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wmt-2020-pl-en-moses/train/working/training.out
Kasia d5fe8b804f first try moses
2021-02-18 00:47:47 +01:00

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nohup: zignorowane dane wejściowe
Using SCRIPTS_ROOTDIR: /home/kasia/mosesdecoder/scripts
Using single-thread GIZA
using gzip
(1) preparing corpus @ Wed Feb 17 14:41:26 CET 2021
Executing: mkdir -p /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus
(1.0) selecting factors @ Wed Feb 17 14:41:26 CET 2021
(1.1) running mkcls @ Wed Feb 17 14:41:26 CET 2021
/home/kasia/mosesdecoder/tools/mkcls -c50 -n2 -p/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.pl -V/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb.classes opt
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb.classes already in place, reusing
(1.1) running mkcls @ Wed Feb 17 14:41:26 CET 2021
/home/kasia/mosesdecoder/tools/mkcls -c50 -n2 -p/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.en -V/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb.classes opt
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb.classes already in place, reusing
(1.2) creating vcb file /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb @ Wed Feb 17 14:41:26 CET 2021
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(2.1b) running giza pl-en @ Wed Feb 17 14:42:19 CET 2021
/home/kasia/mosesdecoder/tools/GIZA++ -CoocurrenceFile /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.pl-en/pl-en.cooc -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl-en-int-train.snt -m1 5 -m2 0 -m3 3 -m4 3 -model1dumpfrequency 1 -model4smoothfactor 0.4 -nodumps 1 -nsmooth 4 -o /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.pl-en/pl-en -onlyaldumps 1 -p0 0.999 -s /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb -t /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.pl-en/pl-en.A3.final.gz seems finished, reusing.
(2.1a) running snt2cooc en-pl @ Wed Feb 17 14:42:19 CET 2021
Executing: mkdir -p /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl
Executing: /home/kasia/mosesdecoder/tools/snt2cooc.out /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc
/home/kasia/mosesdecoder/tools/snt2cooc.out /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc
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(2.1b) running giza en-pl @ Wed Feb 17 14:43:29 CET 2021
/home/kasia/mosesdecoder/tools/GIZA++ -CoocurrenceFile /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt -m1 5 -m2 0 -m3 3 -m4 3 -model1dumpfrequency 1 -model4smoothfactor 0.4 -nodumps 1 -nsmooth 4 -o /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl -onlyaldumps 1 -p0 0.999 -s /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb -t /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb
Executing: /home/kasia/mosesdecoder/tools/GIZA++ -CoocurrenceFile /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt -m1 5 -m2 0 -m3 3 -m4 3 -model1dumpfrequency 1 -model4smoothfactor 0.4 -nodumps 1 -nsmooth 4 -o /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl -onlyaldumps 1 -p0 0.999 -s /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb -t /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb
/home/kasia/mosesdecoder/tools/GIZA++ -CoocurrenceFile /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt -m1 5 -m2 0 -m3 3 -m4 3 -model1dumpfrequency 1 -model4smoothfactor 0.4 -nodumps 1 -nsmooth 4 -o /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl -onlyaldumps 1 -p0 0.999 -s /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb -t /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb
Parameter 'coocurrencefile' changed from '' to '/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.cooc'
Parameter 'c' changed from '' to '/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt'
Parameter 'm3' changed from '5' to '3'
Parameter 'm4' changed from '5' to '3'
Parameter 'model1dumpfrequency' changed from '0' to '1'
Parameter 'model4smoothfactor' changed from '0.2' to '0.4'
Parameter 'nodumps' changed from '0' to '1'
Parameter 'nsmooth' changed from '64' to '4'
Parameter 'o' changed from '2021-02-17.144329.kasia' to '/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl'
Parameter 'onlyaldumps' changed from '0' to '1'
Parameter 'p0' changed from '-1' to '0.999'
Parameter 's' changed from '' to '/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb'
Parameter 't' changed from '' to '/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb'
general parameters:
-------------------
ml = 101 (maximum sentence length)
No. of iterations:
-------------------
