diff options
Diffstat (limited to 'training/dtrain/examples/parallelized/work')
31 files changed, 30869 insertions, 465 deletions
diff --git a/training/dtrain/examples/parallelized/work/out.0.0 b/training/dtrain/examples/parallelized/work/out.0.0 index 77749404..da7c20a4 100644 --- a/training/dtrain/examples/parallelized/work/out.0.0 +++ b/training/dtrain/examples/parallelized/work/out.0.0 @@ -2,42 +2,43 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.0.0.in' + input 'work/shard.0.0' output 'work/weights.0.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = +0.1984 + WordPenalty = +0.06119 + LanguageModel = +0.6184 + LanguageModel_OOV = -0.2584 + PhraseModel_0 = -0.3803 + PhraseModel_1 = +0.6495 + PhraseModel_2 = +0.9499 + PhraseModel_3 = -0.4945 + PhraseModel_4 = -0.4588 PhraseModel_5 = +0 - PhraseModel_6 = -0.3681 - PassThrough = -0.3304 + PhraseModel_6 = -0.2935 + PassThrough = -0.2742 --- - 1best avg score: 0.19474 (+0.19474) - 1best avg model score: 0.52232 - avg # pairs: 2513 - non-0 feature count: 11 + 1best avg score: 22.94 (+22.94) + 1best avg model score: +33.08 + avg # updates: 2169 + non-0 feature count: 441 + avg f count: 143.9 avg list sz: 100 - avg f count: 11.42 -(time 0.32 min, 6 s/S) +(time 0.1667 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.19474]. -This took 0.31667 min. +Best iteration: 1 [GOLD = 22.94]. +This took 0.1667 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.1 b/training/dtrain/examples/parallelized/work/out.0.1 index d0dee623..c18747fb 100644 --- a/training/dtrain/examples/parallelized/work/out.0.1 +++ b/training/dtrain/examples/parallelized/work/out.0.1 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.0.0.in' + input 'work/shard.0.0' output 'work/weights.0.1' weights in 'work/weights.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = +0.08417 + WordPenalty = +0.1674 + LanguageModel = +0.5448 + LanguageModel_OOV = -0.6311 + PhraseModel_0 = -0.2931 + PhraseModel_1 = +1.173 + PhraseModel_2 = +1.369 + PhraseModel_3 = +0.1819 + PhraseModel_4 = -0.8439 + PhraseModel_5 = +0.02055 + PhraseModel_6 = -0.3794 + PassThrough = -0.6827 --- - 1best avg score: 0.15735 (+0.15735) - 1best avg model score: 46.831 - avg # pairs: 2132.3 - non-0 feature count: 12 + 1best avg score: 16.83 (+16.83) + 1best avg model score: +66.56 + avg # updates: 2090 + non-0 feature count: 2218 + avg f count: 142.5 avg list sz: 100 - avg f count: 10.64 -(time 0.38 min, 7 s/S) +(time 0.1833 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.15735]. -This took 0.38333 min. +Best iteration: 1 [GOLD = 16.83]. +This took 0.1833 min. diff --git a/training/dtrain/examples/parallelized/work/out.0.2 b/training/dtrain/examples/parallelized/work/out.0.2 index 9c4b110b..c859db3f 100644 --- a/training/dtrain/examples/parallelized/work/out.0.2 +++ b/training/dtrain/examples/parallelized/work/out.0.2 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.0.0.in' + input 'work/shard.0.0' output 'work/weights.0.2' weights in 'work/weights.1' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = -0.1266 + WordPenalty = +0.2244 + LanguageModel = +0.4891 + LanguageModel_OOV = -0.6065 + PhraseModel_0 = -0.634 + PhraseModel_1 = +0.6576 + PhraseModel_2 = +1.165 + PhraseModel_3 = +0.01649 + PhraseModel_4 = -0.8815 + PhraseModel_5 = +0.04098 + PhraseModel_6 = -0.5361 + PassThrough = -0.6292 --- - 1best avg score: 0.24722 (+0.24722) - 1best avg model score: 61.971 - avg # pairs: 2017.7 - non-0 feature count: 12 + 1best avg score: 27.3 (+27.3) + 1best avg model score: +27.47 + avg # updates: 1764 + non-0 feature count: 2824 + avg f count: 153 avg list sz: 100 - avg f count: 10.42 -(time 0.3 min, 6 s/S) +(time 0.1833 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.24722]. -This took 0.3 min. +Best iteration: 1 [GOLD = 27.3]. +This took 0.1833 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.0 b/training/dtrain/examples/parallelized/work/out.1.0 index 3dc4dca6..7a72e275 100644 --- a/training/dtrain/examples/parallelized/work/out.1.0 +++ b/training/dtrain/examples/parallelized/work/out.1.0 @@ -2,42 +2,43 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.1.0.in' + input 'work/shard.1.0' output 'work/weights.1.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = +0.2684 + WordPenalty = -0.2237 + LanguageModel = -1.104 + LanguageModel_OOV = +0.1174 + PhraseModel_0 = -0.9356 + PhraseModel_1 = -0.9926 + PhraseModel_2 = -0.2008 + PhraseModel_3 = -0.7721 + PhraseModel_4 = +0.5111 + PhraseModel_5 = +0 + PhraseModel_6 = -0.6298 + PassThrough = -0.0118 --- - 1best avg score: 0.071329 (+0.071329) - 1best avg model score: -41.362 - avg # pairs: 1862.3 - non-0 feature count: 12 + 1best avg score: 4.189 (+4.189) + 1best avg model score: +319.9 + avg # updates: 2100 + non-0 feature count: 599 + avg f count: 213.9 avg list sz: 100 - avg f count: 11.847 -(time 0.28 min, 5 s/S) +(time 0.1667 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.071329]. -This took 0.28333 min. +Best iteration: 1 [GOLD = 4.189]. +This took 0.1667 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.1 b/training/dtrain/examples/parallelized/work/out.1.1 index 79ac35dc..bd209601 100644 --- a/training/dtrain/examples/parallelized/work/out.1.1 +++ b/training/dtrain/examples/parallelized/work/out.1.1 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.1.0.in' + input 'work/shard.1.0' output 'work/weights.1.1' weights in 'work/weights.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = +0.4661 + WordPenalty = +0.07374 + LanguageModel = +0.3354 + LanguageModel_OOV = -0.6514 + PhraseModel_0 = -0.4878 + PhraseModel_1 = +1.085 + PhraseModel_2 = +1.48 + PhraseModel_3 = -0.03441 + PhraseModel_4 = -0.5739 + PhraseModel_5 = +0.1023 + PhraseModel_6 = -0.3455 + PassThrough = -0.3826 --- - 1best avg score: 0.13017 (+0.13017) - 1best avg model score: 14.53 - avg # pairs: 1968 - non-0 feature count: 12 + 1best avg score: 10.18 (+10.18) + 1best avg model score: +71.15 + avg # updates: 2121 + non-0 feature count: 2275 + avg f count: 150.8 avg list sz: 100 - avg f count: 11 -(time 0.33 min, 6 s/S) +(time 0.15 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.13017]. -This took 0.33333 min. +Best iteration: 1 [GOLD = 10.18]. +This took 0.15 min. diff --git a/training/dtrain/examples/parallelized/work/out.1.2 b/training/dtrain/examples/parallelized/work/out.1.2 index 8c4f8b03..f5fc817b 100644 --- a/training/dtrain/examples/parallelized/work/out.1.2 +++ b/training/dtrain/examples/parallelized/work/out.1.2 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.1.0.in' + input 'work/shard.1.0' output 'work/weights.1.2' weights in 'work/weights.1' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = +0.3277 + WordPenalty = +0.1759 + LanguageModel = +0.2799 + LanguageModel_OOV = -0.5643 + PhraseModel_0 = -0.7466 + PhraseModel_1 = +0.6823 + PhraseModel_2 = +1.309 + PhraseModel_3 = -0.3185 + PhraseModel_4 = -0.94 + PhraseModel_5 = +0.04098 + PhraseModel_6 = -0.412 + PassThrough = -0.587 --- - 1best avg score: 0.15478 (+0.15478) - 1best avg model score: -7.2154 - avg # pairs: 1776 - non-0 feature count: 12 + 1best avg score: 13.7 (+13.7) + 1best avg model score: +71.09 + avg # updates: 2223 + non-0 feature count: 2791 + avg f count: 152.8 avg list sz: 100 - avg f count: 11.327 -(time 0.27 min, 5 s/S) +(time 0.15 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.15478]. -This took 0.26667 min. +Best iteration: 1 [GOLD = 13.7]. +This took 0.15 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.0 b/training/dtrain/examples/parallelized/work/out.2.0 index 07c85963..2d27fdc6 100644 --- a/training/dtrain/examples/parallelized/work/out.2.0 +++ b/training/dtrain/examples/parallelized/work/out.2.0 @@ -2,42 +2,43 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.2.0.in' + input 'work/shard.2.0' output 'work/weights.2.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 = +0.0676 - PassThrough = -0.6343 + Glue = -0.0099 + WordPenalty = +0.5556 + LanguageModel = +3.129 + LanguageModel_OOV = +0.1064 + PhraseModel_0 = -0.5801 + PhraseModel_1 = -0.3003 + PhraseModel_2 = +0.1759 + PhraseModel_3 = -0.3496 + PhraseModel_4 = -2.562 + PhraseModel_5 = +0.0102 + PhraseModel_6 = -0.4384 + PassThrough = +0.0809 --- - 1best avg score: 0.072374 (+0.072374) - 1best avg model score: -27.384 - avg # pairs: 2582 - non-0 feature count: 11 + 1best avg score: 9.987 (+9.987) + 1best avg model score: -102.2 + avg # updates: 1862 + non-0 feature count: 850 + avg f count: 144.5 avg list sz: 100 - avg f count: 11.54 -(time 0.32 min, 6 s/S) +(time 0.2 min, 4 s/S) --- -Best iteration: 1 [GOLD = 0.072374]. -This took 0.31667 min. +Best iteration: 1 [GOLD = 9.987]. +This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.1 b/training/dtrain/examples/parallelized/work/out.2.1 index c54bb1b1..a6cef2b1 100644 --- a/training/dtrain/examples/parallelized/work/out.2.1 +++ b/training/dtrain/examples/parallelized/work/out.2.1 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.2.0.in' + input 'work/shard.2.0' output 'work/weights.2.1' weights in 'work/weights.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = -0.2622 + WordPenalty = +0.3185 + LanguageModel = +1.89 + LanguageModel_OOV = -0.6097 + PhraseModel_0 = +0.09434 + PhraseModel_1 = +0.2635 + PhraseModel_2 = +0.1182 + PhraseModel_3 = +1.151 + PhraseModel_4 = -0.7466 + PhraseModel_5 = +0.02055 + PhraseModel_6 = -0.3454 + PassThrough = -0.6294 --- - 1best avg score: 0.12881 (+0.12881) - 1best avg model score: -9.6731 - avg # pairs: 2020.3 - non-0 feature count: 12 + 1best avg score: 9.998 (+9.998) + 1best avg model score: -27.44 + avg # updates: 1910 + non-0 feature count: 2256 + avg f count: 148.7 avg list sz: 100 - avg f count: 12 -(time 0.32 min, 6 s/S) +(time 0.2 min, 4 s/S) --- -Best iteration: 1 [GOLD = 0.12881]. -This took 0.31667 min. +Best iteration: 1 [GOLD = 9.998]. +This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.2.2 b/training/dtrain/examples/parallelized/work/out.2.2 index f5d6229f..908e5214 100644 --- a/training/dtrain/examples/parallelized/work/out.2.2 +++ b/training/dtrain/examples/parallelized/work/out.2.2 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.2.0.in' + input 'work/shard.2.0' output 'work/weights.2.2' weights in 'work/weights.1' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .... 3 + ... 3 WEIGHTS - 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 + Glue = -0.1781 + WordPenalty = +0.262 + LanguageModel = +1.468 + LanguageModel_OOV = -0.4828 + PhraseModel_0 = -0.4867 + PhraseModel_1 = +0.3306 + PhraseModel_2 = +0.7159 + PhraseModel_3 = +0.01232 + PhraseModel_4 = -1.128 + PhraseModel_5 = +0.04098 + PhraseModel_6 = -0.3829 + PassThrough = -0.5045 --- - 1best avg score: 0.12788 (+0.12788) - 1best avg model score: 41.302 - avg # pairs: 2246.3 - non-0 feature count: 12 + 1best avg score: 16.34 (+16.34) + 1best avg model score: +12.6 + avg # updates: 1823 + non-0 feature count: 2883 + avg f count: 160 avg list sz: 100 - avg f count: 10.98 -(time 0.35 min, 7 s/S) +(time 0.2 min, 4 s/S) --- -Best iteration: 1 [GOLD = 0.12788]. -This took 0.35 min. +Best iteration: 1 [GOLD = 16.34]. +This took 0.2 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.0 b/training/dtrain/examples/parallelized/work/out.3.0 index fa499523..d2bad0b2 100644 --- a/training/dtrain/examples/parallelized/work/out.3.0 +++ b/training/dtrain/examples/parallelized/work/out.3.0 @@ -2,42 +2,43 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.3.0.in' + input 'work/shard.3.0' output 'work/weights.3.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .. 1 + . 1 WEIGHTS - 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 + Glue = -0.081 + WordPenalty = +0.383 + LanguageModel = +1.541 + LanguageModel_OOV = +0.045 + PhraseModel_0 = -0.36 + PhraseModel_1 = -0.4623 + PhraseModel_2 = -0.09999 + PhraseModel_3 = +0.07974 + PhraseModel_4 = -1.442 + PhraseModel_5 = +0.072 + PhraseModel_6 = +0.0898 + PassThrough = +0.009 --- - 1best avg score: 0.034204 (+0.034204) - 1best avg model score: 0 - avg # pairs: 1700 - non-0 feature count: 12 + 1best avg score: 3.357 (+3.357) + 1best avg model score: +0 + avg # updates: 1699 + non-0 feature count: 564 + avg f count: 206.7 avg list sz: 100 - avg f count: 10.8 -(time 0.1 min, 6 s/S) +(time 0.05 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.034204]. -This took 0.1 min. +Best iteration: 1 [GOLD = 3.357]. +This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.1 b/training/dtrain/examples/parallelized/work/out.3.1 index c4b3aa3c..3f8c45c4 100644 --- a/training/dtrain/examples/parallelized/work/out.3.1 +++ b/training/dtrain/examples/parallelized/work/out.3.1 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.3.0.in' + input 'work/shard.3.0' output 'work/weights.3.1' weights in 'work/weights.0' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .. 1 + . 