From 4223261682388944fe1b1cf31b9d51d88f9ad53b Mon Sep 17 00:00:00 2001 From: Patrick Simianer Date: Thu, 26 Feb 2015 13:26:37 +0100 Subject: refactoring --- training/dtrain/examples/parallelized/README | 2 +- training/dtrain/examples/parallelized/dtrain.ini | 13 +--- training/dtrain/examples/parallelized/work/out.0.0 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.0.1 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.0.2 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.1.0 | 72 +++++++------------- training/dtrain/examples/parallelized/work/out.1.1 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.1.2 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.2.0 | 72 +++++++------------- training/dtrain/examples/parallelized/work/out.2.1 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.2.2 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.3.0 | 74 +++++++------------- training/dtrain/examples/parallelized/work/out.3.1 | 72 +++++++------------- training/dtrain/examples/parallelized/work/out.3.2 | 72 +++++++------------- .../dtrain/examples/parallelized/work/shard.0.0.in | 4 +- .../dtrain/examples/parallelized/work/shard.1.0.in | 4 +- .../dtrain/examples/parallelized/work/shard.2.0.in | 4 +- .../dtrain/examples/parallelized/work/shard.3.0.in | 2 +- .../dtrain/examples/parallelized/work/weights.0 | 24 +++---- .../dtrain/examples/parallelized/work/weights.0.0 | 23 +++---- .../dtrain/examples/parallelized/work/weights.0.1 | 24 +++---- .../dtrain/examples/parallelized/work/weights.0.2 | 24 +++---- .../dtrain/examples/parallelized/work/weights.1 | 24 +++---- .../dtrain/examples/parallelized/work/weights.1.0 | 23 ++++--- .../dtrain/examples/parallelized/work/weights.1.1 | 24 +++---- .../dtrain/examples/parallelized/work/weights.1.2 | 24 +++---- .../dtrain/examples/parallelized/work/weights.2 | 24 +++---- .../dtrain/examples/parallelized/work/weights.2.0 | 22 +++--- .../dtrain/examples/parallelized/work/weights.2.1 | 24 +++---- .../dtrain/examples/parallelized/work/weights.2.2 | 24 +++---- .../dtrain/examples/parallelized/work/weights.3.0 | 24 +++---- .../dtrain/examples/parallelized/work/weights.3.1 | 24 +++---- .../dtrain/examples/parallelized/work/weights.3.2 | 24 +++---- training/dtrain/examples/standard/dtrain.ini | 29 ++------ training/dtrain/examples/toy/dtrain.ini | 10 +-- training/dtrain/examples/toy/expected-output | 79 +++++++--------------- training/dtrain/examples/toy/weights | 4 ++ 37 files changed, 534 insertions(+), 853 deletions(-) create mode 100644 training/dtrain/examples/toy/weights (limited to 'training/dtrain/examples') diff --git a/training/dtrain/examples/parallelized/README b/training/dtrain/examples/parallelized/README index 2fb3b54e..c4addd81 100644 --- a/training/dtrain/examples/parallelized/README +++ b/training/dtrain/examples/parallelized/README @@ -1,5 +1,5 @@ run for example - ../../parallelize.rb -c dtrain.ini -s 4 -e 3 -z -d ../../dtrain -p 2 -i in + ../../parallelize.rb -c dtrain.ini -s 4 -e 3 -d ../../dtrain -p 2 -i in final weights will be in the file work/weights.2 diff --git a/training/dtrain/examples/parallelized/dtrain.ini b/training/dtrain/examples/parallelized/dtrain.ini index 0b0932d6..9fc205a3 100644 --- a/training/dtrain/examples/parallelized/dtrain.ini +++ b/training/dtrain/examples/parallelized/dtrain.ini @@ -1,14 +1,7 @@ k=100 N=4 learning_rate=0.0001 -gamma=0 -loss_margin=1.0 -epochs=1 -scorer=stupid_bleu -sample_from=kbest -filter=uniq -pair_sampling=XYX -hi_lo=0.1 -select_weights=last -print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough +error_margin=1.0 +iterations=1 decoder_config=cdec.ini +print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough diff --git a/training/dtrain/examples/parallelized/work/out.0.0 b/training/dtrain/examples/parallelized/work/out.0.0 index 9154c906..77749404 100644 --- a/training/dtrain/examples/parallelized/work/out.0.0 +++ b/training/dtrain/examples/parallelized/work/out.0.0 @@ -1,65 +1,43 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 4087834873 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.0.0.in' output 'work/weights.0.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = +0.257 - WordPenalty = +0.026926 - LanguageModel = +0.67342 - LanguageModel_OOV = -0.046 - PhraseModel_0 = +0.25329 - PhraseModel_1 = +0.20036 - PhraseModel_2 = +0.00060731 - PhraseModel_3 = +0.65578 - PhraseModel_4 = +0.47916 - PhraseModel_5 = +0.004 - PhraseModel_6 = +0.1829 - PassThrough = -0.082 + Glue = +0.3404 + WordPenalty = -0.017632 + LanguageModel = +0.72958 + LanguageModel_OOV = -0.235 + PhraseModel_0 = -0.43721 + PhraseModel_1 = +1.01 + PhraseModel_2 = +1.3525 + PhraseModel_3 = -0.25541 + PhraseModel_4 = -0.78115 + PhraseModel_5 = +0 + PhraseModel_6 = -0.3681 + PassThrough = -0.3304 --- - 1best avg score: 0.04518 (+0.04518) - 1best avg model score: 32.803 (+32.803) - avg # pairs: 1266.3 - avg # rank err: 857 - avg # margin viol: 386.67 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.19474 (+0.19474) + 1best avg model score: 0.52232 + avg # pairs: 2513 + non-0 feature count: 11 avg list sz: 100 - avg f count: 10.853 -(time 0.47 min, 9.3 s/S) - -Writing weights file to 'work/weights.0.0' ... -done + avg f count: 11.42 +(time 0.32 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.04518]. -This took 0.46667 min. +Best iteration: 1 [GOLD = 0.19474]. +This took 0.31667 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.1 b/training/dtrain/examples/parallelized/work/out.0.1 index 0dbc7bd3..d0dee623 100644 --- a/training/dtrain/examples/parallelized/work/out.0.1 +++ b/training/dtrain/examples/parallelized/work/out.0.1 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 2283043509 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.0.0.in' output 'work/weights.0.1' weights in 'work/weights.