mirror of
https://github.com/Helsinki-NLP/OPUS-MT-train.git
synced 2024-09-11 20:27:19 +03:00
merged
This commit is contained in:
Joerg Tiedemann
commit
f4006170bd
1
TODO.md
1
TODO.md
@ -12,6 +12,7 @@ grep for job is (pattern: 'Submitted batch job 946074')
|
||||
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## Issues
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* racing situations in work/data with jobs that fetch data for the same language pairs!
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* get rid of BPE to simplify the scripts
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@ -37,10 +37,17 @@ DATA_IS_SHUFFLED = 1
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## Tatoeba specific data sets
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TATOEBA_DATASET := opusTC${TATOEBA_VERSION_NOHYPHEN}
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TATOEBA_TRAINSET := Tatoeba-train-${TATOEBA_VERSION}
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TATOEBA_DEVSET := Tatoeba-dev-${TATOEBA_VERSION}
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TATOEBA_TESTSET := Tatoeba-test-${TATOEBA_VERSION}
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TATOEBA_DATASET := opusTC${TATOEBA_VERSION_NOHYPHEN}
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TATOEBA_TRAINSET := Tatoeba-train-${TATOEBA_VERSION}
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TATOEBA_DEVSET := Tatoeba-dev-${TATOEBA_VERSION}
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TATOEBA_TESTSET := Tatoeba-test-${TATOEBA_VERSION}
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## the name is by default the same as the data set specifier
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## (for some tasks the name can differ, i.e. tuning of multilingual models)
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TATOEBA_DEVSET_NAME := ${TATOEBA_DEVSET}
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TATOEBA_TESTSET_NAME := ${TATOEBA_TESTSET}
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TATOEBA_TRAINSET_NAME := ${TATOEBA_TRAINSET}
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## change data set names
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## DATASET will also be the base name of the model file
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@ -48,9 +55,9 @@ DATASET := ${TATOEBA_DATASET}
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TRAINSET := ${TATOEBA_TRAINSET}
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DEVSET := ${TATOEBA_DEVSET}
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TESTSET := ${TATOEBA_TESTSET}
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DEVSET_NAME := ${TATOEBA_DEVSET}
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TESTSET_NAME := ${TATOEBA_TESTSET}
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TRAINSET_NAME := ${TATOEBA_TRAINSET}
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DEVSET_NAME := ${TATOEBA_DEVSET_NAME}
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TESTSET_NAME := ${TATOEBA_TESTSET_NAME}
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TRAINSET_NAME := ${TATOEBA_TRAINSET_NAME}
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##
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BACKTRANS_HOME = ${PWD}/back-translate
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52
lib/data.mk
52
lib/data.mk
@ -107,7 +107,7 @@ endif
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# backward translation using pivoting (source language is automatically created)
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ifeq (${USE_BACKWARD_PIVOTING},1)
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PIVOTING_SRC = ${sort ${wildcard ${PIVOTTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz}}
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PIVOTING_SRC += ${sort ${wildcard ${PIVOTTRANS_HOME}/${SRC}-${TRG}/latest/*.${SRCEXT}.gz}}
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PIVOTING_TRG = ${patsubst %.${SRCEXT}.gz,%.${TRGEXT}.gz,${PIVOTING_SRC}}
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endif
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@ -120,6 +120,13 @@ endif
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print-datasets:
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-@for s in ${SRCLANGS}; do \
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for t in ${TRGLANGS}; do \
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${MAKE} SRC=$$s TRG=$$t print-datasets-current-langpair; \
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done \
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done
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print-datasets-current-langpair:
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@echo ${TATOEBA_TRAINSET}
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@echo ${TRAINSET}
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@echo "all data:"
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@ -245,7 +252,6 @@ endif
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.PHONY: clean-data rawdata
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clean-data rawdata:
