swe-nor

opus-2020-06-17.zip

• dataset: opus
• model: transformer-align
• source language(s): swe
• target language(s): nno nob
• model: transformer-align
• pre-processing: normalization + SentencePiece (spm4k,spm4k)
• a sentence initial language token is required in the form of >>id<< (id = valid target language ID)
• download: opus-2020-06-17.zip
• test set translations: opus-2020-06-17.test.txt
• test set scores: opus-2020-06-17.eval.txt

Benchmarks

testset	BLEU	chr-F
Tatoeba-test.swe.nor	65.8	0.796

opus-2021-02-23.zip

• dataset: opus
• model: transformer
• source language(s): swe
• target language(s): nno nob
• model: transformer
• pre-processing: normalization + SentencePiece (spm32k,spm32k)
• a sentence initial language token is required in the form of >>id<< (id = valid target language ID)
• valid language labels: >>nob<< >>nno<<
• download: opus-2021-02-23.zip
• test set translations: opus-2021-02-23.test.txt
• test set scores: opus-2021-02-23.eval.txt

Benchmarks

testset	BLEU	chr-F	#sent	#words	BP
Tatoeba-test.swe-nno	20.4	0.565	2	10	1.000
Tatoeba-test.swe-nob	73.7	0.842	560	3671	0.993
Tatoeba-test.swe-nor	73.6	0.843	562	3682	0.994