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.17905 - WordPenalty = +0.062126 - LanguageModel = +0.66825 - LanguageModel_OOV = -0.15248 - PhraseModel_0 = -0.55811 - PhraseModel_1 = +0.12741 - PhraseModel_2 = +0.60388 - PhraseModel_3 = -0.44464 - PhraseModel_4 = -0.63137 - PhraseModel_5 = -0.0084 - PhraseModel_6 = -0.20165 - PassThrough = -0.23468 + Glue = -0.40908 + WordPenalty = +0.12967 + LanguageModel = +0.39892 + LanguageModel_OOV = -0.6314 + PhraseModel_0 = -0.63992 + PhraseModel_1 = +0.74198 + PhraseModel_2 = +1.3096 + PhraseModel_3 = -0.1216 + PhraseModel_4 = -1.2274 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.21093 + PassThrough = -0.66155 --- - 1best avg score: 0.14066 (+0.14066) - 1best avg model score: -37.614 (-37.614) - avg # pairs: 1244.7 - avg # rank err: 728 - avg # margin viol: 516.67 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.15735 (+0.15735) + 1best avg model score: 46.831 + avg # pairs: 2132.3 + non-0 feature count: 12 avg list sz: 100 - avg f count: 11.507 -(time 0.45 min, 9 s/S) - -Writing weights file to 'work/weights.0.1' ... -done + avg f count: 10.64 +(time 0.38 min, 7 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.14066]. -This took 0.45 min. +Best iteration: 1 [GOLD = 0.15735]. +This took 0.38333 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.2 b/training/dtrain/examples/parallelized/work/out.0.2 index fcecc7e1..9c4b110b 100644 --- a/training/dtrain/examples/parallelized/work/out.0.2 +++ b/training/dtrain/examples/parallelized/work/out.0.2 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 3693132895 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.0.0.in' output 'work/weights.0.2' weights in 'work/weights.1' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.019275 - WordPenalty = +0.022192 - LanguageModel = +0.40688 - LanguageModel_OOV = -0.36397 - PhraseModel_0 = -0.36273 - PhraseModel_1 = +0.56432 - PhraseModel_2 = +0.85638 - PhraseModel_3 = -0.20222 - PhraseModel_4 = -0.48295 - PhraseModel_5 = +0.03145 - PhraseModel_6 = -0.26092 - PassThrough = -0.38122 + Glue = -0.44422 + WordPenalty = +0.1032 + LanguageModel = +0.66474 + LanguageModel_OOV = -0.62252 + PhraseModel_0 = -0.59993 + PhraseModel_1 = +0.78992 + PhraseModel_2 = +1.3149 + PhraseModel_3 = +0.21434 + PhraseModel_4 = -1.0174 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.18452 + PassThrough = -0.65268 --- - 1best avg score: 0.18982 (+0.18982) - 1best avg model score: 1.7096 (+1.7096) - avg # pairs: 1524.3 - avg # rank err: 813.33 - avg # margin viol: 702.67 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.24722 (+0.24722) + 1best avg model score: 61.971 + avg # pairs: 2017.7 + non-0 feature count: 12 avg list sz: 100 - avg f count: 11.32 -(time 0.53 min, 11 s/S) - -Writing weights file to 'work/weights.0.2' ... -done + avg f count: 10.42 +(time 0.3 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.18982]. -This took 0.53333 min. +Best iteration: 1 [GOLD = 0.24722]. +This took 0.3 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.0 b/training/dtrain/examples/parallelized/work/out.1.0 index 595dfc94..3dc4dca6 100644 --- a/training/dtrain/examples/parallelized/work/out.1.0 +++ b/training/dtrain/examples/parallelized/work/out.1.0 @@ -1,65 +1,43 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 859043351 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.1.0.in' output 'work/weights.1.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.3229 - WordPenalty = +0.27969 - LanguageModel = +1.3645 - LanguageModel_OOV = -0.0443 - PhraseModel_0 = -0.19049 - PhraseModel_1 = -0.077698 - PhraseModel_2 = +0.058898 - PhraseModel_3 = +0.017251 - PhraseModel_4 = -1.5474 - PhraseModel_5 = +0 - PhraseModel_6 = -0.1818 - PassThrough = -0.193 + Glue = -0.2722 + WordPenalty = +0.05433 + LanguageModel = +0.69948 + LanguageModel_OOV = -0.2641 + PhraseModel_0 = -1.4208 + PhraseModel_1 = -1.563 + PhraseModel_2 = -0.21051 + PhraseModel_3 = -0.17764 + PhraseModel_4 = -1.6583 + PhraseModel_5 = +0.0794 + PhraseModel_6 = +0.1528 + PassThrough = -0.2367 --- - 1best avg score: 0.070229 (+0.070229) - 1best avg model score: -44.01 (-44.01) - avg # pairs: 1294 - avg # rank err: 878.67 - avg # margin viol: 350.67 - k-best loss imp: 100% - non0 feature count: 11 + 1best avg score: 0.071329 (+0.071329) + 1best avg model score: -41.362 + avg # pairs: 1862.3 + non-0 feature count: 12 avg list sz: 100 - avg f count: 11.487 -(time 0.28 min, 5.7 s/S) - -Writing weights file to 'work/weights.1.0' ... -done + avg f count: 11.847 +(time 0.28 min, 5 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.070229]. +Best iteration: 1 [GOLD = 0.071329]. This took 0.28333 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.1 b/training/dtrain/examples/parallelized/work/out.1.1 index 9346fc82..79ac35dc 100644 --- a/training/dtrain/examples/parallelized/work/out.1.1 +++ b/training/dtrain/examples/parallelized/work/out.1.1 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 3557309480 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.1.0.in' output 'work/weights.1.1' weights in 'work/weights.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.26425 - WordPenalty = +0.047881 - LanguageModel = +0.78496 - LanguageModel_OOV = -0.49307 - PhraseModel_0 = -0.58703 - PhraseModel_1 = -0.33425 - PhraseModel_2 = +0.20834 - PhraseModel_3 = -0.043346 - PhraseModel_4 = -0.60761 - PhraseModel_5 = +0.123 - PhraseModel_6 = -0.05415 - PassThrough = -0.42167 + Glue = -0.20488 + WordPenalty = -0.0091745 + LanguageModel = +0.79433 + LanguageModel_OOV = -0.4309 + PhraseModel_0 = -0.56242 + PhraseModel_1 = +0.85363 + PhraseModel_2 = +1.3458 + PhraseModel_3 = -0.13095 + PhraseModel_4 = -0.94762 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.16003 + PassThrough = -0.46105 --- - 1best avg score: 0.085952 (+0.085952) - 1best avg model score: -45.175 (-45.175) - avg # pairs: 1180.7 - avg # rank err: 668.33 - avg # margin viol: 512.33 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.13017 (+0.13017) + 1best avg model score: 14.53 + avg # pairs: 1968 + non-0 feature count: 12 avg list sz: 100 - avg f count: 12 -(time 0.27 min, 5.3 s/S) - -Writing weights file to 'work/weights.1.1' ... -done + avg f count: 11 +(time 0.33 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.085952]. -This took 0.26667 min. +Best iteration: 1 [GOLD = 0.13017]. +This took 0.33333 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.2 b/training/dtrain/examples/parallelized/work/out.1.2 index 08f07a75..8c4f8b03 100644 --- a/training/dtrain/examples/parallelized/work/out.1.2 +++ b/training/dtrain/examples/parallelized/work/out.1.2 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 56743915 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.1.0.in' output 'work/weights.1.2' weights in 'work/weights.1' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.23608 - WordPenalty = +0.10931 - LanguageModel = +0.81339 - LanguageModel_OOV = -0.33238 - PhraseModel_0 = -0.53685 - PhraseModel_1 = -0.049658 - PhraseModel_2 = +0.40277 - PhraseModel_3 = +0.14601 - PhraseModel_4 = -0.72851 - PhraseModel_5 = +0.03475 - PhraseModel_6 = -0.27192 - PassThrough = -0.34763 + Glue = -0.49853 + WordPenalty = +0.07636 + LanguageModel = +1.3183 + LanguageModel_OOV = -0.60902 + PhraseModel_0 = -0.22481 + PhraseModel_1 = +0.86369 + PhraseModel_2 = +1.0747 + PhraseModel_3 = +0.18002 + PhraseModel_4 = -0.84661 + PhraseModel_5 = +0.02435 + PhraseModel_6 = +0.11247 + PassThrough = -0.63918 --- - 1best avg score: 0.10073 (+0.10073) - 1best avg model score: -38.422 (-38.422) - avg # pairs: 1505.3 - avg # rank err: 777 - avg # margin viol: 691.67 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.15478 (+0.15478) + 1best avg model score: -7.2154 + avg # pairs: 1776 + non-0 feature count: 12 avg list sz: 100 - avg f count: 12 -(time 0.35 min, 7 s/S) - -Writing weights file to 'work/weights.1.2' ... -done + avg f count: 11.327 +(time 0.27 min, 5 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.10073]. -This took 0.35 min. +Best iteration: 1 [GOLD = 0.15478]. +This took 0.26667 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.0 b/training/dtrain/examples/parallelized/work/out.2.0 index 25ef6d4e..07c85963 100644 --- a/training/dtrain/examples/parallelized/work/out.2.0 +++ b/training/dtrain/examples/parallelized/work/out.2.0 @@ -1,65 +1,43 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 2662215673 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.2.0.in' output 'work/weights.2.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.1259 - WordPenalty = +0.048294 - LanguageModel = +0.36254 - LanguageModel_OOV = -0.1228 - PhraseModel_0 = +0.26357 - PhraseModel_1 = +0.24793 - PhraseModel_2 = +0.0063763 - PhraseModel_3 = -0.18966 - PhraseModel_4 = -0.226 + Glue = -0.2109 + WordPenalty = +0.14922 + LanguageModel = +0.79686 + LanguageModel_OOV = -0.6627 + PhraseModel_0 = +0.37999 + PhraseModel_1 = +0.69213 + PhraseModel_2 = +0.3422 + PhraseModel_3 = +1.1426 + PhraseModel_4 = -0.55413 PhraseModel_5 = +0 - PhraseModel_6 = +0.0743 - PassThrough = -0.1335 + PhraseModel_6 = +0.0676 + PassThrough = -0.6343 --- - 1best avg score: 0.072836 (+0.072836) - 1best avg model score: -0.56296 (-0.56296) - avg # pairs: 1094.7 - avg # rank err: 658 - avg # margin viol: 436.67 - k-best loss imp: 100% - non0 feature count: 11 + 1best avg score: 0.072374 (+0.072374) + 1best avg model score: -27.384 + avg # pairs: 2582 + non-0 feature count: 11 avg list sz: 100 - avg f count: 10.813 -(time 0.13 min, 2.7 s/S) - -Writing weights file to 'work/weights.2.0' ... -done + avg f count: 11.54 +(time 0.32 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.072836]. -This took 0.13333 min. +Best iteration: 1 [GOLD = 0.072374]. +This took 0.31667 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.1 b/training/dtrain/examples/parallelized/work/out.2.1 index 8e4efde9..c54bb1b1 100644 --- a/training/dtrain/examples/parallelized/work/out.2.1 +++ b/training/dtrain/examples/parallelized/work/out.2.1 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 3092904479 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.2.0.in' output 'work/weights.2.1' weights in 'work/weights.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.10385 - WordPenalty = +0.038717 - LanguageModel = +0.49413 - LanguageModel_OOV = -0.24887 - PhraseModel_0 = -0.32102 - PhraseModel_1 = +0.34413 - PhraseModel_2 = +0.62366 - PhraseModel_3 = -0.49337 - PhraseModel_4 = -0.77005 - PhraseModel_5 = +0.007 - PhraseModel_6 = -0.05055 - PassThrough = -0.23928 + Glue = -0.76608 + WordPenalty = +0.15938 + LanguageModel = +1.5897 + LanguageModel_OOV = -0.521 + PhraseModel_0 = -0.58348 + PhraseModel_1 = +0.29828 + PhraseModel_2 = +0.78493 + PhraseModel_3 = +0.083222 + PhraseModel_4 = -0.93843 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.27382 + PassThrough = -0.55115 --- - 1best avg score: 0.10245 (+0.10245) - 1best avg model score: -20.384 (-20.384) - avg # pairs: 1741.7 - avg # rank err: 953.67 - avg # margin viol: 585.33 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.12881 (+0.12881) + 1best avg model score: -9.6731 + avg # pairs: 2020.3 + non-0 feature count: 12 avg list sz: 100 - avg f count: 11.977 -(time 0.12 min, 2.3 s/S) - -Writing weights file to 'work/weights.2.1' ... -done + avg f count: 12 +(time 0.32 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.10245]. -This took 0.11667 min. +Best iteration: 1 [GOLD = 0.12881]. +This took 0.31667 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.2 b/training/dtrain/examples/parallelized/work/out.2.2 index e0ca2110..f5d6229f 100644 --- a/training/dtrain/examples/parallelized/work/out.2.2 +++ b/training/dtrain/examples/parallelized/work/out.2.2 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 2803362953 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.2.0.in' output 'work/weights.2.2' weights in 'work/weights.1' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 3 + .... 3 WEIGHTS - Glue = -0.32907 - WordPenalty = +0.049596 - LanguageModel = +0.33496 - LanguageModel_OOV = -0.44357 - PhraseModel_0 = -0.3068 - PhraseModel_1 = +0.59376 - PhraseModel_2 = +0.86416 - PhraseModel_3 = -0.21072 - PhraseModel_4 = -0.65734 - PhraseModel_5 = +0.03475 - PhraseModel_6 = -0.10653 - PassThrough = -0.46082 + Glue = -0.90863 + WordPenalty = +0.10819 + LanguageModel = +0.5239 + LanguageModel_OOV = -0.41623 + PhraseModel_0 = -0.86868 + PhraseModel_1 = +0.40784 + PhraseModel_2 = +1.1793 + PhraseModel_3 = -0.24698 + PhraseModel_4 = -1.2353 + PhraseModel_5 = +0.03375 + PhraseModel_6 = -0.17883 + PassThrough = -0.44638 --- - 1best avg score: 0.25055 (+0.25055) - 1best avg model score: -1.4459 (-1.4459) - avg # pairs: 1689 - avg # rank err: 755.67 - avg # margin viol: 829.33 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.12788 (+0.12788) + 1best avg model score: 41.302 + avg # pairs: 2246.3 + non-0 feature count: 12 avg list sz: 100 - avg f count: 10.53 -(time 0.13 min, 2.7 s/S) - -Writing weights file to 'work/weights.2.2' ... -done + avg f count: 10.98 +(time 0.35 min, 7 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.25055]. -This took 0.13333 min. +Best iteration: 1 [GOLD = 0.12788]. +This took 0.35 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.0 b/training/dtrain/examples/parallelized/work/out.3.0 index 3c074f04..fa499523 100644 --- a/training/dtrain/examples/parallelized/work/out.3.0 +++ b/training/dtrain/examples/parallelized/work/out.3.0 @@ -1,65 +1,43 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 316107185 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.3.0.in' output 'work/weights.3.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 1 + .. 