Benchmarks#

We provide several pretrained models with their benchmark results.

JoeyNMT v2.x#

IWSLT14 de/en/fr multilingual#

We trained this multilingual model with JoeyNMT v2.3.0 using DDP.

Direction

Architecture

Tokenizer

dev

test

#params

download

en->de

Transformer

sentencepiece

-

28.88

200M

iwslt14_prompt

de->en

-

35.28

en->fr

-

38.86

fr->en

-

40.35

sacrebleu signature: nrefs:1|case:lc|eff:no|tok:13a|smooth:exp|version:2.4.0

WMT14 ende / deen#

We trained the models with JoeyNMT v2.1.0 from scratch.

cf) wmt14 deen leaderboard in paperswithcode

Direction

Architecture

Tokenizer

dev

test

#params

download

en->de

Transformer

sentencepiece

24.36

24.38

60.5M

wmt14_ende.tar.gz (766M)

de->en

Transformer

sentencepiece

30.60

30.51

60.5M

wmt14_deen.tar.gz (766M)

sacrebleu signature: nrefs:1|case:mixed|eff:no|tok:13a|smooth:exp|version:2.2.0

JoeyNMT v1.x#

Warning

The following models are trained with JoeynNMT v1.x, and decoded with Joey NMT v2.0. See config_v1.yaml and config_v2.yaml in the linked tar.gz, respectively. Joey NMT v1.x benchmarks are archived here.

IWSLT14 deen#

Pre-processing with Moses decoder tools as in this script.

Direction

Architecture

Tokenizer

dev

test

#params

download

de->en

RNN

subword-nmt

31.77

30.74

61M

rnn_iwslt14_deen_bpe.tar.gz (672M)

de->en

Transformer

subword-nmt

34.53

33.73

19M

transformer_iwslt14_deen_bpe.tar.gz (221M)

sacrebleu signature: nrefs:1|case:lc|eff:no|tok:13a|smooth:exp|version:2.0.0

Note

For interactive translate mode, you should specify pretokenizer: "moses" in both src’s and trg’s tokenizer_cfg, so that you can input raw sentences. Then MosesTokenizer and MosesDetokenizer will be applied internally. For test mode, we used the preprocessed texts as input and set pretokenizer: "none" in the config.

Masakhane JW300 afen / enaf#

We picked the pretrained models and configs (bpe codes file etc.) from masakhane.io.

Direction

Architecture

Tokenizer

dev

test

#params

download

af->en

Transformer

subword-nmt

-

57.70

46M

transformer_jw300_afen.tar.gz (525M)

en->af

Transformer

subword-nmt

47.24

47.31

24M

transformer_jw300_enaf.tar.gz (285M)

sacrebleu signature: nrefs:1|case:mixed|eff:no|tok:intl|smooth:exp|version:2.0.0

JParaCrawl enja / jaen#

For training, we split JparaCrawl v2 into train and dev set and trained a model on them. Please check the preprocessing script here. We tested then on kftt test set and wmt20 test set, respectively.

Direction

Architecture

Tokenizer

kftt

wmt20

#params

download

af->en

Transformer

sentencepiece

17.66

14.31

225M

jparacrawl_enja.tar.gz (2.3GB)

en->af

Transformer

sentencepiece

14.97

11.49

221M

jparacrawl_jaen.tar.gz (2.2GB)

sacrebleu signature:
  • en->ja: nrefs:1|case:mixed|eff:no|tok:ja-mecab-0.996-IPA|smooth:exp|version:2.0.0

  • ja->en: nrefs:1|case:mixed|eff:no|tok:intl|smooth:exp|version:2.0.0

(Note: In wmt20 test set, newstest2020-enja has 1000 examples, newstest2020-jaen has 993 examples.)