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cdec cfg './cdec.ini'
Loading the LM will be faster if you build a binary file.
Reading ./nc-wmt11.en.srilm.gz
----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
****************************************************************************************************
Example feature: Shape_S00000_T00000
Seeding random number sequence to 2679584485
dtrain
Parameters:
k 100
N 4
T 2
scorer 'stupid_bleu'
sample from 'kbest'
filter 'uniq'
learning rate 1
gamma 0
loss margin 0
faster perceptron 1
pairs 'XYX'
hi lo 0.1
pair threshold 0
select weights 'VOID'
l1 reg 0 'none'
max pairs 4294967295
cdec cfg './cdec.ini'
input './nc-wmt11.de.gz'
refs './nc-wmt11.en.gz'
output '-'
stop_after 10
(a dot represents 10 inputs)
Iteration #1 of 2.
. 10
Stopping after 10 input sentences.
WEIGHTS
Glue = -576
WordPenalty = +417.79
LanguageModel = +5117.5
LanguageModel_OOV = -1307
PhraseModel_0 = -1612
PhraseModel_1 = -2159.6
PhraseModel_2 = -677.36
PhraseModel_3 = +2663.8
PhraseModel_4 = -1025.9
PhraseModel_5 = -8
PhraseModel_6 = +70
PassThrough = -1455
---
1best avg score: 0.27697 (+0.27697)
1best avg model score: -47918 (-47918)
avg # pairs: 581.9 (meaningless)
avg # rank err: 581.9
avg # margin viol: 0
non0 feature count: 703
avg list sz: 90.9
avg f count: 100.09
(time 0.25 min, 1.5 s/S)
Iteration #2 of 2.
. 10
WEIGHTS
Glue = -622
WordPenalty = +898.56
LanguageModel = +8066.2
LanguageModel_OOV = -2590
PhraseModel_0 = -4335.8
PhraseModel_1 = -5864.4
PhraseModel_2 = -1729.8
PhraseModel_3 = +2831.9
PhraseModel_4 = -5384.8
PhraseModel_5 = +1449
PhraseModel_6 = +480
PassThrough = -2578
---
1best avg score: 0.37119 (+0.094226)
1best avg model score: -1.3174e+05 (-83822)
avg # pairs: 584.1 (meaningless)
avg # rank err: 584.1
avg # margin viol: 0
non0 feature count: 1115
avg list sz: 91.3
avg f count: 90.755
(time 0.3 min, 1.8 s/S)
Writing weights file to '-' ...
done
---
Best iteration: 2 [SCORE 'stupid_bleu'=0.37119].
This took 0.55 min.
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