mirror of
https://github.com/Helsinki-NLP/OPUS-MT-train.git
synced 2024-08-17 16:20:50 +03:00
finetuning for fi-en
This commit is contained in:
parent
870804f4ee
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0e893a06e0
@ -687,12 +687,14 @@ add-to-local-mono-data:
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$(LOAD_MOSES) cat $< |\
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$(TOKENIZER)/replace-unicode-punctuation.perl |\
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$(TOKENIZER)/remove-non-printing-char.perl |\
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$(TOKENIZER)/deescape-special-chars.perl |\
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sed 's/ */ /g;s/^ *//g;s/ *$$//g' > $@
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%.simple.gz: %.gz
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$(LOAD_MOSES) zcat $< |\
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$(TOKENIZER)/replace-unicode-punctuation.perl |\
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$(TOKENIZER)/remove-non-printing-char.perl |\
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$(TOKENIZER)/deescape-special-chars.perl |\
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sed 's/ */ /g;s/^ *//g;s/ *$$//g' | gzip -c > $@
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@ -842,7 +844,7 @@ SPMTRGMODEL = ${WORKDIR}/train/opus.trg.spm${TRGBPESIZE:000=}k-model
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.PRECIOUS: ${SPMSRCMODEL} ${SPMTRGMODEL}
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# ${SPMSRCMODEL}: ${WORKDIR}/%.spm${SRCBPESIZE:000=}k-model: ${TMPDIR}/${LANGPAIRSTR}/%
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${SPMSRCMODEL}: ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_SRC}.charfreq
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${SPMSRCMODEL}: ${LOCAL_TRAIN_SRC}
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ifeq ($(wildcard ${SPMSRCMODEL}),)
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mkdir -p ${dir $@}
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ifeq ($(TRGLANGS),${firstword ${TRGLANGS}})
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@ -850,7 +852,8 @@ ifeq ($(TRGLANGS),${firstword ${TRGLANGS}})
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else
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cut -f2- -d ' ' $< | grep . | shuf > $<.text
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endif
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if [ `cat ${word 2,$^} | wc -l` -gt 1000 ]; then \
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${MAKE} ${LOCAL_TRAIN_SRC}.charfreq
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if [ `cat ${LOCAL_TRAIN_SRC}.charfreq | wc -l` -gt 1000 ]; then \
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${SPM_HOME}/spm_train \
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--model_prefix=$@ --vocab_size=$(SRCBPESIZE) --input=$<.text \
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--character_coverage=0.9995 --hard_vocab_limit=false; \
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@ -871,11 +874,12 @@ endif
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## no labels on the target language side
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# ${SPMTRGMODEL}: ${WORKDIR}/%.spm${TRGBPESIZE:000=}k-model: ${TMPDIR}/${LANGPAIRSTR}/%
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${SPMTRGMODEL}: ${LOCAL_TRAIN_TRG} ${LOCAL_TRAIN_TRG}.charfreq
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${SPMTRGMODEL}: ${LOCAL_TRAIN_TRG}
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ifeq ($(wildcard ${SPMTRGMODEL}),)
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mkdir -p ${dir $@}
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grep . $< | shuf > $<.text
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if [ `cat ${word 2,$^} | wc -l` -gt 1000 ]; then \
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${MAKE} ${LOCAL_TRAIN_TRG}.charfreq
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if [ `cat ${LOCAL_TRAIN_TRG}.charfreq | wc -l` -gt 1000 ]; then \
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${SPM_HOME}/spm_train \
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--model_prefix=$@ --vocab_size=$(TRGBPESIZE) --input=$<.text \
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--character_coverage=0.9995 --hard_vocab_limit=false; \
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@ -952,11 +956,12 @@ ifneq (${SPMMODEL},${SPMTRGMONO})
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endif
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${SPMMODEL}: ${LOCAL_MONO_DATA}.${PRE} ${LOCAL_MONO_DATA}.${PRE}.charfreq
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${SPMMODEL}: ${LOCAL_MONO_DATA}.${PRE}