1 WEIGHTS - Glue = +0.046 - WordPenalty = +0.17328 - LanguageModel = +1.1667 - LanguageModel_OOV = +0.066 - PhraseModel_0 = -1.1694 - PhraseModel_1 = -0.9883 - PhraseModel_2 = +0.036205 - PhraseModel_3 = -0.77387 - PhraseModel_4 = -1.5019 - PhraseModel_5 = +0.024 - PhraseModel_6 = -0.514 - PassThrough = +0.031 + Glue = -0.09 + WordPenalty = +0.32442 + LanguageModel = +2.5769 + LanguageModel_OOV = -0.009 + PhraseModel_0 = -0.58972 + PhraseModel_1 = +0.063691 + PhraseModel_2 = +0.5366 + PhraseModel_3 = +0.12867 + PhraseModel_4 = -1.9801 + PhraseModel_5 = +0.018 + PhraseModel_6 = -0.486 + PassThrough = -0.09 --- - 1best avg score: 0.032916 (+0.032916) - 1best avg model score: 0 (+0) - avg # pairs: 900 - avg # rank err: 900 - avg # margin viol: 0 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.034204 (+0.034204) + 1best avg model score: 0 + avg # pairs: 1700 + non-0 feature count: 12 avg list sz: 100 - avg f count: 11.72 -(time 0.23 min, 14 s/S) - -Writing weights file to 'work/weights.3.0' ... -done + avg f count: 10.8 +(time 0.1 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.032916]. -This took 0.23333 min. +Best iteration: 1 [GOLD = 0.034204]. +This took 0.1 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.1 b/training/dtrain/examples/parallelized/work/out.3.1 index 241d3455..c4b3aa3c 100644 --- a/training/dtrain/examples/parallelized/work/out.3.1 +++ b/training/dtrain/examples/parallelized/work/out.3.1 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 353677750 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.3.0.in' output 'work/weights.3.1' weights in 'work/weights.0' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 1 + .. 1 WEIGHTS - Glue = -0.08475 - WordPenalty = +0.11151 - LanguageModel = +1.0635 - LanguageModel_OOV = -0.11468 - PhraseModel_0 = -0.062922 - PhraseModel_1 = +0.0035552 - PhraseModel_2 = +0.039692 - PhraseModel_3 = +0.080265 - PhraseModel_4 = -0.57787 - PhraseModel_5 = +0.0174 - PhraseModel_6 = -0.17095 - PassThrough = -0.18248 + Glue = +0.31832 + WordPenalty = +0.11139 + LanguageModel = +0.95438 + LanguageModel_OOV = -0.0608 + PhraseModel_0 = -0.98113 + PhraseModel_1 = -0.090531 + PhraseModel_2 = +0.79088 + PhraseModel_3 = -0.57623 + PhraseModel_4 = -1.4382 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.10812 + PassThrough = -0.09095 --- - 1best avg score: 0.16117 (+0.16117) - 1best avg model score: -67.89 (-67.89) - avg # pairs: 1411 - avg # rank err: 460 - avg # margin viol: 951 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.084989 (+0.084989) + 1best avg model score: -52.323 + avg # pairs: 2487 + non-0 feature count: 12 avg list sz: 100 avg f count: 12 -(time 0.22 min, 13 s/S) - -Writing weights file to 'work/weights.3.1' ... -done +(time 0.1 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.16117]. -This took 0.21667 min. +Best iteration: 1 [GOLD = 0.084989]. +This took 0.1 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.2 b/training/dtrain/examples/parallelized/work/out.3.2 index b995daf5..eb27dac2 100644 --- a/training/dtrain/examples/parallelized/work/out.3.2 +++ b/training/dtrain/examples/parallelized/work/out.3.2 @@ -1,66 +1,44 @@ - cdec cfg 'cdec.ini' Loading the LM will be faster if you build a binary file. Reading ../standard/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 **************************************************************************************************** -Seeding random number sequence to 3001145976 - dtrain Parameters: k 100 N 4 T 1 - batch 0 - scorer 'stupid_bleu' - sample from 'kbest' - filter 'uniq' learning rate 0.0001 - gamma 0 - loss margin 1 - faster perceptron 0 - pairs 'XYX' - hi lo 0.1 - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' + error margin 1 + l1 reg 0 + decoder conf 'cdec.ini' + input 'work/shard.3.0.in' output 'work/weights.3.2' weights in 'work/weights.1' -(a dot represents 10 inputs) +(a dot per input) Iteration #1 of 1. - 1 + .. 1 WEIGHTS - Glue = -0.13247 - WordPenalty = +0.053592 - LanguageModel = +0.72105 - LanguageModel_OOV = -0.30827 - PhraseModel_0 = -0.37053 - PhraseModel_1 = +0.17551 - PhraseModel_2 = +0.5 - PhraseModel_3 = -0.1459 - PhraseModel_4 = -0.59563 - PhraseModel_5 = +0.03475 - PhraseModel_6 = -0.11143 - PassThrough = -0.32553 + Glue = -0.12993 + WordPenalty = +0.13651 + LanguageModel = +0.58946 + LanguageModel_OOV = -0.48362 + PhraseModel_0 = -0.81262 + PhraseModel_1 = +0.44273 + PhraseModel_2 = +1.1733 + PhraseModel_3 = -0.1826 + PhraseModel_4 = -1.2213 + PhraseModel_5 = +0.02435 + PhraseModel_6 = -0.18823 + PassThrough = -0.51378 --- - 1best avg score: 0.12501 (+0.12501) - 1best avg model score: -62.128 (-62.128) - avg # pairs: 979 - avg # rank err: 539 - avg # margin viol: 440 - k-best loss imp: 100% - non0 feature count: 12 + 1best avg score: 0.12674 (+0.12674) + 1best avg model score: -7.2878 + avg # pairs: 1769 + non-0 feature count: 12 avg list sz: 100 avg f count: 12 -(time 0.22 min, 13 s/S) - -Writing weights file to 'work/weights.3.2' ... -done +(time 0.1 min, 6 s/S) --- -Best iteration: 1 [SCORE 'stupid_bleu'=0.12501]. -This took 0.21667 min. +Best iteration: 1 [GOLD = 0.12674]. +This took 0.1 min. diff --git a/training/dtrain/examples/parallelized/work/shard.0.0.in b/training/dtrain/examples/parallelized/work/shard.0.0.in index d1b48321..a0ef6f54 100644 --- a/training/dtrain/examples/parallelized/work/shard.0.0.in +++ b/training/dtrain/examples/parallelized/work/shard.0.0.in @@ -1,3 +1,3 @@ -der erste schritt , um mit der rassenfrage umzugehen ist , ursache und folgen rassistischer feindseligkeiten zu verstehen , auch dann , wenn das bedeutet , unangenehme tatsachen aufzudecken . ||| the first step to address racial politics is to understand the origin and consequences of racial animosity , even if it means uncovering unpleasant truths . -die großen parteien der rechten und der linken mitte haben sich dem problem gestellt , in dem sie den kopf in den sand gesteckt und allen aussichten zuwider gehofft haben , es möge bald verschwinden . ||| mainstream parties of the center left and center right have confronted this prospect by hiding their heads in the ground , hoping against hope that the problem will disappear . +europas nach rassen geteiltes haus ||| europe 's divided racial house +ein gemeinsames merkmal aller extremen rechten in europa ist ihr rassismus und die tatsache , daß sie das einwanderungsproblem als politischen hebel benutzen . ||| a common feature of europe 's extreme right is its racism and use of the immigration issue as a political wedge . der lega nord in italien , der vlaams block in den niederlanden , die anhänger von le pens nationaler front in frankreich , sind beispiele für parteien oder bewegungen , die sich um das gemeinsame thema : ablehnung der zuwanderung gebildet haben und um forderung nach einer vereinfachten politik , um sie zu regeln . ||| the lega nord in italy , the vlaams blok in the netherlands , the supporters of le pen 's national