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Diffstat (limited to 'dtrain/test/example/expected-output')
| -rw-r--r-- | dtrain/test/example/expected-output | 125 |
1 files changed, 0 insertions, 125 deletions
diff --git a/dtrain/test/example/expected-output b/dtrain/test/example/expected-output deleted file mode 100644 index 25d2c069..00000000 --- a/dtrain/test/example/expected-output +++ /dev/null @@ -1,125 +0,0 @@ - cdec cfg 'test/example/cdec.ini' -feature: WordPenalty (no config parameters) -State is 0 bytes for feature WordPenalty -feature: KLanguageModel (with config parameters 'test/example/nc-wmt11.en.srilm.gz') -Loading the LM will be faster if you build a binary file. -Reading test/example/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 -**************************************************************************************************** -Loaded 5-gram KLM from test/example/nc-wmt11.en.srilm.gz (MapSize=49581) -State is 98 bytes for feature KLanguageModel test/example/nc-wmt11.en.srilm.gz -feature: RuleIdentityFeatures (no config parameters) -State is 0 bytes for feature RuleIdentityFeatures -feature: RuleNgramFeatures (no config parameters) -State is 0 bytes for feature RuleNgramFeatures -feature: RuleShape (no config parameters) - Example feature: Shape_S00000_T00000 -State is 0 bytes for feature RuleShape -Seeding random number sequence to 1072059181 - -dtrain -Parameters: - k 100 - N 4 - T 3 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' - learning rate 0.0001 - gamma 0 - loss margin 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'VOID' - l1 reg 0 'none' - cdec cfg 'test/example/cdec.ini' - input 'test/example/nc-wmt11.1k.gz' - output '-' - stop_after 10 -(a dot represents 10 inputs) -Iteration #1 of 3. - . 10 -Stopping after 10 input sentences. -WEIGHTS - Glue = -0.0293 - WordPenalty = +0.049075 - LanguageModel = +0.24345 - LanguageModel_OOV = -0.2029 - PhraseModel_0 = +0.0084102 - PhraseModel_1 = +0.021729 - PhraseModel_2 = +0.014922 - PhraseModel_3 = +0.104 - PhraseModel_4 = -0.14308 - PhraseModel_5 = +0.0247 - PhraseModel_6 = -0.012 - PassThrough = -0.2161 - --- - 1best avg score: 0.16872 (+0.16872) - 1best avg model score: -1.8276 (-1.8276) - avg # pairs: 1121.1 - avg # rank err: 555.6 - avg # margin viol: 0 - non0 feature count: 277 - avg list sz: 77.2 - avg f count: 90.96 -(time 0.1 min, 0.6 s/S) - -Iteration #2 of 3. - . 10 -WEIGHTS - Glue = -0.3526 - WordPenalty = +0.067576 - LanguageModel = +1.155 - LanguageModel_OOV = -0.2728 - PhraseModel_0 = -0.025529 - PhraseModel_1 = +0.095869 - PhraseModel_2 = +0.094567 - PhraseModel_3 = +0.12482 - PhraseModel_4 = -0.36533 - PhraseModel_5 = +0.1068 - PhraseModel_6 = -0.1517 - PassThrough = -0.286 - --- - 1best avg score: 0.18394 (+0.015221) - 1best avg model score: 3.205 (+5.0326) - avg # pairs: 1168.3 - avg # rank err: 594.8 - avg # margin viol: 0 - non0 feature count: 543 - avg list sz: 77.5 - avg f count: 85.916 -(time 0.083 min, 0.5 s/S) - -Iteration #3 of 3. - . 10 -WEIGHTS - Glue = -0.392 - WordPenalty = +0.071963 - LanguageModel = +0.81266 - LanguageModel_OOV = -0.4177 - PhraseModel_0 = -0.2649 - PhraseModel_1 = -0.17931 - PhraseModel_2 = +0.038261 - PhraseModel_3 = +0.20261 - PhraseModel_4 = -0.42621 - PhraseModel_5 = +0.3198 - PhraseModel_6 = -0.1437 - PassThrough = -0.4309 - --- - 1best avg score: 0.2962 (+0.11225) - 1best avg model score: -36.274 (-39.479) - avg # pairs: 1109.6 - avg # rank err: 515.9 - avg # margin viol: 0 - non0 feature count: 741 - avg list sz: 77 - avg f count: 88.982 -(time 0.083 min, 0.5 s/S) - -Writing weights file to '-' ... -done - ---- -Best iteration: 3 [SCORE 'stupid_bleu'=0.2962]. -This took 0.26667 min. |