ServerRun 11212
Creatorfavre
Programsvm-hmm
Datasetsequence-conll-sample
Task typeSequenceTagging
Created6y288d ago
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21s
408M
SequenceTagging
1
1
0.200
0

Log file

LICENSE.txt
Makefile
svm_struct_api.h
svm_struct_api.c
svm_struct_api_types.h
svm_struct_learn_custom.c
svm_struct/Makefile
svm_struct/svm_struct_main.c
svm_struct/svm_struct_learn.h
svm_struct/svm_struct_learn.c
svm_struct/svm_struct_common.h
svm_struct/svm_struct_common.c
svm_struct/svm_struct_classify.c
svm_light/LICENSE.txt
svm_light/Makefile
svm_light/svm_learn.c
svm_light/kernel.h
svm_light/svm_learn.h
svm_light/svm_learn_main.c
svm_light/svm_classify.c
svm_light/svm_loqo.c
svm_light/svm_common.c
svm_light/svm_common.h
svm_light/svm_hideo.c
cd svm_light; make svm_learn_hideo_noexe
make[1]: Entering directory `/home/mlcomp/worker/scratch/program1/svm_light'
gcc -c  -O3                      svm_learn_main.c -o svm_learn_main.o 
gcc -c  -O3                      svm_learn.c -o svm_learn.o 
gcc -c  -O3                      svm_common.c -o svm_common.o 
gcc -c  -O3                      svm_hideo.c -o svm_hideo.o 
make[1]: Leaving directory `/home/mlcomp/worker/scratch/program1/svm_light'
cd svm_struct; make svm_struct_noexe
make[1]: Entering directory `/home/mlcomp/worker/scratch/program1/svm_struct'
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_learn.c -o svm_struct_learn.o
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_classify.c -o svm_struct_classify.o
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_common.c -o svm_struct_common.o
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_main.c -o svm_struct_main.o
make[1]: Leaving directory `/home/mlcomp/worker/scratch/program1/svm_struct'
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_api.c -o svm_struct_api.o
svm_struct_api.c: In function ‘find_most_violated_constraint_slackrescaling’:
svm_struct_api.c:417: warning: ‘ybar.length’ is used uninitialized in this function
svm_struct_api.c:417: warning: ‘ybar.labels’ is used uninitialized in this function
svm_struct_api.c: In function ‘read_struct_model’:
svm_struct_api.c:905: warning: ‘sm.walpha’ is used uninitialized in this function
svm_struct_api.c:905: warning: ‘sm.add_your_variables_here’ is used uninitialized in this function
gcc -c  -O3 -fomit-frame-pointer -ffast-math -Wall  svm_struct_learn_custom.c -o svm_struct_learn_custom.o
gcc  -O3 -lm -Wall svm_struct/svm_struct_learn.o svm_struct_learn_custom.o svm_struct_api.o svm_light/svm_hideo.o svm_light/svm_learn.o svm_light/svm_common.o svm_struct/svm_struct_common.o svm_struct/svm_struct_main.o -o svm_hmm_learn 
gcc  -O3 -lm -Wall svm_struct_api.o svm_struct/svm_struct_classify.o svm_light/svm_common.o svm_struct/svm_struct_common.o -o svm_hmm_classify 
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
read 3 templates from "template"
Reading training examples... 2 examples, 6 tokens, 3 features, 3 classes... done
Iter 1: ..*(NumConst=1, SV=1, CEps=3.0000, QPEps=0.0000)
Iter 2: *(NumConst=2, SV=1, CEps=2.7900, QPEps=0.0000)
Iter 3: ..*(NumConst=3, SV=2, CEps=0.2700, QPEps=0.0000)
Iter 4: ..(NumConst=3, SV=2, CEps=0.0969, QPEps=0.0000)
Final epsilon on KKT-Conditions: 0.09692
Upper bound on duality gap: 0.00582
Dual objective value: dval=0.17557
Primal objective value: pval=0.18138
Total number of constraints in final working set: 3 (of 3)
Number of iterations: 4
Number of calls to 'find_most_violated_constraint': 6
Number of SV: 2 
Norm of weight vector: |w|=0.09414
Value of slack variable (on working set): xi=2.85231
Value of slack variable (global): xi=2.94923
Norm of longest difference vector: ||Psi(x,y)-Psi(x,ybar)||=3.74166
Runtime in cpu-seconds: 0.00
Final number of constraints in cache: 8
Viterbi timing: CreateTransEmitMatrix=0.000000 Viterbi=0.000000
Compacting linear model...done
Writing learned model...done
=== END program1: ./run learn ../dataset2/train --- OK [1s]

===== 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
read 3 templates from "template"
Reading model...done.
Reading test examples... 2 examples, 6 tokens, 3 features, 4 classes... done.
Classifying test examples...done
Runtime (without IO) in cpu-seconds: 0.00
Average loss on test set: 3.0000
Zero/one-error on test set: 100.00% (0 correct, 2 incorrect, 2 total)
Average loss per token: 1.0000
=== 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 [0s]

===== 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
read 3 templates from "template"
Reading model...done.
Reading test examples... 1 examples, 5 tokens, 3 features, 4 classes... done.
Classifying test examples...done
Runtime (without IO) in cpu-seconds: 0.00
Average loss on test set: 5.0000
Zero/one-error on test set: 100.00% (0 correct, 1 incorrect, 1 total)
Average loss per token: 1.0000
=== 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 [1s]


real	0m22.865s
user	0m4.556s
sys	0m0.428s

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