front in france , are all examples of parties or movements formed on the common theme of aversion to immigrants and promotion of simplistic policies to control them . diff --git a/training/dtrain/examples/parallelized/work/shard.1.0.in b/training/dtrain/examples/parallelized/work/shard.1.0.in index a63f05bd..05f0273b 100644 --- a/training/dtrain/examples/parallelized/work/shard.1.0.in +++ b/training/dtrain/examples/parallelized/work/shard.1.0.in @@ -1,3 +1,3 @@ -eine alternde einheimische bevölkerung und immer offenere grenzen vermehren die rassistische zersplitterung in den europäischen ländern . ||| an aging population at home and ever more open borders imply increasing racial fragmentation in european countries . -genau das haben in den usa eine große anzahl an forschungsvorhaben in wirtschaft , soziologie , psychologie und politikwissenschaft geleistet . diese forschungen zeigten , daß menschen unterschiedlicher rasse einander deutlich weniger vertrauen . ||| this is precisely what a large amount of research in economics , sociology , psychology and political science has done for the us . während individuen wie jörg haidar und jean @-@ marie le pen kommen und ( leider nicht zu bald ) wieder gehen mögen , wird die rassenfrage aus der europäischer politik nicht so bald verschwinden . ||| while individuals like jorg haidar and jean @-@ marie le pen may come and ( never to soon ) go , the race question will not disappear from european politics anytime soon . +eine alternde einheimische bevölkerung und immer offenere grenzen vermehren die rassistische zersplitterung in den europäischen ländern . ||| an aging population at home and ever more open borders imply increasing racial fragmentation in european countries . +die großen parteien der rechten und der linken mitte haben sich dem problem gestellt , in dem sie den kopf in den sand gesteckt und allen aussichten zuwider gehofft haben , es möge bald verschwinden . ||| mainstream parties of the center left and center right have confronted this prospect by hiding their heads in the ground , hoping against hope that the problem will disappear . diff --git a/training/dtrain/examples/parallelized/work/shard.2.0.in b/training/dtrain/examples/parallelized/work/shard.2.0.in index fe542b40..0528d357 100644 --- a/training/dtrain/examples/parallelized/work/shard.2.0.in +++ b/training/dtrain/examples/parallelized/work/shard.2.0.in @@ -1,3 +1,3 @@ -ein gemeinsames merkmal aller extremen rechten in europa ist ihr rassismus und die tatsache , daß sie das einwanderungsproblem als politischen hebel benutzen . ||| a common feature of europe 's extreme right is its racism and use of the immigration issue as a political wedge . -europas nach rassen geteiltes haus ||| europe 's divided racial house das aber wird es nicht , wie die geschichte des rassismus in amerika deutlich zeigt . ||| it will not , as america 's racial history clearly shows . +die beziehungen zwischen den rassen standen in den usa über jahrzehnte - und tun das noch heute - im zentrum der politischen debatte . das ging so weit , daß rassentrennung genauso wichtig wie das einkommen wurde , - wenn nicht sogar noch wichtiger - um politische zuneigungen und einstellungen zu bestimmen . ||| race relations in the us have been for decades - and remain - at the center of political debate , to the point that racial cleavages are as important as income , if not more , as determinants of political preferences and attitudes . +der erste schritt , um mit der rassenfrage umzugehen ist , ursache und folgen rassistischer feindseligkeiten zu verstehen , auch dann , wenn das bedeutet , unangenehme tatsachen aufzudecken . ||| the first step to address racial politics is to understand the origin and consequences of racial animosity , even if it means uncovering unpleasant truths . diff --git a/training/dtrain/examples/parallelized/work/shard.3.0.in b/training/dtrain/examples/parallelized/work/shard.3.0.in index 4a8fa5b1..f7cbb3e3 100644 --- a/training/dtrain/examples/parallelized/work/shard.3.0.in +++ b/training/dtrain/examples/parallelized/work/shard.3.0.in @@ -1 +1 @@ -die beziehungen zwischen den rassen standen in den usa über jahrzehnte - und tun das noch heute - im zentrum der politischen debatte . das ging so weit , daß rassentrennung genauso wichtig wie das einkommen wurde , - wenn nicht sogar noch wichtiger - um politische zuneigungen und einstellungen zu bestimmen . ||| race relations in the us have been for decades - and remain - at the center of political debate , to the point that racial cleavages are as important as income , if not more , as determinants of political preferences and attitudes . +genau das haben in den usa eine große anzahl an forschungsvorhaben in wirtschaft , soziologie , psychologie und politikwissenschaft geleistet . diese forschungen zeigten , daß menschen unterschiedlicher rasse einander deutlich weniger vertrauen . ||| this is precisely what a large amount of research in economics , sociology , psychology and political science has done for the us . diff --git a/training/dtrain/examples/parallelized/work/weights.0 b/training/dtrain/examples/parallelized/work/weights.0 index c560fdbd..816269cd 100644 --- a/training/dtrain/examples/parallelized/work/weights.0 +++ b/training/dtrain/examples/parallelized/work/weights.0 @@ -1,12 +1,12 @@ -PhraseModel_4 -0.6990170657294328 -LanguageModel 0.891784887346263 -PhraseModel_0 -0.2107507586515428 -PhraseModel_1 -0.15442709655871997 -PhraseModel_3 -0.07262514338204715 -PhraseModel_6 -0.10965000000000148 -Glue -0.03644999999999783 -WordPenalty 0.13204723722268177 -PassThrough -0.09437500000000089 -LanguageModel_OOV -0.036775000000000564 -PhraseModel_2 0.025521702385571707 -PhraseModel_5 0.006999999999999977 +LanguageModel 1.200704259340465 +PhraseModel_4 -1.2434381298299035 +PhraseModel_1 0.050697726409824076 +PhraseModel_0 -0.516923312932941 +PhraseModel_2 0.5051987092783867 +PhraseModel_3 0.20955092377784057 +PassThrough -0.32285 +LanguageModel_OOV -0.29269999999999996 +PhraseModel_6 -0.158425 +Glue -0.05817500000000002 +WordPenalty 0.12758486142112804 +PhraseModel_5 0.02435 diff --git a/training/dtrain/examples/parallelized/work/weights.0.0 b/training/dtrain/examples/parallelized/work/weights.0.0 index 91eedc7b..be386c62 100644 --- a/training/dtrain/examples/parallelized/work/weights.0.0 +++ b/training/dtrain/examples/parallelized/work/weights.0.0 @@ -1,12 +1,11 @@ -PassThrough -0.082000000000001058 -Glue 0.25700000000000267 -LanguageModel_OOV -0.046000000000000034 -LanguageModel 0.67341721152744249 -PhraseModel_6 0.18290000000000028 -PhraseModel_5 