[okazaki@mlesna CoNLL2000]$ time ../bin/crf -trn -d . option.txt FlexCRFs - A Flexible Conditional Random Field Toolkit Copyright (C) 2004 by Hieu Xuan Phan & Minh Le Nguyen {hieuxuan, nguyenml}@jaist.ac.jp Graduate School of Information Science, Japan Advanced Institute of Science and Technology (JAIST) reading training data ... reading 8936 training sequence completed. generating dictionary ... generating 338547 context predicates completed. generating CRF features from training data ... generating 456436 CRF features completed. pruning unused context predicates ... the number of context predicates after pruning: 338547 saving context predicate map ... saving context predicate map completed. saving label map file ... saving label map completed. saving the context predicate dictionary to file ... saving the dictionary completed. start to train the CRF model ... Iteration: 1 Log-likelihood = -654457.145522 Norm(log-likelihood gradient vector) = 103742.515669 Norm(lambda vector) = 0.000000 Iteration elapsed: 128 seconds Iteration: 2 Log-likelihood = -552264.926895 Norm(log-likelihood gradient vector) = 99261.101643 Norm(lambda vector) = 1.000000 Iteration elapsed: 129 seconds Iteration: 3 Log-likelihood = -265523.395513 Norm(log-likelihood gradient vector) = 42791.346626 Norm(lambda vector) = 5.000000 Iteration elapsed: 130 seconds Iteration: 4 Log-likelihood = -169493.898320 Norm(log-likelihood gradient vector) = 36997.713789 Norm(lambda vector) = 8.183361 Iteration elapsed: 129 seconds Iteration: 5 Log-likelihood = -116221.829014 Norm(log-likelihood gradient vector) = 19499.716560 Norm(lambda vector) = 13.818995 Iteration elapsed: 130 seconds Iteration: 6 Log-likelihood = -95410.872765 Norm(log-likelihood gradient vector) = 13819.472708 Norm(lambda vector) = 17.754669 Iteration elapsed: 129 seconds Iteration: 7 Log-likelihood = -76717.843107 Norm(log-likelihood gradient vector) = 8741.458063 Norm(lambda vector) = 22.833347 Iteration elapsed: 130 seconds Iteration: 8 Log-likelihood = -71318.592788 Norm(log-likelihood gradient vector) = 14410.705425 Norm(lambda vector) = 30.227063 Iteration elapsed: 130 seconds Iteration: 9 Log-likelihood = -61268.808991 Norm(log-likelihood gradient vector) = 4342.782732 Norm(lambda vector) = 34.709949 Iteration elapsed: 129 seconds Iteration: 10 Log-likelihood = -59703.779449 Norm(log-likelihood gradient vector) = 4185.304438 Norm(lambda vector) = 38.208819 Iteration elapsed: 130 seconds Iteration: 11 Log-likelihood = -55068.951474 Norm(log-likelihood gradient vector) = 7500.263673 Norm(lambda vector) = 48.329447 Iteration elapsed: 129 seconds Iteration: 12 Log-likelihood = -54233.602865 Norm(log-likelihood gradient vector) = 8616.525647 Norm(lambda vector) = 54.746708 Iteration elapsed: 130 seconds Iteration: 13 Log-likelihood = -48739.799778 Norm(log-likelihood gradient vector) = 3578.388876 Norm(lambda vector) = 53.414173 Iteration elapsed: 129 seconds Iteration: 14 Log-likelihood = -46297.912766 Norm(log-likelihood gradient vector) = 2208.219397 Norm(lambda vector) = 53.828661 Iteration elapsed: 130 seconds Iteration: 15 Log-likelihood = -43816.465855 Norm(log-likelihood gradient vector) = 2529.598980 Norm(lambda vector) = 55.936210 Iteration elapsed: 129 seconds Iteration: 16 Log-likelihood = -40668.850172 Norm(log-likelihood gradient vector) = 2789.221605 Norm(lambda vector) = 58.992667 Iteration elapsed: 130 seconds Iteration: 17 Log-likelihood = -42778.090802 Norm(log-likelihood gradient vector) = 10695.714312 Norm(lambda vector) = 65.019519 Iteration elapsed: 129 seconds Iteration: 18 Log-likelihood = -38186.514001 Norm(log-likelihood gradient vector) = 4394.282227 Norm(lambda vector) = 61.394169 Iteration elapsed: 130 seconds Iteration: 19 