18485 lines
486 KiB
Markdown
18485 lines
486 KiB
Markdown
---
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language:
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- multilingual
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- af
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- am
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- ar
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- as
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- az
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- be
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- bg
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- bn
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- br
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- bs
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- ca
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- cs
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- cy
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- da
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- de
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- el
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- en
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- eo
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- es
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- et
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- eu
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- fa
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- fi
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- fr
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- fy
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- ga
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- gd
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- gl
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- gu
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- ha
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- he
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- hi
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- hr
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- hu
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- hy
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- id
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- is
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- it
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- ja
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- jv
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- ka
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- kk
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- km
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- kn
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- ko
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- ku
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- ky
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- la
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- lo
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- lt
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- lv
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- mg
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- mk
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- ml
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- mn
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- mr
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- ms
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- my
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- ne
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- nl
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- 'no'
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- om
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- or
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- pa
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- pl
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- ps
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- pt
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- ro
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- ru
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- sa
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- sd
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- si
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- sk
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- sl
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- so
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- sq
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- sr
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- su
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- sv
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- sw
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- ta
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- te
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- th
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- tl
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- tr
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- ug
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- uk
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- ur
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- uz
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- vi
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- xh
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- yi
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- zh
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license: mit
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model-index:
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- name: intfloat/multilingual-e5-small
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results:
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- dataset:
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config: en
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name: MTEB AmazonCounterfactualClassification (en)
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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split: test
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type: mteb/amazon_counterfactual
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metrics:
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- type: accuracy
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value: 73.79104477611939
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- type: ap
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value: 36.9996434842022
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- type: f1
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value: 67.95453679103099
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task:
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type: Classification
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- dataset:
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config: de
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name: MTEB AmazonCounterfactualClassification (de)
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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split: test
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type: mteb/amazon_counterfactual
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metrics:
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- type: accuracy
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value: 71.64882226980728
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- type: ap
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value: 82.11942130026586
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- type: f1
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value: 69.87963421606715
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task:
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type: Classification
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- dataset:
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config: en-ext
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name: MTEB AmazonCounterfactualClassification (en-ext)
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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split: test
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type: mteb/amazon_counterfactual
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metrics:
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- type: accuracy
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value: 75.8095952023988
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- type: ap
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value: 24.46869495579561
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- type: f1
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value: 63.00108480037597
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task:
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type: Classification
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- dataset:
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config: ja
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name: MTEB AmazonCounterfactualClassification (ja)
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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split: test
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type: mteb/amazon_counterfactual
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metrics:
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- type: accuracy
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value: 64.186295503212
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- type: ap
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value: 15.496804690197042
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- type: f1
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value: 52.07153895475031
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task:
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type: Classification
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- dataset:
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config: default
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name: MTEB AmazonPolarityClassification
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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split: test
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type: mteb/amazon_polarity
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metrics:
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- type: accuracy
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value: 88.699325
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- type: ap
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value: 85.27039559917269
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- type: f1
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value: 88.65556295032513
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task:
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type: Classification
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- dataset:
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config: en
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name: MTEB AmazonReviewsClassification (en)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 44.69799999999999
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- type: f1
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value: 43.73187348654165
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task:
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type: Classification
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- dataset:
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config: de
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name: MTEB AmazonReviewsClassification (de)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 40.245999999999995
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- type: f1
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value: 39.3863530637684
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task:
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type: Classification
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- dataset:
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config: es
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name: MTEB AmazonReviewsClassification (es)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 40.394
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- type: f1
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value: 39.301223469483446
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task:
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type: Classification
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- dataset:
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config: fr
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name: MTEB AmazonReviewsClassification (fr)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 38.864
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- type: f1
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value: 37.97974261868003
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task:
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type: Classification
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- dataset:
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config: ja
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name: MTEB AmazonReviewsClassification (ja)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 37.682
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- type: f1
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value: 37.07399369768313
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task:
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type: Classification
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- dataset:
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config: zh
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name: MTEB AmazonReviewsClassification (zh)
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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split: test
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type: mteb/amazon_reviews_multi
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metrics:
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- type: accuracy
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value: 37.504
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- type: f1
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value: 36.62317273874278
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task:
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type: Classification
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- dataset:
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config: default
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name: MTEB ArguAna
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revision: None
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split: test
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type: arguana
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metrics:
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- type: map_at_1
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value: 19.061
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- type: map_at_10
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value: 31.703
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- type: map_at_100
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value: 32.967
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- type: map_at_1000
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value: 33.001000000000005
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- type: map_at_3
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value: 27.466
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- type: map_at_5
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value: 29.564
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- type: mrr_at_1
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value: 19.559
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- type: mrr_at_10
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value: 31.874999999999996
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- type: mrr_at_100
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value: 33.146
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- type: mrr_at_1000
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value: 33.18
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- type: mrr_at_3
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value: 27.667
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- type: mrr_at_5
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value: 29.74
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- type: ndcg_at_1
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value: 19.061
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- type: ndcg_at_10
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value: 39.062999999999995
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- type: ndcg_at_100
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value: 45.184000000000005
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- type: ndcg_at_1000
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value: 46.115
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- type: ndcg_at_3
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value: 30.203000000000003
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- type: ndcg_at_5
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value: 33.953
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- type: precision_at_1
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value: 19.061
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- type: precision_at_10
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value: 6.279999999999999
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- type: precision_at_100
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value: 0.9129999999999999
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- type: precision_at_1000
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value: 0.099
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- type: precision_at_3
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value: 12.706999999999999
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- type: precision_at_5
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value: 9.431000000000001
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- type: recall_at_1
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value: 19.061
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- type: recall_at_10
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value: 62.802
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- type: recall_at_100
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value: 91.323
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- type: recall_at_1000
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value: 98.72
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- type: recall_at_3
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value: 38.122
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- type: recall_at_5
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value: 47.155
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task:
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type: Retrieval
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- dataset:
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config: default
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name: MTEB ArxivClusteringP2P
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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split: test
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type: mteb/arxiv-clustering-p2p
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metrics:
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- type: v_measure
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value: 39.22266660528253
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task:
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type: Clustering
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- dataset:
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config: default
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name: MTEB ArxivClusteringS2S
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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split: test
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type: mteb/arxiv-clustering-s2s
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metrics:
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- type: v_measure
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value: 30.79980849482483
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task:
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type: Clustering
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- dataset:
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config: default
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name: MTEB AskUbuntuDupQuestions
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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split: test
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type: mteb/askubuntudupquestions-reranking
|
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metrics:
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- type: map
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value: 57.8790068352054
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- type: mrr
|
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value: 71.78791276436706
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task:
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type: Reranking
|
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- dataset:
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config: default
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name: MTEB BIOSSES
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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split: test
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type: mteb/biosses-sts
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metrics:
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- type: cos_sim_pearson
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value: 82.36328364043163
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- type: cos_sim_spearman
|
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value: 82.26211536195868
|
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- type: euclidean_pearson
|
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value: 80.3183865039173
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- type: euclidean_spearman
|
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value: 79.88495276296132
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- type: manhattan_pearson
|
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value: 80.14484480692127
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- type: manhattan_spearman
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value: 80.39279565980743
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task:
