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| author | Patrick Simianer <p@simianer.de> | 2013-03-15 16:06:05 +0100 |
|---|---|---|
| committer | Patrick Simianer <p@simianer.de> | 2013-03-15 16:06:05 +0100 |
| commit | a416615b81380d664246f11a8047098c59185838 (patch) | |
| tree | 9f0d094247d7af80e90f15cabb3620b8e71140a5 /training/dtrain/examples/standard/dtrain.ini | |
| parent | ae6a76dfc04698029616232b39d9f47347ec9d4b (diff) | |
fix
Diffstat (limited to 'training/dtrain/examples/standard/dtrain.ini')
| -rw-r--r-- | training/dtrain/examples/standard/dtrain.ini | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/training/dtrain/examples/standard/dtrain.ini b/training/dtrain/examples/standard/dtrain.ini index a05e9c29..e1072d30 100644 --- a/training/dtrain/examples/standard/dtrain.ini +++ b/training/dtrain/examples/standard/dtrain.ini @@ -1,12 +1,12 @@ input=./nc-wmt11.de.gz refs=./nc-wmt11.en.gz output=- # a weights file (add .gz for gzip compression) or STDOUT '-' -select_weights=avg # output average (over epochs) weight vector +select_weights=VOID # output average (over epochs) weight vector decoder_config=./cdec.ini # config for cdec # weights for these features will be printed on each iteration -print_weights= EgivenFCoherent SampleCountF CountEF MaxLexFgivenE MaxLexEgivenF IsSingletonF IsSingletonFE Glue WordPenalty PassThrough LanguageModel LanguageModel_OOV +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 +#print_weights= EgivenFCoherent SampleCountF CountEF MaxLexFgivenE MaxLexEgivenF IsSingletonF IsSingletonFE Glue WordPenalty PassThrough LanguageModel LanguageModel_OOV stop_after=10 # stop epoch after 10 inputs # interesting stuff @@ -21,4 +21,4 @@ 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 +loss_margin=0 # update if correctly ranked, but within this margin |