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@for s in ${SRCLANGS}; do \
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@ -263,6 +269,32 @@ clean-data-source:
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## shuffle training data (if one wants to do that after they have been created already)
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.PHONY: shuffle-training-data
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shuffle-training-data:
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ifneq (${wildcard ${TRAIN_ALG}},)
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paste <(gzip -cd ${TRAIN_SRC}.clean.${PRE_SRC}.gz) \
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<(gzip -cd ${TRAIN_TRG}.clean.${PRE_TRG}.gz) \
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<(gzip -cd ${TRAIN_ALG}) |\
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${SHUFFLE} |\
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tee >(cut -f1 | gzip -c >${TRAIN_SRC}.clean.${PRE_SRC}.new.gz) \
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>(cut -f2 | gzip -c >${TRAIN_TRG}.clean.${PRE_TRG}.new.gz) | \
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cut -f3 | gzip -c > ${TRAIN_ALG}.new.gz
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mv -f ${TRAIN_SRC}.clean.${PRE_SRC}.new.gz ${TRAIN_SRC}.clean.${PRE_SRC}.gz
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mv -f ${TRAIN_TRG}.clean.${PRE_TRG}.new.gz ${TRAIN_TRG}.clean.${PRE_TRG}.gz
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mv ${TRAIN_ALG}.new.gz ${TRAIN_ALG}
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else
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paste <(gzip -cd ${TRAIN_SRC}.clean.${PRE_SRC}.gz) \
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<(gzip -cd ${TRAIN_TRG}.clean.${PRE_TRG}.gz) |\
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${SHUFFLE} |\
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tee >(cut -f1 | gzip -c >${TRAIN_SRC}.clean.${PRE_SRC}.new.gz) \
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>(cut -f2 | gzip -c >${TRAIN_TRG}.clean.${PRE_TRG}.new.gz)
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mv -f ${TRAIN_SRC}.clean.${PRE_SRC}.new.gz ${TRAIN_SRC}.clean.${PRE_SRC}.gz
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mv -f ${TRAIN_TRG}.clean.${PRE_TRG}.new.gz ${TRAIN_TRG}.clean.${PRE_TRG}.gz
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endif
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## monolingual data sets (for sentence piece models)
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.INTERMEDIATE: ${LOCAL_MONO_DATA}.${PRE} ${LOCAL_MONO_DATA}.raw
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@ -414,6 +446,16 @@ ifeq (${USE_REST_DEVDATA},1)
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endif
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## for multilingual systems:
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## shuffle the complete training data set
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## if the option is set to 1
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ifeq (${SHUFFLE_MULTILINGUAL_DATA},1)
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ifneq ($(words ${SRCLANGS} ${TRGLANGS}),2)
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SHUFFLE_TRAINING_DATA = 1
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endif
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endif
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## add training data for each language combination
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## and put it together in local space
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${LOCAL_TRAIN_SRC}: ${LOCAL_TRAINDATA_DEPENDENCIES}
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@ -444,15 +486,13 @@ ifeq (${USE_REST_DEVDATA},1)
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${GZIP} -cd < ${DEV_TRG}.notused.gz >> ${LOCAL_TRAIN_TRG}; \
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fi
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endif
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ifeq (${SHUFFLE_MULTILINGUAL_DATA},1)
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ifneq ($(words ${SRCLANGS} ${TRGLANGS}),2)
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@echo ".... shuffle multilingual data"
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ifeq (${SHUFFLE_TRAINING_DATA},1)
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@echo ".... shuffle complete training data"
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@paste ${LOCAL_TRAIN_SRC} ${LOCAL_TRAIN_TRG} | ${SHUFFLE} > ${LOCAL_TRAIN_SRC}.shuffled
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@cut -f1 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_SRC}
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@cut -f2 ${LOCAL_TRAIN_SRC}.shuffled > ${LOCAL_TRAIN_TRG}
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@rm -f ${LOCAL_TRAIN_SRC}.shuffled
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endif
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endif
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## everything is done in the target above