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type: STS
|
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- dataset:
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config: de-en
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name: MTEB BUCC (de-en)
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revision: d51519689f32196a32af33b075a01d0e7c51e252
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split: test
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type: mteb/bucc-bitext-mining
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metrics:
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- type: accuracy
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value: 98.0375782881002
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- type: f1
|
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value: 97.86012526096033
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- type: precision
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value: 97.77139874739039
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- type: recall
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value: 98.0375782881002
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task:
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type: BitextMining
|
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- dataset:
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config: fr-en
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name: MTEB BUCC (fr-en)
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revision: d51519689f32196a32af33b075a01d0e7c51e252
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split: test
|
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type: mteb/bucc-bitext-mining
|
|
metrics:
|
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- type: accuracy
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value: 93.35241030156286
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- type: f1
|
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value: 92.66050333846944
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- type: precision
|
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value: 92.3306919069631
|
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- type: recall
|
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value: 93.35241030156286
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task:
|
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type: BitextMining
|
|
- dataset:
|
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config: ru-en
|
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name: MTEB BUCC (ru-en)
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revision: d51519689f32196a32af33b075a01d0e7c51e252
|
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split: test
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type: mteb/bucc-bitext-mining
|
|
metrics:
|
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- type: accuracy
|
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value: 94.0699688257707
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- type: f1
|
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value: 93.50236693222492
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- type: precision
|
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value: 93.22791825424315
|
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- type: recall
|
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value: 94.0699688257707
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|
task:
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type: BitextMining
|
|
- dataset:
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config: zh-en
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name: MTEB BUCC (zh-en)
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revision: d51519689f32196a32af33b075a01d0e7c51e252
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split: test
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type: mteb/bucc-bitext-mining
|
|
metrics:
|
|
- type: accuracy
|
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value: 89.25750394944708
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- type: f1
|
|
value: 88.79234684921889
|
|
- type: precision
|
|
value: 88.57293312269616
|
|
- type: recall
|
|
value: 89.25750394944708
|
|
task:
|
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type: BitextMining
|
|
- dataset:
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config: default
|
|
name: MTEB Banking77Classification
|
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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|
split: test
|
|
type: mteb/banking77
|
|
metrics:
|
|
- type: accuracy
|
|
value: 79.41558441558442
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|
- type: f1
|
|
value: 79.25886487487219
|
|
task:
|
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type: Classification
|
|
- dataset:
|
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config: default
|
|
name: MTEB BiorxivClusteringP2P
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|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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|
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
|
|
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|
task:
|
|
type: Retrieval
|
|
- dataset:
|
|
config: eng_Latn-rus_Cyrl
|
|
name: MTEB BelebeleRetrieval (eng_Latn-rus_Cyrl)
|
|
revision: 75b399394a9803252cfec289d103de462763db7c
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|
split: test
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|
type: facebook/belebele
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|
metrics:
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|
- type: nauc_precision_at_1000_max
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|
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|
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- type: nauc_precision_at_1000_std
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|
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- type: nauc_precision_at_100_diff1
|
|
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|
|
- type: nauc_precision_at_100_max
|
|
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|
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- type: nauc_precision_at_100_std
|
|
value: 85.60090702947922
|
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- type: nauc_precision_at_10_diff1
|
|
value: 76.26517273576093
|
|
- type: nauc_precision_at_10_max
|
|
value: 65.2013694366636
|
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- 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
|
|
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|
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- type: nauc_precision_at_20_diff1
|
|
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- type: nauc_precision_at_20_max
|
|
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|
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- type: nauc_precision_at_20_std
|
|
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|
|
- type: nauc_precision_at_3_diff1
|
|
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|
|
- type: nauc_precision_at_3_max
|
|
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|
|
- type: nauc_precision_at_3_std
|
|
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|
|
- type: nauc_precision_at_5_diff1
|
|
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|
|
- 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
|
|
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|
task:
|
|
type: Retrieval
|
|
- dataset:
|
|
config: default
|
|
name: MTEB RuBQReranking (default)
|
|
revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
|
|
split: test
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|
type: ai-forever/rubq-reranking
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|
metrics:
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|
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|
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|
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|
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value: 22.47139593052269
|
|
task:
|
|
type: Reranking
|
|
- dataset:
|
|
config: default
|
|
name: MTEB RuBQRetrieval (default)
|
|
revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
|
|
split: test
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|
type: ai-forever/rubq-retrieval
|
|
metrics:
|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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](https://arxiv.org/pdf/2402.05672).
|
|
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024
|
|
|
|
This model has 12 layers and the embedding size is 384.
|
|
|
|
## Usage
|
|
|
|
Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
|
|
|
|
```python
|
|
import torch.nn.functional as F
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from torch import Tensor
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from transformers import AutoTokenizer, AutoModel
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def average_pool(last_hidden_states: Tensor,
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attention_mask: Tensor) -> Tensor:
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last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
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return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
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# Each input text should start with "query: " or "passage: ", even for non-English texts.
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# For tasks other than retrieval, you can simply use the "query: " prefix.
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input_texts = ['query: how much protein should a female eat',
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'query: 南瓜的家常做法',
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"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.",
|
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"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"]
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tokenizer = AutoTokenizer.from_pretrained('intfloat/multilingual-e5-small')
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model = AutoModel.from_pretrained('intfloat/multilingual-e5-small')
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# Tokenize the input texts
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batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
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outputs = model(**batch_dict)
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embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
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# normalize embeddings
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embeddings = F.normalize(embeddings, p=2, dim=1)
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scores = (embeddings[:2] @ embeddings[2:].T) * 100
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print(scores.tolist())
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```
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## Supported Languages
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This model is initialized from [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384)
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and continually trained on a mixture of multilingual datasets.
|
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It supports 100 languages from xlm-roberta,
|
|
but low-resource languages may see performance degradation.
