OPTION VALUES: Model directory: ./Fold16-IOB2/ Training data file: train.tagged Testing data file: test.tagged Unlabeled data file: data.untagged Model file: model.txt Training log file (this one): trainlog.txt Label representation: IOB2 Second-order Markov CRFs Number of labels: 4 Number of training sequences: 1032 (one data partition) Number of testing sequences: 62 (one data partition) Number of unlabeled sequences: 0 Number of context predicates: 793772 Number of features: 1513871 Feature rare threshold: 1 Context predicate rare threshold: 1 Using multiple rare thresholds for features: 0 Highlight feature: 0 Number of training iterations: 150 Initial lambda value: 0.0000 Sigma square (for smoothing): 100.0000 Epsilon for L-BFGS convergence: 0.000100 Number of approximated hessian matrixes: 7 Start to train ... Iteration: 1 Log-likelihood = -3069557.927690 Norm (log-likelihood gradient vector) = 633309.197866 Norm (lambda vector) = 0.000000 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 15197 12214 80.37 71.45 75.65 i-np 19923 19883 16250 81.73 81.56 81.65 o 29640 31577 26479 83.86 89.34 86.51 ----- ------ ----- ----- ------- ------- ------------- Avg1. 81.98 80.78 81.38 Avg2. 66657 66657 54943 82.43 82.43 82.43 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 15197 9565 62.94 55.96 59.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 62.94 55.96 59.24 Avg2. 17094 15197 9565 62.94 55.96 59.24 Current max chunk-based F1: 59.24 (iteration 1) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 2 Log-likelihood = -2469181.339530 Norm (log-likelihood gradient vector) = 554341.236323 Norm (lambda vector) = 1.000000 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 15585 12791 82.07 74.83 78.28 i-np 19923 21118 17259 81.73 86.63 84.11 o 29640 29954 26341 87.94 88.87 88.40 ----- ------ ----- ----- ------- ------- ------------- Avg1. 83.91 83.44 83.68 Avg2. 66657 66657 56391 84.60 84.60 84.60 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 15585 10284 65.99 60.16 62.94 ----- ------ ----- ----- ------- ------- ------------- Avg1. 65.99 60.16 62.94 Avg2. 17094 15585 10284 65.99 60.16 62.94 Current max chunk-based F1: 62.94 (iteration 2) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 3 Log-likelihood = -981617.656494 Norm (log-likelihood gradient vector) = 379465.391389 Norm (lambda vector) = 10.181525 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 14159 13187 93.14 77.14 84.39 i-np 19923 22187 18839 84.91 94.56 89.48 o 29640 30311 28040 92.51 94.60 93.54 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.18 88.77 89.47 Avg2. 66657 66657 60066 90.11 90.11 90.11 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 14159 11517 81.34 67.37 73.70 ----- ------ ----- ----- ------- ------- ------------- Avg1. 81.34 67.37 73.70 Avg2. 17094 14159 11517 81.34 67.37 73.70 Current max chunk-based F1: 73.70 (iteration 3) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 4 Log-likelihood = -711994.058588 Norm (log-likelihood gradient vector) = 168545.036335 Norm (lambda vector) = 9.817494 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16655 15071 90.49 88.17 89.31 i-np 19923 19771 18242 92.27 91.56 91.91 o 29640 30231 28529 94.37 96.25 95.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.38 91.99 92.18 Avg2. 66657 66657 61842 92.78 92.78 92.78 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16655 13849 83.15 81.02 82.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 83.15 81.02 82.07 Avg2. 17094 16655 13849 83.15 81.02 82.07 Current max chunk-based F1: 82.07 (iteration 4) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 5 Log-likelihood = -656954.831644 Norm (log-likelihood gradient vector) = 106674.916362 Norm (lambda vector) = 9.349848 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16832 15456 91.83 90.42 91.12 i-np 19923 19146 18165 94.88 91.18 92.99 o 29640 30679 28878 94.13 97.43 95.75 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.61 93.01 93.31 Avg2. 66657 66657 62499 93.76 93.76 93.76 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16832 14551 86.45 85.12 85.78 ----- ------ ----- ----- ------- ------- ------------- Avg1. 86.45 85.12 85.78 Avg2. 17094 16832 14551 86.45 85.12 85.78 Current max chunk-based F1: 85.78 (iteration 5) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 6 Log-likelihood = -621711.140805 Norm (log-likelihood gradient vector) = 72973.476680 Norm (lambda vector) = 9.395723 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16665 15581 93.50 91.15 92.31 i-np 19923 19536 18573 95.07 93.22 94.14 o 29640 30456 28978 95.15 97.77 96.44 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.57 94.05 94.31 Avg2. 66657 66657 63132 94.71 94.71 94.71 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16665 14880 89.29 87.05 88.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 89.29 87.05 88.15 Avg2. 17094 16665 14880 89.29 87.05 88.15 Current max chunk-based F1: 88.15 (iteration 6) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 7 Log-likelihood = -568372.696203 Norm (log-likelihood gradient vector) = 70454.939910 Norm (lambda vector) = 10.311351 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16774 15839 94.43 92.66 93.53 i-np 19923 19403 18646 96.10 93.59 94.83 o 29640 30480 29120 95.54 98.25 96.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.35 94.83 95.09 Avg2. 66657 66657 63605 95.42 95.42 95.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16774 15193 90.57 88.88 89.