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-rw-r--r--training/dtrain/examples/standard/dtrain.ini24
-rw-r--r--training/dtrain/examples/standard/expected-output84
2 files changed, 54 insertions, 54 deletions
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..9a25062b 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 1677737427
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 = -1155
+ WordPenalty = -329.63
+ LanguageModel = +3903
+ LanguageModel_OOV = -1630
+ PhraseModel_0 = +2746.9
+ PhraseModel_1 = +1200.3
+ PhraseModel_2 = -1004.1
+ PhraseModel_3 = +2223.1
+ PhraseModel_4 = +551.58
+ PhraseModel_5 = +217
+ PhraseModel_6 = +1816
+ PassThrough = -1603
---
- 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: 0.19344 (+0.19344)
+ 1best avg model score: 81387 (+81387)
+ avg # pairs: 616.3 (meaningless)
+ avg # rank err: 616.3
avg # margin viol: 0
- non0 feature count: 703
+ non0 feature count: 673
avg list sz: 90.9
- avg f count: 100.09
-(time 0.25 min, 1.5 s/S)
+ avg f count: 104.26
+(time 0.38 min, 2.3 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 = -994
+ WordPenalty = -778.69
+ LanguageModel = +2348.9
+ LanguageModel_OOV = -1967
+ PhraseModel_0 = -412.72
+ PhraseModel_1 = +1428.9
+ PhraseModel_2 = +1967.4
+ PhraseModel_3 = -944.99
+ PhraseModel_4 = -239.7
+ PhraseModel_5 = +708
+ PhraseModel_6 = +645
+ PassThrough = -1866
---
- 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: 0.22395 (+0.03051)
+ 1best avg model score: -31388 (-1.1278e+05)
+ avg # pairs: 702.3 (meaningless)
+ avg # rank err: 702.3
avg # margin viol: 0
- non0 feature count: 1115
+ non0 feature count: 955
avg list sz: 91.3
- avg f count: 90.755
-(time 0.3 min, 1.8 s/S)
+ avg f count: 103.45
+(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'=0.22395].
+This took 0.7 min.