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||||
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4
lib/env/puhti.mk
vendored
4
lib/env/puhti.mk
vendored
@ -8,8 +8,8 @@ DATA_PREPARE_HPCPARAMS = CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=5
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DATA_ALIGN_HPCPARAMS = CPUJOB_HPC_CORES=4 CPUJOB_HPC_JOBS=2 CPUJOB_HPC_MEM=64g CPUJOB_HPC_DISK=500
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||||
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||||
CSCPROJECT = project_2002688
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# CSCPROJECT = project_2002982
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# CSCPROJECT = project_2002688
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CSCPROJECT = project_2002982
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||||
WORKHOME = ${shell realpath ${PWD}/work}
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GPU = v100
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HPC_QUEUE = small
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||||
@ -242,7 +242,7 @@ listallmodels:
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||||
## include all backtranslation data as well in training
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||||
%-bt:
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${MAKE} DATASET=${DATASET}+bt USE_BACKTRANS=1 ${@:-bt=}
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${MAKE} DATASET=${DATASET}+bt USE_BACKTRANS=1 SHUFFLE_TRAINING_DATA=1 ${@:-bt=}
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## adding a pivot language to the model
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@ -271,7 +271,7 @@ PIVOT_LANG ?= ${DEFAULT_PIVOT_LANG}
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||||
## add forward translations
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||||
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||||
%-ft:
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||||
${MAKE} DATASET=${DATASET}+ft USE_FORWARDTRANS=1 ${@:-ft=}
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${MAKE} DATASET=${DATASET}+ft USE_FORWARDTRANS=1 SHUFFLE_TRAINING_DATA=1 ${@:-ft=}
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# use a selected set of forward translation
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@ -289,6 +289,7 @@ FT_SELECTED ?= 95
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done
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${MAKE} DATASET=${DATASET}+ft${FT_SELECTED} \
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USE_FORWARDTRANS_SELECTED=${FT_SELECTED} \
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SHUFFLE_TRAINING_DATA=1 \
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${@:-ftbest=}
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%-ftrawbest:
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@ -302,20 +303,21 @@ FT_SELECTED ?= 95
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||||
done
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${MAKE} DATASET=${DATASET}+ftraw${FT_SELECTED} \
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USE_FORWARDTRANS_SELECTED_RAW=${FT_SELECTED} \
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SHUFFLE_TRAINING_DATA=1 \
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${@:-ftrawbest=}
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## add forward translation of monolingual data
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%-ftmono:
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${MAKE} DATASET=${DATASET}+ftmono USE_FORWARDTRANSMONO=1 ${@:-ftmono=}
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${MAKE} DATASET=${DATASET}+ftmono USE_FORWARDTRANSMONO=1 SHUFFLE_TRAINING_DATA=1 ${@:-ftmono=}
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## pivot-based backward translation
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%-pbt:
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${MAKE} DATASET=${DATASET}+pbt USE_BACKWARD_PIVOTING=1 ${@:-pbt=}
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${MAKE} DATASET=${DATASET}+pbt USE_BACKWARD_PIVOTING=1 SHUFFLE_TRAINING_DATA=1 ${@:-pbt=}
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||||
## pivot-based backward translation
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%-pft:
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${MAKE} DATASET=${DATASET}+pft USE_FORWARD_PIVOTING=1 ${@:-pft=}
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${MAKE} DATASET=${DATASET}+pft USE_FORWARD_PIVOTING=1 SHUFFLE_TRAINING_DATA=1 ${@:-pft=}
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## pivot-based backward translation
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%-pivot:
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@ -1,4 +1,10 @@
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||||
# -*-makefile-*-
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#
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# TODO: problems with racing situations in data pre-processing?
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# (e.g. when starting simultanously jobs for both translation directions)