hmmiterations = 5 (mh)
model1iterations = 5 (number of iterations for Model 1)
model2iterations = 0 (number of iterations for Model 2)
model3iterations = 3 (number of iterations for Model 3)
model4iterations = 3 (number of iterations for Model 4)
model5iterations = 0 (number of iterations for Model 5)
model6iterations = 0 (number of iterations for Model 6)
parameter for various heuristics in GIZA++ for efficient training:
------------------------------------------------------------------
countincreasecutoff = 1e-06 (Counts increment cutoff threshold)
countincreasecutoffal = 1e-05 (Counts increment cutoff threshold for alignments in training of fertility models)
mincountincrease = 1e-07 (minimal count increase)
peggedcutoff = 0.03 (relative cutoff probability for alignment-centers in pegging)
probcutoff = 1e-07 (Probability cutoff threshold for lexicon probabilities)
probsmooth = 1e-07 (probability smoothing (floor) value )
parameters for describing the type and amount of output:
-----------------------------------------------------------
compactalignmentformat = 0 (0: detailled alignment format, 1: compact alignment format )
hmmdumpfrequency = 0 (dump frequency of HMM)
l = 2021-02-17.144329.kasia.log (log file name)
log = 0 (0: no logfile; 1: logfile)
model1dumpfrequency = 1 (dump frequency of Model 1)
model2dumpfrequency = 0 (dump frequency of Model 2)
model345dumpfrequency = 0 (dump frequency of Model 3/4/5)
nbestalignments = 0 (for printing the n best alignments)
nodumps = 1 (1: do not write any files)
o = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl (output file prefix)
onlyaldumps = 1 (1: do not write any files)
outputpath = (output path)
transferdumpfrequency = 0 (output: dump of transfer from Model 2 to 3)
verbose = 0 (0: not verbose; 1: verbose)
verbosesentence = -10 (number of sentence for which a lot of information should be printed (negative: no output))
parameters describing input files:
----------------------------------
c = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt (training corpus file name)
d = (dictionary file name)
s = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb (source vocabulary file name)
t = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb (target vocabulary file name)
tc = (test corpus file name)
smoothing parameters:
---------------------
emalsmooth = 0.2 (f-b-trn: smoothing factor for HMM alignment model (can be ignored by -emSmoothHMM))
model23smoothfactor = 0 (smoothing parameter for IBM-2/3 (interpolation with constant))
model4smoothfactor = 0.4 (smooting parameter for alignment probabilities in Model 4)
model5smoothfactor = 0.1 (smooting parameter for distortion probabilities in Model 5 (linear interpolation with constant))
nsmooth = 4 (smoothing for fertility parameters (good value: 64): weight for wordlength-dependent fertility parameters)
nsmoothgeneral = 0 (smoothing for fertility parameters (default: 0): weight for word-independent fertility parameters)
parameters modifying the models:
--------------------------------
compactadtable = 1 (1: only 3-dimensional alignment table for IBM-2 and IBM-3)
deficientdistortionforemptyword = 0 (0: IBM-3/IBM-4 as described in (Brown et al. 1993); 1: distortion model of empty word is deficient; 2: distoriton model of empty word is deficient (differently); setting this parameter also helps to avoid that during IBM-3 and IBM-4 training too many words are aligned with the empty word)
depm4 = 76 (d_{=1}: &1:l, &2:m, &4:F, &8:E, d_{>1}&16:l, &32:m, &64:F, &128:E)
depm5 = 68 (d_{=1}: &1:l, &2:m, &4:F, &8:E, d_{>1}&16:l, &32:m, &64:F, &128:E)
emalignmentdependencies = 2 (lextrain: dependencies in the HMM alignment model. &1: sentence length; &2: previous class; &4: previous position; &8: French position; &16: French class)
emprobforempty = 0.4 (f-b-trn: probability for empty word)
parameters modifying the EM-algorithm:
--------------------------------------
m5p0 = -1 (fixed value for parameter p_0 in IBM-5 (if negative then it is determined in training))
manlexfactor1 = 0 ()
manlexfactor2 = 0 ()
manlexmaxmultiplicity = 20 ()
maxfertility = 10 (maximal fertility for fertility models)
p0 = 0.999 (fixed value for parameter p_0 in IBM-3/4 (if negative then it is determined in training))
pegging = 0 (0: no pegging; 1: do pegging)
general parameters:
-------------------
ml = 101 (maximum sentence length)
No. of iterations:
-------------------
hmmiterations = 5 (mh)
model1iterations = 5 (number of iterations for Model 1)
model2iterations = 0 (number of iterations for Model 2)
model3iterations = 3 (number of iterations for Model 3)