Log-likelihood = -35385.277666 Norm(log-likelihood gradient vector) = 2525.272742 Norm(lambda vector) = 65.040584 Iteration elapsed: 129 seconds Iteration: 20 Log-likelihood = -33087.505756 Norm(log-likelihood gradient vector) = 1705.330422 Norm(lambda vector) = 64.672674 Iteration elapsed: 130 seconds Iteration: 21 Log-likelihood = -30385.734272 Norm(log-likelihood gradient vector) = 1823.183794 Norm(lambda vector) = 65.574105 Iteration elapsed: 130 seconds Iteration: 22 Log-likelihood = -30105.952079 Norm(log-likelihood gradient vector) = 4810.812395 Norm(lambda vector) = 67.525535 Iteration elapsed: 129 seconds Iteration: 23 Log-likelihood = -28186.165853 Norm(log-likelihood gradient vector) = 1543.323187 Norm(lambda vector) = 66.850387 Iteration elapsed: 130 seconds Iteration: 24 Log-likelihood = -27638.071029 Norm(log-likelihood gradient vector) = 1433.113974 Norm(lambda vector) = 67.354226 Iteration elapsed: 129 seconds Iteration: 25 Log-likelihood = -26767.623554 Norm(log-likelihood gradient vector) = 1853.226170 Norm(lambda vector) = 68.802759 Iteration elapsed: 130 seconds Iteration: 26 Log-likelihood = -25673.755236 Norm(log-likelihood gradient vector) = 1840.021790 Norm(lambda vector) = 71.044841 Iteration elapsed: 129 seconds Iteration: 27 Log-likelihood = -26493.174386 Norm(log-likelihood gradient vector) = 5603.189751 Norm(lambda vector) = 74.433367 Iteration elapsed: 130 seconds Iteration: 28 Log-likelihood = -25021.442033 Norm(log-likelihood gradient vector) = 1864.343854 Norm(lambda vector) = 72.310229 Iteration elapsed: 129 seconds Iteration: 29 Log-likelihood = -24133.197267 Norm(log-likelihood gradient vector) = 1305.171451 Norm(lambda vector) = 74.713918 Iteration elapsed: 130 seconds Iteration: 30 Log-likelihood = -23286.902474 Norm(log-likelihood gradient vector) = 1182.743705 Norm(lambda vector) = 76.532041 Iteration elapsed: 129 seconds Iteration: 31 Log-likelihood = -22224.070853 Norm(log-likelihood gradient vector) = 1907.121608 Norm(lambda vector) = 81.521091 Iteration elapsed: 130 seconds Iteration: 32 Log-likelihood = -21732.274158 Norm(log-likelihood gradient vector) = 2167.480941 Norm(lambda vector) = 83.110485 Iteration elapsed: 130 seconds Iteration: 33 Log-likelihood = -21142.133654 Norm(log-likelihood gradient vector) = 1130.629435 Norm(lambda vector) = 82.790456 Iteration elapsed: 129 seconds Iteration: 34 Log-likelihood = -20632.266210 Norm(log-likelihood gradient vector) = 982.483113 Norm(lambda vector) = 83.074187 Iteration elapsed: 130 seconds Iteration: 35 Log-likelihood = -20269.511042 Norm(log-likelihood gradient vector) = 1045.955097 Norm(lambda vector) = 84.136738 Iteration elapsed: 129 seconds Iteration: 36 Log-likelihood = -19757.528148 Norm(log-likelihood gradient vector) = 2171.125501 Norm(lambda vector) = 87.077935 Iteration elapsed: 130 seconds Iteration: 37 Log-likelihood = -19082.141955 Norm(log-likelihood gradient vector) = 951.050213 Norm(lambda vector) = 90.731771 Iteration elapsed: 129 seconds Iteration: 38 Log-likelihood = -18724.057641 Norm(log-likelihood gradient vector) = 791.796113 Norm(lambda vector) = 90.958122 Iteration elapsed: 130 seconds Iteration: 39 Log-likelihood = -17975.113823 Norm(log-likelihood gradient vector) = 721.963247 Norm(lambda vector) = 93.476012 Iteration elapsed: 130 seconds Iteration: 40 Log-likelihood = -17793.100850 Norm(log-likelihood gradient vector) = 1875.154563 Norm(lambda vector) = 96.822009 Iteration elapsed: 129 seconds Iteration: 41 Log-likelihood = -17353.186570 Norm(log-likelihood gradient vector) = 808.330679 Norm(lambda vector) = 97.760683 Iteration elapsed: 130 seconds Iteration: 42 Log-likelihood = -17136.096596 Norm(log-likelihood gradient vector) = 650.626244 Norm(lambda vector) = 98.315464 