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
T=1 I=1 D=1
Seeding random number sequence to 2327685089

dtrain
Parameters:
                       k 100
                       N 4
                       T 3
                   batch 0
                  scorer 'fixed_stupid_bleu'
             sample from 'kbest'
                  filter 'uniq'
           learning rate 0.1
                   gamma 0
             loss margin 0
       faster perceptron 1
                   pairs 'XYX'
                   hi lo 0.1
          pair threshold 0
          select weights 'avg'
                  l1 reg 0 'none'
                    pclr no
               max pairs 4294967295
                  repeat 1
                cdec cfg './cdec.ini'
                   input './nc-wmt11.gz'
                  output '-'
              stop_after 10
(a dot represents 10 inputs)
Iteration #1 of 3.
 . 10
Stopping after 10 input sentences.
WEIGHTS
              Glue = +6.9
       WordPenalty = -46.426
     LanguageModel = +535.12
 LanguageModel_OOV = -123.5
     PhraseModel_0 = -160.73
     PhraseModel_1 = -350.13
     PhraseModel_2 = -187.81
     PhraseModel_3 = +172.04
     PhraseModel_4 = +0.90108
     PhraseModel_5 = +21.6
     PhraseModel_6 = +67.2
       PassThrough = -149.7
        ---
       1best avg score: 0.23327 (+0.23327)
 1best avg model score: -9084.9 (-9084.9)
           avg # pairs: 780.7
        avg # rank err: 0 (meaningless)
     avg # margin viol: 0
       k-best loss imp: 100%
    non0 feature count: 1389
           avg list sz: 91.3
           avg f count: 146.2
(time 0.37 min, 2.2 s/S)

Iteration #2 of 3.
 . 10
WEIGHTS
              Glue = -43
       WordPenalty = -22.019
     LanguageModel = +591.53
 LanguageModel_OOV = -252.1
     PhraseModel_0 = -120.21
     PhraseModel_1 = -43.589
     PhraseModel_2 = +73.53
     PhraseModel_3 = +113.7
     PhraseModel_4 = -223.81
     PhraseModel_5 = +64
     PhraseModel_6 = +54.8
       PassThrough = -331.1
        ---
       1best avg score: 0.29568 (+0.062413)
 1best avg model score: -15879 (-6794.1)
           avg # pairs: 566.1
        avg # rank err: 0 (meaningless)
     avg # margin viol: 0
       k-best loss imp: 100%
    non0 feature count: 1931
           avg list sz: 91.3
           avg f count: 139.89
(time 0.33 min, 2 s/S)

Iteration #3 of 3.
 . 10
WEIGHTS
              Glue = -44.3
       WordPenalty = -131.85
     LanguageModel = +230.91
 LanguageModel_OOV = -285.4
     PhraseModel_0 = -194.27
     PhraseModel_1 = -294.83
     PhraseModel_2 = -92.043
     PhraseModel_3 = -140.24
     PhraseModel_4 = +85.613
     PhraseModel_5 = +238.1
     PhraseModel_6 = +158.7
       PassThrough = -359.6
        ---
       1best avg score: 0.37375 (+0.078067)
 1best avg model score: -14519 (+1359.7)
           avg # pairs: 545.4
        avg # rank err: 0 (meaningless)
     avg # margin viol: 0
       k-best loss imp: 100%
    non0 feature count: 2218
           avg list sz: 91.3
           avg f count: 137.77
(time 0.35 min, 2.1 s/S)

Writing weights file to '-' ...
done

---
Best iteration: 3 [SCORE 'fixed_stupid_bleu'=0.37375].
This took 1.05 min.