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||||
# --> strict filtering is done in work/data/simple/ ...
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#
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#
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||||
## 23 official EU languages:
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#
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||||
@ -61,6 +67,12 @@ engukr-quantize-student:
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||||
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||||
elg-eval:
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||||
${MAKE} elg-eval-tfbig
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${MAKE} elg-eval-multi
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||||
${MAKE} elg-eval-zle
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${MAKE} elg-pivot-eval
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||||
elg-eval-tfbig:
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for l in ${ELG_EU_SELECTED} ${ELG_EU_SELECTED_BIG}; do \
|
||||
if [ -e ${wildcard work/eng-$$l/*.npz} ]; then \
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${MAKE} MODELTYPE=transformer-big tatoeba-eng2$${l}-eval-bt; \
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||||
@ -73,6 +85,8 @@ elg-eval:
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||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${l}2eng-eval-testsets-bt; \
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||||
fi; \
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||||
done
|
||||
|
||||
elg-eval-multi:
|
||||
for l in ${ELG_EU_SELECTED_MULTILANG}; do \
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||||
${MAKE} MODELTYPE=transformer-big SRCLANGS="$$l" TRGLANGS=eng eval-bt-tatoeba; \
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${MAKE} MODELTYPE=transformer-big SRCLANGS="$$l" TRGLANGS=eng tatoeba-multilingual-eval-bt; \
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||||
@ -82,14 +96,129 @@ elg-eval:
|
||||
${MAKE} MODELTYPE=transformer-big TRGLANGS="$$l" SRCLANGS=eng eval-testsets-bt-tatoeba; \
|
||||
done
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||||
|
||||
## only separate languages in multilingual models (set of individual languages)
|
||||
elg-multieval:
|
||||
for l in ${ELG_EU_SELECTED_MULTILANG}; do \
|
||||
${MAKE} MODELTYPE=transformer-big SRCLANGS="$$l" TRGLANGS=eng tatoeba-multilingual-eval-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big TRGLANGS="$$l" SRCLANGS=eng tatoeba-multilingual-eval-bt; \
|
||||
elg-eval-zle:
|
||||
for p in zle2zle zlw2zle zle2fin zle2zlw; do \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-eval-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-multieval-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-eval-testsets-bt; \
|
||||
done
|
||||
|
||||
# multieval-bt-tatoeba; \
|
||||
elg-pivot-eval:
|
||||
for l in dan swe fin deu ron tur; do \
|
||||
if [ -e work/$$l-ukr ]; then \
|
||||
${MAKE} tatoeba-$${l}2ukr-eval-pbt; \
|
||||
fi; \
|
||||
if [ -e work/ukr-$$l ]; then \
|
||||
${MAKE} tatoeba-ukr2$${l}-eval-pft; \
|
||||
fi; \
|
||||
done
|
||||
${MAKE} SRCLANGS="ces slk" TRGLANGS=ukr eval-pbt-tatoeba
|
||||
${MAKE} SRCLANGS="ces slk" TRGLANGS=ukr tatoeba-multilingual-eval-pbt
|
||||
${MAKE} TRGLANGS="ces slk" SRCLANGS=ukr eval-pft-tatoeba
|
||||
${MAKE} TRGLANGS="ces slk" SRCLANGS=ukr tatoeba-multilingual-eval-pft
|
||||
|
||||
|
||||
|
||||
elg-dist-zle:
|
||||
for p in zle2zle zlw2zle zle2zlw; do \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-eval-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-multieval-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-eval-testsets-bt; \
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-$${p}-dist-bt; \
|
||||
done
|
||||
|
||||
|
||||
elg-dist-pivot:
|
||||
for l in deu dan swe tur fin ron hun; do \
|
||||
${MAKE} tatoeba-$${l}2ukr-dist-pbt; \
|
||||
${MAKE} tatoeba-ukr2$${l}-dist-pft; \
|
||||
done
|
||||
${MAKE} SRCLANGS="ces slk" TRGLANGS=ukr dist-pbt-tatoeba
|
||||
${MAKE} TRGLANGS="ces slk" SRCLANGS=ukr dist-pft-tatoeba
|
||||
${MAKE} tatoeba-gmq2zle-dist-pbt
|
||||
${MAKE} tatoeba-zle2gmq-dist-pft
|
||||
|
||||
|
||||
elg-dist-pivot-tmp:
|
||||
${MAKE} SRCLANGS="ces slk" TRGLANGS=ukr dist-pbt-tatoeba
|
||||
${MAKE} TRGLANGS="ces slk" SRCLANGS=ukr dist-pft-tatoeba
|
||||
|
||||
|
||||
elg-gmq2zle-pivot:
|
||||
${MAKE} MODELTYPE=transformer-big CPUJOB_HPC_MEM=32g tatoeba-gmq2zle-trainjob-pbt
|
||||
|
||||
elg-zle2gmq-pivot:
|
||||
${MAKE} MODELTYPE=transformer-big CPUJOB_HPC_MEM=32g tatoeba-zle2gmq-trainjob-pft
|
||||
|
||||
|
||||
elg-bat2zle:
|
||||
${MAKE} tatoeba-bat2zle-trainjob
|
||||
|
||||
elg-zle2bat:
|
||||
