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author | Patrick Simianer <p@simianer.de> | 2013-11-12 20:07:47 +0100 |
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committer | Patrick Simianer <p@simianer.de> | 2013-11-12 20:07:47 +0100 |
commit | 68b0969b1f41eacb4b336a66625894995b2f1e74 (patch) | |
tree | c74cb14d7a01ed420572ba6d4d4bf85018c385b4 /training/dtrain/examples | |
parent | a8ea0a66b798326061bc9f0da153b96b730130f1 (diff) |
impl repeat param
Diffstat (limited to 'training/dtrain/examples')
-rw-r--r-- | training/dtrain/examples/standard/dtrain.ini | 6 |
1 files changed, 4 insertions, 2 deletions
diff --git a/training/dtrain/examples/standard/dtrain.ini b/training/dtrain/examples/standard/dtrain.ini index 4d096dfb..ef022469 100644 --- a/training/dtrain/examples/standard/dtrain.ini +++ b/training/dtrain/examples/standard/dtrain.ini @@ -11,11 +11,11 @@ print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 Phr stop_after=10 # stop epoch after 10 inputs # interesting stuff -epochs=100 # run over input 3 times +epochs=3 # run over input 3 times k=100 # use 100best lists N=4 # optimize (approx) BLEU4 scorer=fixed_stupid_bleu # use 'stupid' BLEU+1 -learning_rate=0.0001 # learning rate, don't care if gamma=0 (perceptron) and loss_margin=0 (not margin perceptron) +learning_rate=0.0001 # learning rate, don't care if gamma=0 (perceptron) and loss_margin=0 (not margin 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) @@ -23,3 +23,5 @@ 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 +repeat=1 # repeat training on a kbest list 1 times +#batch=true # batch tuning, update after accumulating over all sentences and all kbest lists |