1 WEIGHTS - 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 + Glue = -0.2588 + WordPenalty = +0.2907 + LanguageModel = +1.633 + LanguageModel_OOV = -0.0845 + PhraseModel_0 = -0.3393 + PhraseModel_1 = -0.02459 + PhraseModel_2 = +0.2491 + PhraseModel_3 = +0.07205 + PhraseModel_4 = -0.9481 + PhraseModel_5 = +0.02055 + PhraseModel_6 = -0.2971 + PassThrough = -0.3728 --- - 1best avg score: 0.084989 (+0.084989) - 1best avg model score: -52.323 - avg # pairs: 2487 - non-0 feature count: 12 + 1best avg score: 4.499 (+4.499) + 1best avg model score: -45.68 + avg # updates: 2016 + non-0 feature count: 2130 + avg f count: 175.9 avg list sz: 100 - avg f count: 12 -(time 0.1 min, 6 s/S) +(time 0.05 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.084989]. -This took 0.1 min. +Best iteration: 1 [GOLD = 4.499]. +This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/out.3.2 b/training/dtrain/examples/parallelized/work/out.3.2 index eb27dac2..d616560d 100644 --- a/training/dtrain/examples/parallelized/work/out.3.2 +++ b/training/dtrain/examples/parallelized/work/out.3.2 @@ -2,43 +2,44 @@ 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 **************************************************************************************************** + Example feature: Shape_S00000_T00000 dtrain Parameters: k 100 N 4 T 1 learning rate 0.0001 - error margin 1 + margin 1 l1 reg 0 decoder conf 'cdec.ini' - input 'work/shard.3.0.in' + input 'work/shard.3.0' output 'work/weights.3.2' weights in 'work/weights.1' -(a dot per input) +(1 dot per processed input) Iteration #1 of 1. - .. 1 + . 1 WEIGHTS - 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 + Glue = +0.2167 + WordPenalty = +0.2738 + LanguageModel = +0.813 + LanguageModel_OOV = -0.6426 + PhraseModel_0 = -0.5211 + PhraseModel_1 = +0.4933 + PhraseModel_2 = +0.9179 + PhraseModel_3 = +0.5142 + PhraseModel_4 = -0.8559 + PhraseModel_5 = +0.03138 + PhraseModel_6 = -0.4129 + PassThrough = -0.6653 --- - 1best avg score: 0.12674 (+0.12674) - 1best avg model score: -7.2878 - avg # pairs: 1769 - non-0 feature count: 12 + 1best avg score: 21.4 (+21.4) + 1best avg model score: +8.744 + avg # updates: 2287 + non-0 feature count: 2743 + avg f count: 174.8 avg list sz: 100 - avg f count: 12 -(time 0.1 min, 6 s/S) +(time 0.05 min, 3 s/S) --- -Best iteration: 1 [GOLD = 0.12674]. -This took 0.1 min. +Best iteration: 1 [GOLD = 21.4]. +This took 0.05 min. diff --git a/training/dtrain/examples/parallelized/work/shard.0.0.in b/training/dtrain/examples/parallelized/work/shard.0.0 index a0ef6f54..a0ef6f54 100644 --- a/training/dtrain/examples/parallelized/work/shard.0.0.in +++ b/training/dtrain/examples/parallelized/work/shard.0.0 diff --git a/training/dtrain/examples/parallelized/work/shard.1.0.in b/training/dtrain/examples/parallelized/work/shard.1.0 index 05f0273b..05f0273b 100644 --- a/training/dtrain/examples/parallelized/work/shard.1.0.in +++ b/training/dtrain/examples/parallelized/work/shard.1.0 diff --git a/training/dtrain/examples/parallelized/work/shard.2.0.in b/training/dtrain/examples/parallelized/work/shard.2.0 index 0528d357..0528d357 100644 --- a/training/dtrain/examples/parallelized/work/shard.2.0.in +++ b/training/dtrain/examples/parallelized/work/shard.2.0 diff --git a/training/dtrain/examples/parallelized/work/shard.3.0.in b/training/dtrain/examples/parallelized/work/shard.3.0 index f7cbb3e3..f7cbb3e3 100644 --- a/training/dtrain/examples/parallelized/work/shard.3.0.in +++ b/training/dtrain/examples/parallelized/work/shard.3.0 diff --git a/training/dtrain/examples/parallelized/work/weights.0 b/training/dtrain/examples/parallelized/work/weights.0 index 816269cd..560bab86 100644 --- a/training/dtrain/examples/parallelized/work/weights.0 +++ b/training/dtrain/examples/parallelized/work/weights.0 @@ -1,12 +1,2072 @@ -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 +LanguageModel 1.0461718569464984 +PhraseModel_4 -0.9877757214580491 +PhraseModel_1 -0.27641632310025577 +PhraseModel_0 -0.5640090252696333 +PhraseModel_2 0.20626506994462934 +PhraseModel_3 -0.38409074694928547 +PhraseModel_6 -0.31797499999999995 +WordPenalty 0.1940427745143702 +RBT:X1_</r> -0.16625 +RBS:<r>_X -0.14205 +RBT:X2_</r> 0.08432500000000001 +Shape_S10000_T10000 -0.0010500000000000023 +RBS:X_</r> -0.010700000000000005 +RBT:<r>_X1 0.041625000000000016 +R:S:NS_NX:N1_N2 0.093975 +RBT:S1_X2 0.093975 +RBT:<r>_S1 0.093975 +RBS:<r>_S 0.093975 +RBS:S_X 0.093975 +Glue 0.093975 +Shape_S01010_T01010 0.093975 +Shape_S11000_T11000 -0.06510000000000002 +LanguageModel_OOV 0.0026000000000000103 +PassThrough -0.04902499999999999 +Shape_S01110_T01110 0.032375 +RBT:a_X1 -0.070925 +Shape_S01110_T11110 -0.07705 +RBT:<r>_X2 -0.040150000000000005 +RBT:X1_, 0.057374999999999995 +Shape_S01100_T01100 -0.03432500000000001 +Shape_S01111_T01111 0.015300000000000001 +RBT:the_X2 0.0363 +RBT:X1_X2 -0.035675000000000005 +RBT:,_</r> -0.0070250000000000035 +Shape_S01110_T01111 -0.008275000000000001 +Shape_S11000_T01100 0.03605 +RBT:<r>_be -0.059675000000000006 +RBS:die_</r> -0.06317500000000001 +RBT:be_</r> -0.016925000000000003 +RBT:in_the 0.04882500000000001 +RBT:which_is -0.0463 +RBT:intended_X2 -0.0463 +RBT:ensure_X1 -0.0463 +RBT:X2_ensure -0.0463 +R:X:NX_dem_NX:which_is_intended_N2_ensure_N1 -0.0463 +RBT:is_intended -0.0463 +RBT:._</r> -0.0338 +RBT:<r>_have 0.04765 +RBT:demands_X1 -0.016874999999999998 +RBT:made_demands -0.016874999999999998 +R:X:nicht_NX:not_made_demands_N1 -0.016874999999999998 +RBT:not_made -0.016874999999999998 +RBT:jean_@-@ 0.045000000000000005 +RBT:X2_, 0.0427 +RBT:into_</r> -0.0444 +RBT:being_attracted -0.0444 +R:X:NX_dem_NX_in:N1_make_its_choices_count_in_the_N2_,_within 0.0444 +RBT:make_its 0.0444 +RBT:its_choices 0.0444 +RBT:within_</r> 0.0444 +RBT:attracted_into -0.0444 +RBT:X1_being -0.0444 +RBT:X1_make 0.0444 +RBT:choices_count 0.0444 +R:X:NX_in:N1_being_attracted_into -0.0444 +RBT:count_in 0.0444 +RBT:,_within 0.0444 +RBS:X_wie -0.043750000000000004 +RBT:is_</r> -0.04505000000000001 +RBT:history_</r> -0.041675000000000004 +R:X:wird:be -0.041675000000000004 +R:X:das:what -0.041675000000000004 +RBT:for_example -0.041675000000000004 +RBT:what_</r> -0.041675000000000004 +R:X:NX_wie_die:N1_for_example_the -0.041675000000000004 +RBT:for_a -0.041675000000000004 +R:X:NX_geschichte_NX:N2_for_a_N1_history -0.041675000000000004 +RBT:example_the -0.041675000000000004 +RBT:X1_history -0.041675000000000004 +RBT:<r>_what -0.041675000000000004 +R:X:aber:is -0.041675000000000004 +RBT:X2_for -0.041675000000000004 +RBS:X_geschichte -0.041325 +RBT:the_united -0.041325 +RBT:<r>_is -0.044125000000000004 +RBT:gone_ahead 0.0409 +RBT:in_connection -0.0409 +RBT:have_gone 0.0409 +RBT:experience_in -0.0409 +RBT:ahead_X1 0.0409 +R:X:NX_haben:have_gone_ahead_N1 0.0409 +RBT:<r>_experience -0.0409 +RBT:connection_X1 -0.0409 +R:X:NX_haben:experience_in_connection_N1 -0.0409 +RBS:die_X 0.055975000000000004 +RBT:X1_for -0.040625 +RBT:<r>_it 0.0374 +RBT:<r>_, -0.011199999999999998 +RBT:the_</r> -0.051675 +RBT:united_states -0.031950000000000006 +RBT:when_</r> -0.039025 +RBS:aber_</r> -0.037450000000000004 +RBT:and_</r> 0.066825 +RBT:,_X2 -0.015875 +RBT:<r>_history 0.035325 +RBS:wird_</r> -0.027875000000000004 +RBT:<r>_the -0.05772500000000001 +RBT:X1_will 0.010274999999999996 +RBT:<r>_not -0.008274999999999998 +RBS:wird_X 0.011525 +RBT:for_</r> -0.003599999999999999 +RBS:<r>_geschichte 0.034125 +R:X:.:, -0.036275 +RBT:<r>_for -0.03185 +RBT:people_X1 0.035824999999999996 +R:X:und:and 0.0446 +RBS:,_wie 0.0315 +RBT:<r>_people 0.033575 +R:X:es_NX:people_N1 0.031325 +RBS:<r>_wird -0.039725 +RBT:,_and 0.029875000000000002 +R:X:,_wie_die_NX:N1_,_and 0.03045 +RBT:of_</r> 0.030275000000000003 +RBT:<r>_. 