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ifeq ($(wildcard ${SPMMODEL}),)
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mkdir -p ${dir $@}
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grep . $< | shuf > $<.text
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if [ `cat ${word 2,$^} | wc -l` -gt 1000 ]; then \
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${MAKE} ${LOCAL_MONO_DATA}.${PRE}.charfreq
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if [ `cat ${LOCAL_MONO_DATA}.${PRE}.charfreq | wc -l` -gt 1000 ]; then \
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${SPM_HOME}/spm_train \
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--model_prefix=$@ --vocab_size=$(TRGBPESIZE) --input=$<.text \
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--character_coverage=0.9995 --hard_vocab_limit=false; \
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@ -992,11 +997,15 @@ endif
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## python-based char-counter (seems to be the fastest version)
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%.charfreq: %
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python -c "import collections, pprint; pprint.pprint(dict(collections.Counter(open('$<', 'r').read())))" > $@
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head -10000000 $< > $<.10m
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python -c "import collections, pprint; pprint.pprint(dict(collections.Counter(open('$<.10m', 'r').read())))" > $@
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rm -f $<.10m
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## slow version
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%.charfreq2: %
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sed 's/./& /g' < $< | tr ' ' "\n" | grep . |\
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head -10000000 $< |\
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sed 's/./& /g' | \
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tr ' ' "\n" | grep . |\
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sort | uniq -c > $@
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@ -84,6 +84,7 @@ ifeq (${wildcard ${BT_MODEL_START}},)
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cp ${MODEL_VOCAB} ${BT_MODEL_VOCAB}
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endif
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endif
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rm -f ${WORKHOME}/${LANGPAIRSTR}/train.submit
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${MAKE} DATASET=opus+bt \
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CLEAN_TRAIN_SRC="${CLEAN_TRAIN_SRC} ${BACKTRANS_SRC}" \
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CLEAN_TRAIN_TRG="${CLEAN_TRAIN_TRG} ${BACKTRANS_TRG}" \
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@ -94,6 +95,7 @@ endif
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## run a multigpu job (2 or 4 GPUs)
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%-multigpu %-0123:
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@ -275,13 +275,16 @@ icelandic:
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${MAKE} SRCLANGS=is TRGLANGS="da no nn nb sv" bilingual
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${MAKE} SRCLANGS=is TRGLANGS=fi bilingual
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## include yandex data in training
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enru-yandex:
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${MAKE} DATASET=opus+yandex SRCLANGS=ru TRGLANGS=en EXTRA_TRAINSET=yandex data
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${MAKE} DATASET=opus+yandex SRCLANGS=ru TRGLANGS=en EXTRA_TRAINSET=yandex reverse-data
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${MAKE} DATASET=opus+yandex SRCLANGS=en TRGLANGS=ru EXTRA_TRAINSET=yandex \
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WALLTIME=72 HPC_CORES=1 HPC_MEM=8g MARIAN_WORKSPACE=12000 train.submit-multigpu
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${MAKE} DATASET=opus+yandex SRCLANGS=ru TRGLANGS=en EXTRA_TRAINSET=yandex \
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WALLTIME=72 HPC_CORES=1 HPC_MEM=4g train.submit-multigpu
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${MAKE} DATASET=opus+yandex MODELTYPE=transformer SRCLANGS=en TRGLANGS=ru EXTRA_TRAINSET=yandex data
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${MAKE} DATASET=opus+yandex MODELTYPE=transformer SRCLANGS=en TRGLANGS=ru EXTRA_TRAINSET=yandex reverse-data
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${MAKE} DATASET=opus+yandex MODELTYPE=transformer SRCLANGS=en TRGLANGS=ru EXTRA_TRAINSET=yandex \
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WALLTIME=72 HPC_CORES=1 HPC_MEM=8g MARIAN_WORKSPACE=12000 MARIAN_EARLY_STOPPING=15 train.submit-multigpu