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.57 88.88 89.72 Avg2. 17094 16774 15193 90.57 88.88 89.72 Current max chunk-based F1: 89.72 (iteration 7) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 8 Log-likelihood = -491425.611432 Norm (log-likelihood gradient vector) = 58305.507677 Norm (lambda vector) = 12.143023 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16600 15927 95.95 93.17 94.54 i-np 19923 20556 19274 93.76 96.74 95.23 o 29640 29501 28800 97.62 97.17 97.39 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.78 95.69 95.74 Avg2. 66657 66657 64001 96.02 96.02 96.02 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16600 15222 91.70 89.05 90.35 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.70 89.05 90.35 Avg2. 17094 16600 15222 91.70 89.05 90.35 Current max chunk-based F1: 90.35 (iteration 8) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 9 Log-likelihood = -401585.268438 Norm (log-likelihood gradient vector) = 71695.072832 Norm (lambda vector) = 16.720420 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16898 16149 95.57 94.47 95.02 i-np 19923 19721 18967 96.18 95.20 95.69 o 29640 30038 29128 96.97 98.27 97.62 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.24 95.98 96.11 Avg2. 66657 66657 64244 96.38 96.38 96.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16898 15560 92.08 91.03 91.55 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.08 91.03 91.55 Avg2. 17094 16898 15560 92.08 91.03 91.55 Current max chunk-based F1: 91.55 (iteration 9) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 10 Log-likelihood = -363947.252479 Norm (log-likelihood gradient vector) = 30233.136841 Norm (lambda vector) = 18.125636 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17005 16235 95.47 94.97 95.22 i-np 19923 19521 18882 96.73 94.77 95.74 o 29640 30131 29190 96.88 98.48 97.67 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.36 96.08 96.22 Avg2. 66657 66657 64307 96.47 96.47 96.47 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17005 15659 92.08 91.61 91.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.08 91.61 91.84 Avg2. 17094 17005 15659 92.08 91.61 91.84 Current max chunk-based F1: 91.84 (iteration 10) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 11 Log-likelihood = -340313.231563 Norm (log-likelihood gradient vector) = 30953.935252 Norm (lambda vector) = 20.158651 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17117 16316 95.32 95.45 95.38 i-np 19923 19409 18823 96.98 94.48 95.71 o 29640 30131 29212 96.95 98.56 97.75 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.42 96.16 96.29 Avg2. 66657 66657 64351 96.54 96.54 96.54 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17117 15735 91.93 92.05 91.99 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.93 92.05 91.99 Avg2. 17094 17117 15735 91.93 92.05 91.99 Current max chunk-based F1: 91.99 (iteration 11) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 12 Log-likelihood = -316461.420307 Norm (log-likelihood gradient vector) = 27889.079594 Norm (lambda vector) = 22.630425 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16719 16191 96.84 94.72 95.77 i-np 19923 20316 19346 95.23 97.10 96.16 o 29640 29622 29016 97.95 97.89 97.92 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.67 96.57 96.62 Avg2. 66657 66657 64553 96.84 96.84 96.84 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16719 15601 93.31 91.27 92.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.31 91.27 92.28 Avg2. 17094 16719 15601 93.31 91.27 92.28 Current max chunk-based F1: 92.28 (iteration 12) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 13 Log-likelihood = -314400.829479 Norm (log-likelihood gradient vector) = 92579.524782 Norm (lambda vector) = 27.587822 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17006 16368 96.25 95.75 96.00 i-np 19923 19809 19150 96.67 96.12 96.40 o 29640 29842 29158 97.71 98.37 98.04 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.88 96.75 96.81 Avg2. 66657 66657 64676 97.03 97.03 97.03 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17006 15845 93.17 92.69 92.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.17 92.69 92.93 Avg2. 17094 17006 15845 93.17 92.69 92.93 Current max chunk-based F1: 92.93 (iteration 13) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 14 Log-likelihood = -286181.353253 Norm (log-likelihood gradient vector) = 25831.819567 Norm (lambda vector) = 28.047263 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17059 16400 96.14 95.94 96.04 i-np 19923 19743 19121 96.85 95.97 96.41 o 29640 29855 29166 97.69 98.40 98.05 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.89 96.77 96.83 Avg2. 66657 66657 64687 97.04 97.04 97.04 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17059 15880 93.09 92.90 92.99 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.09 92.90 92.99 Avg2. 17094 17059 15880 93.09 92.90 92.99 Current max chunk-based F1: 92.99 (iteration 14) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 15 Log-likelihood = -282643.739131 Norm (log-likelihood gradient vector) = 17409.414910 Norm (lambda vector) = 28.309287 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17084 16414 96.08 96.02 96.05 i-np 19923 19700 19095 96.93 95.84 96.38 o 29640 29873 29175 97.66 98.43 98.05 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.89 96.77 96.83 Avg2. 66657 66657 64684 97.04 97.04 97.04 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17084 15889 93.01 92.95 92.98 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.01 92.95 92.98 Avg2. 