388743
  - type: nauc_precision_at_20_std value: -0.36518465159326174
  - type: nauc_precision_at_3_diff1 value: 60.94100093991508
  - type: nauc_precision_at_3_max value: 31.422239034357673
  - type: nauc_precision_at_3_std value: -12.72576556537896
  - type: nauc_precision_at_5_diff1 value: 59.450505195434054
  - type: nauc_precision_at_5_max value: 32.07638712418377
  - type: nauc_precision_at_5_std value: -10.024459103498598
  - type: nauc_recall_at_1000_diff1 value: 48.854814170024184
  - type: nauc_recall_at_1000_max value: 57.129837326697164
  - type: nauc_recall_at_1000_std value: 37.88952499990672
  - type: nauc_recall_at_100_diff1 value: 53.37467232678822
  - type: nauc_recall_at_100_max value: 43.8193330622079
  - type: nauc_recall_at_100_std value: 21.387064885769398
  - type: nauc_recall_at_10_diff1 value: 57.66571169774447
  - type: nauc_recall_at_10_max value: 31.779694837242133
  - 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: Retrieval
- dataset: config: default name: MTEB RuBQReranking (default) revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2 split: test type: ai-forever/rubq-reranking 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: Reranking
- dataset: config: default name: MTEB RuBQRetrieval (default) revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b split: test type: ai-forever/rubq-retrieval 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: Retrieval
- dataset: config: default name: MTEB RuReviewsClassification (default) revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a split: test type: ai-forever/ru-reviews-classification 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: Classification
- dataset: config: default name: MTEB RuSTSBenchmarkSTS (default) revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018 split: test type: ai-forever/ru-stsbenchmark-sts 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: STS
- dataset: config: default name: MTEB RuSciBenchGRNTIClassification (default) revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1 split: test type: ai-forever/ru-scibench-grnti-classification 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: Classification
- dataset: config: default name: MTEB RuSciBenchGRNTIClusteringP2P (default) revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1 split: test type: ai-forever/ru-scibench-grnti-classification metrics:
  - type: main_score value: 50.775228895355106
  - type: v_measure value: 50.775228895355106
  - type: v_measure_std value: 0.9533571150165796 task: type: Clustering
- dataset: config: default name: MTEB RuSciBenchOECDClassification (default) revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471 split: test type: ai-forever/ru-scibench-oecd-classification 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: Classification
- dataset: config: default name: MTEB RuSciBenchOECDClusteringP2P (default) revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471 split: test type: ai-forever/ru-scibench-oecd-classification metrics:
  - type: main_score value: 45.10904808834516
  - type: v_measure value: 45.10904808834516
  - type: v_measure_std value: 1.0572643410157534 task: type: Clustering
- dataset: config: rus_Cyrl name: MTEB SIB200Classification (rus_Cyrl) revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b split: test type: mteb/sib200 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: Classification
- dataset: config: rus_Cyrl name: MTEB SIB200ClusteringS2S (rus_Cyrl) revision: a74d7350ea12af010cfb1c21e34f1f81fd2e615b split: test type: mteb/sib200 metrics:
  - type: main_score value: 33.99178497314711
  - type: v_measure value: 33.99178497314711
  - type: v_measure_std value: 4.036337464043786 task: type: Clustering
- dataset: config: ru name: MTEB STS22.v2 (ru) revision: d31f33a128469b20e357535c39b82fb3c3f6f2bd split: test type: mteb/sts22-crosslingual-sts 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: config: ru name: MTEB STSBenchmarkMultilingualSTS (ru) revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c split: dev type: mteb/stsb_multi_mt 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: STS
- dataset: config: default name: MTEB SensitiveTopicsClassification (default) revision: 416b34a802308eac30e4192afc0ff99bb8dcc7f2 split: test type: ai-forever/sensitive-topics-classification metrics:
  - type: accuracy value: 22.8125
  - type: f1 value: 17.31969589593409
  - type: lrap value: 33.82412380642287
  - type: main_score value: 22.8125 task: type: MultilabelClassification
- dataset: config: default name: MTEB TERRa (default) revision: 7b58f24536063837d644aab9a023c62199b2a612 split: dev type: ai-forever/terra-pairclassification 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: config: ru name: MTEB XNLI (ru) revision: 09698e0180d87dc247ca447d3a1248b931ac0cdb split: test type: mteb/xnli 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: config: russian name: MTEB XNLIV2 (russian) revision: 5b7d477a8c62cdd18e2fed7e015497c20b4371ad split: test type: mteb/xnli2.0-multi-pair 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: PairClassification
- dataset: config: ru name: MTEB XQuADRetrieval (ru) revision: 51adfef1c1287aab1d2d91b5bead9bcfb9c68583 split: validation type: google/xquad 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 task: type: Retrieval