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${MAKE} DATASET=opus+yandex MODELTYPE=transformer SRCLANGS=ru TRGLANGS=en EXTRA_TRAINSET=yandex \
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WALLTIME=72 HPC_CORES=1 HPC_MEM=4g MARIAN_EARLY_STOPPING=15 train.submit-multigpu
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enit:
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@ -29,7 +29,7 @@ MODELZIP = ${lastword ${sort ${wildcard ${MODELHOME}/*-20*.zip}}}
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MODELNAME = ${patsubst %.zip,%,${notdir ${MODELZIP}}}
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ifeq (${MODELNAME},)
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MODELHOME = ../work-filter/models/${LANGPAIR}
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MODELHOME = ../work-langid/models/${LANGPAIR}
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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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@ -128,6 +128,7 @@ print-names:
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echo ${LANGNAME}
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echo ${UDPIPE_MODEL}
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echo ${WIKI_JSON}
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echo ${MODELNAME}
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## fetch the latest model
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@ -66,7 +66,7 @@ MARIAN_EARLY_STOPPING = 5
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.PHONY: all
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all: ${TEST_SRC}.${TRG}.compare ${TEST_SRC}.baseline.${TRG}.compare
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all: ${TEST_SRC}.${BASEMODELNAME}.${TRG}.compare ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.compare
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@ -250,11 +250,13 @@ ${LANGPAIR}/${BASEMODELNAME}/decoder.yml:
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cp ${BASEMODELZIP} ${dir $@}
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cd ${dir $@} && unzip -u *.zip
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.INTERMEDIATE: ${TRAIN_SRC}.pre.gz ${DEV_SRC}.pre.gz ${TEST_SRC}.pre.gz
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${TRAIN_SRC}.pre.gz ${DEV_SRC}.pre.gz ${TEST_SRC}.pre.gz: %.pre.gz: %.gz ${LANGPAIR}/${BASEMODELNAME}/decoder.yml
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zcat $< |\
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${LANGPAIR}/${BASEMODELNAME}/preprocess.sh ${SRC} ${LANGPAIR}/${BASEMODELNAME}/source.spm |\
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gzip -c > $@
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.INTERMEDIATE: ${TRAIN_TRG}.pre.gz ${DEV_TRG}.pre.gz
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${TRAIN_TRG}.pre.gz ${DEV_TRG}.pre.gz: %.pre.gz: %.gz ${LANGPAIR}/${BASEMODELNAME}/decoder.yml
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zcat $< |\
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${LANGPAIR}/${BASEMODELNAME}/preprocess.sh ${SRC} ${LANGPAIR}/${BASEMODELNAME}/target.spm |\
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@ -314,10 +316,10 @@ ${TUNED_MODEL}.done: ${TRAIN_SRC}.pre.gz ${TRAIN_TRG}.pre.gz ${DEV_SRC}.pre.gz $
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.PHONY: translate
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translate: ${TEST_SRC}.${TRG}.gz
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translate: ${TEST_SRC}.${BASEMODELNAME}.${TRG}.gz
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## translate test set
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${TEST_SRC}.${TRG}.gz: ${TEST_SRC}.pre.gz ${TUNED_MODEL}.npz.best-perplexity.npz
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${TEST_SRC}.${BASEMODELNAME}.${TRG}.gz: ${TEST_SRC}.pre.gz ${TUNED_MODEL}.npz.best-perplexity.npz
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mkdir -p ${dir $@}
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${LOADMODS} && ${MARIAN}/marian-decoder \
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-i $< \
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@ -329,10 +331,10 @@ ${TEST_SRC}.${TRG}.gz: ${TEST_SRC}.pre.gz ${TUNED_MODEL}.npz.best-perplexity.npz
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.PHONY: translate-baseline
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translate-baseline: ${TEST_SRC}.baseline.${TRG}.gz
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translate-baseline: ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.gz
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## translate test set
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${TEST_SRC}.baseline.${TRG}.gz: ${TEST_SRC}.pre.gz ${LANGPAIR}/${BASEMODELNAME}/decoder.yml