0.002450000000000001 +RBS:deutlich_</r> 0.0361 +R:X:für:of 0.030100000000000002 +R:X:für:for -0.030100000000000002 +RBS:X_, 0.018100000000000005 +RBT::_</r> 0.022500000000000003 +R:X:.:: 0.022500000000000003 +RBT:<r>_: 0.022500000000000003 +RBT:if_</r> 0.029950000000000004 +RBT:<r>_but -0.024525 +RBT:but_X1 -0.026625000000000003 +RBT:of_a -0.027000000000000003 +RBT:<r>_when -0.029150000000000002 +R:X:in:to -0.02925 +RBT:states_X2 -0.02925 +R:X:NX_amerika_NX_.:N1_the_united_states_N2_. -0.02925 +RBT:<r>_racist -0.02925 +R:X:rassismus_NX:racist_action_N1 -0.02925 +R:X:in:when -0.02925 +R:X:des_NX:of_a_N1 -0.02925 +RBT:will_soon 0.02925 +RBT:racist_action -0.02925 +RBT:action_X1 -0.02925 +RBT:<r>_do 0.041275000000000006 +RBS:-_X -0.029175000000000003 +RBT:<r>_europe 0.0292 +R:X:es_NX:there_is_,_N1 -0.028900000000000002 +RBT:there_is -0.028900000000000002 +RBT:is_, -0.028900000000000002 +RBT:not_X2 -0.004475 +RBT:<r>_eu 0.0045000000000000005 +RBT:eu_</r> 0.0045000000000000005 +RBT:history_project 0.028650000000000002 +RBT:project_X1 0.028650000000000002 +R:X:geschichte_NX:history_project_N1 0.028650000000000002 +RBT:X2_. -0.028625 +RBT:health_</r> 0.028475 +RBT:<r>_health 0.028475 +R:X:das:health 0.028475 +RBT:<r>_that -0.0323 +RBT:<r>_there -0.033800000000000004 +RBT:<r>_of -0.02105 +RBT:X1_the -0.040825 +RBS:und_</r> -0.00030000000000000165 +RBT:will_</r> 0.016724999999999997 +RBS:und_X -0.001075000000000003 +RBT:to_</r> -0.03025 +RBS:aber_wird 0.027075000000000002 +RBS:geteiltes_X 0.02705 +RBS:geteiltes_</r> -0.02705 +RBS:X_haus -0.02705 +RBS:<r>_haus 0.02705 +RBT:racism_</r> 0.028625000000000005 +RBT:X1_of 0.008625000000000002 +RBT:,_X1 -0.033800000000000004 +R:X:NX_amerika_NX:americans_N1_N2 0.0262 +RBT:<r>_americans 0.0262 +RBT:americans_X1 0.0262 +RBT:<r>_nord 0.0261 +RBT:nord_</r> 0.0261 +R:X:lega:lega 0.0261 +RBT:<r>_northern -0.0261 +RBT:northern_</r> -0.0261 +R:X:nord:northern -0.0261 +R:X:lega_NX:N1_league -0.0261 +RBT:X1_league -0.0261 +RBS:lega_X -0.0261 +RBT:league_</r> -0.0261 +RBT:lega_</r> 0.0261 +RBT:<r>_lega 0.0261 +RBS:lega_</r> 0.0261 +R:X:nord:nord 0.0261 +RBT:<r>_those 0.030100000000000002 +R:X:aber_wird_NX:,_N1_will 0.026025 +Shape_S11000_T11100 0.026025 +R:X:NX_.:N1_, 0.026025 +RBT:those_countries 0.0257 +RBT:countries_</r> 0.0257 +R:X:ländern:those_countries 0.0257 +R:X:rassismus_NX:N1_racism 0.025675 +R:X:in:it 0.025675 +RBT:X1_racism 0.025675 +Shape_S01110_T11010 -0.005425000000000003 +RBT:<r>_racial 0.03425 +RBT:it_</r> 0.03215 +Shape_S01100_T11000 -0.03445 +RBT:<r>_and 0.023174999999999998 +RBT:<r>_soon -0.02475 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+RBT:about_</r> 0.023800000000000002 +RBT:on_</r> 0.0035000000000000001 +RBT:<r>_under -0.021500000000000002 +RBT:<r>_follow -0.0044000000000000003 +RBT:<r>_in -0.0022000000000000001 +R:X:nach:,_on 0.0035000000000000001 +RBT:<r>_, 0.0026999999999999993 +RBT:,_on 0.0035000000000000001 +RBT:<r>_with 0.037600000000000001 +RBT:<r>_as 0.086300000000000002 +RBT:<r>_wake -0.0044000000000000003 +RBT:<r>_to -0.0134 +RBT:as_</r> 0.086199999999999999 +RBT:<r>_when 0.00040000000000000002 +R:X:nach_NX:wake_of_N1 -0.0044000000000000003 +RBS:nach_X -0.0094000000000000004 +RBT:wake_of -0.0044000000000000003 +R:X:nach_NX:follow_N1 -0.0044000000000000003 +RBT:follow_X1 -0.0044000000000000003 +R:X:nach_NX:about_N1 -0.0109 +RBT:about_X1 -0.0109 +R:X:nach_NX:call_N1 -0.0058000000000000005 +RBT:call_X1 -0.0058000000000000005 +RBT:that_X1 -0.0079000000000000008 +R:X:nach_NX:with_N1 0.037600000000000001 +RBT:with_X1 0.037600000000000001 +RBT:and_X1 0.0025000000000000001 +R:X:nach_NX:under_N1 -0.021500000000000002 +RBT:under_X1 -0.021500000000000002 +RBT:X1_that 0.010700000000000001 +RBT:,_</r> -0.0087000000000000011 +RBT:X1_as 0.00040000000000000002 +R:S:NS_NX:N1_N2 0.19840000000000002 +RBS:<r>_S 0.19840000000000002 +RBS:S_X 0.19840000000000002 +RBT:<r>_S1 0.19840000000000002 +RBT:S1_X2 0.19840000000000002 +RBT:<r>_is -0.013000000000000001 +RBT:is_</r> -0.013000000000000001 +R:X:ein:a 0.046600000000000003 +RBT:<r>_this 0.00040000000000000002 +RBT:this_</r> 0.00020000000000000001 +RBT:<r>_it 0.0114 +RBT:it_</r> 0.0114 +R:X:ein:ein -0.046600000000000003 +RBT:<r>_ein -0.046600000000000003 +RBT:ein_</r> -0.046600000000000003 +RBT:<r>_are -0.00060000000000000006 +RBT:are_</r> -0.00060000000000000006 +RBT:<r>_will -0.0012000000000000001 +RBT:will_</r> -0.0012000000000000001 +RBT:when_</r> 0.00040000000000000002 +RBT:X2_, -0.0079000000000000008 +RBT:as_X2 0.00050000000000000001 +RBT:<r>_political 0.045700000000000005 +RBT:this_X1 0.00020000000000000001 +RBT:X1_than 0.00020000000000000001 +R:X:politischen:political 0.045700000000000005 +RBT:political_</r> 0.045700000000000005 +R:X:politischen:politischen -0.045700000000000005 +RBT:<r>_politischen -0.045700000000000005 +RBT:politischen_</r> -0.045700000000000005 +R:X:als:and 0.0016000000000000001 +RBS:<r>_als 0.048000000000000001 +RBS:als_</r> 0.039199999999999999 +R:X:als:when 0.00040000000000000002 +R:X:als:than -0.040600000000000004 +RBT:<r>_than -0.040600000000000004 +RBT:than_</r> -0.049200000000000001 +R:X:als:a 0.00020000000000000001 +R:X:als:the 0.00020000000000000001 +R:X:als:as 0.086000000000000007 +RBT:<r>_itself -0.00020000000000000001 +RBS:als_X -0.039199999999999999 +R:X:als_NX:N1_as 0.00020000000000000001 +RBS:X_als -0.048000000000000001 +R:X:NX_als_NX:N1_as_N2 0.00020000000000000001 +R:X:NX_als_NX:as_N2_N1 0.00030000000000000003 +R:X:NX_als_NX:N1_than_N2 0.00020000000000000001 +RBT:than_X2 0.00020000000000000001 +RBS:<r>_das -0.035300000000000005 +RBS:das_</r> 0.035400000000000001 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0.00020000000000000001 +R:X:daß:daß -0.030300000000000001 +RBT:<r>_daß -0.030300000000000001 +RBT:daß_</r> -0.030300000000000001 +RBS:daß_X 0.0026000000000000003 +RBS:daß_sie 0.00020000000000000001 +RBS:X_sie 0.0012000000000000001 +R:X:NX_sie_das_NX:N1_the_N2 0.0012000000000000001 +RBS:<r>_, 0.0036000000000000003 +RBS:,_</r> -0.023700000000000002 +R:X:,:, -0.015800000000000002 +RBT:<r>_fact 0.0287 +RBT:fact_</r> 0.037200000000000004 +RBS:,_X -0.0064000000000000003 +RBT:fact_X1 -0.0083000000000000001 +RBS:,_daß 0.030100000000000002 +R:X:,_daß:that 0.027300000000000001 +R:X:,_daß_sie_NX:that_N1 0.00020000000000000001 +R:X:,_daß_NX_das_NX:that_N1_N2 -0.0083000000000000001 +R:X:,_daß_NX_als_NX:that_N1_N2 0.00020000000000000001 +RBS:<r>_tatsache -0.00020000000000000001 +RBS:tatsache_</r> 0.0080999999999999996 +R:X:tatsache:fact 0.037000000000000005 +R:X:tatsache:tatsache -0.028900000000000002 +RBT:<r>_tatsache -0.028900000000000002 +RBT:tatsache_</r> -0.028900000000000002 +RBS:tatsache_X -0.0080999999999999996 +RBS:X_, -0.0036000000000000003 +RBT:X1_fact 0.00020000000000000001 +R:X:NX_,_daß_NX:N1_that_N2 0.010700000000000001 +R:X:tatsache_NX_als_NX:fact_N1_N2 -0.0083000000000000001 +RBS:<r>_die 0.0055999999999999999 +RBS:die_</r> 0.0026000000000000003 +R:X:die:the 0.0060000000000000001 +R:X:die:which -0.0034000000000000002 +RBS:die_X -0.0026000000000000003 +RBS:X_tatsache 0.00020000000000000001 +R:X:NX_tatsache_NX:N2_N1_fact 0.00020000000000000001 +R:X:die_NX_,_NX:the_N1_N2 -0.0077000000000000002 +R:X:die_NX_das_NX:the_N1_N2 0.010700000000000001 +RBS:und_</r> -0.0025000000000000001 +R:X:und:and 0.088400000000000006 +R:X:und:und -0.090900000000000009 +RBT:<r>_und -0.090900000000000009 +RBT:und_</r> -0.090900000000000009 +RBS:und_X 0.00020000000000000001 +R:X:und_NX:and_N1 0.00020000000000000001 +RBS:und_die 0.0023 +RBS:X_die -0.0079000000000000008 +R:X:und_die_NX:and_N1 0.001 +R:X:NX_die_NX_,:N1_N2_, -0.0079000000000000008 +R:X:und_die_NX_,_NX:and_N1_N2 0.0013000000000000002 +R:X:rassismus:racism 0.0090000000000000011 +R:X:rassismus:rassismus -0.0090000000000000011 +RBT:<r>_rassismus -0.0090000000000000011 +RBT:rassismus_</r> -0.0090000000000000011 +R:X:block:bloc -0.0038 +RBT:<r>_bloc -0.0038 +RBT:bloc_</r> -0.0038 +R:X:block:block 0.0038 +RBT:<r>_block 0.0038 +RBT:block_</r> 0.0038 +R:X:vlaams:flemish -0.0014 +RBT:<r>_flemish -0.0014 +RBT:flemish_</r> -0.0014 +R:X:vlaams:vlaams 0.0014 +RBT:<r>_vlaams 0.0014 +RBT:vlaams_</r> 0.0014 +R:X:nord:northern -0.10440000000000001 +RBT:<r>_northern -0.10440000000000001 +RBT:northern_</r> -0.10440000000000001 +R:X:nord:nord 0.10440000000000001 +RBT:<r>_nord 0.10440000000000001 +RBT:nord_</r> 0.10440000000000001 +R:X:lega:lega 0.10440000000000001 +RBS:lega_</r> 0.10440000000000001 +RBT:<r>_lega 0.10440000000000001 +RBT:lega_</r> 0.10440000000000001 +RBT:league_</r> -0.10440000000000001 +RBS:lega_X -0.10440000000000001 +RBT:X1_league -0.10440000000000001 +R:X:lega_NX:N1_league -0.10440000000000001 +RBT:supporters_</r> 0.0096000000000000009 +R:X:anhänger:followers -0.0096000000000000009 +RBT:<r>_followers -0.0096000000000000009 +RBT:followers_</r> -0.0096000000000000009 +R:X:anhänger:supporters 0.0096000000000000009 +RBT:<r>_supporters 0.0096000000000000009 +R:X:um:in -0.0022000000000000001 +R:X:um:for 0.016 +R:X:um:about -0.00040000000000000002 +R:X:um:to -0.0134 +R:X:sich:is -0.013000000000000001 +R:X:sich:, 0.015000000000000001 +R:X:sich:will -0.0012000000000000001 +R:X:sich:are -0.00060000000000000006 +R:X:sich:itself -0.00020000000000000001 +R:X:für:of 0.12040000000000001 +R:X:für:for -0.12040000000000001 +RBS:gebildet_</r> -0.00060000000000000006 +R:X:gebildet:formed -0.00060000000000000006 +RBT:<r>_formed -0.00060000000000000006 +RBS:gebildet_X 0.00060000000000000006 +R:X:gebildet_NX:N1_formed 0.00060000000000000006 +RBT:X1_formed 0.00060000000000000006 diff --git a/training/dtrain/examples/parallelized/work/weights.0.1 b/training/dtrain/examples/parallelized/work/weights.0.1 index d4c77d07..d78646b3 100644 --- a/training/dtrain/examples/parallelized/work/weights.0.1 +++ b/training/dtrain/examples/parallelized/work/weights.0.1 @@ -1,12 +1,2218 @@ -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 +WordPenalty 0.16742052277370129 +LanguageModel 0.54482869365140818 +LanguageModel_OOV -0.63109999999999999 +Shape_S10000_T10000 -0.01415000000000001 +Shape_S11000_T11000 -0.06150000000000002 +Shape_S11000_T01100 0.0046500000000000014 +Shape_S11000_T11100 0.026025 +Shape_S01100_T11000 -0.035250000000000004 +Shape_S01100_T01100 -0.025325000000000007 +Shape_S01100_T11100 -0.0045000000000000005 +Shape_S11100_T11100 0.013775000000000003 +Shape_S01010_T01010 0.084175 +Shape_S01110_T11010 -0.008825000000000003 +Shape_S01110_T01110 0.032375000000000001 +Shape_S01110_T11110 -0.077049999999999993 +Shape_S01110_T01011 -0.016924999999999999 +Shape_S01110_T01111 -0.0082750000000000011 +Shape_S11110_T11010 -0.010574999999999999 +Shape_S11110_T01110 -0.013950000000000001 +Shape_S11110_T11110 -0.0017249999999999991 +Shape_S01111_T01011 -0.0086750000000000004 +Shape_S01111_T01111 0.015300000000000001 +PhraseModel_0 -0.29310472504848095 +PhraseModel_1 1.1730255793479065 +PhraseModel_2 1.3691400218388254 +PhraseModel_3 0.18192573135943255 +PhraseModel_4 -0.84388912484694545 +PhraseModel_5 0.020550000000000002 +PhraseModel_6 -0.37937499999999996 +Glue 0.084175 +RBT:X1_</r> -0.16685 +RBS:<r>_X -0.13714999999999999 +RBT:X2_</r> 0.074525000000000008 +RBS:X_</r> -0.051600000000000007 +RBT:<r>_X1 0.019225000000000034 +R:S:NS_NX:N1_N2 0.084175 +RBT:S1_X2 0.084175 +RBT:<r>_S1 0.084175 +RBS:<r>_S 0.084175 +RBS:S_X 0.084175 +PassThrough -0.68272500000000003 +RBT:a_X1 -0.070925000000000002 +RBT:<r>_X2 -0.040050000000000002 +RBT:X1_, 0.057374999999999995 +RBT:the_X2 0.036299999999999999 +RBT:X1_X2 -0.035675000000000005 +RBT:,_</r> 0.0016749999999999977 +RBT:<r>_be -0.059675000000000006 +RBS:die_</r> -0.063175000000000009 +RBT:be_</r> -0.016925000000000003 +RBT:in_the 0.048825000000000007 +RBT:which_is -0.046300000000000001 +RBT:intended_X2 -0.046300000000000001 +RBT:ensure_X1 -0.046300000000000001 +RBT:X2_ensure -0.046300000000000001 +R:X:NX_dem_NX:which_is_intended_N2_ensure_N1 -0.046300000000000001 +RBT:is_intended -0.046300000000000001 +RBT:._</r> -0.033799999999999997 +RBT:<r>_have 0.05425 +RBT:demands_X1 -0.016874999999999998 +RBT:made_demands -0.016874999999999998 +R:X:nicht_NX:not_made_demands_N1 -0.016874999999999998 +RBT:not_made -0.016874999999999998 +RBT:jean_@-@ 0.045000000000000005 +RBT:X2_, 0.042700000000000002 +RBT:into_</r> -0.047699999999999999 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0.035325000000000002 +RBS:wird_</r> -0.027875000000000004 +RBT:<r>_the -0.10732500000000002 +RBT:X1_will 0.010274999999999996 +RBT:<r>_not -0.0082749999999999976 +RBS:wird_X 0.011525000000000001 +RBT:for_</r> -0.10299999999999999 +RBS:<r>_geschichte 0.034125000000000003 +R:X:.:, -0.036275000000000002 +RBT:<r>_for -0.13125000000000001 +RBT:people_X1 0.035824999999999996 +R:X:und:and 0.044600000000000001 +RBS:,_wie 0.0315 +RBT:<r>_people 0.033575000000000001 +R:X:es_NX:people_N1 0.031324999999999999 +RBS:<r>_wird -0.039725000000000003 +RBT:,_and 0.029875000000000002 +R:X:,_wie_die_NX:N1_,_and 0.030450000000000001 +RBT:of_</r> 0.238375 +RBT:<r>_. 