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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 1677737427
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 = -1155
WordPenalty = -329.63
LanguageModel = +3903
LanguageModel_OOV = -1630
PhraseModel_0 = +2746.9
PhraseModel_1 = +1200.3
PhraseModel_2 = -1004.1
PhraseModel_3 = +2223.1
PhraseModel_4 = +551.58
PhraseModel_5 = +217
PhraseModel_6 = +1816
PassThrough = -1603
---
1best avg score: 0.19344 (+0.19344)
1best avg model score: 81387 (+81387)
avg # pairs: 616.3 (meaningless)
avg # rank err: 616.3
avg # margin viol: 0
non0 feature count: 673
avg list sz: 90.9
avg f count: 104.26
(time 0.38 min, 2.3 s/S)
Iteration #2 of 2.
. 10
WEIGHTS
Glue = -994
WordPenalty = -778.69
LanguageModel = +2348.9
LanguageModel_OOV = -1967
PhraseModel_0 = -412.72
PhraseModel_1 = +1428.9
PhraseModel_2 = +1967.4
PhraseModel_3 = -944.99
PhraseModel_4 = -239.7
PhraseModel_5 = +708
PhraseModel_6 = +645
PassThrough = -1866
---
1best avg score: 0.22395 (+0.03051)
1best avg model score: -31388 (-1.1278e+05)
avg # pairs: 702.3 (meaningless)
avg # rank err: 702.3
avg # margin viol: 0
non0 feature count: 955
avg list sz: 91.3
avg f count: 103.45
(time 0.32 min, 1.9 s/S)
Writing weights file to '-' ...
done
---
Best iteration: 2 [SCORE 'fixed_stupid_bleu'=0.22395].
This took 0.7 min.
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