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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 970626287
dtrain
Parameters:
k 100
N 4
T 2
scorer 'fixed_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 = -614
WordPenalty = +1256.8
LanguageModel = +5610.5
LanguageModel_OOV = -1449
PhraseModel_0 = -2107
PhraseModel_1 = -4666.1
PhraseModel_2 = -2713.5
PhraseModel_3 = +4204.3
PhraseModel_4 = -1435.8
PhraseModel_5 = +916
PhraseModel_6 = +190
PassThrough = -2527
---
1best avg score: 0.17874 (+0.17874)
1best avg model score: 88399 (+88399)
avg # pairs: 798.2 (meaningless)
avg # rank err: 798.2
avg # margin viol: 0
non0 feature count: 887
avg list sz: 91.3
avg f count: 126.85
(time 0.33 min, 2 s/S)
Iteration #2 of 2.
. 10
WEIGHTS
Glue = -1025
WordPenalty = +1751.5
LanguageModel = +10059
LanguageModel_OOV = -4490
PhraseModel_0 = -2640.7
PhraseModel_1 = -3757.4
PhraseModel_2 = -1133.1
PhraseModel_3 = +1837.3
PhraseModel_4 = -3534.3
PhraseModel_5 = +2308
PhraseModel_6 = +1677
PassThrough = -6222
---
1best avg score: 0.30764 (+0.12891)
1best avg model score: -2.5042e+05 (-3.3882e+05)
avg # pairs: 725.9 (meaningless)
avg # rank err: 725.9
avg # margin viol: 0
non0 feature count: 1499
avg list sz: 91.3
avg f count: 114.34
(time 0.32 min, 1.9 s/S)
Writing weights file to '-' ...
done
---
Best iteration: 2 [SCORE 'fixed_stupid_bleu'=0.30764].
This took 0.65 min.
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