17094 17084 15889 93.01 92.95 92.98 Current max chunk-based F1: 92.99 (iteration 14) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 16 Log-likelihood = -278054.806806 Norm (log-likelihood gradient vector) = 18733.301961 Norm (lambda vector) = 28.912768 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17103 16454 96.21 96.26 96.23 i-np 19923 19679 19110 97.11 95.92 96.51 o 29640 29875 29193 97.72 98.49 98.10 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.01 96.89 96.95 Avg2. 66657 66657 64757 97.15 97.15 97.15 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17103 15945 93.23 93.28 93.25 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.23 93.28 93.25 Avg2. 17094 17103 15945 93.23 93.28 93.25 Current max chunk-based F1: 93.25 (iteration 16) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 17 Log-likelihood = -265589.862289 Norm (log-likelihood gradient vector) = 18351.055742 Norm (lambda vector) = 30.628441 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17048 16475 96.64 96.38 96.51 i-np 19923 19895 19282 96.92 96.78 96.85 o 29640 29714 29156 98.12 98.37 98.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.23 97.18 97.20 Avg2. 66657 66657 64913 97.38 97.38 97.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17048 16012 93.92 93.67 93.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 93.92 93.67 93.80 Avg2. 17094 17048 16012 93.92 93.67 93.80 Current max chunk-based F1: 93.80 (iteration 17) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 18 Log-likelihood = -241719.915780 Norm (log-likelihood gradient vector) = 31009.235089 Norm (lambda vector) = 34.198034 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17299 16563 95.75 96.89 96.32 i-np 19923 19333 18904 97.78 94.89 96.31 o 29640 30025 29252 97.43 98.69 98.05 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.98 96.82 96.90 Avg2. 66657 66657 64719 97.09 97.09 97.09 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17299 16057 92.82 93.93 93.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.82 93.93 93.37 Avg2. 17094 17299 16057 92.82 93.93 93.37 Current max chunk-based F1: 93.80 (iteration 17) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 19 Log-likelihood = -235145.251417 Norm (log-likelihood gradient vector) = 53132.971030 Norm (lambda vector) = 39.626482 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17109 16529 96.61 96.69 96.65 i-np 19923 19721 19210 97.41 96.42 96.91 o 29640 29827 29215 97.95 98.57 98.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.32 97.23 97.27 Avg2. 66657 66657 64954 97.45 97.45 97.45 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17109 16085 94.01 94.10 94.06 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.01 94.10 94.06 Avg2. 17094 17109 16085 94.01 94.10 94.06 Current max chunk-based F1: 94.06 (iteration 19) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 20 Log-likelihood = -218510.397281 Norm (log-likelihood gradient vector) = 17152.705181 Norm (lambda vector) = 39.461322 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17047 16508 96.84 96.57 96.70 i-np 19923 19849 19292 97.19 96.83 97.01 o 29640 29761 29194 98.09 98.50 98.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.38 97.30 97.34 Avg2. 66657 66657 64994 97.51 97.51 97.51 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17047 16069 94.26 94.00 94.13 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.26 94.00 94.13 Avg2. 17094 17047 16069 94.26 94.00 94.13 Current max chunk-based F1: 94.13 (iteration 20) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 21 Log-likelihood = -212465.129896 Norm (log-likelihood gradient vector) = 10742.695351 Norm (lambda vector) = 39.812469 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16992 16491 97.05 96.47 96.76 i-np 19923 19959 19370 97.05 97.22 97.14 o 29640 29706 29177 98.22 98.44 98.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.44 97.38 97.41 Avg2. 66657 66657 65038 97.57 97.57 97.57 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16992 16077 94.62 94.05 94.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.62 94.05 94.33 Avg2. 17094 16992 16077 94.62 94.05 94.33 Current max chunk-based F1: 94.33 (iteration 21) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 22 Log-likelihood = -205595.292179 Norm (log-likelihood gradient vector) = 10421.590677 Norm (lambda vector) = 40.581851 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17008 16510 97.07 96.58 96.83 i-np 19923 19940 19366 97.12 97.20 97.16 o 29640 29709 29188 98.25 98.48 98.36 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.48 97.42 97.45 Avg2. 66657 66657 65064 97.61 97.61 97.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17008 16099 94.66 94.18 94.42 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.66 94.18 94.42 Avg2. 17094 17008 16099 94.66 94.18 94.42 Current max chunk-based F1: 94.42 (iteration 22) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 23 Log-likelihood = -195946.533796 Norm (log-likelihood gradient vector) = 10175.841878 Norm (lambda vector) = 42.043912 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16792 16410 97.73 96.00 96.85 i-np 19923 20465 19590 95.72 98.33 97.01 o 29640 29400 29027 98.73 97.93 98.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.39 97.42 97.41 Avg2. 66657 66657 65027 97.55 97.55 97.55 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16792 15950 94.99 93.31 94.14 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.99 93.31 94.14 Avg2. 