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https://github.com/Helsinki-NLP/OPUS-MT-train.git
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finetuning anc backtranslations
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4b7ae1a39b
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870804f4ee
@ -23,11 +23,14 @@ scores:
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## get the best model from all kind of alternative setups
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## in the following sub directories (add prefix work-)
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ALT_MODEL_BASE = work-
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# ALT_MODEL_DIR = bpe-old bpe-memad bpe spm-noalign bpe-align spm
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ALT_MODEL_DIR = spm langid
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# ALT_MODEL_DIR = spm langid
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ALT_MODEL_DIR = langid
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best_dist_all:
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for l in $(sort ${shell ls work* | grep -- '-' | grep -v old | grep -v work}); do \
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for l in $(sort ${shell ls ${ALT_MODEL_BASE}* | grep -- '-' | grep -v old | grep -v work}); do \
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if [ `find work*/$$l -name '*.npz' | wc -l` -gt 0 ]; then \
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d=`find work-spm/$$l -name '*.best-perplexity.npz' -exec basename {} \; | cut -f1 -d.`; \
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${MAKE} SRCLANGS="`echo $$l | cut -f1 -d'-' | sed 's/\\+/ /g'`" \
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@ -30,7 +30,8 @@ MODELNAME = ${patsubst %.zip,%,${notdir ${MODELZIP}}}
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ifeq (${MODELNAME},)
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MODELHOME = ../work-filter/models/${LANGPAIR}
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MODELZIP = ${lastword ${sort ${wildcard ${MODELHOME}/*-20*.zip}}}
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# MODELZIP = ${lastword ${sort ${wildcard ${MODELHOME}/*-20*.zip}}}
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MODELZIP = ${lastword ${sort ${wildcard ${MODELHOME}/opus-20*.zip}}}
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MODELNAME = ${patsubst %.zip,%,${notdir ${MODELZIP}}}
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endif
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@ -77,9 +78,10 @@ all: index.html
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${MAKE} ${WIKI_SRC} ${WIKI_TRG}
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WIKISOURCES = wiki wikibooks wikinews wikiquote wikisource wiktionary
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# WIKISOURCES = wiki wikibooks wikinews wikiquote wikisource wiktionary
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WIKISOURCES = wiki wikibooks wikinews wikiquote wikisource
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all-wikis:
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all-wikis: ${LANGPAIR}/${MODELNAME}/decoder.yml
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for w in ${WIKISOURCES}; do \
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${MAKE} WIKISOURCE=$$w extract-text; \
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echo "find ${WIKI_DIR} -name '$$w.${LANGID}.${PART}.gz'"; \
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@ -104,18 +106,18 @@ focus-wikis:
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get-data: ${WIKI_JSON}
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extract-text: ${WIKI_TXT}
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prepare-model: ${LANGPAIR}/decoder.yml
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prepare-model: ${LANGPAIR}/${MODELNAME}/decoder.yml
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prepare-data: ${WIKI_PRE}
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translate: ${WIKI_SRC} ${WIKI_TRG}
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## translate all parts
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translate-all-parts:
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translate-all-parts: ${LANGPAIR}/${MODELNAME}/decoder.yml
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for p in ${PARTS}; do \
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${MAKE} PART=$$p translate; \
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done
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## create jobs for translating all parts
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submit-translate-all-parts:
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submit-translate-all-parts: ${LANGPAIR}/${MODELNAME}/decoder.yml
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for p in ${PARTS}; do \
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${MAKE} PART=$$p translate.submit; \
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done
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@ -71,17 +71,36 @@ all: ${TEST_SRC}.${TRG}.compare ${TEST_SRC}.baseline.${TRG}.compare
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## convert a TMX file to create dev-test-train data
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## and start fine-tuning
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## and start fine-tuning in the direction of sorted lang-IDs
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## set REVERSE = 1 to run in the opposite direction
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##
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## - this also does some filtering of the TMX
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## based on language identification and simple scripts and regexes
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## - it assumes that ${TMX} points to a valid TMX files
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## - it assumes that there are only 2 languages in the TMX (it will only use 2)
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TMX = vero-20200123.tmx.gz
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REVERSE = 0
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tmx-tune:
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zcat ${TMX} |\
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tmx2moses -r -o ${TMX:.tmx.gz=}
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s=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | head -1`; \
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t=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | tail -1`; \
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if [ ${REVERSE} -gt 0 ]; then \
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t=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | head -1`; \
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s=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | tail -1`; \
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else \
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s=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | head -1`; \
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t=`ls ${TMX:.tmx.gz=}.*-* | sort | sed 's/^.*\.\([a-z]*\)$$/\1/' | tail -1`; \
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fi; \
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echo $$s; echo $$t; \
