$ /home/okazaki/projects/crfsuite/frontend/crfsuite learn -a ap -p feature.possible_states=1 -p feature.possible_transitions=1 -p max_iterations=50 -m crfsuite/ap-dense.model train.crfsuite > crfsuite/ap-dense.tr.log CRFSuite 0.11.2 Copyright (c) 2007-2011 Naoaki Okazaki Start time of the training: 2011-07-01T06:32:58Z Reading the data set(s) [1] train.crfsuite 0....1....2....3....4....5....6....7....8....9....10 Number of instances: 8937 Seconds required: 5.090 Statistics the data set(s) Number of data sets (groups): 1 Number of instances: 8936 Number of items: 211727 Number of attributes: 335674 Number of labels: 22 Feature generation type: CRF1d feature.minfreq: 0.000000 feature.possible_states: 1 feature.possible_transitions: 1 0....1....2....3....4....5....6....7....8....9....10 Number of features: 7385312 Seconds required: 31.620 Averaged perceptron max_iterations: 50 epsilon: 0.000000 ***** Iteration #1 ***** Loss: 709.889165 Feature norm: 393.200859 Seconds required for this iteration: 2.720 ***** Iteration #2 ***** Loss: 386.285993 Feature norm: 510.840446 Seconds required for this iteration: 2.380 ***** Iteration #3 ***** Loss: 247.164585 Feature norm: 593.629220 Seconds required for this iteration: 2.250 ***** Iteration #4 ***** Loss: 171.017019 Feature norm: 656.309857 Seconds required for this iteration: 2.130 ***** Iteration #5 ***** Loss: 125.795411 Feature norm: 705.901172 Seconds required for this iteration: 2.070 ***** Iteration #6 ***** Loss: 100.823348 Feature norm: 746.730024 Seconds required for this iteration: 2.010 ***** Iteration #7 ***** Loss: 73.234470 Feature norm: 781.080259 Seconds required for this iteration: 1.950 ***** Iteration #8 ***** Loss: 55.564924 Feature norm: 810.126844 Seconds required for this iteration: 1.930 ***** Iteration #9 ***** Loss: 47.612568 Feature norm: 835.051579 Seconds required for this iteration: 1.910 ***** Iteration #10 ***** Loss: 41.240830 Feature norm: 856.819044 Seconds required for this iteration: 1.890 ***** Iteration #11 ***** Loss: 34.775182 Feature norm: 876.043085 Seconds required for this iteration: 1.870 ***** Iteration #12 ***** Loss: 28.241615 Feature norm: 893.178292 Seconds required for this iteration: 1.870 ***** Iteration #13 ***** Loss: 27.048529 Feature norm: 908.537283 Seconds required for this iteration: 1.850 ***** Iteration #14 ***** Loss: 22.688075 Feature norm: 922.391134 Seconds required for this iteration: 1.840 ***** Iteration #15 ***** Loss: 24.914290 Feature norm: 934.992730 Seconds required for this iteration: 1.850 ***** Iteration #16 ***** Loss: 17.990528 Feature norm: 946.552569 Seconds required for this iteration: 1.840 ***** Iteration #17 ***** Loss: 16.360170 Feature norm: 957.157518 Seconds required for this iteration: 1.830 ***** Iteration #18 ***** Loss: 16.182219 Feature norm: 966.972872 Seconds required for this iteration: 1.830 ***** Iteration #19 ***** Loss: 14.571196 Feature norm: 976.064713 Seconds required for this iteration: 1.810 ***** Iteration #20 ***** Loss: 14.451306 Feature norm: 984.552716 Seconds required for this iteration: 1.820 ***** Iteration #21 ***** Loss: 11.028689 Feature norm: 992.465717 Seconds required for this iteration: 1.820 ***** Iteration #22 ***** Loss: 12.248599 Feature norm: 999.864335 Seconds required for this iteration: 1.820 ***** Iteration #23 ***** Loss: 10.275820 Feature norm: 1006.801516 