diff options
Diffstat (limited to 'training/dtrain/examples')
| -rw-r--r-- | training/dtrain/examples/parallelized/cdec.ini | 2 | ||||
| -rw-r--r-- | training/dtrain/examples/parallelized/dtrain.ini | 2 | ||||
| -rw-r--r-- | training/dtrain/examples/parallelized/work/out.0.0 | 9 | ||||
| -rw-r--r-- | training/dtrain/examples/parallelized/work/out.0.1 | 9 | ||||
| -rw-r--r-- | training/dtrain/examples/parallelized/work/out.1.0 | 9 | ||||
| -rw-r--r-- | training/dtrain/examples/parallelized/work/out.1.1 | 9 | ||||
| -rw-r--r-- | training/dtrain/examples/standard/dtrain.ini | 24 | ||||
| -rw-r--r-- | training/dtrain/examples/standard/expected-output | 86 | 
8 files changed, 76 insertions, 74 deletions
| diff --git a/training/dtrain/examples/parallelized/cdec.ini b/training/dtrain/examples/parallelized/cdec.ini index e43ba1c4..5773029a 100644 --- a/training/dtrain/examples/parallelized/cdec.ini +++ b/training/dtrain/examples/parallelized/cdec.ini @@ -4,7 +4,7 @@ intersection_strategy=cube_pruning  cubepruning_pop_limit=200  scfg_max_span_limit=15  feature_function=WordPenalty -feature_function=KLanguageModel ../example/nc-wmt11.en.srilm.gz +feature_function=KLanguageModel ../standard//nc-wmt11.en.srilm.gz  #feature_function=ArityPenalty  #feature_function=CMR2008ReorderingFeatures  #feature_function=Dwarf diff --git a/training/dtrain/examples/parallelized/dtrain.ini b/training/dtrain/examples/parallelized/dtrain.ini index f19ef891..0b0932d6 100644 --- a/training/dtrain/examples/parallelized/dtrain.ini +++ b/training/dtrain/examples/parallelized/dtrain.ini @@ -11,6 +11,4 @@ pair_sampling=XYX  hi_lo=0.1  select_weights=last  print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough -# newer version of the grammar extractor use different feature names:  -#print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough  decoder_config=cdec.ini diff --git a/training/dtrain/examples/parallelized/work/out.0.0 b/training/dtrain/examples/parallelized/work/out.0.0 index 7a00ed0f..c559dd4d 100644 --- a/training/dtrain/examples/parallelized/work/out.0.0 +++ b/training/dtrain/examples/parallelized/work/out.0.0 @@ -1,9 +1,9 @@                  cdec cfg 'cdec.ini'  Loading the LM will be faster if you build a binary file. -Reading ../example/nc-wmt11.en.srilm.gz +Reading ../standard//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  **************************************************************************************************** -Seeding random number sequence to 3121929377 +Seeding random number sequence to 405292278  dtrain  Parameters: @@ -16,6 +16,7 @@ Parameters:             learning rate 0.0001                     gamma 0               loss margin 1 +       faster perceptron 0                     pairs 'XYX'                     hi lo 0.1            pair threshold 0 @@ -51,11 +52,11 @@ WEIGHTS      non0 feature count: 12             avg list sz: 100             avg f count: 11.32 -(time 0.37 min, 4.4 s/S) +(time 0.35 min, 4.2 s/S)  Writing weights file to 'work/weights.0.0' ...  done  ---  Best iteration: 1 [SCORE 'stupid_bleu'=0.17521]. -This took 0.36667 min. +This took 0.35 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.1 b/training/dtrain/examples/parallelized/work/out.0.1 index e2bd6649..8bc7ea9c 100644 --- a/training/dtrain/examples/parallelized/work/out.0.1 +++ b/training/dtrain/examples/parallelized/work/out.0.1 @@ -1,9 +1,9 @@                  cdec cfg 'cdec.ini'  Loading the LM will be faster if you build a binary file. -Reading ../example/nc-wmt11.en.srilm.gz +Reading ../standard//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  **************************************************************************************************** -Seeding random number sequence to 2767202922 +Seeding random number sequence to 43859692  dtrain  Parameters: @@ -16,6 +16,7 @@ Parameters:             learning rate 0.0001                     gamma 0               loss margin 1 +       faster perceptron 0                     pairs 'XYX'                     hi lo 0.1            pair threshold 0 @@ -52,11 +53,11 @@ WEIGHTS      non0 feature count: 12             avg list sz: 100             avg f count: 10.496 -(time 0.32 min, 3.8 s/S) +(time 0.35 min, 4.2 s/S)  Writing weights file to 'work/weights.0.1' ...  done  ---  Best iteration: 1 [SCORE 'stupid_bleu'=0.26638]. -This took 0.31667 min. +This took 0.35 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.0 b/training/dtrain/examples/parallelized/work/out.1.0 index 6e790e38..65d1e7dc 100644 --- a/training/dtrain/examples/parallelized/work/out.1.0 +++ b/training/dtrain/examples/parallelized/work/out.1.0 @@ -1,9 +1,9 @@                  cdec cfg 'cdec.ini'  Loading the LM will be faster if you build a binary file. -Reading ../example/nc-wmt11.en.srilm.gz +Reading ../standard//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  **************************************************************************************************** -Seeding random number sequence to 1432415010 +Seeding random number sequence to 4126799437  dtrain  Parameters: @@ -16,6 +16,7 @@ Parameters:             learning rate 0.0001                     gamma 0               loss margin 1 +       faster perceptron 0                     pairs 'XYX'                     hi lo 0.1            pair threshold 0 @@ -51,11 +52,11 @@ WEIGHTS      non0 feature count: 11             avg list sz: 100             avg f count: 11.814 -(time 0.45 min, 5.4 s/S) +(time 0.43 min, 5.2 s/S)  Writing weights file to 'work/weights.1.0' ...  