model4iterations = 3 (number of iterations for Model 4)
model5iterations = 0 (number of iterations for Model 5)
model6iterations = 0 (number of iterations for Model 6)
parameter for various heuristics in GIZA++ for efficient training:
------------------------------------------------------------------
countincreasecutoff = 1e-06 (Counts increment cutoff threshold)
countincreasecutoffal = 1e-05 (Counts increment cutoff threshold for alignments in training of fertility models)
mincountincrease = 1e-07 (minimal count increase)
peggedcutoff = 0.03 (relative cutoff probability for alignment-centers in pegging)
probcutoff = 1e-07 (Probability cutoff threshold for lexicon probabilities)
probsmooth = 1e-07 (probability smoothing (floor) value )
parameters for describing the type and amount of output:
-----------------------------------------------------------
compactalignmentformat = 0 (0: detailled alignment format, 1: compact alignment format )
hmmdumpfrequency = 0 (dump frequency of HMM)
l = 2021-02-17.144329.kasia.log (log file name)
log = 0 (0: no logfile; 1: logfile)
model1dumpfrequency = 1 (dump frequency of Model 1)
model2dumpfrequency = 0 (dump frequency of Model 2)
model345dumpfrequency = 0 (dump frequency of Model 3/4/5)
nbestalignments = 0 (for printing the n best alignments)
nodumps = 1 (1: do not write any files)
o = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl (output file prefix)
onlyaldumps = 1 (1: do not write any files)
outputpath = (output path)
transferdumpfrequency = 0 (output: dump of transfer from Model 2 to 3)
verbose = 0 (0: not verbose; 1: verbose)
verbosesentence = -10 (number of sentence for which a lot of information should be printed (negative: no output))
parameters describing input files:
----------------------------------
c = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt (training corpus file name)
d = (dictionary file name)
s = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb (source vocabulary file name)
t = /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb (target vocabulary file name)
tc = (test corpus file name)
smoothing parameters:
---------------------
emalsmooth = 0.2 (f-b-trn: smoothing factor for HMM alignment model (can be ignored by -emSmoothHMM))
model23smoothfactor = 0 (smoothing parameter for IBM-2/3 (interpolation with constant))
model4smoothfactor = 0.4 (smooting parameter for alignment probabilities in Model 4)
model5smoothfactor = 0.1 (smooting parameter for distortion probabilities in Model 5 (linear interpolation with constant))
nsmooth = 4 (smoothing for fertility parameters (good value: 64): weight for wordlength-dependent fertility parameters)
nsmoothgeneral = 0 (smoothing for fertility parameters (default: 0): weight for word-independent fertility parameters)
parameters modifying the models:
--------------------------------
compactadtable = 1 (1: only 3-dimensional alignment table for IBM-2 and IBM-3)
deficientdistortionforemptyword = 0 (0: IBM-3/IBM-4 as described in (Brown et al. 1993); 1: distortion model of empty word is deficient; 2: distoriton model of empty word is deficient (differently); setting this parameter also helps to avoid that during IBM-3 and IBM-4 training too many words are aligned with the empty word)
depm4 = 76 (d_{=1}: &1:l, &2:m, &4:F, &8:E, d_{>1}&16:l, &32:m, &64:F, &128:E)
depm5 = 68 (d_{=1}: &1:l, &2:m, &4:F, &8:E, d_{>1}&16:l, &32:m, &64:F, &128:E)
emalignmentdependencies = 2 (lextrain: dependencies in the HMM alignment model. &1: sentence length; &2: previous class; &4: previous position; &8: French position; &16: French class)
emprobforempty = 0.4 (f-b-trn: probability for empty word)
parameters modifying the EM-algorithm:
--------------------------------------
m5p0 = -1 (fixed value for parameter p_0 in IBM-5 (if negative then it is determined in training))
manlexfactor1 = 0 ()
manlexfactor2 = 0 ()
manlexmaxmultiplicity = 20 ()
maxfertility = 10 (maximal fertility for fertility models)
p0 = 0.999 (fixed value for parameter p_0 in IBM-3/4 (if negative then it is determined in training))
pegging = 0 (0: no pegging; 1: do pegging)
reading vocabulary files
Reading vocabulary file from:/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/pl.vcb
Reading vocabulary file from:/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en.vcb
Source vocabulary list has 44236 unique tokens
Target vocabulary list has 19029 unique tokens
Calculating vocabulary frequencies from corpus /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/corpus/en-pl-int-train.snt
Reading more sentence pairs into memory ...
