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-rw-r--r--training/dtrain/examples/standard/expected-output123
-rw-r--r--training/dtrain/examples/standard/expected-output.gzbin0 -> 625304 bytes
-rw-r--r--training/dtrain/examples/standard/nc-wmt11.de.gzbin58324 -> 0 bytes
-rw-r--r--training/dtrain/examples/standard/nc-wmt11.en.gzbin49600 -> 0 bytes
4 files changed, 0 insertions, 123 deletions
diff --git a/training/dtrain/examples/standard/expected-output b/training/dtrain/examples/standard/expected-output
deleted file mode 100644
index 2460cfbb..00000000
--- a/training/dtrain/examples/standard/expected-output
+++ /dev/null
@@ -1,123 +0,0 @@
- cdec cfg './cdec.ini'
-Loading the LM will be faster if you build a binary file.
-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
-T=1 I=1 D=1
-Seeding random number sequence to 2327685089
-
-dtrain
-Parameters:
- k 100
- N 4
- T 3
- batch 0
- scorer 'fixed_stupid_bleu'
- sample from 'kbest'
- filter 'uniq'
- learning rate 0.1
- gamma 0
- loss margin 0
- faster perceptron 1
- pairs 'XYX'
- hi lo 0.1
- pair threshold 0
- select weights 'avg'
- l1 reg 0 'none'
- pclr no
- max pairs 4294967295
- repeat 1
- cdec cfg './cdec.ini'
- input './nc-wmt11.gz'
- output '-'
- stop_after 10
-(a dot represents 10 inputs)
-Iteration #1 of 3.
- . 10
-Stopping after 10 input sentences.
-WEIGHTS
- Glue = +6.9
- WordPenalty = -46.426
- LanguageModel = +535.12
- LanguageModel_OOV = -123.5
- PhraseModel_0 = -160.73
- PhraseModel_1 = -350.13
- PhraseModel_2 = -187.81
- PhraseModel_3 = +172.04
- PhraseModel_4 = +0.90108
- PhraseModel_5 = +21.6
- PhraseModel_6 = +67.2
- PassThrough = -149.7
- ---
- 1best avg score: 0.23327 (+0.23327)
- 1best avg model score: -9084.9 (-9084.9)
- avg # pairs: 780.7
- avg # rank err: 0 (meaningless)
- avg # margin viol: 0
- k-best loss imp: 100%
- non0 feature count: 1389
- avg list sz: 91.3
- avg f count: 146.2
-(time 0.37 min, 2.2 s/S)
-
-Iteration #2 of 3.
- . 10
-WEIGHTS
- Glue = -43
- WordPenalty = -22.019
- LanguageModel = +591.53
- LanguageModel_OOV = -252.1
- PhraseModel_0 = -120.21
- PhraseModel_1 = -43.589
- PhraseModel_2 = +73.53
- PhraseModel_3 = +113.7
- PhraseModel_4 = -223.81
- PhraseModel_5 = +64
- PhraseModel_6 = +54.8
- PassThrough = -331.1
- ---
- 1best avg score: 0.29568 (+0.062413)
- 1best avg model score: -15879 (-6794.1)
- avg # pairs: 566.1
- avg # rank err: 0 (meaningless)
- avg # margin viol: 0
- k-best loss imp: 100%
- non0 feature count: 1931
- avg list sz: 91.3
- avg f count: 139.89
-(time 0.33 min, 2 s/S)
-
-Iteration #3 of 3.
- . 10
-WEIGHTS
- Glue = -44.3
- WordPenalty = -131.85
- LanguageModel = +230.91
- LanguageModel_OOV = -285.4
- PhraseModel_0 = -194.27
- PhraseModel_1 = -294.83
- PhraseModel_2 = -92.043
- PhraseModel_3 = -140.24
- PhraseModel_4 = +85.613
- PhraseModel_5 = +238.1
- PhraseModel_6 = +158.7
- PassThrough = -359.6
- ---
- 1best avg score: 0.37375 (+0.078067)
- 1best avg model score: -14519 (+1359.7)
- avg # pairs: 545.4
- avg # rank err: 0 (meaningless)
- avg # margin viol: 0
- k-best loss imp: 100%
- non0 feature count: 2218
- avg list sz: 91.3
- avg f count: 137.77
-(time 0.35 min, 2.1 s/S)
-
-Writing weights file to '-' ...
-done
-
----
-Best iteration: 3 [SCORE 'fixed_stupid_bleu'=0.37375].
-This took 1.05 min.
diff --git a/training/dtrain/examples/standard/expected-output.gz b/training/dtrain/examples/standard/expected-output.gz
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diff --git a/training/dtrain/examples/standard/nc-wmt11.de.gz b/training/dtrain/examples/standard/nc-wmt11.de.gz
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diff --git a/training/dtrain/examples/standard/nc-wmt11.en.gz b/training/dtrain/examples/standard/nc-wmt11.en.gz
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