0.0039999999999999975 -PhraseModel_4 0.47916377173928498 -PhraseModel_3 0.65577926367715722 -PhraseModel_2 0.00060731048591637909 -PhraseModel_0 0.25329462707903372 -WordPenalty 0.026926257878001431 -PhraseModel_1 0.20035945197369062 +WordPenalty -0.017632355965271129 +LanguageModel 0.72957628464102753 +LanguageModel_OOV -0.23499999999999999 +PhraseModel_0 -0.43720953659541578 +PhraseModel_1 1.0100170838129212 +PhraseModel_2 1.3524984123857073 +PhraseModel_3 -0.25541132249775761 +PhraseModel_4 -0.78115161368856911 +PhraseModel_6 -0.36810000000000004 +Glue 0.34040000000000004 +PassThrough -0.33040000000000003 diff --git a/training/dtrain/examples/parallelized/work/weights.0.1 b/training/dtrain/examples/parallelized/work/weights.0.1 index 6fcc9999..d4c77d07 100644 --- a/training/dtrain/examples/parallelized/work/weights.0.1 +++ b/training/dtrain/examples/parallelized/work/weights.0.1 @@ -1,12 +1,12 @@ -PassThrough -0.2346750000000028 -Glue -0.17904999999999763 -WordPenalty 0.062125825636256168 -LanguageModel 0.66824625053667575 -LanguageModel_OOV -0.15247500000000355 -PhraseModel_0 -0.5581144363944085 -PhraseModel_1 0.12740874153205478 -PhraseModel_2 0.6038779278708799 -PhraseModel_3 -0.44463820299544454 -PhraseModel_4 -0.63136538282212662 -PhraseModel_5 -0.0084000000000000324 -PhraseModel_6 -0.20164999999999911 +WordPenalty 0.12966947493426365 +LanguageModel 0.3989224621154368 +LanguageModel_OOV -0.63139999999999996 +PhraseModel_0 -0.63991953012355962 +PhraseModel_1 0.74197897612368646 +PhraseModel_2 1.3096163833051435 +PhraseModel_3 -0.12160001974680773 +PhraseModel_4 -1.2274031286515816 +PhraseModel_5 0.02435 +PhraseModel_6 -0.210925 +Glue -0.40907500000000002 +PassThrough -0.66155000000000008 diff --git a/training/dtrain/examples/parallelized/work/weights.0.2 b/training/dtrain/examples/parallelized/work/weights.0.2 index 5668915d..8ce1449b 100644 --- a/training/dtrain/examples/parallelized/work/weights.0.2 +++ b/training/dtrain/examples/parallelized/work/weights.0.2 @@ -1,12 +1,12 @@ -PassThrough -0.38122499999999337 -Glue -0.019274999999998679 -WordPenalty 0.022192448025253487 -LanguageModel 0.4068780855136106 -LanguageModel_OOV -0.363974999999992 -PhraseModel_0 -0.36273429313029715 -PhraseModel_1 0.56431752511029298 -PhraseModel_2 0.85638010019687694 -PhraseModel_3 -0.20222345248738063 -PhraseModel_4 -0.48295466434310252 -PhraseModel_5 0.031450000000000339 -PhraseModel_6 -0.26092499999998625 +WordPenalty 0.10319922626226019 +LanguageModel 0.6647396869692952 +LanguageModel_OOV -0.622525 +PhraseModel_0 -0.59993441316076157 +PhraseModel_1 0.78991513935858193 +PhraseModel_2 1.3148638774685031 +PhraseModel_3 0.2143393571820455 +PhraseModel_4 -1.0173894637028262 +PhraseModel_5 0.02435 +PhraseModel_6 -0.18452499999999999 +Glue -0.44422499999999998 +PassThrough -0.65267500000000012 diff --git a/training/dtrain/examples/parallelized/work/weights.1 b/training/dtrain/examples/parallelized/work/weights.1 index f52e07b8..2a00be2e 100644 --- a/training/dtrain/examples/parallelized/work/weights.1 +++ b/training/dtrain/examples/parallelized/work/weights.1 @@ -1,12 +1,12 @@ -LanguageModel 0.7527067666152598 -PhraseModel_4 -0.6467221787583058 -PhraseModel_2 0.36889175522051015 -PhraseModel_0 -0.38227173053779245 -PhraseModel_3 -0.2252732111174934 -LanguageModel_OOV -0.25227499999999975 -PassThrough -0.2695250000000011 -PhraseModel_1 0.03521067244127414 -Glue -0.1579749999999981 -PhraseModel_6 -0.11932500000000047 -WordPenalty 0.0650573133891042 -PhraseModel_5 0.03475000000000043 +PhraseModel_4 -1.1379250444170055 +PhraseModel_2 1.0578050661336098 +LanguageModel 0.9343385461706668 +PhraseModel_0 -0.6917392152965985 +PhraseModel_1 0.4508371141128957 +PassThrough -0.4411750000000001 +Glue -0.265425 +LanguageModel_OOV -0.411025 +PhraseModel_3 -0.186390082624459 +PhraseModel_6 -0.188225 +WordPenalty 0.09781397468665984 +PhraseModel_5 0.02435 diff --git a/training/dtrain/examples/parallelized/work/weights.1.0 b/training/dtrain/examples/parallelized/work/weights.1.0 index 31e08d81..cdcf959e 100644 --- a/training/dtrain/examples/parallelized/work/weights.1.0 +++ b/training/dtrain/examples/parallelized/work/weights.1.0 @@ -1,11 +1,12 @@ -LanguageModel_OOV -0.044300000000000235 -PassThrough -0.19300000000000087 -PhraseModel_6 -0.18180000000000701 -LanguageModel 1.3644969337716422 -PhraseModel_3 0.017250706134911725 -PhraseModel_4 -1.5473728273858063 -Glue -0.32289999999999447 -PhraseModel_1 -0.077697953502182365 -WordPenalty 0.27968564634568688 -PhraseModel_0 -0.19048660891012237 -PhraseModel_2 0.05889844333199834 +WordPenalty 0.05433023968609621 +LanguageModel 0.69947965605855011 +LanguageModel_OOV -0.2641 +PhraseModel_0 -1.4207505705360111 +PhraseModel_1 -1.563047680441811 +PhraseModel_2 -0.21050528366541305 +PhraseModel_3 -0.17764037275860439 +PhraseModel_4 -1.6583462458159566 +PhraseModel_5 0.079399999999999998 +PhraseModel_6 0.15280000000000002 +Glue -0.27220000000000005 +PassThrough -0.23670000000000002 diff --git a/training/dtrain/examples/parallelized/work/weights.1.1 b/training/dtrain/examples/parallelized/work/weights.1.1 index 544ff462..c1bb2cf0 100644 --- a/training/dtrain/examples/parallelized/work/weights.1.1 +++ b/training/dtrain/examples/parallelized/work/weights.1.1 @@ -1,12 +1,12 @@ -PassThrough -0.42167499999999858 -Glue -0.26424999999999721 -WordPenalty 0.04788096662983269 -LanguageModel 0.78495517342352483 -LanguageModel_OOV -0.49307499999999477 -PhraseModel_0 -0.58703462849498356 -PhraseModel_1 -0.33425278954714266 -PhraseModel_2 0.20834221229630179 -PhraseModel_3 -0.043345645640208569 -PhraseModel_4 -0.60760531115816907 -PhraseModel_5 0.12300000000000186 -PhraseModel_6 -0.054150000000001031 +WordPenalty -0.0091744709302067785 +LanguageModel 0.79433413663506514 +LanguageModel_OOV -0.43090000000000001 +PhraseModel_0 -0.56242499947237046 +PhraseModel_1 0.85362516703032698 +PhraseModel_2 1.3457900890481096 +PhraseModel_3 -0.13095079554478939 +PhraseModel_4 -0.94761908497413061 +PhraseModel_5 0.02435 +PhraseModel_6 -0.160025 +Glue -0.20487500000000003 +PassThrough -0.46105000000000007 diff --git a/training/dtrain/examples/parallelized/work/weights.1.2 b/training/dtrain/examples/parallelized/work/weights.1.2 index ac3284b9..c9598a04 100644 --- a/training/dtrain/examples/parallelized/work/weights.1.2 +++ b/training/dtrain/examples/parallelized/work/weights.1.2 @@ -1,12 +1,12 @@ -PassThrough -0.34762500000000224 -Glue -0.23607500000000026 -WordPenalty 0.10931192109504413 -LanguageModel 0.81339027211983694 -LanguageModel_OOV -0.33237500000000098 -PhraseModel_0 -0.53685104648974269 -PhraseModel_1 -0.049657790506137042 -PhraseModel_2 0.40277066454544108 -PhraseModel_3 0.14600791389785803 -PhraseModel_4 -0.72850673041349101 -PhraseModel_5 0.034750000000000433 -PhraseModel_6 -0.27192499999999448 +WordPenalty 0.076359827280638559 +LanguageModel 1.3183380272921175 +LanguageModel_OOV -0.60902499999999993 +PhraseModel_0 -0.2248075206657828 +PhraseModel_1 0.86368802571834491 +PhraseModel_2 1.0746702462261808 +PhraseModel_3 0.18002263643876637 +PhraseModel_4 -0.84660750337519441 +PhraseModel_5 0.02435 +PhraseModel_6 0.11247499999999999 +Glue -0.49852500000000005 +PassThrough -0.63917500000000005 diff --git a/training/dtrain/examples/parallelized/work/weights.2 b/training/dtrain/examples/parallelized/work/weights.2 index dedaf165..310973ec 100644 --- a/training/dtrain/examples/parallelized/work/weights.2 +++ b/training/dtrain/examples/parallelized/work/weights.2 @@ -1,12 +1,12 @@ -PhraseModel_2 0.6558266927225778 -PhraseModel_4 -0.6161090299356294 -LanguageModel 0.5690697644415413 -PhraseModel_1 0.32098232482479416 -PhraseModel_0 -0.39422813904895143 -PassThrough -0.37879999999999764 -LanguageModel_OOV -0.3620499999999963 -Glue -0.1792249999999967 -PhraseModel_6 -0.18769999999999526 -PhraseModel_3 -0.10321074877850786 -WordPenalty 0.05867318450512617 -PhraseModel_5 0.03392500000000041 +PhraseModel_2 1.185520780812669 +PhraseModel_4 -1.0801541070647134 +LanguageModel 0.7741099486587568 +PhraseModel_0 -0.6265095873268189 +PhraseModel_1 0.6260421233840029 +PassThrough -0.5630000000000002 +Glue -0.495325 +LanguageModel_OOV -0.53285 +PhraseModel_3 -0.008805626854390465 +PhraseModel_6 -0.10977500000000001 +WordPenalty 0.1060655698428214 +PhraseModel_5 0.026699999999999998 diff --git a/training/dtrain/examples/parallelized/work/weights.2.0 b/training/dtrain/examples/parallelized/work/weights.2.0 index f7ece54d..3e87fed4 100644 --- a/training/dtrain/examples/parallelized/work/weights.2.0 +++ b/training/dtrain/examples/parallelized/work/weights.2.0 @@ -1,11 +1,11 @@ -LanguageModel_OOV -0.12280000000000209 -PassThrough -0.13350000000000165 -Glue -0.1259000000000001 -PhraseModel_1 0.24792740418949952 -WordPenalty 0.048293546387642321 -PhraseModel_0 0.26356693580129958 -PhraseModel_2 0.0063762787517740458 -PhraseModel_3 -0.18966358382769741 -PhraseModel_4 -0.22599681869670471 -PhraseModel_6 0.074299999999999047 -LanguageModel 0.3625416478537038 +WordPenalty 0.14922358398195767 +LanguageModel 0.79685677298009394 +LanguageModel_OOV -0.66270000000000007 +PhraseModel_0 0.37998874905310187 +PhraseModel_1 0.69213063228111271 +PhraseModel_2 0.34219807728516061 +PhraseModel_3 1.1425846772648622 +PhraseModel_4 -0.55412548521619742 +PhraseModel_6 0.067599999999999993 +Glue -0.21090000000000003 +PassThrough -0.63429999999999997 diff --git a/training/dtrain/examples/parallelized/work/weights.2.1 b/training/dtrain/examples/parallelized/work/weights.2.1 index 0946609d..d129dc49 100644 --- a/training/dtrain/examples/parallelized/work/weights.2.1 +++ b/training/dtrain/examples/parallelized/work/weights.2.1 @@ -1,12 +1,12 @@ -PassThrough -0.23927500000000015 -Glue -0.10384999999999919 -WordPenalty 0.038717353061671053 -LanguageModel 0.49412782572695274 -LanguageModel_OOV -0.24887499999999915 -PhraseModel_0 -0.32101572713801541 -PhraseModel_1 0.34413149733472631 -PhraseModel_2 0.62365535622061474 -PhraseModel_3 -0.49337445280658987 -PhraseModel_4 -0.77004673375347765 -PhraseModel_5 0.0069999999999999767 -PhraseModel_6 -0.05055000000000108 +WordPenalty 0.1593752174964457 +LanguageModel 1.5897162231676281 +LanguageModel_OOV -0.52100000000000002 +PhraseModel_0 -0.5834836741748588 +PhraseModel_1 0.29827543837280185 +PhraseModel_2 0.78493316593562568 +PhraseModel_3 0.083221832554333464 +PhraseModel_4 -0.93843312963279457 +PhraseModel_5 0.02435 +PhraseModel_6 -0.27382499999999999 +Glue -0.76607500000000006 +PassThrough -0.55115000000000003 diff --git a/training/dtrain/examples/parallelized/work/weights.2.2 b/training/dtrain/examples/parallelized/work/weights.2.2 index b766fc75..bcc83b44 100644 --- a/training/dtrain/examples/parallelized/work/weights.2.2 +++ b/training/dtrain/examples/parallelized/work/weights.2.2 @@ -1,12 +1,12 @@ -PassThrough -0.46082499999999499 -Glue -0.32907499999998979 -WordPenalty 0.049596429833348527 -LanguageModel 0.33496341201347335 -LanguageModel_OOV -0.44357499999999361 -PhraseModel_0 -0.30679883980783829 -PhraseModel_1 0.5937585900939707 -PhraseModel_2 0.86415970329021152 -PhraseModel_3 -0.21072279838022553 -PhraseModel_4 -0.65734339854224544 -PhraseModel_5 0.034750000000000433 -PhraseModel_6 -0.10652500000000011 +WordPenalty 0.10819361280414735 +LanguageModel 0.52389743342585859 +LanguageModel_OOV -0.41622500000000001 +PhraseModel_0 -0.86867995703334211 +PhraseModel_1 0.40783818771767943 +PhraseModel_2 1.1792706530114188 +PhraseModel_3 -0.2469805689928464 +PhraseModel_4 -1.2352895858909159 +PhraseModel_5 0.033750000000000002 +PhraseModel_6 -0.17882500000000001 +Glue -0.90862500000000002 +PassThrough -0.44637500000000013 diff --git a/training/dtrain/examples/parallelized/work/weights.3.0 b/training/dtrain/examples/parallelized/work/weights.3.0 index 403ffbb3..e3586048 100644 --- a/training/dtrain/examples/parallelized/work/weights.3.0 +++ b/training/dtrain/examples/parallelized/work/weights.3.0 @@ -1,12 +1,12 @@ -PhraseModel_4 -1.501862388574505 -PhraseModel_3 -0.77386695951256013 -PhraseModel_6 -0.51399999999999824 -PhraseModel_5 0.02399999999999991 -LanguageModel 1.1666837562322641 -PhraseModel_2 0.036204776972598059 -PassThrough 0.030999999999999975 -Glue 0.046000000000000582 -PhraseModel_1 -0.98829728889588764 -WordPenalty 0.1732834982793964 -PhraseModel_0 -1.1693779885763822 -LanguageModel_OOV 0.066000000000000086 +WordPenalty 0.32441797798172944 +LanguageModel 2.5769043236821889 +LanguageModel_OOV -0.0090000000000000011 +PhraseModel_0 -0.58972189365343919 +PhraseModel_1 0.063690869987073351 +PhraseModel_2 0.53660363110809217 +PhraseModel_3 0.12867071310286207 +PhraseModel_4 -1.9801291745988916 +PhraseModel_5 0.018000000000000002 +PhraseModel_6 -0.48600000000000004 +Glue -0.090000000000000011 +PassThrough -0.090000000000000011 diff --git a/training/dtrain/examples/parallelized/work/weights.3.1 b/training/dtrain/examples/parallelized/work/weights.3.1 index c171d586..b27687d3 100644 --- a/training/dtrain/examples/parallelized/work/weights.3.1 +++ b/training/dtrain/examples/parallelized/work/weights.3.1 @@ -1,12 +1,12 @@ -PassThrough -0.18247500000000313 -Glue -0.084749999999998368 -WordPenalty 0.11150510822865688 -LanguageModel 1.063497816773886 -LanguageModel_OOV -0.1146750000000015 -PhraseModel_0 -0.062922130123762257 -PhraseModel_1 0.0035552404454581212 -PhraseModel_2 0.039691524494244249 -PhraseModel_3 0.080265456972269417 -PhraseModel_4 -0.57787128729945014 -PhraseModel_5 0.017399999999999922 -PhraseModel_6 -0.17095000000000066 +WordPenalty 0.11138567724613679 +LanguageModel 0.95438136276453733 +LanguageModel_OOV -0.060799999999999937 +PhraseModel_0 -0.98112865741560529 +PhraseModel_1 -0.090531125075232435 +PhraseModel_2 0.79088062624556033 +PhraseModel_3 -0.57623134776057228 +PhraseModel_4 -1.4382448344095151 +PhraseModel_5 0.02435 +PhraseModel_6 -0.108125 +Glue 0.31832499999999997 +PassThrough -0.090950000000000003 diff --git a/training/dtrain/examples/parallelized/work/weights.3.2 b/training/dtrain/examples/parallelized/work/weights.3.2 index 3ff0411d..ccb591a2 100644 --- a/training/dtrain/examples/parallelized/work/weights.3.2 +++ b/training/dtrain/examples/parallelized/work/weights.3.2 @@ -1,12 +1,12 @@ -PassThrough -0.32552500000000006 -Glue -0.13247499999999815 -WordPenalty 0.053591939066858545 -LanguageModel 0.72104728811924446 -LanguageModel_OOV -0.30827499999999869 -PhraseModel_0 -0.37052837676792744 -PhraseModel_1 0.17551097460105014 -PhraseModel_2 0.49999630285778179 -PhraseModel_3 -0.14590465814428336 -PhraseModel_4 -0.59563132644367889 -PhraseModel_5 0.034750000000000433 -PhraseModel_6 -0.11142500000000025 +WordPenalty 0.13650961302423945 +LanguageModel 0.58946464694775647 +LanguageModel_OOV -0.48362499999999997 +PhraseModel_0 -0.81261645844738917 +PhraseModel_1 0.44272714074140529 +PhraseModel_2 1.1732783465445731 +PhraseModel_3 -0.18260393204552733 +PhraseModel_4 -1.2213298752899167 +PhraseModel_5 0.02435 +PhraseModel_6 -0.188225 +Glue -0.12992500000000001 +PassThrough -0.51377500000000009 diff --git a/training/dtrain/examples/standard/dtrain.ini b/training/dtrain/examples/standard/dtrain.ini index a515db02..f2698007 100644 --- a/training/dtrain/examples/standard/dtrain.ini +++ b/training/dtrain/examples/standard/dtrain.ini @@ -1,27 +1,10 @@ -#input=./nc-wmt11.de.gz -#refs=./nc-wmt11.en.gz -bitext=./nc-wmt11.gz +bitext=./nc-wmt11.gz # input bitext output=- # a weights file (add .gz for gzip compression) or STDOUT '-' -select_weights=avg # output average (over epochs) weight vector decoder_config=./cdec.ini # config for cdec -# weights for these features will be printed on each iteration +iterations=3 # run over input 3 times +k=100 # use 100best lists +N=4 # optimize (approx.) BLEU4 +learning_rate=0.1 # learning rate +error_margin=1.0 # margin for margin perceptron print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough -# newer version of the grammar extractor use different feature names: -#print_weights= EgivenFCoherent SampleCountF CountEF MaxLexFgivenE MaxLexEgivenF IsSingletonF IsSingletonFE Glue WordPenalty PassThrough LanguageModel LanguageModel_OOV -stop_after=10 # stop epoch after 10 inputs -# interesting stuff -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=0.1 # 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) -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 -repeat=1 # repeat training on a kbest list 1 times -#batch=true # batch tuning, update after accumulating over all sentences and all kbest lists diff --git a/training/dtrain/examples/toy/dtrain.ini b/training/dtrain/examples/toy/dtrain.ini index 70c7331c..378224b8 100644 --- a/training/dtrain/examples/toy/dtrain.ini +++ b/training/dtrain/examples/toy/dtrain.ini @@ -1,12 +1,8 @@ decoder_config=cdec.ini bitext=in -output=- -print_weights=logp shell_rule house_rule small_rule little_rule PassThrough PassThrough_1 PassThrough_2 PassThrough_3 PassThrough_4 PassThrough_5 PassThrough_6 +output=weights k=4 N=4 -epochs=2 -scorer=bleu -sample_from=kbest -filter=uniq -pair_sampling=all +iterations=2 learning_rate=1 +print_weights=logp shell_rule house_rule small_rule little_rule PassThrough PassThrough_1 PassThrough_2 PassThrough_3 PassThrough_4 PassThrough_5 PassThrough_6 diff --git a/training/dtrain/examples/toy/expected-output b/training/dtrain/examples/toy/expected-output index 3c3a5a18..8c758d00 100644 --- a/training/dtrain/examples/toy/expected-output +++ b/training/dtrain/examples/toy/expected-output @@ -1,40 +1,24 @@ -Warning: hi_lo only works with pair_sampling XYX. - cdec cfg 'cdec.ini' -Seeding random number sequence to 3644621239 - dtrain Parameters: k 4 N 4 T 2 - batch 0 - scorer 'bleu' - sample from 'kbest' - filter 'uniq' learning rate 1 - gamma 0 - loss margin 0 - faster perceptron 1 - pairs 'all' - pair threshold 0 - select weights 'last' - l1 reg 0 'none' - pclr no - max pairs 4294967295 - repeat 1 - cdec cfg 'cdec.ini' - input '' - output '-' -(a dot represents 10 inputs) + error margin 0 + l1 reg 0 + decoder conf 'cdec.ini' + input 'in' + output 'weights' +(a dot per input) Iteration #1 of 2. - 2 + ... 2 WEIGHTS logp = +0 - shell_rule = -1 - house_rule = +2 - small_rule = -2 + shell_rule = +0 + house_rule = +3 + small_rule = +0 little_rule = +3 - PassThrough = -5 + PassThrough = -15 PassThrough_1 = +0 PassThrough_2 = +0 PassThrough_3 = +0 @@ -42,26 +26,23 @@ WEIGHTS PassThrough_5 = +0 PassThrough_6 = +0 --- - 1best avg score: 0.5 (+0.5) - 1best avg model score: 2.5 (+2.5) - avg # pairs: 1.5 - avg # rank err: 1.5 (meaningless) - avg # margin viol: 0 - k-best loss imp: 100% - non0 feature count: 6 + 1best avg score: 0.40937 (+0.40937) + 1best avg model score: 3 + avg # pairs: 2.5 + non-0 feature count: 4 avg list sz: 4 avg f count: 2.875 (time 0 min, 0 s/S) Iteration #2 of 2. - 2 + ... 2 WEIGHTS logp = +0 - shell_rule = -1 - house_rule = +2 - small_rule = -2 + shell_rule = +0 + house_rule = +3 + small_rule = +0 little_rule = +3 - PassThrough = -5 + PassThrough = -15 PassThrough_1 = +0 PassThrough_2 = +0 PassThrough_3 = +0 @@ -69,26 +50,14 @@ WEIGHTS PassThrough_5 = +0 PassThrough_6 = +0 --- - 1best avg score: 1 (+0.5) - 1best avg model score: 5 (+2.5) + 1best avg score: 0.81873 (+0.40937) + 1best avg model score: 6 avg # pairs: 0 - avg # rank err: 0 (meaningless) - avg # margin viol: 0 - k-best loss imp: 100% - non0 feature count: 6 + non-0 feature count: 4 avg list sz: 4 avg f count: 3 (time 0 min, 0 s/S) -Writing weights file to '-' ... -house_rule 2 -little_rule 3 -Glue -4 -PassThrough -5 -small_rule -2 -shell_rule -1 -done - --- -Best iteration: 2 [SCORE 'bleu'=1]. +Best iteration: 2 [GOLD = 0.81873]. This took 0 min. diff --git a/training/dtrain/examples/toy/weights b/training/dtrain/examples/toy/weights new file mode 100644 index 00000000..f6f32772 --- /dev/null +++ b/training/dtrain/examples/toy/weights @@ -0,0 +1,4 @@ +house_rule 3 +little_rule 3 +Glue -12 +PassThrough -15 -- cgit v1.2.3