17094 16792 15950 94.99 93.31 94.14 Current max chunk-based F1: 94.42 (iteration 22) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 24 Log-likelihood = -192757.491976 Norm (log-likelihood gradient vector) = 54701.073258 Norm (lambda vector) = 46.050037 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16919 16482 97.42 96.42 96.92 i-np 19923 20144 19470 96.65 97.73 97.19 o 29640 29594 29136 98.45 98.30 98.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.51 97.48 97.49 Avg2. 66657 66657 65088 97.65 97.65 97.65 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16919 16068 94.97 94.00 94.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.97 94.00 94.48 Avg2. 17094 16919 16068 94.97 94.00 94.48 Current max chunk-based F1: 94.48 (iteration 24) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 25 Log-likelihood = -190888.386186 Norm (log-likelihood gradient vector) = 23210.540939 Norm (lambda vector) = 43.587564 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16999 16530 97.24 96.70 96.97 i-np 19923 20012 19418 97.03 97.47 97.25 o 29640 29646 29173 98.40 98.42 98.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.56 97.53 97.54 Avg2. 66657 66657 65121 97.70 97.70 97.70 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16999 16127 94.87 94.34 94.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.87 94.34 94.61 Avg2. 17094 16999 16127 94.87 94.34 94.61 Current max chunk-based F1: 94.61 (iteration 25) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 26 Log-likelihood = -183279.991828 Norm (log-likelihood gradient vector) = 12829.141660 Norm (lambda vector) = 45.104788 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17069 16560 97.02 96.88 96.95 i-np 19923 19925 19351 97.12 97.13 97.12 o 29640 29663 29169 98.33 98.41 98.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.49 97.47 97.48 Avg2. 66657 66657 65080 97.63 97.63 97.63 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17069 16150 94.62 94.48 94.55 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.62 94.48 94.55 Avg2. 17094 17069 16150 94.62 94.48 94.55 Current max chunk-based F1: 94.61 (iteration 25) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 27 Log-likelihood = -176408.964047 Norm (log-likelihood gradient vector) = 9340.251026 Norm (lambda vector) = 48.069716 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17070 16574 97.09 96.96 97.03 i-np 19923 19933 19371 97.18 97.23 97.20 o 29640 29654 29169 98.36 98.41 98.39 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.55 97.53 97.54 Avg2. 66657 66657 65114 97.69 97.69 97.69 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17070 16179 94.78 94.65 94.71 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.78 94.65 94.71 Avg2. 17094 17070 16179 94.78 94.65 94.71 Current max chunk-based F1: 94.71 (iteration 27) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 28 Log-likelihood = -169449.851521 Norm (log-likelihood gradient vector) = 7481.924985 Norm (lambda vector) = 50.371197 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17154 16630 96.95 97.29 97.12 i-np 19923 19766 19286 97.57 96.80 97.19 o 29640 29737 29219 98.26 98.58 98.42 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.59 97.56 97.57 Avg2. 66657 66657 65135 97.72 97.72 97.72 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17154 16226 94.59 94.92 94.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.59 94.92 94.76 Avg2. 17094 17154 16226 94.59 94.92 94.76 Current max chunk-based F1: 94.76 (iteration 28) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 29 Log-likelihood = -162058.488115 Norm (log-likelihood gradient vector) = 12406.452427 Norm (lambda vector) = 54.019766 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17027 16583 97.39 97.01 97.20 i-np 19923 20048 19447 97.00 97.61 97.31 o 29640 29582 29158 98.57 98.37 98.47 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.65 97.67 97.66 Avg2. 66657 66657 65188 97.80 97.80 97.80 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17027 16184 95.05 94.68 94.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.05 94.68 94.86 Avg2. 17094 17027 16184 95.05 94.68 94.86 Current max chunk-based F1: 94.86 (iteration 29) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 30 Log-likelihood = -159506.861182 Norm (log-likelihood gradient vector) = 20072.979861 Norm (lambda vector) = 57.117584 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17055 16602 97.34 97.12 97.23 i-np 19923 19981 19422 97.20 97.49 97.34 o 29640 29621 29180 98.51 98.45 98.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.69 97.69 97.69 Avg2. 66657 66657 65204 97.82 97.82 97.82 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17055 16213 95.06 94.85 94.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.06 94.85 94.95 Avg2. 17094 17055 16213 95.06 94.85 94.95 Current max chunk-based F1: 94.95 (iteration 30) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 31 Log-likelihood = -157152.967178 Norm (log-likelihood gradient vector) = 9656.656112 Norm (lambda vector) = 56.199434 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17067 16621 97.39 97.23 97.31 i-np 19923 19938 19410 97.35 97.43 97.39 o 29640 29652 29204 98.49 98.53 98.51 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.74 97.73 97.74 Avg2. 66657 66657 65235 97.87 97.87 97.87 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17067 16240 95.15 95.00 95.