Corpus fits in memory, corpus has: 24744 sentence pairs.
Train total # sentence pairs (weighted): 24744
Size of source portion of the training corpus: 564554 tokens
Size of the target portion of the training corpus: 654662 tokens
In source portion of the training corpus, only 44235 unique tokens appeared
In target portion of the training corpus, only 19027 unique tokens appeared
lambda for PP calculation in IBM-1,IBM-2,HMM:= 654662/(589298-24744)== 1.15961
There are 5299035 5299035 entries in table
==========================================================
Model1 Training Started at: Wed Feb 17 14:43:51 2021
-----------
Model1: Iteration 1
Model1: (1) TRAIN CROSS-ENTROPY 14.3728 PERPLEXITY 21214.8
Model1: (1) VITERBI TRAIN CROSS-ENTROPY inf PERPLEXITY inf
Model 1 Iteration: 1 took: 42 seconds
-----------
Model1: Iteration 2
Model1: (2) TRAIN CROSS-ENTROPY 6.99257 PERPLEXITY 127.343
Model1: (2) VITERBI TRAIN CROSS-ENTROPY 9.63962 PERPLEXITY 797.652
Model 1 Iteration: 2 took: 30 seconds
-----------
Model1: Iteration 3
Model1: (3) TRAIN CROSS-ENTROPY 6.21065 PERPLEXITY 74.0614
Model1: (3) VITERBI TRAIN CROSS-ENTROPY 8.25816 PERPLEXITY 306.163
Model 1 Iteration: 3 took: 34 seconds
-----------
Model1: Iteration 4
Model1: (4) TRAIN CROSS-ENTROPY 5.86592 PERPLEXITY 58.3199
Model1: (4) VITERBI TRAIN CROSS-ENTROPY 7.5277 PERPLEXITY 184.528
Model 1 Iteration: 4 took: 36 seconds
-----------
Model1: Iteration 5
Model1: (5) TRAIN CROSS-ENTROPY 5.72968 PERPLEXITY 53.0646
Model1: (5) VITERBI TRAIN CROSS-ENTROPY 7.16976 PERPLEXITY 143.983
Model 1 Iteration: 5 took: 36 seconds
Entire Model1 Training took: 178 seconds
NOTE: I am doing iterations with the HMM model!
Read classes: #words: 44235 #classes: 51
Read classes: #words: 19028 #classes: 51
==========================================================
Hmm Training Started at: Wed Feb 17 14:46:51 2021
-----------
Hmm: Iteration 1
A/D table contains 224673 parameters.
Hmm: (1) TRAIN CROSS-ENTROPY 5.55273 PERPLEXITY 46.9394
Hmm: (1) VITERBI TRAIN CROSS-ENTROPY 6.96819 PERPLEXITY 125.209
Hmm Iteration: 1 took: 349 seconds
-----------
Hmm: Iteration 2
A/D table contains 224673 parameters.
Hmm: (2) TRAIN CROSS-ENTROPY 5.2041 PERPLEXITY 36.863
Hmm: (2) VITERBI TRAIN CROSS-ENTROPY 5.8443 PERPLEXITY 57.4528
Hmm Iteration: 2 took: 326 seconds
-----------
Hmm: Iteration 3
A/D table contains 224673 parameters.
Hmm: (3) TRAIN CROSS-ENTROPY 4.65738 PERPLEXITY 25.2355
Hmm: (3) VITERBI TRAIN CROSS-ENTROPY 5.01702 PERPLEXITY 32.3796
Hmm Iteration: 3 took: 310 seconds
-----------
Hmm: Iteration 4
A/D table contains 224673 parameters.