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mkdir -p $$s-$$t; \
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paste ${TMX:.tmx.gz=}.*-*.$$s ${TMX:.tmx.gz=}.*-*.$$t | \
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sort | uniq | \
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python3 ../bitext-match-lang.py -s $$s -t $$t | \
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grep -v '[<>{}]' |\
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$(TOKENIZER)/replace-unicode-punctuation.perl |\
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perl -CS -pe 'tr[\x{9}\x{A}\x{D}\x{20}-\x{D7FF}\x{E000}-\x{FFFD}\x{10000}-\x{10FFFF}][]cd;' |\
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sed 's/ */ /g;s/^ *//g;s/ *$$//g' |\
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shuf > ${TMX:.tmx.gz=}.$$s-$$t.shuffled; \
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mkdir -p $$s-$$t/${TMX:.tmx.gz=}/dev; \
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mkdir -p $$s-$$t/${TMX:.tmx.gz=}/test; \
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@ -28,3 +28,18 @@
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|-----------------------|-------|-------|
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| JW300.bcl.en | 56.8 | 0.705 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/bcl-en/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bcl-en/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bcl-en/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| JW300.bcl.en | 56.1 | 0.697 |
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@ -28,3 +28,18 @@
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|-----------------------|-------|-------|
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| Tatoeba.bn.en | 49.8 | 0.644 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/bn-en/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bn-en/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bn-en/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| Tatoeba.bn.en | 49.2 | 0.638 |
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@ -28,3 +28,18 @@
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|-----------------------|-------|-------|
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| JW300.en.bcl | 55.3 | 0.729 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-bcl/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-bcl/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-bcl/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| JW300.en.bcl | 53.8 | 0.719 |
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@ -20,3 +20,25 @@
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| newstest2019-enru.en.ru | 22.3 | 0.412 |
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| Tatoeba.en.ru | 46.9 | 0.656 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-ru/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-ru/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-ru/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| newstest2012.en.ru | 31.1 | 0.581 |
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| newstest2013.en.ru | 23.5 | 0.513 |
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| newstest2015-enru.en.ru | 27.5 | 0.564 |
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| newstest2016-enru.en.ru | 26.4 | 0.548 |
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| newstest2017-enru.en.ru | 29.1 | 0.572 |
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| newstest2018-enru.en.ru | 25.4 | 0.554 |
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| newstest2019-enru.en.ru | 27.1 | 0.533 |
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| Tatoeba.en.ru | 48.4 | 0.669 |
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@ -46,3 +46,27 @@
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| newstestB2017-fien.fi.en | 27.3 | 0.556 |
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| Tatoeba.fi.en | 55.3 | 0.705 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| newsdev2015-enfi.fi.en | 25.1 | 0.535 |
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| newstest2015-enfi.fi.en | 26.8 | 0.548 |
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| newstest2016-enfi.fi.en | 29.1 | 0.569 |
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| newstest2017-enfi.fi.en | 32.7 | 0.596 |
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| newstest2018-enfi.fi.en | 23.9 | 0.518 |
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| newstest2019-fien.fi.en | 28.7 | 0.564 |
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| newstestB2016-enfi.fi.en | 24.2 | 0.525 |
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| newstestB2017-enfi.fi.en | 27.7 | 0.559 |
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| newstestB2017-fien.fi.en | 27.7 | 0.559 |
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| Tatoeba.fi.en | 57.2 | 0.717 |
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|-----------------------|-------|-------|
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| Tatoeba.ml.en | 43.0 | 0.601 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/ml-en/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ml-en/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ml-en/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| Tatoeba.ml.en | 42.6 | 0.591 |
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@ -67,3 +67,26 @@
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| newstest2019-ruen.ru.en | 32.0 | 0.581 |
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| Tatoeba.ru.en | 59.8 | 0.726 |
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# opus-2020-02-11.zip
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* dataset: opus
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* model: transformer-align
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* pre-processing: normalization + SentencePiece
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* download: [opus-2020-02-11.zip](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-11.zip)
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* test set translations: [opus-2020-02-11.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-11.test.txt)
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* test set scores: [opus-2020-02-11.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ru-en/opus-2020-02-11.eval.txt)
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## Benchmarks
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| testset | BLEU | chr-F |
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|-----------------------|-------|-------|
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| newstest2012.ru.en | 34.8 | 0.603 |
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| newstest2013.ru.en | 28.1 | 0.546 |
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| newstest2014-ruen.ru.en | 32.1 | 0.593 |
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| newstest2015-enru.ru.en | 30.3 | 0.567 |
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| newstest2016-enru.ru.en | 30.1 | 0.566 |
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| newstest2017-enru.ru.en | 33.4 | 0.593 |
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| newstest2018-enru.ru.en | 29.6 | 0.566 |
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| newstest2019-ruen.ru.en | 31.5 | 0.577 |
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| Tatoeba.ru.en | 60.8 | 0.734 |
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