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.15 95.00 95.08 Avg2. 17094 17067 16240 95.15 95.00 95.08 Current max chunk-based F1: 95.08 (iteration 31) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 32 Log-likelihood = -155827.732934 Norm (log-likelihood gradient vector) = 6858.291955 Norm (lambda vector) = 55.816992 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17066 16632 97.46 97.30 97.38 i-np 19923 19936 19422 97.42 97.49 97.45 o 29640 29655 29213 98.51 98.56 98.53 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.80 97.78 97.79 Avg2. 66657 66657 65267 97.91 97.91 97.91 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17066 16259 95.27 95.12 95.19 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.27 95.12 95.19 Avg2. 17094 17066 16259 95.27 95.12 95.19 Current max chunk-based F1: 95.19 (iteration 32) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 33 Log-likelihood = -153846.689761 Norm (log-likelihood gradient vector) = 8777.772845 Norm (lambda vector) = 56.265600 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17130 16650 97.20 97.40 97.30 i-np 19923 19812 19331 97.57 97.03 97.30 o 29640 29715 29232 98.37 98.62 98.50 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.71 97.68 97.70 Avg2. 66657 66657 65213 97.83 97.83 97.83 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17130 16251 94.87 95.07 94.97 ----- ------ ----- ----- ------- ------- ------------- Avg1. 94.87 95.07 94.97 Avg2. 17094 17130 16251 94.87 95.07 94.97 Current max chunk-based F1: 95.19 (iteration 32) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 34 Log-likelihood = -150555.265286 Norm (log-likelihood gradient vector) = 13310.603940 Norm (lambda vector) = 57.150874 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17038 16621 97.55 97.23 97.39 i-np 19923 20007 19454 97.24 97.65 97.44 o 29640 29612 29198 98.60 98.51 98.56 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.80 97.80 97.80 Avg2. 66657 66657 65273 97.92 97.92 97.92 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17038 16235 95.29 94.97 95.13 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.29 94.97 95.13 Avg2. 17094 17038 16235 95.29 94.97 95.13 Current max chunk-based F1: 95.19 (iteration 32) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 35 Log-likelihood = -147787.970452 Norm (log-likelihood gradient vector) = 12575.809423 Norm (lambda vector) = 59.545436 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17081 16639 97.41 97.34 97.38 i-np 19923 19929 19410 97.40 97.43 97.41 o 29640 29647 29210 98.53 98.55 98.54 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.78 97.77 97.77 Avg2. 66657 66657 65259 97.90 97.90 97.90 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17081 16262 95.21 95.13 95.17 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.21 95.13 95.17 Avg2. 17094 17081 16262 95.21 95.13 95.17 Current max chunk-based F1: 95.19 (iteration 32) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 36 Log-likelihood = -145238.435922 Norm (log-likelihood gradient vector) = 6222.791546 Norm (lambda vector) = 59.153928 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17085 16648 97.44 97.39 97.42 i-np 19923 19921 19418 97.48 97.47 97.47 o 29640 29651 29220 98.55 98.58 98.56 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.82 97.81 97.82 Avg2. 66657 66657 65286 97.94 97.94 97.94 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17085 16277 95.27 95.22 95.25 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.27 95.22 95.25 Avg2. 17094 17085 16277 95.27 95.22 95.25 Current max chunk-based F1: 95.25 (iteration 36) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 37 Log-likelihood = -142294.721241 Norm (log-likelihood gradient vector) = 6986.025574 Norm (lambda vector) = 59.551441 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17092 16660 97.47 97.46 97.47 i-np 19923 19920 19423 97.51 97.49 97.50 o 29640 29645 29226 98.59 98.60 98.59 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.85 97.85 97.85 Avg2. 66657 66657 65309 97.98 97.98 97.98 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17092 16286 95.28 95.27 95.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.28 95.27 95.28 Avg2. 17094 17092 16286 95.28 95.27 95.28 Current max chunk-based F1: 95.28 (iteration 37) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 38 Log-likelihood = -139121.349929 Norm (log-likelihood gradient vector) = 7281.759616 Norm (lambda vector) = 60.311428 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17045 16651 97.69 97.41 97.55 i-np 19923 20021 19507 97.43 97.91 97.67 o 29640 29591 29217 98.74 98.57 98.65 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.95 97.96 97.96 Avg2. 66657 66657 65375 98.08 98.08 98.08 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17045 16303 95.65 95.37 95.51 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.65 95.37 95.51 Avg2. 17094 17045 16303 95.65 95.37 95.51 Current max chunk-based F1: 95.51 (iteration 38) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 39 Log-likelihood = -130731.150339 Norm (log-likelihood gradient vector) = 13388.327096 Norm (lambda vector) = 61.702382 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17171 16698 97.25 97.68 97.46 i-np 19923 19761 19346 97.90 97.10 97.50 o 29640 29725 29262 98.44 98.72 98.58 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.86 97.84 97.85 Avg2. 66657 66657 65306 97.97 97.97 97.