${MAKE} tatoeba-zle2bat-trainjob
|
||||
|
||||
|
||||
elg-dan2ukr:
|
||||
${MAKE} tatoeba-dan2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2dan-trainjob-pft
|
||||
|
||||
elg-swe2ukr:
|
||||
${MAKE} tatoeba-swe2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2swe-trainjob-pft
|
||||
|
||||
elg-fin2ukr:
|
||||
${MAKE} tatoeba-fin2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2fin-trainjob-pft
|
||||
|
||||
elg-ukr2fin:
|
||||
${MAKE} tatoeba-ukr2fin-trainjob-pbt-pft
|
||||
|
||||
|
||||
elg-deu2ukr:
|
||||
${MAKE} tatoeba-deu2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2deu-trainjob-pft
|
||||
|
||||
elg-slk2ukr:
|
||||
${MAKE} tatoeba-slk2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2slk-trainjob-pft
|
||||
|
||||
elg-ces_slk2ukr:
|
||||
${MAKE} SRCLANGS=ukr TRGLANGS="ces slk" tatoeba-job-pft
|
||||
${MAKE} TRGLANGS=ukr SRCLANGS="ces slk" tatoeba-job-pbt
|
||||
|
||||
elg-ron2ukr:
|
||||
${MAKE} tatoeba-ron2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2ron-trainjob-pft
|
||||
|
||||
elg-tur2ukr:
|
||||
${MAKE} tatoeba-tur2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2tur-trainjob-pft
|
||||
|
||||
elg-hun2ukr:
|
||||
${MAKE} tatoeba-hun2ukr-trainjob-pbt
|
||||
${MAKE} tatoeba-ukr2hun-trainjob-pft
|
||||
|
||||
|
||||
|
||||
|
||||
## continue with pivot-based model training (after shuffling)
|
||||
## (because it was not shuffled before, now shuffling is done by default)
|
||||
elg-ukr2deu-continue:
|
||||
rm -f work/ukr-deu/*.done
|
||||
${MAKE} SRCLANGS=ukr TRGLANGS=deu shuffle-training-data-pft-tatoeba
|
||||
${MAKE} MARIAN_EARLY_STOPPING=15 MARIAN_EXTRA=--no-restore-corpus tatoeba-ukr2deu-trainjob-pft
|
||||
|
||||
elg-deu2ukr-continue:
|
||||
rm -f work/deu-ukr/*.done
|
||||
${MAKE} SRCLANGS=deu TRGLANGS=ukr shuffle-training-data-pbt-tatoeba
|
||||
${MAKE} MARIAN_EARLY_STOPPING=15 MARIAN_EXTRA=--no-restore-corpus tatoeba-deu2ukr-trainjob-pbt
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
elg-eng2all:
|
||||
@ -149,11 +278,95 @@ elg-all2eng-eval:
|
||||
done
|
||||
|
||||
|
||||
elg-tune4ukr2eng:
|
||||
${MAKE} MODELTYPE=transformer-big TUNE_SRC=ukr TUNE_TRG=eng tatoeba-zle2eng-langtunejob
|
||||
|
||||
|
||||
## including English as a pivot language
|
||||
elg-zle2zlw-pivot:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2zlw-trainjob-bt-pivotlang
|
||||
|
||||
elg-zlw2zle-pivot:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zlw2zle-trainjob-bt-pivotlang
|
||||
|
||||
|
||||
elg-zle2zlw:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=24g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2zlw-trainjob-bt
|
||||
|
||||
elg-zlw2zle:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=24g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zlw2zle-trainjob-bt
|
||||
|
||||
elg-zle2zls:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=24g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2zls-trainjob-bt
|
||||
|
||||
elg-zls2zle:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=24g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zls2zle-trainjob-bt
|
||||
|
||||
|
||||
elg-zle2zle:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2zle-trainjob-bt
|
||||
|
||||
elg-gmq2zle:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-gmq2zle-trainjob-bt
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2gmq-trainjob-bt
|
||||
|
||||
elg-big2zle:
|
||||
for l in deu fra spa por ita; do \
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-$${l}2zle-trainjob; \
|
||||
done
|
||||
|
||||
elg-zle2big:
|
||||
for l in deu fra spa por ita; do \
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-zle2$${l}-trainjob; \
|
||||
done
|
||||
|
||||
|
||||
elg-zle2fin:
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-zle2fin-trainjob-bt
|
||||
|
||||
elg-fin2zle:
|
||||
${MAKE} MODELTYPE=transformer-big tatoeba-fin2zle-trainjob-bt
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
elg-sla2sla:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
tatoeba-sla2sla-trainjob-bt
|
||||
|
||||
|
||||
elg-eng2cel:
|
||||
@ -213,6 +426,13 @@ elg-multi2eng:
|
||||
TRGLANGS=eng SRCLANGS="por glg" \
|
||||
tatoeba-job-bt
|
||||
|
||||
elg-eng2spa:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
DATA_PREPARE_HPCPARAMS='CPUJOB_HPC_CORES=2 CPUJOB_HPC_MEM=16g CPUJOB_HPC_DISK=1000' \
|
||||
SRCLANGS=eng TRGLANGS="cat oci spa" \
|
||||
tatoeba-job-bt
|
||||
|
||||
|
||||
elg-ces2eng:
|
||||
${MAKE} MODELTYPE=transformer-big \
|
||||
@ -248,3 +468,78 @@ elg-eng2fin:
|
||||
MARIAN_EXTRA=--no-restore-corpus \
|
||||
tatoeba-eng2fin-trainjob-bt
|
||||
|
||||
|
||||
|
||||
good-ukr-models:
|
||||
@grep '^[^ ]*-ukr' ~/research/Tatoeba-Challenge/models/released-model-results-all.txt | \
|
||||