Hmm: (4) TRAIN CROSS-ENTROPY 4.34099 PERPLEXITY 20.266
Hmm: (4) VITERBI TRAIN CROSS-ENTROPY 4.58726 PERPLEXITY 24.0382
Hmm Iteration: 4 took: 357 seconds
-----------
Hmm: Iteration 5
A/D table contains 224673 parameters.
Hmm: (5) TRAIN CROSS-ENTROPY 4.19589 PERPLEXITY 18.3268
Hmm: (5) VITERBI TRAIN CROSS-ENTROPY 4.39346 PERPLEXITY 21.0166
Hmm Iteration: 5 took: 384 seconds
Entire Hmm Training took: 1726 seconds
==========================================================
Read classes: #words: 44235 #classes: 51
Read classes: #words: 19028 #classes: 51
Read classes: #words: 44235 #classes: 51
Read classes: #words: 19028 #classes: 51
==========================================================
Starting H333444: Viterbi Training
H333444 Training Started at: Wed Feb 17 15:15:40 2021
---------------------
THTo3: Iteration 1
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1196.14 #alsophisticatedcountcollection: 0 #hcsteps: 0
#peggingImprovements: 0
A/D table contains 224673 parameters.
A/D table contains 200260 parameters.
NTable contains 442360 parameter.
p0_count is 481744 and p1 is 86458.7; p0 is 0.999 p1: 0.001
THTo3: TRAIN CROSS-ENTROPY 4.07617 PERPLEXITY 16.8675
THTo3: (1) TRAIN VITERBI CROSS-ENTROPY 4.1553 PERPLEXITY 17.8185
THTo3 Viterbi Iteration : 1 took: 316 seconds
---------------------
Model3: Iteration 2
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1202.69 #alsophisticatedcountcollection: 0 #hcsteps: 4.44475
#peggingImprovements: 0
A/D table contains 224673 parameters.
A/D table contains 200260 parameters.
NTable contains 442360 parameter.
p0_count is 578971 and p1 is 37845.7; p0 is 0.999 p1: 0.001
Model3: TRAIN CROSS-ENTROPY 5.90798 PERPLEXITY 60.0455
Model3: (2) TRAIN VITERBI CROSS-ENTROPY 5.99155 PERPLEXITY 63.626
Model3 Viterbi Iteration : 2 took: 227 seconds
---------------------
Model3: Iteration 3
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1203.15 #alsophisticatedcountcollection: 0 #hcsteps: 4.5232
#peggingImprovements: 0
A/D table contains 224673 parameters.
A/D table contains 200260 parameters.
NTable contains 442360 parameter.
p0_count is 602707 and p1 is 25977.5; p0 is 0.999 p1: 0.001
Model3: TRAIN CROSS-ENTROPY 5.70902 PERPLEXITY 52.3104
Model3: (3) TRAIN VITERBI CROSS-ENTROPY 5.78006 PERPLEXITY 54.9506
Model3 Viterbi Iteration : 3 took: 121 seconds
---------------------
T3To4: Iteration 4
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1203.25 #alsophisticatedcountcollection: 68.6223 #hcsteps: 4.50291
#peggingImprovements: 0
D4 table contains 527191 parameters.
A/D table contains 224673 parameters.
A/D table contains 200260 parameters.
NTable contains 442360 parameter.
p0_count is 610028 and p1 is 22316.8; p0 is 0.999 p1: 0.001
T3To4: TRAIN CROSS-ENTROPY 5.65874 PERPLEXITY 50.5185
T3To4: (4) TRAIN VITERBI CROSS-ENTROPY 5.72488 PERPLEXITY 52.8884
T3To4 Viterbi Iteration : 4 took: 118 seconds
---------------------
Model4: Iteration 5
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1203.02 #alsophisticatedcountcollection: 54.8872 #hcsteps: 3.70651
#peggingImprovements: 0
D4 table contains 527191 parameters.
A/D table contains 224673 parameters.
A/D table contains 200565 parameters.
