README.md

metadata

language:
  - en
  - de
tags:
  - translation
  - opus-mt
license: cc-by-4.0
model-index:
  - name: opus-mt-eng-deu
    results:
      - task:
          name: Translation eng-deu
          type: translation
          args: eng-deu
        dataset:
          name: tatoeba-test-v2021-02-22
          type: tatoeba_mt
          args: eng-deu
        metrics:
          - name: BLEU
            type: bleu
            value: 45.8

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 Jörg 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