Seconds required for this iteration: 1.810 ***** Iteration #24 ***** Loss: 11.003054 Feature norm: 1013.346088 Seconds required for this iteration: 1.820 ***** Iteration #25 ***** Loss: 8.269851 Feature norm: 1019.509862 Seconds required for this iteration: 1.810 ***** Iteration #26 ***** Loss: 6.482685 Feature norm: 1025.314099 Seconds required for this iteration: 1.800 ***** Iteration #27 ***** Loss: 8.767749 Feature norm: 1030.788217 Seconds required for this iteration: 1.810 ***** Iteration #28 ***** Loss: 7.831893 Feature norm: 1035.982788 Seconds required for this iteration: 1.800 ***** Iteration #29 ***** Loss: 8.048493 Feature norm: 1040.916770 Seconds required for this iteration: 1.810 ***** Iteration #30 ***** Loss: 8.710035 Feature norm: 1045.631893 Seconds required for this iteration: 1.800 ***** Iteration #31 ***** Loss: 7.097198 Feature norm: 1050.132175 Seconds required for this iteration: 1.810 ***** Iteration #32 ***** Loss: 5.098160 Feature norm: 1054.423339 Seconds required for this iteration: 1.790 ***** Iteration #33 ***** Loss: 5.314279 Feature norm: 1058.514746 Seconds required for this iteration: 1.800 ***** Iteration #34 ***** Loss: 5.218252 Feature norm: 1062.423434 Seconds required for this iteration: 1.790 ***** Iteration #35 ***** Loss: 4.420674 Feature norm: 1066.156910 Seconds required for this iteration: 1.800 ***** Iteration #36 ***** Loss: 4.941745 Feature norm: 1069.735928 Seconds required for this iteration: 1.800 ***** Iteration #37 ***** Loss: 5.249030 Feature norm: 1073.168665 Seconds required for this iteration: 1.790 ***** Iteration #38 ***** Loss: 4.704287 Feature norm: 1076.462030 Seconds required for this iteration: 1.800 ***** Iteration #39 ***** Loss: 5.526588 Feature norm: 1079.637069 Seconds required for this iteration: 1.800 ***** Iteration #40 ***** Loss: 4.068184 Feature norm: 1082.694273 Seconds required for this iteration: 1.790 ***** Iteration #41 ***** Loss: 4.341016 Feature norm: 1085.639464 Seconds required for this iteration: 1.800 ***** Iteration #42 ***** Loss: 3.498655 Feature norm: 1088.474830 Seconds required for this iteration: 1.790 ***** Iteration #43 ***** Loss: 4.804456 Feature norm: 1091.209981 Seconds required for this iteration: 1.790 ***** Iteration #44 ***** Loss: 4.027982 Feature norm: 1093.856047 Seconds required for this iteration: 1.790 ***** Iteration #45 ***** Loss: 4.954663 Feature norm: 1096.418367 Seconds required for this iteration: 1.800 ***** Iteration #46 ***** Loss: 5.302385 Feature norm: 1098.906091 Seconds required for this iteration: 1.790 ***** Iteration #47 ***** Loss: 3.144672 Feature norm: 1101.317251 Seconds required for this iteration: 1.790 ***** Iteration #48 ***** Loss: 3.911565 Feature norm: 1103.650721 Seconds required for this iteration: 1.800 ***** Iteration #49 ***** Loss: 4.166328 Feature norm: 1105.914895 Seconds required for this iteration: 1.790 ***** Iteration #50 ***** Loss: 3.350420 Feature norm: 1108.111771 Seconds required for this iteration: 1.790 Total seconds required for training: 93.650 Storing the model Number of active features: 280768 (7385312) Number of active attributes: 98727 (335674) Number of active labels: 22 (22) Writing labels Writing attributes Writing feature references for transitions Writing feature references for attributes Seconds required: 0.310 End time of the training: 2011-07-01T06:35:10Z