From b6754386f1109b960b05cdf2eabbc97bdd38e8df Mon Sep 17 00:00:00 2001
From: Patrick Simianer <p@simianer.de>
Date: Mon, 29 Apr 2013 15:24:39 +0200
Subject: fix, cleaned up headers

---
 training/dtrain/examples/standard/dtrain.ini      | 24 +++----
 training/dtrain/examples/standard/expected-output | 84 +++++++++++------------
 2 files changed, 54 insertions(+), 54 deletions(-)

(limited to 'training/dtrain/examples')

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.
-- 
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