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17171 16333 95.12 95.55 95.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.12 95.55 95.33 Avg2. 17094 17171 16333 95.12 95.55 95.33 Current max chunk-based F1: 95.51 (iteration 38) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 40 Log-likelihood = -125629.075519 Norm (log-likelihood gradient vector) = 17295.322801 Norm (lambda vector) = 63.740939 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17095 16676 97.55 97.55 97.55 i-np 19923 19891 19435 97.71 97.55 97.63 o 29640 29671 29253 98.59 98.69 98.64 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.95 97.93 97.94 Avg2. 66657 66657 65364 98.06 98.06 98.06 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17095 16318 95.45 95.46 95.46 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.45 95.46 95.46 Avg2. 17094 17095 16318 95.45 95.46 95.46 Current max chunk-based F1: 95.51 (iteration 38) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 41 Log-likelihood = -123693.402774 Norm (log-likelihood gradient vector) = 5309.302315 Norm (lambda vector) = 63.371321 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17079 16676 97.64 97.55 97.60 i-np 19923 19919 19460 97.70 97.68 97.69 o 29640 29659 29256 98.64 98.70 98.67 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.99 97.98 97.99 Avg2. 66657 66657 65392 98.10 98.10 98.10 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17079 16323 95.57 95.49 95.53 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.57 95.49 95.53 Avg2. 17094 17079 16323 95.57 95.49 95.53 Current max chunk-based F1: 95.53 (iteration 41) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 42 Log-likelihood = -122835.156097 Norm (log-likelihood gradient vector) = 4907.970859 Norm (lambda vector) = 63.428903 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17064 16674 97.71 97.54 97.63 i-np 19923 19941 19478 97.68 97.77 97.72 o 29640 29652 29257 98.67 98.71 98.69 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.02 98.01 98.01 Avg2. 66657 66657 65409 98.13 98.13 98.13 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17064 16328 95.69 95.52 95.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.69 95.52 95.60 Avg2. 17094 17064 16328 95.69 95.52 95.60 Current max chunk-based F1: 95.60 (iteration 42) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 43 Log-likelihood = -120931.462653 Norm (log-likelihood gradient vector) = 4860.079415 Norm (lambda vector) = 63.902186 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17052 16671 97.77 97.53 97.65 i-np 19923 19988 19506 97.59 97.91 97.75 o 29640 29617 29241 98.73 98.65 98.69 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.03 98.03 98.03 Avg2. 66657 66657 65418 98.14 98.14 98.14 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17052 16328 95.75 95.52 95.64 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.75 95.52 95.64 Avg2. 17094 17052 16328 95.75 95.52 95.64 Current max chunk-based F1: 95.64 (iteration 43) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 44 Log-likelihood = -117895.431689 Norm (log-likelihood gradient vector) = 9719.051784 Norm (lambda vector) = 64.938244 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17141 16694 97.39 97.66 97.53 i-np 19923 19806 19392 97.91 97.33 97.62 o 29640 29710 29273 98.53 98.76 98.65 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.94 97.92 97.93 Avg2. 66657 66657 65359 98.05 98.05 98.05 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17141 16342 95.34 95.60 95.47 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.34 95.60 95.47 Avg2. 17094 17141 16342 95.34 95.60 95.47 Current max chunk-based F1: 95.64 (iteration 43) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 45 Log-likelihood = -116201.910909 Norm (log-likelihood gradient vector) = 14842.543229 Norm (lambda vector) = 66.674730 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17100 16688 97.59 97.62 97.61 i-np 19923 19898 19454 97.77 97.65 97.71 o 29640 29659 29257 98.64 98.71 98.68 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.00 97.99 98.00 Avg2. 66657 66657 65399 98.11 98.11 98.11 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17100 16347 95.60 95.63 95.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.60 95.63 95.61 Avg2. 17094 17100 16347 95.60 95.63 95.61 Current max chunk-based F1: 95.64 (iteration 43) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 46 Log-likelihood = -114504.986959 Norm (log-likelihood gradient vector) = 5670.822001 Norm (lambda vector) = 65.905946 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17085 16689 97.68 97.63 97.66 i-np 19923 19942 19490 97.73 97.83 97.78 o 29640 29630 29253 98.73 98.69 98.71 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.05 98.05 98.05 Avg2. 66657 66657 65432 98.16 98.16 98.16 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17085 16355 95.73 95.68 95.70 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.73 95.68 95.70 Avg2. 17094 17085 16355 95.73 95.68 95.70 Current max chunk-based F1: 95.70 (iteration 46) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 47 Log-likelihood = -113573.965522 Norm (log-likelihood gradient vector) = 4705.228081 Norm (lambda vector) = 65.846404 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17061 16689 97.82 97.63 97.73 i-np 19923 19986 19519 97.66 97.97 97.82 o 29640 29610 29251 98.79 98.69 98.74 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.09 98.10 98.09 Avg2. 