summaryrefslogtreecommitdiff
path: root/training/dtrain/examples/standard/dtrain.ini
diff options
context:
space:
mode:
Diffstat (limited to 'training/dtrain/examples/standard/dtrain.ini')
-rw-r--r--training/dtrain/examples/standard/dtrain.ini6
1 files changed, 3 insertions, 3 deletions
diff --git a/training/dtrain/examples/standard/dtrain.ini b/training/dtrain/examples/standard/dtrain.ini
index c0912a62..e6d6382e 100644
--- a/training/dtrain/examples/standard/dtrain.ini
+++ b/training/dtrain/examples/standard/dtrain.ini
@@ -1,6 +1,6 @@
input=./nc-wmt11.de.gz
refs=./nc-wmt11.en.gz
-output=asdf # a weights file (add .gz for gzip compression) or STDOUT '-'
+output=- # a weights file (add .gz for gzip compression) or STDOUT '-'
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
@@ -10,11 +10,11 @@ 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
+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=1.0 # learning rate, don't care if gamma=0 (perceptron)
+learning_rate=1.0 # 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)