NTable contains 442360 parameter.
p0_count is 599062 and p1 is 27799.8; p0 is 0.999 p1: 0.001
Model4: TRAIN CROSS-ENTROPY 5.26987 PERPLEXITY 38.5824
Model4: (5) TRAIN VITERBI CROSS-ENTROPY 5.31993 PERPLEXITY 39.9445
Model4 Viterbi Iteration : 5 took: 370 seconds
---------------------
Model4: Iteration 6
10000
20000
#centers(pre/hillclimbed/real): 1 1 1 #al: 1202.95 #alsophisticatedcountcollection: 47.6773 #hcsteps: 3.65204
#peggingImprovements: 0
D4 table contains 527191 parameters.
A/D table contains 224673 parameters.
A/D table contains 200565 parameters.
NTable contains 442360 parameter.
p0_count is 599681 and p1 is 27490.4; p0 is 0.999 p1: 0.001
Model4: TRAIN CROSS-ENTROPY 5.08712 PERPLEXITY 33.9919
Model4: (6) TRAIN VITERBI CROSS-ENTROPY 5.13153 PERPLEXITY 35.0545
Model4 Viterbi Iteration : 6 took: 362 seconds
H333444 Training Finished at: Wed Feb 17 15:40:54 2021
Entire Viterbi H333444 Training took: 1514 seconds
==========================================================
Entire Training took: 3445 seconds
Program Finished at: Wed Feb 17 15:40:54 2021
==========================================================
Executing: rm -f /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.A3.final.gz
Executing: gzip /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.A3.final
(3) generate word alignment @ Wed Feb 17 15:41:01 CET 2021
Combining forward and inverted alignment from files:
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.pl-en/pl-en.A3.final.{bz2,gz}
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.A3.final.{bz2,gz}
Executing: mkdir -p /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model
Executing: /home/kasia/mosesdecoder/scripts/training/giza2bal.pl -d "gzip -cd /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.en-pl/en-pl.A3.final.gz" -i "gzip -cd /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/giza.pl-en/pl-en.A3.final.gz" |/home/kasia/mosesdecoder/scripts/../bin/symal -alignment="grow" -diagonal="yes" -final="yes" -both="yes" > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/aligned.grow-diag-final-and
symal: computing grow alignment: diagonal (1) final (1)both-uncovered (1)
skip=<0> counts=<24744>
(4) generate lexical translation table 0-0 @ Wed Feb 17 15:41:23 CET 2021
(/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.pl,/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.en,/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex)
reusing: /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.f2e and /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.e2f
(5) extract phrases @ Wed Feb 17 15:41:23 CET 2021
/home/kasia/mosesdecoder/scripts/generic/extract-parallel.perl 8 split "sort " /home/kasia/mosesdecoder/scripts/../bin/extract /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.en /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.pl /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/aligned.grow-diag-final-and /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract 7 orientation --model wbe-msd --GZOutput
Executing: /home/kasia/mosesdecoder/scripts/generic/extract-parallel.perl 8 split "sort " /home/kasia/mosesdecoder/scripts/../bin/extract /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.en /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.pl /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/aligned.grow-diag-final-and /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract 7 orientation --model wbe-msd --GZOutput
MAX 7 1 0
Started Wed Feb 17 15:41:23 2021
using gzip
isBSDSplit=0
Executing: mkdir -p /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994; ls -l /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994
total=24744 line-per-split=3094
split -d -l 3094 -a 7 /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.en /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/target.split -d -l 3094 -a 7 /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/corpus/train25k.clean.pl /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/source.split -d -l 3094 -a 7 /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/aligned.grow-diag-final-and /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/align.merging extract / extract.inv
gunzip -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000000.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000001.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000002.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000003.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000004.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000005.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000006.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000007.gz | LC_ALL=C sort -T /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994 2>> /dev/stderr | gzip -c > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.sorted.gz 2>> /dev/stderr
gunzip -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000000.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000001.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000002.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000003.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000004.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000005.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000006.inv.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000007.inv.gz | LC_ALL=C sort -T /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994 2>> /dev/stderr | gzip -c > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.inv.sorted.gz 2>> /dev/stderr
gunzip -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000000.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000001.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000002.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000003.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000004.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000005.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000006.o.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994/extract.0000007.o.gz | LC_ALL=C sort -T /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.12994 2>> /dev/stderr | gzip -c > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.o.sorted.gz 2>> /dev/stderr