Iteration elapsed: 129 seconds Iteration: 43 Log-likelihood = -16825.764377 Norm(log-likelihood gradient vector) = 710.697085 Norm(lambda vector) = 100.071420 Iteration elapsed: 130 seconds Iteration: 44 Log-likelihood = -16475.103265 Norm(log-likelihood gradient vector) = 991.960909 Norm(lambda vector) = 102.222053 Iteration elapsed: 129 seconds Iteration: 45 Log-likelihood = -16143.598233 Norm(log-likelihood gradient vector) = 726.797672 Norm(lambda vector) = 106.732390 Iteration elapsed: 130 seconds Iteration: 46 Log-likelihood = -15881.694823 Norm(log-likelihood gradient vector) = 482.071907 Norm(lambda vector) = 107.405652 Iteration elapsed: 129 seconds Iteration: 47 Log-likelihood = -15562.926905 Norm(log-likelihood gradient vector) = 491.987365 Norm(lambda vector) = 108.506642 Iteration elapsed: 130 seconds Iteration: 48 Log-likelihood = -15264.919456 Norm(log-likelihood gradient vector) = 493.564015 Norm(lambda vector) = 110.251731 Iteration elapsed: 130 seconds Iteration: 49 Log-likelihood = -15205.079607 Norm(log-likelihood gradient vector) = 1709.487363 Norm(lambda vector) = 114.243463 Iteration elapsed: 129 seconds Iteration: 50 Log-likelihood = -14802.632080 Norm(log-likelihood gradient vector) = 469.599137 Norm(lambda vector) = 114.427552 Iteration elapsed: 130 seconds Iteration: 51 Log-likelihood = -14715.393298 Norm(log-likelihood gradient vector) = 393.507298 Norm(lambda vector) = 114.163239 Iteration elapsed: 129 seconds Iteration: 52 Log-likelihood = -14554.885983 Norm(log-likelihood gradient vector) = 1187.833912 Norm(lambda vector) = 115.978684 Iteration elapsed: 130 seconds Iteration: 53 Log-likelihood = -14333.374073 Norm(log-likelihood gradient vector) = 415.056713 Norm(lambda vector) = 117.020474 Iteration elapsed: 129 seconds Iteration: 54 Log-likelihood = -14267.381816 Norm(log-likelihood gradient vector) = 370.919856 Norm(lambda vector) = 117.807918 Iteration elapsed: 130 seconds Iteration: 55 Log-likelihood = -14092.144841 Norm(log-likelihood gradient vector) = 318.943717 Norm(lambda vector) = 119.705734 Iteration elapsed: 129 seconds Iteration: 56 Log-likelihood = -13945.473666 Norm(log-likelihood gradient vector) = 348.243545 Norm(lambda vector) = 121.640018 Iteration elapsed: 130 seconds Iteration: 57 Log-likelihood = -13839.743113 Norm(log-likelihood gradient vector) = 650.723832 Norm(lambda vector) = 123.381756 Iteration elapsed: 130 seconds Iteration: 58 Log-likelihood = -13702.501788 Norm(log-likelihood gradient vector) = 472.819008 Norm(lambda vector) = 123.051489 Iteration elapsed: 129 seconds Iteration: 59 Log-likelihood = -13608.335414 Norm(log-likelihood gradient vector) = 271.625297 Norm(lambda vector) = 122.247025 Iteration elapsed: 130 seconds Iteration: 60 Log-likelihood = -13534.507676 Norm(log-likelihood gradient vector) = 348.630919 Norm(lambda vector) = 121.810291 Iteration elapsed: 129 seconds Iteration: 61 Log-likelihood = -13457.221580 Norm(log-likelihood gradient vector) = 766.738873 Norm(lambda vector) = 121.954978 Iteration elapsed: 130 seconds Iteration: 62 Log-likelihood = -13370.008435 Norm(log-likelihood gradient vector) = 302.639413 Norm(lambda vector) = 122.177893 Iteration elapsed: 129 seconds Iteration: 63 Log-likelihood = -13308.565206 Norm(log-likelihood gradient vector) = 273.872207 Norm(lambda vector) = 122.629203 Iteration elapsed: 130 seconds Iteration: 64 Log-likelihood = -13252.047235 Norm(log-likelihood gradient vector) = 320.712839 Norm(lambda vector) = 123.049636 Iteration elapsed: 129 seconds Iteration: 65 Log-likelihood = -13101.440220 Norm(log-likelihood gradient vector) = 385.819279 Norm(lambda vector) = 123.620502 Iteration elapsed: 130 seconds Iteration: 66 Log-likelihood = -13086.392944 Norm(log-likelihood