grep -v 'tuned4' | rev | uniq -f5 | rev | grep '[3-9][0-9]\.[0-9]' | grep -P '\t[0-9]{3,}\t'
|
||||
@grep '^ukr-' ~/research/Tatoeba-Challenge/models/released-model-results-all.txt | \
|
||||
grep -v 'tuned4' | rev | uniq -f5 | rev | grep '[3-9][0-9]\.[0-9]' | grep -P '\t[0-9]{3,}\t'
|
||||
|
||||
ukr-model-table:
|
||||
make -s good-ukr-models |\
|
||||
cut -f1-4 |\
|
||||
sed 's/ / | /g;s/^/| /;s/$$/ |/' |\
|
||||
sed 's#\(https://object.pouta.csc.fi/Tatoeba-MT-models/\)\(.*\).zip#[\2](\1\2.zip)#'
|
||||
|
||||
|
||||
ukr-model-table2:
|
||||
make -s good-ukr-models | cut -f1-4 > $@.tmp1
|
||||
cut -f1 $@.tmp1 | xargs iso639 -p | sed "s/^\"//;s/\"$$//;s#\" \"#\n#g" > $@.tmp2
|
||||
paste $@.tmp2 $@.tmp1 |\
|
||||
sed 's/ / | /g;s/^/| /;s/$$/ |/' |\
|
||||
sed 's#\(https://object.pouta.csc.fi/Tatoeba-MT-models/\)\(.*\).zip#[\2](\1\2.zip)#'
|
||||
rm -f $@.tmp*
|
||||
|
||||
|
||||
|
||||
# SCORE_BASE_URL = https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master
|
||||
SCORE_BASE_URL = https://github.com/Helsinki-NLP/OPUS-MT-train/blob/puhti
|
||||
|
||||
print-ukr2x-table:
|
||||
@echo '| language pair | lang-IDs | BLEU | model |'
|
||||
@echo '|---------------|----------|------|-------|'
|
||||
@grep '^[1-9][0-9]\.' ../scores/ukr-*/flores101-devtest/bleu-scores*txt | \
|
||||
sed 's/:/ /' | sort -nr | rev | uniq -f2 | rev| sort > $@.tmp1
|
||||
@cut -f3 -d'/' $@.tmp1 > $@.langids
|
||||
@cut -f1 $@.langids | xargs iso639 -p | sed "s/^\"//;s/\"$$//;s#\" \"#\n#g" > $@.langnames
|
||||
@cut -f1 $@.tmp1 | sed 's#^\.\.#${SCORE_BASE_URL}#' > $@.bleufile
|
||||
@cut -f2 $@.tmp1 > $@.bleuscore
|
||||
@cut -f3 $@.tmp1 > $@.link
|
||||
@paste $@.bleuscore $@.bleufile | sed 's/ /\]\(/;s/^/\[/;s/$$/\)/' > $@.bleulink
|
||||
@paste $@.langnames $@.langids $@.bleulink $@.link |\
|
||||
grep -v 'Indonesian' | grep -v 'Afrikaans' |\
|
||||
sed 's/ / | /g;s/^/| /;s/$$/ |/' |\
|
||||
sed 's#\(https://object.pouta.csc.fi/Tatoeba-MT-models/\)\(.*\).zip#[\2](\1\2.zip)#'
|
||||
@rm -f $@.*
|
||||
|
||||
|
||||
print-x2ukr-table:
|
||||
@echo '| language pair | lang-IDs | BLEU | model |'
|
||||
@echo '|---------------|----------|------|-------|'
|
||||
@grep '^[1-9][0-9]\.' ../scores/*-ukr/flores101-devtest/bleu-scores*txt | \
|
||||
sed 's/:/ /' | sort -nr | rev | uniq -f2 | rev| sort > $@.tmp1
|
||||
@cut -f3 -d'/' $@.tmp1 > $@.langids
|
||||
@cut -f1 $@.langids | xargs iso639 -p | sed "s/^\"//;s/\"$$//;s#\" \"#\n#g" > $@.langnames
|
||||
@cut -f1 $@.tmp1 | sed 's#^\.\.#${SCORE_BASE_URL}#' > $@.bleufile
|
||||
@cut -f2 $@.tmp1 > $@.bleuscore
|
||||
@cut -f3 $@.tmp1 > $@.link
|
||||
@paste $@.bleuscore $@.bleufile | sed 's/ /\]\(/;s/^/\[/;s/$$/\)/' > $@.bleulink
|
||||
@paste $@.langnames $@.langids $@.bleulink $@.link |\
|
||||
grep -v 'Indonesian' | grep -v 'Afrikaans' |\
|
||||
sed 's/ / | /g;s/^/| /;s/$$/ |/' |\
|
||||
sed 's#\(https://object.pouta.csc.fi/Tatoeba-MT-models/\)\(.*\).zip#[\2](\1\2.zip)#'
|
||||
@rm -f $@.*
|
||||
|
||||
opus-mt-ukr-flores-devtest.md:
|
||||
echo "# OPUS-MT models for Ukrainian" > $@
|
||||
echo "" >> $@
|
||||
echo "The following tables list the best OPUS-MT models for translating from and to Ukrainian according to the flores101 devtest benchmark. Results are given in standard BLEU scores (using sacrebleu)." >> $@
|
||||
echo "" >> $@
|
||||
echo "## Translations from Ukrainian" >> $@
|
||||
echo "" >> $@
|
||||
make -s print-ukr2x-table >> $@
|
||||
echo "" >> $@
|
||||
echo "## Translations to Ukrainian" >> $@
|
||||
echo "" >> $@
|
||||
make -s print-x2ukr-table >> $@
|
||||
|
||||
@ -244,8 +244,8 @@ OPUS_LANG_GRANDPARENTS := ${sort ${shell langgroup -p -n ${OPUS_LANG_PARENTS} 2>
|
||||
OPUS_LANG_GROUPS := ${sort ${OPUS_LANG_PARENTS} ${OPUS_LANG_GRANDPARENTS}}
|
||||
|
||||
|
||||
.PHONY: tatoeba
|
||||
tatoeba:
|
||||
.PHONY: tatoeba tatoeba-all
|
||||
tatoeba tatoeba-all:
|
||||
${MAKE} tatoeba-prepare
|
||||
${MAKE} all-tatoeba
|
||||
|
||||
|
||||
@ -102,7 +102,7 @@ tatoeba-%-langtune:
|
||||
( s=$(firstword $(subst 2, ,$(patsubst tatoeba-%-langtune,%,$@))); \
|
||||
t=$(lastword $(subst 2, ,$(patsubst tatoeba-%-langtune,%,$@))); \
|
||||
if [ -d ${WORKHOME}/$$s-$$t ]; then \
|
||||
${MAKE} LANGPAIRSTR=$$s-$$t ${TATOEBA_LANGTUNE_PARAMS} tatoeba; \
|
||||
${MAKE} LANGPAIRSTR=$$s-$$t ${TATOEBA_LANGTUNE_PARAMS} tatoeba-all; \
|
||||
fi )
|
||||
|
||||
# SRCLANGS="${call find-srclanggroup,${patsubst tatoeba-%-langtune,%,$@},${PIVOT}}" \
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
10.2 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zlw/opusTCv20210807+bt_transformer-big_2022-03-07.zip
|
||||
8.7 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-10-04.zip
|
||||
8.4 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-21.zip
|
||||