tags:

mteb
Sentence Transformers
sentence-similarity
sentence-transformers

Multilingual-E5-small

Multilingual E5 Text Embeddings: A Technical Report. 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.

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 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

First stage: contrastive pre-training with weak supervision

Dataset	Weak supervision	# of text pairs
Filtered mC4	(title, page content)	1B
CC News	(title, news content)	400M
NLLB	translation pairs	2.4B
Wikipedia	(hierarchical section title, passage)	150M
Filtered Reddit	(comment, response)	800M
S2ORC	(title, abstract) and citation pairs	100M
Stackexchange	(question, answer)	50M
xP3	(input prompt, response)	80M
Miscellaneous unsupervised SBERT data	-	10M

Second stage: supervised fine-tuning

Dataset	Language	# of text pairs
MS MARCO	English	500k
NQ	English	70k
Trivia QA	English	60k
NLI from SimCSE	English	<300k
ELI5	English	500k
DuReader Retrieval	Chinese	86k
KILT Fever	English	70k
KILT HotpotQA	English	70k
SQuAD	English	87k
Quora	English	150k
Mr. TyDi	11 languages	50k
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.

Benchmark Results on Mr. TyDi

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 to reproduce evaluation results on the BEIR and MTEB benchmark.

Support for Sentence Transformers

Below is an example for usage with sentence_transformers.

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

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.

Magnet link

Opens the swarm directly in your torrent client — no file download needed. Copy-paste works too:

magnet:?xt=urn:btih:db06a838255d7d9f6365fd01772f4099a22e2f44&dn=intfloat_multilingual-e5-small

Open magnet in torrent client · infohash db06a838255d7d9f6365fd01772f4099a22e2f44