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${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.gz: ${TEST_SRC}.pre.gz ${LANGPAIR}/${BASEMODELNAME}/decoder.yml
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mkdir -p ${dir $@}
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cd ${LANGPAIR}/${BASEMODELNAME}; \
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${LOADMODS} && ${MARIAN}/marian-decoder \
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@ -346,18 +348,18 @@ ${TEST_SRC}.baseline.${TRG}.gz: ${TEST_SRC}.pre.gz ${LANGPAIR}/${BASEMODELNAME}/
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.PHONY: eval eval-baseline
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eval: ${TEST_SRC}.${TRG}.eval
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eval-baseline: ${TEST_SRC}.baseline.${TRG}.eval
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eval: ${TEST_SRC}.${BASEMODELNAME}.${TRG}.eval
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eval-baseline: ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.eval
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## without reference normalisation
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${TEST_SRC}.${TRG}.eval ${TEST_SRC}.baseline.${TRG}.eval: %.eval: %.gz ${TEST_TRG}.gz
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${TEST_SRC}.${BASEMODELNAME}.${TRG}.eval ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.eval: %.eval: %.gz ${TEST_TRG}.gz
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zcat ${TEST_TRG}.gz > $@.ref
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zcat $< | sacrebleu $@.ref > $@
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zcat $< | sacrebleu --metrics=chrf --width=3 $@.ref >> $@
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rm -f $@.ref
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## with reference normalisation (should not do this)
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${TEST_SRC}.${TRG}.eval-norm ${TEST_SRC}.baseline.${TRG}.eval-norm: %.eval-norm: %.gz ${TEST_TRG}.gz
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${TEST_SRC}.${BASEMODELNAME}.${TRG}.eval-norm ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.eval-norm: %.eval-norm: %.gz ${TEST_TRG}.gz
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zcat ${TEST_TRG}.gz |\
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${TOKENIZER}/replace-unicode-punctuation.perl |\
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${TOKENIZER}/remove-non-printing-char.perl |\
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@ -371,10 +373,10 @@ ${TEST_SRC}.${TRG}.eval-norm ${TEST_SRC}.baseline.${TRG}.eval-norm: %.eval-norm:
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.PHONY: compare compare-baseline
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compare: ${TEST_SRC}.${TRG}.compare
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compare-baseline: ${TEST_SRC}.baseline.${TRG}.compare
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compare: ${TEST_SRC}.${BASEMODELNAME}.${TRG}.compare
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compare-baseline: ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.compare
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${TEST_SRC}.${TRG}.compare ${TEST_SRC}.baseline.${TRG}.compare: %.compare: %.eval
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${TEST_SRC}.${BASEMODELNAME}.${TRG}.compare ${TEST_SRC}.${BASEMODELNAME}.baseline.${TRG}.compare: %.compare: %.eval
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zcat ${TEST_SRC}.gz > $@.1
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zcat ${TEST_TRG}.gz > $@.2
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zcat ${<:.eval=.gz} > $@.3
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Load Diff
@ -0,0 +1,2 @@
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BLEU+case.mixed+numrefs.1+smooth.exp+tok.13a+version.1.4.2 = 22.9 54.2/29.2/17.8/11.3 (BP = 0.962 ratio = 0.963 hyp_len = 36946 ref_len = 38369)
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chrF2+case.mixed+numchars.6+numrefs.1+space.False+version.1.4.2 = 0.548
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BLEU+case.mixed+numrefs.1+smooth.exp+tok.13a+version.1.4.2 = 25.1 56.3/31.7/19.9/13.1 (BP = 0.963 ratio = 0.964 hyp_len = 36977 ref_len = 38369)
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chrF2+case.mixed+numchars.6+numrefs.1+space.False+version.1.4.2 = 0.568
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finetune/fi-en/news/test/newstest2019-fien.fi.gz
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finetune/fi-en/news/test/newstest2019-fien.fi.gz
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BLEU+case.mixed+numrefs.1+smooth.exp+tok.13a+version.1.4.2 = 28.5 62.4/35.5/21.9/13.8 (BP = 0.998 ratio = 0.998 hyp_len = 36157 ref_len = 36215)