gradient vector) = 938.641521 Norm(lambda vector) = 124.225763 Iteration elapsed: 129 seconds Iteration: 67 Log-likelihood = -13022.296162 Norm(log-likelihood gradient vector) = 423.670532 Norm(lambda vector) = 123.892837 Iteration elapsed: 130 seconds Iteration: 68 Log-likelihood = -12899.935998 Norm(log-likelihood gradient vector) = 232.480431 Norm(lambda vector) = 124.077020 Iteration elapsed: 129 seconds Iteration: 69 Log-likelihood = -12813.161421 Norm(log-likelihood gradient vector) = 186.620349 Norm(lambda vector) = 123.983046 Iteration elapsed: 130 seconds Iteration: 70 Log-likelihood = -12672.807989 Norm(log-likelihood gradient vector) = 428.095096 Norm(lambda vector) = 123.509676 Iteration elapsed: 129 seconds Iteration: 71 Log-likelihood = -12700.217715 Norm(log-likelihood gradient vector) = 1091.036910 Norm(lambda vector) = 123.256211 Iteration elapsed: 130 seconds Iteration: 72 Log-likelihood = -12624.310207 Norm(log-likelihood gradient vector) = 392.478746 Norm(lambda vector) = 123.392978 Iteration elapsed: 129 seconds Iteration: 73 Log-likelihood = -12598.688094 Norm(log-likelihood gradient vector) = 258.187225 Norm(lambda vector) = 123.395785 Iteration elapsed: 130 seconds Iteration: 74 Log-likelihood = -12549.342312 Norm(log-likelihood gradient vector) = 163.692415 Norm(lambda vector) = 123.409460 Iteration elapsed: 130 seconds Iteration: 75 Log-likelihood = -12497.948090 Norm(log-likelihood gradient vector) = 206.654046 Norm(lambda vector) = 123.461919 Iteration elapsed: 129 seconds Iteration: 76 Log-likelihood = -12434.322197 Norm(log-likelihood gradient vector) = 431.189518 Norm(lambda vector) = 123.575029 Iteration elapsed: 130 seconds Iteration: 77 Log-likelihood = -12352.373181 Norm(log-likelihood gradient vector) = 196.130495 Norm(lambda vector) = 123.621074 Iteration elapsed: 129 seconds Iteration: 78 Log-likelihood = -12318.419350 Norm(log-likelihood gradient vector) = 144.587910 Norm(lambda vector) = 123.579094 Iteration elapsed: 130 seconds Iteration: 79 Log-likelihood = -12263.718962 Norm(log-likelihood gradient vector) = 230.352696 Norm(lambda vector) = 123.483857 Iteration elapsed: 129 seconds Iteration: 80 Log-likelihood = -12245.819308 Norm(log-likelihood gradient vector) = 375.331639 Norm(lambda vector) = 123.369744 Iteration elapsed: 130 seconds Iteration: 81 Log-likelihood = -12214.709567 Norm(log-likelihood gradient vector) = 168.326308 Norm(lambda vector) = 123.372618 Iteration elapsed: 129 seconds Iteration: 82 Log-likelihood = -12192.189773 Norm(log-likelihood gradient vector) = 172.750708 Norm(lambda vector) = 123.349763 Iteration elapsed: 130 seconds Iteration: 83 Log-likelihood = -12157.387768 Norm(log-likelihood gradient vector) = 194.082872 Norm(lambda vector) = 123.267457 Iteration elapsed: 130 seconds Iteration: 84 Log-likelihood = -12110.311638 Norm(log-likelihood gradient vector) = 183.305770 Norm(lambda vector) = 123.122826 Iteration elapsed: 129 seconds Iteration: 85 Log-likelihood = -12060.563423 Norm(log-likelihood gradient vector) = 276.333732 Norm(lambda vector) = 122.828680 Iteration elapsed: 130 seconds Iteration: 86 Log-likelihood = -12016.300564 Norm(log-likelihood gradient vector) = 152.254852 Norm(lambda vector) = 122.674412 Iteration elapsed: 129 seconds Iteration: 87 Log-likelihood = -12001.872308 Norm(log-likelihood gradient vector) = 117.959353 Norm(lambda vector) = 122.677095 Iteration elapsed: 130 seconds Iteration: 88 Log-likelihood = -11980.511096 Norm(log-likelihood gradient vector) = 143.484748 Norm(lambda vector) = 122.601823 Iteration elapsed: 129 seconds Iteration: 89 Log-likelihood = -11963.018070 Norm(log-likelihood gradient vector) = 183.705763 Norm(lambda vector) = 122.514702 Iteration elapsed: 130 seconds