Files & hashes

Path	Size	sha1	sha256
1_Pooling/config.json	200 B (200 B)	acbd4014202bf4dbc6c03229bcbeef7c4feafb58	987f7a67a38fa564c849bb5d277c52ab9088a84368fc0be31a354125aebb12a0
README.md	485.9 KB (497,538 B)	e56327af55e9742caf76bff9ba83b6904cd2003d	0038de97aee16258cecbad7ffda4b4febd6953e747a00e0ddbc8e6ed241e9c1c
config.json	655 B (655 B)	60a2a84020f1d74cc53ea9e8c4e91cf4af6c2b68	69137736cab8b8903a07fe8afaafdda25aac55415a12a55d1bffa9f581abf959
model.safetensors	448.8 MB (470,641,600 B)	402b5e33b448c7d9815d3b1f01a9fb319d6b7065	1a55775f53449dac10a2bcbc312469fac40b96d53198c407081a831f81c98477
modules.json	387 B (387 B)	ac2039abdf6ff023b27c919bb9675cfe378cb10f	c6e29747481e8b5dd2b58401966aeac910de39092f90cda9a704b1545f902b04
onnx/config.json	653 B (653 B)	698e598c24523f3857295b11abec0703d19ea180	bbb7c1333fc4b3e27fbc9cd5d2070aabcc1d4dfb99917c3633e772f97545a6b6
onnx/sentencepiece.bpe.model	4.8 MB (5,069,051 B)	7e88c49faff6c6c136fdf4a3402d0cb534c6ab10	cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
onnx/special_tokens_map.json	167 B (167 B)	e0b1d18ecd0ae4ff1d47bd297d910c0cf83e504b	d05497f1da52c5e09554c0cd874037a083e1dc1b9cfd48034d1c717f1afc07a7
onnx/tokenizer.json	16.3 MB (17,082,730 B)	0fa80703862a830c3905352086e59299ed06b2b2	0b44a9d7b51c3c62626640cda0e2c2f70fdacdc25bbbd68038369d14ebdf4c39
onnx/tokenizer_config.json	443 B (443 B)	059214673d9d6d2ee319411e2ffec8c024b816d5	a1d6bc8734a6f635dc158508bef000f8e2e5a759c7d92f984b2c86e5ff53425b
openvino/openvino_model.bin	448.3 MB (470,027,936 B)	2ba55734ab21ae55ee7f09584e9330c219b20626	22f5a10ec005a1606ec42758dedd52b59dfcb6e3d85de0b6b86946d0bc6cf232
openvino/openvino_model.xml	354.9 KB (363,385 B)	141b2bf7854f27e1b3369fc19c6377bb799bb215	d5268b47f8d05ca885ffbc77f136c3406ac6acdf85c482caec66eebab7fa5176
pytorch_model.bin	448.9 MB (470,681,649 B)	207b94060e7231855352a58ab9c057ee4002d53b	f0ccb64a2edc689fce7b1895f25146740e4075c3da28c8d0e672a8ba49c51167
sentence_bert_config.json	57 B (57 B)	4eca68d85ecd3034cf4174d8a4033a75344ea62d	948201d8329907aae938fa62f9ceeed53f5694dacc2b87b9f3b78b37ee986529
sentencepiece.bpe.model	4.8 MB (5,069,051 B)	7e88c49faff6c6c136fdf4a3402d0cb534c6ab10	cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
special_tokens_map.json	167 B (167 B)	e0b1d18ecd0ae4ff1d47bd297d910c0cf83e504b	d05497f1da52c5e09554c0cd874037a083e1dc1b9cfd48034d1c717f1afc07a7
tokenizer.json	16.3 MB (17,082,730 B)	0fa80703862a830c3905352086e59299ed06b2b2	0b44a9d7b51c3c62626640cda0e2c2f70fdacdc25bbbd68038369d14ebdf4c39
tokenizer_config.json	443 B (443 B)	059214673d9d6d2ee319411e2ffec8c024b816d5	a1d6bc8734a6f635dc158508bef000f8e2e5a759c7d92f984b2c86e5ff53425b

Cite this release

Canonical URL: https://aiseedbank.org/models/intfloat_multilingual-e5-small/
Slug: intfloat_multilingual-e5-small
Infohash: db06a838255d7d9f6365fd01772f4099a22e2f44
License: mit
Signing key fingerprint: 85a3b32c3712427b

Every file carries a locally computed sha256 — verify a download against the signed sums: intfloat_multilingual-e5-small.SHA256SUMS (+ minisign signature).

Provenance

Upstream repository	intfloat/multilingual-e5-small
Revision (pinned)	614241f622f53c4eeff9890bdc4f31cfecc418b3
Fetched at	2026-09-04T01:03:27Z
License at fetch	mit
Snapshot tool	huggingface · seedbank 0.1.0

Trackers

udp://announce.aitorrent.org:6969/announce
http://announce.aitorrent.org:7070/announce
udp://announce2.aitorrent.org:6970/announce
http://announce2.aitorrent.org:7071/announce
udp://tracker.opentrackr.org:1337/announce
udp://open.demonii.com:1337/announce
udp://open.stealth.si:80/announce
udp://exodus.desync.com:6969/announce
udp://tracker.torrent.eu.org:451/announce

✓ verified · rehash-vs-hf-metadata at 2026-09-04T01:03:44Z

mit1.36 GB (1,456,518,842 bytes)sentence-transformerspytorchonnxsafetensorsopenvinobertmtebSentence Transformerssentence-similaritymultilingualmodel-indexeval-resultstext-embeddings-inferenceendpoints_compatible93 languages (af, am, ar …)paper: 2402.05672paper: 2108.08787paper: 2104.08663paper: 2210.07316