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authorPatrick Simianer <p@simianer.de>2013-11-12 20:07:47 +0100
committerPatrick Simianer <p@simianer.de>2013-11-12 20:07:47 +0100
commit68b0969b1f41eacb4b336a66625894995b2f1e74 (patch)
treec74cb14d7a01ed420572ba6d4d4bf85018c385b4 /training/dtrain/examples
parenta8ea0a66b798326061bc9f0da153b96b730130f1 (diff)
impl repeat param
Diffstat (limited to 'training/dtrain/examples')
-rw-r--r--training/dtrain/examples/standard/dtrain.ini6
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