0.0024500000000000008 +RBS:deutlich_</r> 0.0361 +R:X:für:of 0.1376 +R:X:für:for -0.1376 +RBS:X_, 0.018100000000000005 +RBT::_</r> 0.022500000000000003 +R:X:.:: 0.022500000000000003 +RBT:<r>_: 0.022500000000000003 +RBT:if_</r> 0.027350000000000003 +RBT:<r>_but -0.024525000000000002 +RBT:but_X1 -0.026625000000000003 +RBT:of_a -0.027000000000000003 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+RBS:das_gemeinsame 0.00020000000000000001 +R:X:um_NX:to_N1 0.00060000000000000006 +R:X:um_NX:for_N1 0.00080000000000000004 +R:X:um_NX:by_N1 0.0022000000000000001 +R:X:NX_das_gemeinsame_NX:N1_the_N2 0.00020000000000000001 +RBS:<r>_sich 0.027200000000000002 +RBS:sich_</r> -0.017000000000000001 +RBS:sich_um 0.017000000000000001 +R:X:sich_um_NX:is_N1 0.018000000000000002 +R:X:NX_um_NX:by_N2_N1 0.0091999999999999998 +RBS:X_sich -0.027200000000000002 +R:X:NX_sich:N1_, -0.026200000000000001 +R:X:NX_sich_um:N1_is -0.001 +RBS:<r>_bewegungen 0.0090000000000000011 +R:X:bewegungen:movements 0.0090000000000000011 +RBT:<r>_movements 0.0090000000000000011 +RBT:X1_movements -0.0090000000000000011 +RBS:<r>_oder -0.076999999999999999 +R:X:oder:or -0.076999999999999999 +RBS:X_bewegungen -0.0090000000000000011 +R:X:NX_bewegungen:N1_movements -0.0090000000000000011 +RBS:parteien_</r> 0.076999999999999999 +RBS:X_oder 0.076999999999999999 +R:X:NX_oder:N1_or 0.076999999999999999 +R:X:NX_parteien:N1_parties 0.076999999999999999 +R:X:NX_parteien_NX:N2_N1_parties -0.076999999999999999 +R:X:NX_für:N1_of 0.0066 +R:X:NX_für:N1_for -0.0066 +RBT:formed_X1 -0.0064000000000000003 +RBS:<r>_regeln 0.0132 +RBT:<r>_rules 0.0132 +R:X:regeln:rules 0.0132 +R:X:NX_regeln:N1_rules -0.0132 +RBS:X_regeln -0.0132 +R:X:NX_zu_NX:to_N2_N1 0.0132 +RBS:politik_X 0.00060000000000000006 +R:X:NX_politik:N1_policy -0.00060000000000000006 +R:X:NX_politik_NX:N1_policy_N2 0.00060000000000000006 +RBT:<r>_established 0.0032000000000000002 +RBT:<r>_created 0.0028 +RBS:X_haben -0.0094000000000000004 +R:X:NX_haben:N1_, -0.0097999999999999997 +R:X:NX_haben:have_N1 0.00040000000000000002 +R:X:NX_gebildet:created_N1 0.0028 +R:X:NX_gebildet:formed_N1 -0.015800000000000002 +R:X:NX_gebildet:up_N1 0.00040000000000000002 +R:X:NX_gebildet:established_N1 0.0032000000000000002 +R:X:NX_gebildet_NX:N2_formed_N1 0.0094000000000000004 diff --git a/training/dtrain/examples/parallelized/work/weights.1 b/training/dtrain/examples/parallelized/work/weights.1 index 2a00be2e..270dbb59 100644 --- a/training/dtrain/examples/parallelized/work/weights.1 +++ b/training/dtrain/examples/parallelized/work/weights.1 @@ -1,12 +1,2641 @@ -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 +LanguageModel 1.1008595900906253 +PhraseModel_2 0.804224437304719 +PhraseModel_1 0.6242269758630035 +PhraseModel_4 -0.7781209969878504 +PhraseModel_3 0.34257722211028796 +LanguageModel_OOV -0.494175 +PassThrough -0.5169 +PhraseModel_6 -0.341825 +PhraseModel_0 -0.2564652741416422 +Shape_S01010_T01010 0.007300000000000015 +RBT:S1_X2 0.007300000000000015 +R:S:NS_NX:N1_N2 0.007300000000000015 +RBT:<r>_S1 0.007300000000000015 +RBS:<r>_S 0.007300000000000015 +Glue 0.007300000000000015 +RBS:S_X 0.007300000000000015 +Shape_S10000_T10000 -0.11412499999999999 +RBS:X_</r> -0.08339999999999999 +RBT:X2_</r> 0.007075000000000033 +WordPenalty 0.21258714889163938 +RBT:X1_</r> -0.1372 +RBS:<r>_X -0.12465 +RBT:of_</r> 0.1007 +RBT:<r>_against 0.0555 +RBT:against_</r> 0.0555 +R:X:zuwider:against 0.0555 +RBT:<r>_of 0.04062500000000001 +RBT:<r>_the -0.08017500000000002 +RBT:the_</r> -0.076675 +RBT:<r>_and 0.072 +RBT:X1_X2 -0.06735000000000001 +RBT:countries_</r> 0.059075 +RBT:and_</r> 0.079425 +RBT:as_</r> 0.04820000000000001 +RBT:und_</r> -0.06052500000000001 +R:X:und:und -0.06052500000000001 +RBT:<r>_und -0.06052500000000001 +RBT:<r>_europe 0.059500000000000004 +RBT:,_X1 -0.0626 +Shape_S01110_T11110 -0.07705 +RBS:die_</r> -0.06860000000000001 +R:X:für:for -0.05697500000000001 +R:X:für:of 0.05697500000000001 +RBT:europe_</r> 0.052425000000000006 +RBT:ländern_</r> -0.04187500000000001 +RBT:<r>_ländern -0.04187500000000001 +R:X:ländern:ländern -0.04187500000000001 +RBT:<r>_for -0.0567 +RBT:<r>_X1 0.04132500000000002 +RBT:a_X1 -0.070925 +RBT:X1_, 0.0664 +RBT:zuwider_</r> -0.0335 +R:X:zuwider:zuwider -0.0335 +RBT:<r>_zuwider -0.0335 +R:X:ländern:countries 0.033375 +RBT:<r>_countries 0.033375 +Shape_S01100_T01100 0.005574999999999993 +R:X:und:and 0.060325000000000004 +RBT:<r>_europas -0.031525000000000004 +RBT:europas_</r> -0.031525000000000004 +R:X:europas:europas -0.031525000000000004 +RBT:<r>_as 0.044675000000000006 +RBT:<r>_us 0.042575 +Shape_S01111_T01011 -0.04895 +RBS:,_</r> -0.05367500000000001 +Shape_S11000_T11000 -0.05635000000000002 +RBT:<r>_be -0.059800000000000006 +R:X:europas:europe 0.04055 +RBT:<r>_marie 0.044475 +R:X:marie:marie 0.044475 +RBT:marie_</r> 0.044475 +RBT:<r>_even -0.039525000000000005 +Shape_S01100_T11000 -0.035225 +RBT:,_</r> 0.02045 +R:X:europäischen:europäischen -0.039575 +RBT:<r>_europäischen -0.039575 +RBT:europäischen_</r> -0.039575 +RBT:'s_</r> 0.037725 +RBT:racism_</r> 0.046625000000000014 +PhraseModel_5 0.040975000000000004 +RBS:nicht_</r> -0.031225000000000003 +RBT:for_</r> -0.028449999999999996 +RBT:in_</r> -0.031700000000000006 +R:X:wie:as 0.025625000000000002 +RBT:usa_</r> -0.02645 +R:X:usa:usa -0.02645 +RBT:<r>_usa -0.02645 +RBS:zu_</r> 0.004425 +R:X:zu:to 0.004425 +RBS:noch_wichtiger 0.027274999999999997 +RBS:<r>_wichtiger -0.027274999999999997 +R:X:noch_wichtiger:more 0.027274999999999997 +RBS:<r>_sogar -0.027174999999999998 +RBS:nicht_sogar 0.027174999999999998 +RBS:<r>_zu 0.004024999999999999 +RBT:<r>_lega 0.04190000000000001 +RBT:nord_</r> 0.04190000000000001 +RBT:<r>_nord 0.04190000000000001 +R:X:nord:nord 0.04190000000000001 +RBS:lega_</r> 0.04190000000000001 +R:X:lega:lega 0.04190000000000001 +RBT:lega_</r> 0.04190000000000001 +RBT:<r>_northern -0.04190000000000001 +RBS:lega_X -0.04190000000000001 +RBT:X1_league -0.04190000000000001 +R:X:lega_NX:N1_league -0.04190000000000001 +R:X:nord:northern -0.04190000000000001 +RBT:northern_</r> -0.04190000000000001 +RBT:league_</r> -0.04190000000000001 +RBT:-_</r> -0.031825 +RBS:X_zu -0.0036749999999999994 +RBT:<r>_have 0.049249999999999995 +RBT:even_</r> -0.024475 +R:X:nicht_sogar:not 0.024475 +RBT:in_the 0.04882500000000001 +RBS:in_</r> -0.03345 +R:X:europäischen:european 0.02415 +RBS:noch_</r> -0.0231 +RBS:<r>_in -0.03515 +RBT:is_</r> -0.047200000000000006 +RBT:us_X1 0.035074999999999995 +RBS:X_in 0.032900000000000006 +RBT:<r>_history 0.0439 +RBT:is_intended -0.0463 +RBT:intended_X2 -0.0463 +RBT:ensure_X1 -0.0463 +RBT:X2_ensure -0.0463 +RBT:which_is -0.0463 +R:X:NX_dem_NX:which_is_intended_N2_ensure_N1 -0.0463 +RBS:und_</r> -0.027324999999999995 +RBT:<r>_more 0.02505 +RBS:<r>_noch 0.02505 +RBT:more_</r> 0.02505 +RBT:wichtiger_</r> -0.02505 +R:X:wichtiger:wichtiger -0.02505 +RBT:<r>_wichtiger -0.02505 +RBT:<r>_european 0.016024999999999998 +RBT:wie_</r> -0.009600000000000003 +RBT:<r>_wie -0.009600000000000003 +R:X:wie:wie -0.009600000000000003 +RBS:X_@-@ 0.02255 +RBS:jean_</r> 0.02255 +R:X:aller:aller -0.022500000000000003 +R:X:aller:of 0.022500000000000003 +R:X:merkmal:feature 0.022500000000000003 +RBT:<r>_feature 0.022500000000000003 +RBT:<r>_aller -0.022500000000000003 +RBT:feature_</r> 0.022500000000000003 +RBT:<r>_merkmal -0.022500000000000003 +RBT:jean_@-@ 0.045000000000000005 +RBT:aller_</r> -0.022500000000000003 +RBT:merkmal_</r> -0.022500000000000003 +R:X:merkmal:merkmal -0.022500000000000003 +RBT:within_</r> 0.0447 +RBT:european_</r> 0.00825 +R:X:-:- -0.022250000000000002 +R:X:-:, 0.022250000000000002 +R:X:sogar_noch:even -0.022250000000000002 +RBS:sogar_noch -0.022250000000000002 +RBT:its_choices 0.0444 +RBT:make_its 0.0444 +RBT:count_in 0.0444 +R:X:NX_dem_NX_in:N1_make_its_choices_count_in_the_N2_,_within 0.0444 +RBT:being_attracted -0.0444 +RBT:attracted_into -0.0444 +RBT:X1_make 0.0444 +R:X:NX_in:N1_being_attracted_into -0.0444 +RBT:choices_count 0.0444 +RBT:,_within 0.0444 +RBT:X1_being -0.0444 +RBT:into_</r> -0.04415 +RBS:marie_</r> 0.021975 +R:X:le:le 0.021975 +RBS:<r>_le 0.021975 +RBS:<r>_marie 0.021975 +RBT:<r>_pen 0.021975 +RBS:marie_le -0.021975 +RBS:@-@_marie -0.021975 +R:X:jean_@-@_marie_le_pen:le_pen -0.021975 +R:X:pen:pen 0.021975 +RBT:le_</r> 0.021975 +RBS:le_</r> 0.021975 +R:X:nicht:nicht -0.021575 +RBT:nicht_</r> -0.021575 +RBT:<r>_nicht -0.021575 +RBS:X_wie -0.043750000000000004 +RBT:<r>_is -0.037774999999999996 +RBS:die_X 0.040575 +RBS:<r>_das -0.038125000000000006 +RBS:sogar_</r> 0.019450000000000005 +R:X:in:in -0.0266 +RBS:wird_</r> -0.037125000000000005 +R:X:aber:is -0.041675000000000004 +RBT:X2_for -0.041675000000000004 +RBT:<r>_what -0.041675000000000004 +RBT:X1_history -0.041675000000000004 +RBT:example_the -0.041675000000000004 +R:X:wird:be -0.041675000000000004 +RBT:for_example -0.041675000000000004 +RBT:for_a -0.041675000000000004 +R:X:das:what -0.041675000000000004 +R:X:NX_geschichte_NX:N2_for_a_N1_history -0.041675000000000004 +R:X:NX_wie_die:N1_for_example_the -0.041675000000000004 +RBT:what_</r> -0.041675000000000004 +RBT:when_</r> -0.041425 +RBS:X_geschichte -0.041325 +RBT:the_united -0.041325 +RBS:den_</r> -0.0281 +RBT:ahead_X1 0.0409 +RBT:gone_ahead 0.0409 +RBT:have_gone 0.0409 +RBT:experience_in -0.0409 +RBT:in_connection -0.0409 +R:X:NX_haben:have_gone_ahead_N1 0.0409 +RBT:<r>_experience -0.0409 +R:X:NX_haben:experience_in_connection_N1 -0.0409 +RBT:connection_X1 -0.0409 +RBS:und_jean 0.020425000000000002 +RBS:<r>_jean -0.020425000000000002 +R:X:und_jean:and_jean 0.020425000000000002 +RBT:and_jean 0.020425000000000002 +RBS:haidar_</r> -0.020425000000000002 +RBT:haider_X1 0.020425000000000002 +Shape_S11100_T11000 0.020425000000000002 +RBS:haidar_X 0.020425000000000002 +RBT:<r>_haider 0.020425000000000002 +R:X:haidar_NX_@-@:haider_N1 0.020425000000000002 +RBT:haidar_</r> -0.020425000000000002 +R:X:haidar:haidar -0.020425000000000002 +RBT:<r>_haidar -0.020425000000000002 +RBT:X1_for -0.040625 +RBT:X2_, 0.04045 +RBT:extreme_</r> 0.02025 +RBT:extremen_</r> -0.02025 +RBT:<r>_extreme 0.02025 +R:X:extremen:extreme 0.02025 +RBT:<r>_extremen -0.02025 +R:X:extremen:extremen -0.02025 +RBT:<r>_X2 -0.0403 +R:X:nicht:not -0.020075 +RBT:<r>_in -0.020875 +R:X:zuwider:to -0.02 +RBT:the_X1 -0.039125 +RBT:to_</r> -0.03950000000000001 +RBS:@-@_</r> 0.01985 +RBS:zu_X -0.019299999999999994 +RBT:X1_the -0.03875 +RBS:<r>_) 0.019275 +RBS:X_) -0.019275 +R:X:):) 0.019275 +RBT:X2_) -0.019225000000000003 +R:X:NX_zu_NX_):N1_N2_) -0.019225000000000003 +RBT:<r>_racial 0.037700000000000004 +RBT:the_X2 0.038025 +RBT:<r>_racism 0.022000000000000006 +RBT:<r>_- -0.0010250000000000016 +RBT:le_pen 0.0005250000000000029 +RBS:<r>_pen -0.0005250000000000029 +RBS:jean_@-@ 0.0005250000000000029 +RBT:jean_</r> -0.0005250000000000029 +RBS:le_pen 0.0005250000000000029 +Shape_S01110_T01110 0.03715 +RBT:<r>_do 0.036800000000000006 +RBS:<r>_usa -0.022025000000000003 +RBS:aber_</r> -0.037450000000000004 +R:X:rassismus:racism 0.020425 +R:X:geschichte:geschichte -0.01855 +RBT:geschichte_</r> -0.01855 +RBT:<r>_geschichte -0.01855 +RBT:history_</r> -0.0353 +RBT:if_</r> 0.035175000000000005 +RBS:in_den 0.020225 +RBS:es_nicht 0.020500000000000004 +RBS:rassenfrage_X 0.03225 +RBS:rassenfrage_</r> -0.03225 +RBS:X_, -0.0025999999999999947 +R:X:.:, -0.036275 +RBS:deutlich_</r> 0.0361 +RBT:<r>_it 0.031125 +RBT:<r>_political 0.03242500000000001 +RBT:rassismus_</r> -0.017799999999999996 +RBT:<r>_rassismus -0.017799999999999996 +R:X:rassismus:rassismus -0.017799999999999996 +RBT:<r>_racist -0.03465 +RBT:people_X1 0.035824999999999996 +RBT:not_</r> 0.010675 +R:X:pens:pen_'s 0.017875000000000002 +RBT:pen_'s 0.017875000000000002 +R:X:pens:pen -0.017875000000000002 +RBS:den_usa 0.017525000000000002 +R:X:den:the -0.0173 +RBS:<r>_wird -0.03370000000000001 +RBS:geteiltes_X 0.032775 +RBS:geteiltes_</r> -0.032775 +RBT:<r>_there -0.033800000000000004 +RBT:._</r> -0.0338 +RBT:<r>_) -0.003225000000000004 +RBT:it_</r> 0.0321 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0.020200000000000003 +RBT:great_</r> 0.020200000000000003 +R:X:großen:large 0.0134 +R:X:gestellt:made 0.011900000000000001 diff --git a/training/dtrain/examples/parallelized/work/weights.2 b/training/dtrain/examples/parallelized/work/weights.2 index 310973ec..d4d991cc 100644 --- a/training/dtrain/examples/parallelized/work/weights.2 +++ b/training/dtrain/examples/parallelized/work/weights.2 @@ -1,12 +1,3283 @@ -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 +PhraseModel_2 1.0269510219740419 +PhraseModel_4 -0.9513029895223477 +LanguageModel 0.7624857739903501 +PhraseModel_0 -0.5970851475888205 +PassThrough -0.5965 +LanguageModel_OOV -0.574025 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-0.0088999999999999999 +RBT:<r>_rely -0.0088999999999999999 +RBT:rely_</r> -0.0088999999999999999 +R:X:vertrauen:counting 0.027 +RBT:<r>_counting 0.027 +RBT:counting_</r> 0.027 +R:X:vertrauen:suspicious -0.0001 +RBT:<r>_suspicious -0.0001 +RBT:suspicious_</r> -0.0001 +RBT:<r>_trust -0.063 +R:X:vertrauen:relying 0.0090000000000000011 +RBT:<r>_relying 0.0090000000000000011 +RBT:relying_</r> 0.0090000000000000011 +RBS:vertrauen_X -0.018000000000000002 +R:X:vertrauen_NX:trust_of_a_N1 0.0090000000000000011 +R:X:vertrauen_NX:trust_and_N1 -0.063 +RBT:trust_and -0.063 +RBS:vertrauen_. -0.0090000000000000011 +RBS:X_. 