Opus Tatoeba English-German
*This model was obtained by running the script convert_marian_to_pytorch.py - Instruction available here. The original models were trained by J�rg Tiedemann using the MarianNMT library. See all available MarianMTModel
models on the profile of the Helsinki NLP group.
This is the conversion of checkpoint opus-2021-02-22.zip *
eng-deu
source language name: English
target language name: German
OPUS readme: README.md
model: transformer
source language code: en
target language code: de
dataset: opus
release date: 2021-02-22
pre-processing: normalization + SentencePiece (spm32k,spm32k)
download original weights: opus-2021-02-22.zip
Training data:
- deu-eng: Tatoeba-train (86845165)
Validation data:
- deu-eng: Tatoeba-dev, 284809
- total-size-shuffled: 284809
- devset-selected: top 5000 lines of Tatoeba-dev.src.shuffled!
Test data:
- newssyscomb2009.eng-deu: 502/11271
- news-test2008.eng-deu: 2051/47427
- newstest2009.eng-deu: 2525/62816
- newstest2010.eng-deu: 2489/61511
- newstest2011.eng-deu: 3003/72981
- newstest2012.eng-deu: 3003/72886
- newstest2013.eng-deu: 3000/63737
- newstest2014-deen.eng-deu: 3003/62964
- newstest2015-ende.eng-deu: 2169/44260
- newstest2016-ende.eng-deu: 2999/62670
- newstest2017-ende.eng-deu: 3004/61291
- newstest2018-ende.eng-deu: 2998/64276
- newstest2019-ende.eng-deu: 1997/48969
- Tatoeba-test.eng-deu: 10000/83347
test set translations file: test.txt
test set scores file: eval.txt
BLEU-scores
Test set score newstest2018-ende.eng-deu 46.4 Tatoeba-test.eng-deu 45.8 newstest2019-ende.eng-deu 42.4 newstest2016-ende.eng-deu 37.9 newstest2015-ende.eng-deu 32.0 newstest2017-ende.eng-deu 30.6 newstest2014-deen.eng-deu 29.6 newstest2013.eng-deu 27.6 newstest2010.eng-deu 25.9 news-test2008.eng-deu 23.9 newstest2012.eng-deu 23.8 newssyscomb2009.eng-deu 23.3 newstest2011.eng-deu 22.9 newstest2009.eng-deu 22.7 chr-F-scores
Test set score newstest2018-ende.eng-deu 0.697 newstest2019-ende.eng-deu 0.664 Tatoeba-test.eng-deu 0.655 newstest2016-ende.eng-deu 0.644 newstest2015-ende.eng-deu 0.601 newstest2014-deen.eng-deu 0.595 newstest2017-ende.eng-deu 0.593 newstest2013.eng-deu 0.558 newstest2010.eng-deu 0.55 newssyscomb2009.eng-deu 0.539 news-test2008.eng-deu 0.533 newstest2009.eng-deu 0.533 newstest2012.eng-deu 0.53 newstest2011.eng-deu 0.528
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