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## Training Details
|
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|
**Initialization**: [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384)
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|
**First stage**: contrastive pre-training with weak supervision
|
|
|
|
| Dataset | Weak supervision | # of text pairs |
|
|
|--------------------------------------------------------------------------------------------------------|---------------------------------------|-----------------|
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| Filtered [mC4](https://huggingface.co/datasets/mc4) | (title, page content) | 1B |
|
|
| [CC News](https://huggingface.co/datasets/intfloat/multilingual_cc_news) | (title, news content) | 400M |
|
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| [NLLB](https://huggingface.co/datasets/allenai/nllb) | translation pairs | 2.4B |
|
|
| [Wikipedia](https://huggingface.co/datasets/intfloat/wikipedia) | (hierarchical section title, passage) | 150M |
|
|
| Filtered [Reddit](https://www.reddit.com/) | (comment, response) | 800M |
|
|
| [S2ORC](https://github.com/allenai/s2orc) | (title, abstract) and citation pairs | 100M |
|
|
| [Stackexchange](https://stackexchange.com/) | (question, answer) | 50M |
|
|
| [xP3](https://huggingface.co/datasets/bigscience/xP3) | (input prompt, response) | 80M |
|
|
| [Miscellaneous unsupervised SBERT data](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) | - | 10M |
|
|
|
|
**Second stage**: supervised fine-tuning
|
|
|
|
| Dataset | Language | # of text pairs |
|
|
|----------------------------------------------------------------------------------------|--------------|-----------------|
|
|
| [MS MARCO](https://microsoft.github.io/msmarco/) | English | 500k |
|
|
| [NQ](https://github.com/facebookresearch/DPR) | English | 70k |
|
|
| [Trivia QA](https://github.com/facebookresearch/DPR) | English | 60k |
|
|
| [NLI from SimCSE](https://github.com/princeton-nlp/SimCSE) | English | <300k |
|
|
| [ELI5](https://huggingface.co/datasets/eli5) | English | 500k |
|
|
| [DuReader Retrieval](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval) | Chinese | 86k |
|
|
| [KILT Fever](https://huggingface.co/datasets/kilt_tasks) | English | 70k |
|
|
| [KILT HotpotQA](https://huggingface.co/datasets/kilt_tasks) | English | 70k |
|
|
| [SQuAD](https://huggingface.co/datasets/squad) | English | 87k |
|
|
| [Quora](https://huggingface.co/datasets/quora) | English | 150k |
|
|
| [Mr. TyDi](https://huggingface.co/datasets/castorini/mr-tydi) | 11 languages | 50k |
|
|
| [MIRACL](https://huggingface.co/datasets/miracl/miracl) | 16 languages | 40k |
|
|
|
|
For all labeled datasets, we only use its training set for fine-tuning.
|
|
|
|
For other training details, please refer to our paper at [https://arxiv.org/pdf/2402.05672](https://arxiv.org/pdf/2402.05672).
|
|
|
|
## Benchmark Results on [Mr. TyDi](https://arxiv.org/abs/2108.08787)
|
|
|
|
| Model | Avg MRR@10 | | ar | bn | en | fi | id | ja | ko | ru | sw | te | th |
|
|
|-----------------------|------------|-------|------| --- | --- | --- | --- | --- | --- | --- |------| --- | --- |
|
|
| BM25 | 33.3 | | 36.7 | 41.3 | 15.1 | 28.8 | 38.2 | 21.7 | 28.1 | 32.9 | 39.6 | 42.4 | 41.7 |
|
|
| mDPR | 16.7 | | 26.0 | 25.8 | 16.2 | 11.3 | 14.6 | 18.1 | 21.9 | 18.5 | 7.3 | 10.6 | 13.5 |
|
|
| BM25 + mDPR | 41.7 | | 49.1 | 53.5 | 28.4 | 36.5 | 45.5 | 35.5 | 36.2 | 42.7 | 40.5 | 42.0 | 49.2 |
|
|
| | |
|
|
| multilingual-e5-small | 64.4 | | 71.5 | 66.3 | 54.5 | 57.7 | 63.2 | 55.4 | 54.3 | 60.8 | 65.4 | 89.1 | 70.1 |
|
|
| multilingual-e5-base | 65.9 | | 72.3 | 65.0 | 58.5 | 60.8 | 64.9 | 56.6 | 55.8 | 62.7 | 69.0 | 86.6 | 72.7 |
|
|
| multilingual-e5-large | **70.5** | | 77.5 | 73.2 | 60.8 | 66.8 | 68.5 | 62.5 | 61.6 | 65.8 | 72.7 | 90.2 | 76.2 |
|
|
|
|
## MTEB Benchmark Evaluation
|
|
|
|
Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results
|
|
on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
|
|
|
|
## Support for Sentence Transformers
|
|
|
|
Below is an example for usage with sentence_transformers.