done  ---  Best iteration: 1 [SCORE 'stupid_bleu'=0.10863]. -This took 0.45 min. +This took 0.43333 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.1 b/training/dtrain/examples/parallelized/work/out.1.1 index 0b984761..f479fbbc 100644 --- a/training/dtrain/examples/parallelized/work/out.1.1 +++ b/training/dtrain/examples/parallelized/work/out.1.1 @@ -1,9 +1,9 @@                  cdec cfg 'cdec.ini'  Loading the LM will be faster if you build a binary file. -Reading ../example/nc-wmt11.en.srilm.gz +Reading ../standard//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  **************************************************************************************************** -Seeding random number sequence to 1771918374 +Seeding random number sequence to 2112412848  dtrain  Parameters: @@ -16,6 +16,7 @@ Parameters:             learning rate 0.0001                     gamma 0               loss margin 1 +       faster perceptron 0                     pairs 'XYX'                     hi lo 0.1            pair threshold 0 @@ -52,11 +53,11 @@ WEIGHTS      non0 feature count: 12             avg list sz: 100             avg f count: 11.224 -(time 0.42 min, 5 s/S) +(time 0.45 min, 5.4 s/S)  Writing weights file to 'work/weights.1.1' ...  done  ---  Best iteration: 1 [SCORE 'stupid_bleu'=0.13169]. -This took 0.41667 min. +This took 0.45 min. diff --git a/training/dtrain/examples/standard/dtrain.ini b/training/dtrain/examples/standard/dtrain.ini index e1072d30..23e94285 100644 --- a/training/dtrain/examples/standard/dtrain.ini +++ b/training/dtrain/examples/standard/dtrain.ini @@ -10,15 +10,15 @@ print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 Phr  stop_after=10 # stop epoch after 10 inputs  # interesting stuff -epochs=2                # run over input 2 times -k=100                   # use 100best lists -N=4                     # optimize (approx) BLEU4 -scorer=stupid_bleu      # use 'stupid' BLEU+1 -learning_rate=1.0       # learning rate, don't care if gamma=0 (perceptron) -gamma=0                 # use SVM reg -sample_from=kbest       # use kbest lists (as opposed to forest) -filter=uniq             # only unique entries in kbest (surface form) -pair_sampling=XYX       # -hi_lo=0.1               # 10 vs 80 vs 10 and 80 vs 10 here -pair_threshold=0        # minimum distance in BLEU (here: > 0) -loss_margin=0           # update if correctly ranked, but within this margin +epochs=2                 # run over input 2 times +k=100                    # use 100best lists +N=4                      # optimize (approx) BLEU4 +scorer=fixed_stupid_bleu # use 'stupid' BLEU+1 +learning_rate=1.0        # learning rate, don't care if gamma=0 (perceptron) +gamma=0                  # use SVM reg +sample_from=kbest        # use kbest lists (as opposed to forest) +filter=uniq              # only unique entries in kbest (surface form) +pair_sampling=XYX        # +hi_lo=0.1                # 10 vs 80 vs 10 and 80 vs 10 here +pair_threshold=0         # minimum distance in BLEU (here: > 0) +loss_margin=0            # update if correctly ranked, but within this margin diff --git a/training/dtrain/examples/standard/expected-output b/training/dtrain/examples/standard/expected-output index 7cd09dbf..21f91244 100644 --- a/training/dtrain/examples/standard/expected-output +++ b/training/dtrain/examples/standard/expected-output @@ -4,14 +4,14 @@ 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 +Seeding random number sequence to 970626287  dtrain  Parameters:                         k 100                         N 4                         T 2 -                  scorer 'stupid_bleu' +                  scorer 'fixed_stupid_bleu'               sample from 'kbest'                    filter 'uniq'             learning rate 1 @@ -34,58 +34,58 @@ 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 +              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: 0.27697 (+0.27697) - 1best avg model score: -47918 (-47918) -           avg # pairs: 581.9 (meaningless) -        avg # rank err: 581.9 +       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: 703 -           avg list sz: 90.9 -           avg f count: 100.09 -(time 0.25 min, 1.5 s/S) +    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 = -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 +              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: 0.37119 (+0.094226) - 1best avg model score: -1.3174e+05 (-83822) -           avg # pairs: 584.1 (meaningless) -        avg # rank err: 584.1 +       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: 1115 +    non0 feature count: 1499             avg list sz: 91.3 -           avg f count: 90.755 -(time 0.3 min, 1.8 s/S) +           avg f count: 114.34 +(time 0.32 min, 1.9 s/S)  Writing weights file to '-' ...  done  --- -Best iteration: 2 [SCORE 'stupid_bleu'=0.37119]. -This took 0.55 min. +Best iteration: 2 [SCORE 'fixed_stupid_bleu'=0.30764]. +This took 0.65 min. | 