66657 66657 65459 98.20 98.20 98.20 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17061 16360 95.89 95.71 95.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.89 95.71 95.80 Avg2. 17094 17061 16360 95.89 95.71 95.80 Current max chunk-based F1: 95.80 (iteration 47) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 48 Log-likelihood = -111390.235430 Norm (log-likelihood gradient vector) = 4296.563030 Norm (lambda vector) = 66.036335 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17034 16680 97.92 97.58 97.75 i-np 19923 20056 19561 97.53 98.18 97.86 o 29640 29567 29237 98.88 98.64 98.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.11 98.13 98.12 Avg2. 66657 66657 65478 98.23 98.23 98.23 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17034 16354 96.01 95.67 95.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.01 95.67 95.84 Avg2. 17094 17034 16354 96.01 95.67 95.84 Current max chunk-based F1: 95.84 (iteration 48) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 49 Log-likelihood = -107379.234194 Norm (log-likelihood gradient vector) = 7404.605153 Norm (lambda vector) = 67.211728 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17031 16679 97.93 97.57 97.75 i-np 19923 20030 19549 97.60 98.12 97.86 o 29640 29596 29253 98.84 98.69 98.77 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.12 98.13 98.13 Avg2. 66657 66657 65481 98.24 98.24 98.24 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17031 16356 96.04 95.68 95.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.04 95.68 95.86 Avg2. 17094 17031 16356 96.04 95.68 95.86 Current max chunk-based F1: 95.86 (iteration 49) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 50 Log-likelihood = -104718.601497 Norm (log-likelihood gradient vector) = 16581.312472 Norm (lambda vector) = 68.757872 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17031 16679 97.93 97.57 97.75 i-np 19923 20039 19552 97.57 98.14 97.85 o 29640 29587 29247 98.85 98.67 98.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.12 98.13 98.12 Avg2. 66657 66657 65478 98.23 98.23 98.23 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17031 16353 96.02 95.67 95.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.02 95.67 95.84 Avg2. 17094 17031 16353 96.02 95.67 95.84 Current max chunk-based F1: 95.86 (iteration 49) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 51 Log-likelihood = -104762.782423 Norm (log-likelihood gradient vector) = 8020.428410 Norm (lambda vector) = 67.961165 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17086 16707 97.78 97.74 97.76 i-np 19923 19923 19502 97.89 97.89 97.89 o 29640 29648 29283 98.77 98.80 98.78 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.15 98.14 98.14 Avg2. 66657 66657 65492 98.25 98.25 98.25 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17086 16391 95.93 95.89 95.91 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.93 95.89 95.91 Avg2. 17094 17086 16391 95.93 95.89 95.91 Current max chunk-based F1: 95.91 (iteration 51) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 52 Log-likelihood = -102641.058672 Norm (log-likelihood gradient vector) = 4761.696567 Norm (lambda vector) = 68.539633 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17079 16703 97.80 97.71 97.76 i-np 19923 19933 19508 97.87 97.92 97.89 o 29640 29645 29283 98.78 98.80 98.79 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.15 98.14 98.15 Avg2. 66657 66657 65494 98.26 98.26 98.26 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17079 16388 95.95 95.87 95.91 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.95 95.87 95.91 Avg2. 17094 17079 16388 95.95 95.87 95.91 Current max chunk-based F1: 95.91 (iteration 52) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 53 Log-likelihood = -101213.289113 Norm (log-likelihood gradient vector) = 4341.838480 Norm (lambda vector) = 68.909163 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17098 16717 97.77 97.79 97.78 i-np 19923 19907 19497 97.94 97.86 97.90 o 29640 29652 29289 98.78 98.82 98.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.16 98.16 98.16 Avg2. 66657 66657 65503 98.27 98.27 98.27 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17098 16399 95.91 95.93 95.92 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.91 95.93 95.92 Avg2. 17094 17098 16399 95.91 95.93 95.92 Current max chunk-based F1: 95.92 (iteration 53) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 54 Log-likelihood = -98097.866172 Norm (log-likelihood gradient vector) = 5856.304063 Norm (lambda vector) = 69.664739 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17027 16685 97.99 97.61 97.80 i-np 19923 20021 19559 97.69 98.17 97.93 o 29640 29609 29271 98.86 98.76 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.18 98.18 98.18 Avg2. 66657 66657 65515 98.29 98.29 98.29 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17027 16364 96.11 95.73 95.92 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.11 95.73 95.92 Avg2. 17094 17027 16364 96.11 95.73 95.92 Current max chunk-based F1: 95.92 (iteration 53) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 55 Log-likelihood = -94586.240374 Norm (log-likelihood gradient vector) = 12876.282645 Norm (lambda vector) = 71.077391 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17063 16709 97.93 97.75 97.84 i-np 19923 19970 19541 97.85 98.08 97.97 o 29640 29624 29284 98.85 98.80 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.21 98.21 98.21 Avg2. 