0.027 +R:X:NX_.:N1_business_. 0.027 +RBT:business_. 0.027 +R:X:NX_.:N1_the_issues_. 0.0088999999999999999 +RBT:the_issues 0.0088999999999999999 +RBT:issues_. 0.0088999999999999999 +R:X:NX_.:N1_cause_concern_. -0.0088999999999999999 +RBT:X1_cause -0.0088999999999999999 +RBT:cause_concern -0.0088999999999999999 +RBT:concern_. -0.0088999999999999999 +RBS:<r>_weniger -0.027 +RBS:weniger_</r> 0.027 +RBT:<r>_less -0.0269 +R:X:weniger:not_so_much -0.0090000000000000011 +RBT:not_so -0.0090000000000000011 +RBT:so_much -0.0090000000000000011 +R:X:weniger:short 0.0090000000000000011 +RBT:<r>_short 0.0090000000000000011 +RBT:short_</r> 0.0090000000000000011 +RBT:<r>_reduction 0.027 +RBS:weniger_X -0.027 +R:X:weniger_NX:less_N1 -0.035900000000000001 +R:X:weniger_NX:not_N1 -0.0090000000000000011 +RBT:X1_less 0.027 +R:X:weniger_NX:less_,_N1 0.0090000000000000011 +RBT:less_, 0.0090000000000000011 +R:X:weniger_NX:N1_not 0.0088999999999999999 +RBT:X1_not 0.0088999999999999999 +RBS:X_vertrauen 0.027 +RBT:be_confidence 0.0090000000000000011 +RBT:X1_suspicious 0.027 +R:X:NX_vertrauen_NX:N1_suspicious_N2 0.027 +RBT:suspicious_X2 0.027 +RBT:confidence_X2 0.0090000000000000011 +R:X:NX_vertrauen_NX:N1_to_be_confidence_N2 0.0090000000000000011 +R:X:NX_vertrauen_.:trust_of_N1_. -0.0090000000000000011 +RBS:<r>_deutlich 0.053999999999999999 +RBS:deutlich_</r> 0.027 +R:X:deutlich:demonstrate 0.027 +RBT:<r>_demonstrate 0.027 +RBT:demonstrate_</r> 0.027 +RBT:evidenced_</r> 0.027 +RBT:much_higher -0.027 +RBS:deutlich_X -0.027 +R:X:deutlich_NX:N1_evidenced 0.027 +RBT:X1_evidenced 0.027 +RBS:X_weniger 0.027 +RBT:be_less -0.027 +R:X:NX_weniger:reduction_N1 0.027 +RBT:reduction_X1 0.027 +R:X:NX_weniger_NX:N1_would_be_less_N2 -0.027 +R:X:einander:convergence -0.027 +RBS:<r>_einander 0.0090000000000000011 +RBS:einander_</r> -0.053999999999999999 +RBT:<r>_convergence -0.027 +RBT:convergence_</r> -0.027 +RBT:harmonize_</r> 0.027 +RBT:one_another 0.027 +RBT:each_other 0.018000000000000002 +RBT:are_regarded -0.027 +RBT:diverging_</r> 0.0090000000000000011 +R:X:einander_NX:N1_diverging 0.0090000000000000011 +RBS:einander_X 0.053999999999999999 +RBT:X1_diverging 0.0090000000000000011 +R:X:einander_NX:N1_harmonize 0.027 +RBT:X1_harmonize 0.027 +RBT:X1_each 0.018000000000000002 +R:X:einander_NX:one_another_N1 0.027 +R:X:einander_NX:are_regarded_N1 -0.027 +RBT:regarded_X1 -0.027 +RBS:X_deutlich -0.053999999999999999 +RBT:is_much -0.027 +R:X:NX_deutlich_NX:N2_clear_N1 -0.027 +RBT:X2_clear -0.027 +R:X:NX_deutlich_NX:N1_is_much_higher_N2 -0.027 +RBT:higher_X2 -0.027 +RBS:<r>_rasse 0.018000000000000002 +RBS:rasse_</r> -0.0090000000000000011 +RBT:<r>_regular 0.053999999999999999 +RBT:regular_racial 0.053999999999999999 +RBT:<r>_grounds -0.027 +RBT:grounds_of -0.027 +RBT:of_race -0.027 +R:X:rasse:be 0.018000000000000002 +R:X:rasse:de_race_ou_d -0.027 +RBT:<r>_de -0.027 +RBT:de_race -0.027 +RBT:race_ou -0.027 +RBT:ou_d -0.027 +RBT:d_</r> -0.027 +R:X:rasse_NX:regular_racial_N1 0.053999999999999999 +RBS:rasse_X 0.0090000000000000011 +RBT:racial_X1 0.053999999999999999 +RBT:race_X1 -0.027 +R:X:rasse_NX:grounds_of_race_N1 -0.027 +RBS:X_einander -0.0090000000000000011 +R:X:NX_einander:another_N1 -0.027 +R:X:NX_einander_NX:N1_each_other_N2 0.018000000000000002 +RBT:X1_race 0.0090000000000000011 +RBS:<r>_unterschiedlicher 0.0090000000000000011 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0.0090000000000000011 +R:X:daß_NX:allowing_N1 -0.027 +RBS:daß_X -0.018000000000000002 +RBT:allowing_X1 -0.027 +R:X:daß_NX:but_N1 -0.027 +R:X:daß_NX:if_N1 0.018000000000000002 +RBS:X_menschen 0.018000000000000002 +RBT:long_, 0.018000000000000002 +RBT:,_people 0.018000000000000002 +R:X:NX_menschen_NX:N1_long_,_people_N2 0.018000000000000002 +R:X:NX_menschen_NX:N1_human_being_N2 0.027 +RBT:being_X2 0.027 +RBS:X_daß 0.018000000000000002 +R:X:NX_daß_NX:that_it_is_N1_N2 0.018000000000000002 +RBS:<r>_zeigten 0.036000000000000004 +RBS:zeigten_</r> -0.036000000000000004 +RBT:have_shown 0.0090000000000000011 +RBT:shown_, 0.0090000000000000011 +RBT:revealed_</r> 0.0090000000000000011 +RBT:<r>_showed -0.045000000000000005 +R:X:zeigten:they 0.018000000000000002 +R:X:zeigten:have_revealed 0.0090000000000000011 +RBT:have_revealed 0.0090000000000000011 +R:X:zeigten:displayed -0.018000000000000002 +RBT:<r>_displayed -0.018000000000000002 +RBT:displayed_</r> -0.018000000000000002 +RBT:<r>_showing 0.027 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+R:X:diese_NX:N1_those 0.072000000000000008 +RBS:X_forschungen 0.018000000000000002 +R:X:NX_forschungen_NX:N2_top_@-@_N1_research 0.018000000000000002 +RBT:X2_top 0.018000000000000002 +RBT:top_@-@ 0.018000000000000002 +R:X:diese_NX_menschen_NX:that_N1_people_N2 -0.027 +R:X:geleistet:accomplished -0.090000000000000011 +RBS:geleistet_</r> -0.090000000000000011 +RBT:<r>_accomplished -0.090000000000000011 +RBT:accomplished_</r> -0.090000000000000011 +RBT:undertaken_</r> 0.090000000000000011 +R:X:geleistet_NX:N1_undertaken 0.090000000000000011 +RBS:geleistet_X 0.090000000000000011 +RBT:X1_undertaken 0.090000000000000011 diff --git a/training/dtrain/examples/parallelized/work/weights.3.1 b/training/dtrain/examples/parallelized/work/weights.3.1 index b27687d3..bed63560 100644 --- a/training/dtrain/examples/parallelized/work/weights.3.1 +++ b/training/dtrain/examples/parallelized/work/weights.3.1 @@ -1,12 +1,2130 @@ -WordPenalty 0.11138567724613679 -LanguageModel 0.95438136276453733 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0.044400000000000002 +RBT:attracted_into -0.044400000000000002 +RBT:X1_being -0.044400000000000002 +RBT:X1_make 0.044400000000000002 +RBT:choices_count 0.044400000000000002 +R:X:NX_in:N1_being_attracted_into -0.044400000000000002 +RBT:count_in 0.044400000000000002 +RBT:,_within 0.044400000000000002 +RBS:X_wie -0.043750000000000004 +RBT:is_</r> -0.045050000000000007 +RBT:history_</r> -0.041675000000000004 +R:X:wird:be -0.041675000000000004 +R:X:das:what -0.041675000000000004 +RBT:for_example -0.041675000000000004 +RBT:what_</r> -0.041675000000000004 +R:X:NX_wie_die:N1_for_example_the -0.041675000000000004 +RBT:for_a -0.041675000000000004 +R:X:NX_geschichte_NX:N2_for_a_N1_history -0.041675000000000004 +RBT:example_the -0.041675000000000004 +RBT:X1_history -0.041675000000000004 +RBT:<r>_what -0.041675000000000004 +R:X:aber:is -0.041675000000000004 +RBT:X2_for -0.041675000000000004 +RBS:X_geschichte -0.041325000000000001 +RBT:the_united -0.041325000000000001 +RBT:<r>_is 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