8.2 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-27.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.40907 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zlw/opusTCv20210807+bt_transformer-big_2022-03-07.zip
|
||||
0.380 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-27.zip
|
||||
0.378 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-10-04.zip
|
||||
0.375 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-21.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
10.7 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zlw/opusTCv20210807+bt_transformer-big_2022-03-07.zip
|
||||
9.0 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-27.zip
|
||||
8.7 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-10-04.zip
|
||||
8.3 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-21.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.41037 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zlw/opusTCv20210807+bt_transformer-big_2022-03-07.zip
|
||||
0.383 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-07-27.zip
|
||||
0.380 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-10-04.zip
|
||||
0.376 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-09-26.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
17.8 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
14.6 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
13.5 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
13.0 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus4m-2020-08-12.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.51962 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
0.493 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
0.488 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
0.464 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
18.0 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
15.5 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
15.2 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
13.9 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.51689 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
0.495 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
0.489 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
0.464 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
48.0 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
43.5 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
42.6 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
42.1 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus2m-2020-08-01.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.65132 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
0.620 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
0.609 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
0.603 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
48.0 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
43.5 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
42.6 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
42.1 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus2m-2020-08-01.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.65132 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
0.620 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
0.609 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
0.603 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
48.0 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
43.4 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
42.6 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
42.1 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-eng/opus2m-2020-08-01.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
0.65132 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opusTCv20210807+bt_transformer-big_2022-03-03.zip
|
||||
0.620 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-eng/opus1m+bt-2021-05-02.zip
|
||||
0.609 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-eng/opus4m-2020-08-12.zip
|
||||
0.603 https://object.pouta.csc.fi/Tatoeba-MT-models/bel-eng/opus+bt-2021-04-30.zip
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
9.6 https://object.pouta.csc.fi/Tatoeba-MT-models/zle-zlw/opusTCv20210807+bt_transformer-big_2022-03-07.zip
|
||||
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||||
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||||
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||||
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||||
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0.678 https://object.pouta.csc.fi/Tatoeba-MT-models/sla-sla/opus-2020-09-26.zip
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23.5 https://object.pouta.csc.fi/Tatoeba-MT-models/dan-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
9.7 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