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chrF2+case.mixed+numchars.6+numrefs.1+space.False+version.1.4.2 = 0.564
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BLEU+case.mixed+numrefs.1+smooth.exp+tok.13a+version.1.4.2 = 31.4 64.7/38.5/24.7/16.2 (BP = 0.992 ratio = 0.992 hyp_len = 35930 ref_len = 36215)
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chrF2+case.mixed+numchars.6+numrefs.1+space.False+version.1.4.2 = 0.583
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@ -44,3 +44,26 @@
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| newstestB2017-enfi.en.fi | 22.4 | 0.559 |
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| Tatoeba.en.fi | 39.4 | 0.627 |
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# opus-2020-02-13.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-2020-02-13.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-fi/opus-2020-02-13.zip)
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* test set translations: [opus-2020-02-13.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-fi/opus-2020-02-13.test.txt)
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* test set scores: [opus-2020-02-13.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-fi/opus-2020-02-13.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.en.fi | 21.1 | 0.552 |
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| newstest2015-enfi.en.fi | 22.7 | 0.563 |
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| newstest2016-enfi.en.fi | 24.3 | 0.572 |
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| newstest2017-enfi.en.fi | 27.1 | 0.601 |
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| newstest2018-enfi.en.fi | 18.0 | 0.529 |
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| newstest2019-enfi.en.fi | 22.9 | 0.548 |
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| newstestB2016-enfi.en.fi | 19.2 | 0.537 |
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| newstestB2017-enfi.en.fi | 22.3 | 0.560 |
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| Tatoeba.en.fi | 41.1 | 0.645 |
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@ -70,3 +70,27 @@
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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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# opus-2020-02-13.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-2020-02-13.zip](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-13.zip)
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* test set translations: [opus-2020-02-13.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-13.test.txt)
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* test set scores: [opus-2020-02-13.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/fi-en/opus-2020-02-13.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 | 25.4 | 0.538 |
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| newstest2015-enfi.fi.en | 27.1 | 0.549 |
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| newstest2016-enfi.fi.en | 29.5 | 0.572 |
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| newstest2017-enfi.fi.en | 33.1 | 0.598 |
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| newstest2018-enfi.fi.en | 24.0 | 0.519 |
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| newstest2019-fien.fi.en | 28.9 | 0.566 |
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| newstestB2016-enfi.fi.en | 24.5 | 0.527 |
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| newstestB2017-enfi.fi.en | 27.9 | 0.560 |
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| newstestB2017-fien.fi.en | 27.9 | 0.560 |
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| Tatoeba.fi.en | 57.4 | 0.718 |
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@ -14,3 +14,19 @@
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| fiskmo_testset.sv.fi | 26.4 | 0.616 |
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| Tatoeba.sv.fi | 44.7 | 0.667 |
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# opus-2020-02-13.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-2020-02-13.zip](https://object.pouta.csc.fi/OPUS-MT-models/sv-fi/opus-2020-02-13.zip)
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* test set translations: [opus-2020-02-13.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/sv-fi/opus-2020-02-13.test.txt)
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* test set scores: [opus-2020-02-13.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/sv-fi/opus-2020-02-13.eval.txt)
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|
||||
## Benchmarks
|
||||
|
||||
| testset | BLEU | chr-F |
|
||||
|-----------------------|-------|-------|
|
||||
| fiskmo_testset.sv.fi | 26.1 | 0.613 |
|
||||
| Tatoeba.sv.fi | 44.8 | 0.673 |
|
||||
|
||||
|
Loading…
Reference in New Issue
Block a user