Iteration: 90 Log-likelihood = -11943.608745 Norm(log-likelihood gradient vector) = 111.409890 Norm(lambda vector) = 122.427226 Iteration elapsed: 129 seconds Iteration: 91 Log-likelihood = -11915.050992 Norm(log-likelihood gradient vector) = 117.806500 Norm(lambda vector) = 122.283672 Iteration elapsed: 130 seconds Iteration: 92 Log-likelihood = -11894.543937 Norm(log-likelihood gradient vector) = 122.817576 Norm(lambda vector) = 122.159084 Iteration elapsed: 129 seconds Iteration: 93 Log-likelihood = -11858.268586 Norm(log-likelihood gradient vector) = 270.881195 Norm(lambda vector) = 121.905246 Iteration elapsed: 130 seconds Iteration: 94 Log-likelihood = -11832.558553 Norm(log-likelihood gradient vector) = 120.111425 Norm(lambda vector) = 121.708871 Iteration elapsed: 130 seconds Iteration: 95 Log-likelihood = -11830.443718 Norm(log-likelihood gradient vector) = 89.894836 Norm(lambda vector) = 121.751601 Iteration elapsed: 129 seconds Iteration: 96 Log-likelihood = -11822.570718 Norm(log-likelihood gradient vector) = 142.422112 Norm(lambda vector) = 121.697487 Iteration elapsed: 130 seconds Iteration: 97 Log-likelihood = -11817.361457 Norm(log-likelihood gradient vector) = 155.009982 Norm(lambda vector) = 121.616678 Iteration elapsed: 129 seconds Iteration: 98 Log-likelihood = -11807.168437 Norm(log-likelihood gradient vector) = 73.408395 Norm(lambda vector) = 121.565919 Iteration elapsed: 130 seconds Iteration: 99 Log-likelihood = -11796.065249 Norm(log-likelihood gradient vector) = 78.665688 Norm(lambda vector) = 121.469703 Iteration elapsed: 129 seconds Iteration: 100 Log-likelihood = -11786.629053 Norm(log-likelihood gradient vector) = 88.923427 Norm(lambda vector) = 121.374769 Iteration elapsed: 130 seconds Iteration: 101 Log-likelihood = -11772.523641 Norm(log-likelihood gradient vector) = 114.143000 Norm(lambda vector) = 121.215234 Iteration elapsed: 129 seconds Iteration: 102 Log-likelihood = -11770.845050 Norm(log-likelihood gradient vector) = 145.718521 Norm(lambda vector) = 121.058498 Iteration elapsed: 130 seconds Iteration: 103 Log-likelihood = -11765.938887 Norm(log-likelihood gradient vector) = 57.589626 Norm(lambda vector) = 121.128280 Iteration elapsed: 129 seconds Iteration: 104 Log-likelihood = -11765.078811 Norm(log-likelihood gradient vector) = 65.487064 Norm(lambda vector) = 121.155356 Iteration elapsed: 130 seconds Iteration: 105 Log-likelihood = -11762.953770 Norm(log-likelihood gradient vector) = 62.251165 Norm(lambda vector) = 121.157209 Iteration elapsed: 129 seconds Iteration: 106 Log-likelihood = -11764.695056 Norm(log-likelihood gradient vector) = 257.213559 Norm(lambda vector) = 121.098476 Iteration elapsed: 130 seconds Iteration: 107 Log-likelihood = -11760.706560 Norm(log-likelihood gradient vector) = 125.585837 Norm(lambda vector) = 121.133271 Iteration elapsed: 130 seconds Iteration: 108 Log-likelihood = -11756.198654 Norm(log-likelihood gradient vector) = 64.875118 Norm(lambda vector) = 121.077573 Iteration elapsed: 129 seconds Iteration: 109 Log-likelihood = -11751.627630 Norm(log-likelihood gradient vector) = 45.933401 Norm(lambda vector) = 121.040878 Iteration elapsed: 130 seconds Iteration: 110 Log-likelihood = -11743.651468 Norm(log-likelihood gradient vector) = 65.107250 Norm(lambda vector) = 120.981397 Iteration elapsed: 129 seconds Iteration: 111 Log-likelihood = -11735.845007 Norm(log-likelihood gradient vector) = 64.499006 Norm(lambda vector) = 120.932526 Iteration elapsed: 130 seconds Iteration: 112 Log-likelihood = -11728.116417 Norm(log-likelihood gradient vector) = 257.623769 Norm(lambda vector) = 120.847143 Iteration elapsed: 129 seconds Iteration: 113 Log-likelihood = -11727.763512 Norm(log-likelihood gradient vector) = 129.778348 Norm(lambda