9.2 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-21.zip
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||||
23.8 https://object.pouta.csc.fi/Tatoeba-MT-models/dan-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
10.0 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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9.3 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-21.zip
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||||
23.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
14.3 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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||||
14.2 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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||||
9.2 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
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||||
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0.421 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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0.351 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
23.6 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
14.7 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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||||
14.6 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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9.2 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
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0.52614 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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0.436 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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0.427 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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0.360 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
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||||
40.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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||||
39.3 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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39.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
27.0 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
26.1 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-21.zip
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||||
23.6 https://object.pouta.csc.fi/Tatoeba-MT-models/tatoeba-lowest/opus-2020-06-15.zip
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||||
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||||
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||||
0.61732 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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0.486 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
40.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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||||
39.3 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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39.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
26.9 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
26.0 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-21.zip
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23.6 https://object.pouta.csc.fi/Tatoeba-MT-models/tatoeba-lowest/opus-2020-06-15.zip
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||||
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40.0 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opus-2021-02-18.zip
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||||
39.3 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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39.1 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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||||
26.9 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
26.0 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-21.zip
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||||
23.5 https://object.pouta.csc.fi/Tatoeba-MT-models/tatoeba-lowest/opus-2020-06-15.zip
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||||
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0.61767 https://object.pouta.csc.fi/Tatoeba-MT-models/deu-ukr/opusTCv20210807+pbt_transformer-align_2022-03-07.zip
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0.605 https://object.pouta.csc.fi/Tatoeba-MT-models/gmw-zle/opus1m-2021-02-12.zip
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0.485 https://object.pouta.csc.fi/Tatoeba-MT-models/ine-ine/opus-2020-07-27.zip
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||||
|
||||
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