ServerRun 8225
Creatorinternal
Programcrfpp
DatasetNikhilDatasetTokenWithPTBT
Task typeSequenceTagging
Created6y349d ago
Done! Flag_green
1s
54M
SequenceTagging
1
0
0.961
0

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
CRF++: Yet Another CRF Tool Kit
Copyright (C) 2005-2009 Taku Kudo, All rights reserved.

reading training data: 100.. 200.. 
Done!0.11 s

Number of sentences: 268
Number of features:  96088
Number of thread(s): 1
Freq:                1
eta:                 0.00010
C:                   1.00000
shrinking size:      20
iter=0 terr=0.05874 serr=0.41045 act=96088 obj=6726.30024 diff=1.00000
iter=1 terr=0.05874 serr=0.41045 act=96088 obj=2675.65713 diff=0.60221
iter=2 terr=0.05874 serr=0.41045 act=96088 obj=1349.35880 diff=0.49569
iter=3 terr=0.05874 serr=0.41045 act=96088 obj=1231.57902 diff=0.08729
iter=4 terr=0.05874 serr=0.41045 act=96088 obj=1055.78840 diff=0.14274
iter=5 terr=0.05874 serr=0.41045 act=96088 obj=957.54112 diff=0.09306
iter=6 terr=0.05874 serr=0.41045 act=96088 obj=861.64564 diff=0.10015
iter=7 terr=0.04349 serr=0.35075 act=96088 obj=646.79569 diff=0.24935
iter=8 terr=0.04225 serr=0.34328 act=96088 obj=571.60377 diff=0.11625
iter=9 terr=0.03607 serr=0.31716 act=96088 obj=452.10424 diff=0.20906
iter=10 terr=0.02721 serr=0.27612 act=96088 obj=355.33426 diff=0.21404
iter=11 terr=0.01525 serr=0.18657 act=96088 obj=295.29413 diff=0.16897
iter=12 terr=0.01463 serr=0.17164 act=96088 obj=267.12043 diff=0.09541
iter=13 terr=0.01051 serr=0.14925 act=96088 obj=248.64310 diff=0.06917
iter=14 terr=0.00907 serr=0.13806 act=96088 obj=238.34794 diff=0.04141
iter=15 terr=0.00598 serr=0.10448 act=96088 obj=224.83845 diff=0.05668
iter=16 terr=0.00453 serr=0.07836 act=96088 obj=211.23691 diff=0.06049
iter=17 terr=0.00103 serr=0.01866 act=96088 obj=197.35335 diff=0.06573
iter=18 terr=0.00041 serr=0.00746 act=96088 obj=186.95949 diff=0.05267
iter=19 terr=0.00144 serr=0.02612 act=96088 obj=183.45770 diff=0.01873
iter=20 terr=0.00144 serr=0.02612 act=96088 obj=181.69202 diff=0.00962
iter=21 terr=0.00062 serr=0.01119 act=96088 obj=177.22609 diff=0.02458
iter=22 terr=0.00021 serr=0.00373 act=96088 obj=175.53825 diff=0.00952
iter=23 terr=0.00000 serr=0.00000 act=96088 obj=174.11642 diff=0.00810
iter=24 terr=0.00000 serr=0.00000 act=96088 obj=173.41553 diff=0.00403
iter=25 terr=0.00000 serr=0.00000 act=96088 obj=172.70791 diff=0.00408
iter=26 terr=0.00000 serr=0.00000 act=96088 obj=172.82326 diff=0.00067
iter=27 terr=0.00000 serr=0.00000 act=96088 obj=172.45132 diff=0.00215
iter=28 terr=0.00000 serr=0.00000 act=96088 obj=172.10264 diff=0.00202
iter=29 terr=0.00000 serr=0.00000 act=96088 obj=171.99882 diff=0.00060
iter=30 terr=0.00000 serr=0.00000 act=96088 obj=171.78797 diff=0.00123
iter=31 terr=0.00000 serr=0.00000 act=96088 obj=171.66317 diff=0.00073
iter=32 terr=0.00000 serr=0.00000 act=96088 obj=171.55590 diff=0.00062
iter=33 terr=0.00000 serr=0.00000 act=96088 obj=171.49459 diff=0.00036
iter=34 terr=0.00000 serr=0.00000 act=96088 obj=171.45705 diff=0.00022
iter=35 terr=0.00000 serr=0.00000 act=96088 obj=171.48147 diff=0.00014
iter=36 terr=0.00000 serr=0.00000 act=96088 obj=171.43635 diff=0.00026
iter=37 terr=0.00000 serr=0.00000 act=96088 obj=171.41479 diff=0.00013
iter=38 terr=0.00000 serr=0.00000 act=96088 obj=171.40423 diff=0.00006
iter=39 terr=0.00000 serr=0.00000 act=96088 obj=171.38650 diff=0.00010
iter=40 terr=0.00000 serr=0.00000 act=96088 obj=171.37055 diff=0.00009
iter=41 terr=0.00000 serr=0.00000 act=96088 obj=171.36402 diff=0.00004
iter=42 terr=0.00000 serr=0.00000 act=96088 obj=171.35745 diff=0.00004

Done!2.14 s

=== END program1: ./run learn ../dataset2/train --- OK [6s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s]

===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s]


real	0m6.902s
user	0m2.844s
sys	0m0.148s

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