vector) = 120.895343 Iteration elapsed: 130 seconds Iteration: 114 Log-likelihood = -11717.334284 Norm(log-likelihood gradient vector) = 57.763789 Norm(lambda vector) = 120.842673 Iteration elapsed: 130 seconds Iteration: 115 Log-likelihood = -11713.813837 Norm(log-likelihood gradient vector) = 50.559477 Norm(lambda vector) = 120.849587 Iteration elapsed: 130 seconds Iteration: 116 Log-likelihood = -11709.110536 Norm(log-likelihood gradient vector) = 145.137506 Norm(lambda vector) = 120.852668 Iteration elapsed: 129 seconds Iteration: 117 Log-likelihood = -11707.955735 Norm(log-likelihood gradient vector) = 62.566083 Norm(lambda vector) = 120.859550 Iteration elapsed: 130 seconds Iteration: 118 Log-likelihood = -11705.968430 Norm(log-likelihood gradient vector) = 35.163180 Norm(lambda vector) = 120.861344 Iteration elapsed: 129 seconds Iteration: 119 Log-likelihood = -11703.087419 Norm(log-likelihood gradient vector) = 47.873666 Norm(lambda vector) = 120.855990 Iteration elapsed: 130 seconds Iteration: 120 Log-likelihood = -11698.599774 Norm(log-likelihood gradient vector) = 52.896617 Norm(lambda vector) = 120.847232 Iteration elapsed: 129 seconds Iteration: 121 Log-likelihood = -11692.423338 Norm(log-likelihood gradient vector) = 114.481085 Norm(lambda vector) = 120.835961 Iteration elapsed: 130 seconds Iteration: 122 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 123 Log-likelihood = -11688.428632 Norm(log-likelihood gradient vector) = 29.774019 Norm(lambda vector) = 120.836625 Iteration elapsed: 129 seconds Iteration: 124 Log-likelihood = -11687.826698 Norm(log-likelihood gradient vector) = 35.833540 Norm(lambda vector) = 120.833328 Iteration elapsed: 129 seconds Iteration: 125 Log-likelihood = -11687.772732 Norm(log-likelihood gradient vector) = 37.230587 Norm(lambda vector) = 120.832900 Iteration elapsed: 130 seconds Iteration: 126 Log-likelihood = -11687.765709 Norm(log-likelihood gradient vector) = 37.432035 Norm(lambda vector) = 120.832840 Iteration elapsed: 129 seconds Iteration: 127 Log-likelihood = -11687.764738 Norm(log-likelihood gradient vector) = 37.460293 Norm(lambda vector) = 120.832832 Iteration elapsed: 130 seconds Iteration: 128 Log-likelihood = -11687.764603 Norm(log-likelihood gradient vector) = 37.464243 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 129 Log-likelihood = -11687.764584 Norm(log-likelihood gradient vector) = 37.464795 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 130 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464872 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 131 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464883 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 132 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464884 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 133 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 134 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 135 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 136 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 137 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 138 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 139 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 140 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 130 seconds Iteration: 141 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 Iteration elapsed: 129 seconds Iteration: 142 Log-likelihood = -11687.764581 Norm(log-likelihood gradient vector) = 37.464885 Norm(lambda vector) = 120.832831 LBFGS routine encounters an error The training process elapsed: 18394 seconds saving the CRF features to file ... saving the CRF features completed. 18421.988u 2.310s 5:07:09.44 99.9% 0+0k 0+0io 0pf+0w [okazaki@mlesna CoNLL2000]$