Downloads · 30 days
15
2% of all-time downloads
teelinsan/opus-mt-eng-deu
opus-mt-eng-deu is a translation model from teelinsan. Use it when you need text moved from one language to another. It is set up for transformers. The card lists the license as cc-by-4.0.
This model was obtained by running the script convertmariantopytorch.py - Instruction available here. The original models were trained by J�rg Tiedemann using the MarianNMT library. See all available MarianMTModel mod…
Downloads · 30 days
15
2% of all-time downloads
All-time downloads
753
Public
Parameters
111M
443 MB on disk
Likes
0
Public
Click a slice to open those files.
.bin222 MB · 50%
From the Hugging Face model README
*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 *
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:
Validation data:
Test data:
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|