Finished Wed Feb 17 15:42:43 2021
(6) score phrases @ Wed Feb 17 15:42:43 CET 2021
(6.1) creating table half /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.f2e @ Wed Feb 17 15:42:43 CET 2021
/home/kasia/mosesdecoder/scripts/generic/score-parallel.perl 8 "sort " /home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.sorted.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.f2e /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.f2e.gz 0
Executing: /home/kasia/mosesdecoder/scripts/generic/score-parallel.perl 8 "sort " /home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.sorted.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.f2e /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.f2e.gz 0
using gzip
Started Wed Feb 17 15:42:43 2021
/home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/extract.0.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.f2e /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/phrase-table.half.0000000.gz 2>> /dev/stderr
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.0.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.1.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.2.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.3.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.4.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.5.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.6.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/run.7.shmv /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112/phrase-table.half.0000000.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.f2e.gzrm -rf /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13112
Finished Wed Feb 17 15:46:08 2021
(6.3) creating table half /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.e2f @ Wed Feb 17 15:46:08 CET 2021
/home/kasia/mosesdecoder/scripts/generic/score-parallel.perl 8 "sort " /home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.inv.sorted.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.e2f /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.e2f.gz --Inverse 1
Executing: /home/kasia/mosesdecoder/scripts/generic/score-parallel.perl 8 "sort " /home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.inv.sorted.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.e2f /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.e2f.gz --Inverse 1
using gzip
Started Wed Feb 17 15:46:08 2021
/home/kasia/mosesdecoder/scripts/../bin/score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/extract.0.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.e2f /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/phrase-table.half.0000000.gz --Inverse 2>> /dev/stderr
/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.0.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.1.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.2.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.3.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.4.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.5.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.7.sh/home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/run.6.shgunzip -c /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381/phrase-table.half.*.gz 2>> /dev/stderr| LC_ALL=C sort -T /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381 | gzip -c > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.e2f.gz 2>> /dev/stderr rm -rf /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/tmp.13381
Finished Wed Feb 17 15:50:05 2021
(6.6) consolidating the two halves @ Wed Feb 17 15:50:05 CET 2021
Executing: /home/kasia/mosesdecoder/scripts/../bin/consolidate /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.f2e.gz /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.e2f.gz /dev/stdout | gzip -c > /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.gz
Consolidate v2.0 written by Philipp Koehn
consolidating direct and indirect rule tables
.................
Executing: rm -f /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/phrase-table.half.*
(7) learn reordering model @ Wed Feb 17 15:51:14 CET 2021
(7.1) [no factors] learn reordering model @ Wed Feb 17 15:51:14 CET 2021
(7.2) building tables @ Wed Feb 17 15:51:14 CET 2021
Executing: /home/kasia/mosesdecoder/scripts/../bin/lexical-reordering-score /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/extract.o.sorted.gz 0.5 /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/reordering-table. --model "wbe msd wbe-msd-bidirectional-fe"
Lexical Reordering Scorer
scores lexical reordering models of several types (hierarchical, phrase-based and word-based-extraction
(8) learn generation model @ Wed Feb 17 15:52:27 CET 2021
no generation model requested, skipping step
(9) create moses.ini @ Wed Feb 17 15:52:27 CET 2021
ng Scorer
scores lexical reordering models of several types (hierarchical, phrase-based and word-based-extraction
(8) learn generation model @ Wed Feb 17 15:35:45 CET 2021
no generation model requested, skipping step
(9) create moses.ini @ Wed Feb 17 15:35:45 CET 2021
PhraseExtract v1.5, written by Philipp Koehn et al.PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
PhraseExtract v1.5, written by Philipp Koehn et al.
phrase extraction from an aligned parallel corpus
..
Score v2.1 -- scoring methods for extracted rules
Loading lexical translation table from /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.f2e.
......................
Score v2.1 -- scoring methods for extracted rules
using inverse mode
Loading lexical translation table from /home/kasia/Pulpit/TAU/wmt-2020-pl-en/train/working/train/model/lex.e2f.
......................
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