|
|
```python
|
|
from sentence_transformers import SentenceTransformer
|
|
model = SentenceTransformer('intfloat/multilingual-e5-small')
|
|
input_texts = [
|
|
'query: how much protein should a female eat',
|
|
'query: 南瓜的家常做法',
|
|
"passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 i s 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or traini ng for a marathon. Check out the chart below to see how much protein you should be eating each day.",
|
|
"passage: 1.清炒南瓜丝 原料:嫩南瓜半个 调料:葱、盐、白糖、鸡精 做法: 1、南瓜用刀薄薄的削去表面一层皮 ,用勺子刮去瓤 2、擦成细丝(没有擦菜板就用刀慢慢切成细丝) 3、锅烧热放油,入葱花煸出香味 4、入南瓜丝快速翻炒一分钟左右, 放盐、一点白糖和鸡精调味出锅 2.香葱炒南瓜 原料:南瓜1只 调料:香葱、蒜末、橄榄油、盐 做法: 1、将南瓜去皮,切成片 2、油 锅8成热后,将蒜末放入爆香 3、爆香后,将南瓜片放入,翻炒 4、在翻炒的同时,可以不时地往锅里加水,但不要太多 5、放入盐,炒匀 6、南瓜差不多软和绵了之后,就可以关火 7、撒入香葱,即可出锅"
|
|
]
|
|
embeddings = model.encode(input_texts, normalize_embeddings=True)
|
|
```
|
|
|
|
Package requirements
|
|
|
|
`pip install sentence_transformers~=2.2.2`
|
|
|
|
Contributors: [michaelfeil](https://huggingface.co/michaelfeil)
|
|
|
|
## FAQ
|
|
|
|
**1. Do I need to add the prefix "query: " and "passage: " to input texts?**
|
|
|
|
Yes, this is how the model is trained, otherwise you will see a performance degradation.
|
|
|
|
Here are some rules of thumb:
|
|
- Use "query: " and "passage: " correspondingly for asymmetric tasks such as passage retrieval in open QA, ad-hoc information retrieval.
|
|
|
|
- Use "query: " prefix for symmetric tasks such as semantic similarity, bitext mining, paraphrase retrieval.
|
|
|
|
- Use "query: " prefix if you want to use embeddings as features, such as linear probing classification, clustering.
|
|
|
|
**2. Why are my reproduced results slightly different from reported in the model card?**
|
|
|
|
Different versions of `transformers` and `pytorch` could cause negligible but non-zero performance differences.
|
|
|
|
**3. Why does the cosine similarity scores distribute around 0.7 to 1.0?**
|
|
|
|
This is a known and expected behavior as we use a low temperature 0.01 for InfoNCE contrastive loss.
|
|
|
|
For text embedding tasks like text retrieval or semantic similarity,
|
|
what matters is the relative order of the scores instead of the absolute values,
|
|
so this should not be an issue.
|
|
|
|
## Citation
|
|
|
|
If you find our paper or models helpful, please consider cite as follows:
|
|
|
|
```
|
|
@article{wang2024multilingual,
|
|
title={Multilingual E5 Text Embeddings: A Technical Report},
|
|
author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
|
|
journal={arXiv preprint arXiv:2402.05672},
|
|
year={2024}
|
|
}
|
|
```
|
|
|
|
## Limitations
|
|
|
|
Long texts will be truncated to at most 512 tokens.
|
|
|