66657 66657 65534 98.32 98.32 98.32 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17063 16394 96.08 95.90 95.99 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.08 95.90 95.99 Avg2. 17094 17063 16394 96.08 95.90 95.99 Current max chunk-based F1: 95.99 (iteration 55) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 56 Log-likelihood = -93170.865859 Norm (log-likelihood gradient vector) = 4042.470728 Norm (lambda vector) = 70.860019 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17071 16711 97.89 97.76 97.83 i-np 19923 19960 19533 97.86 98.04 97.95 o 29640 29626 29282 98.84 98.79 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.20 98.20 98.20 Avg2. 66657 66657 65526 98.30 98.30 98.30 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17071 16394 96.03 95.90 95.97 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.03 95.90 95.97 Avg2. 17094 17071 16394 96.03 95.90 95.97 Current max chunk-based F1: 95.99 (iteration 55) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 57 Log-likelihood = -92625.959006 Norm (log-likelihood gradient vector) = 3421.513869 Norm (lambda vector) = 70.803735 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17070 16708 97.88 97.74 97.81 i-np 19923 19956 19521 97.82 97.98 97.90 o 29640 29631 29280 98.82 98.79 98.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.17 98.17 98.17 Avg2. 66657 66657 65509 98.28 98.28 98.28 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17070 16383 95.98 95.84 95.91 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.98 95.84 95.91 Avg2. 17094 17070 16383 95.98 95.84 95.91 Current max chunk-based F1: 95.99 (iteration 55) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 58 Log-likelihood = -91323.842333 Norm (log-likelihood gradient vector) = 3661.244197 Norm (lambda vector) = 71.012080 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17065 16715 97.95 97.78 97.87 i-np 19923 19973 19546 97.86 98.11 97.98 o 29640 29619 29285 98.87 98.80 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.23 98.23 Avg2. 66657 66657 65546 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17065 16403 96.12 95.96 96.04 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.12 95.96 96.04 Avg2. 17094 17065 16403 96.12 95.96 96.04 Current max chunk-based F1: 96.04 (iteration 58) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 59 Log-likelihood = -89564.792271 Norm (log-likelihood gradient vector) = 3453.283775 Norm (lambda vector) = 71.534170 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17014 16679 98.03 97.57 97.80 i-np 19923 20082 19587 97.54 98.31 97.92 o 29640 29561 29244 98.93 98.66 98.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.16 98.18 98.17 Avg2. 66657 66657 65510 98.28 98.28 98.28 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17014 16358 96.14 95.69 95.92 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.14 95.69 95.92 Avg2. 17094 17014 16358 96.14 95.69 95.92 Current max chunk-based F1: 96.04 (iteration 58) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 60 Log-likelihood = -86967.742968 Norm (log-likelihood gradient vector) = 21127.950025 Norm (lambda vector) = 75.054571 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 28 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17052 16708 97.98 97.74 97.86 i-np 19923 20012 19564 97.76 98.20 97.98 o 29640 29593 29272 98.92 98.76 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.22 98.23 98.23 Avg2. 66657 66657 65544 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17052 16390 96.12 95.88 96.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.12 95.88 96.00 Avg2. 17094 17052 16390 96.12 95.88 96.00 Current max chunk-based F1: 96.04 (iteration 58) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 61 Log-likelihood = -87147.662502 Norm (log-likelihood gradient vector) = 9298.661084 Norm (lambda vector) = 72.792132 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17072 16715 97.91 97.78 97.85 i-np 19923 19951 19528 97.88 98.02 97.95 o 29640 29634 29285 98.82 98.80 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.20 98.20 98.20 Avg2. 66657 66657 65528 98.31 98.31 98.31 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17072 16403 96.08 95.96 96.02 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.08 95.96 96.02 Avg2. 17094 17072 16403 96.08 95.96 96.02 Current max chunk-based F1: 96.04 (iteration 58) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 62 Log-likelihood = -85180.078525 Norm (log-likelihood gradient vector) = 4821.102268 Norm (lambda vector) = 73.943928 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17042 16706 98.03 97.73 97.88 i-np 19923 20017 19569 97.76 98.22 97.99 o 29640 29598 29271 98.90 98.76 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.24 98.23 Avg2. 66657 66657 65546 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17042 16396 96.21 95.92 96.06 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.21 95.92 96.06 Avg2. 17094 17042 16396 96.21 95.92 96.06 Current max chunk-based F1: 96.06 (iteration 62) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 63 Log-likelihood = -85192.724861 Norm (log-likelihood gradient vector) = 4106.842915 Norm (lambda vector) = 74.082105 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 28 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17071 16717 97.93 97.79 97.86 i-np 19923 19964 19538 97.87 98.07 97.97 o 29640 29622 29283 98.86 98.80 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.22 98.22 98.22 Avg2. 66657 66657 65538 98.32 98.32 98.32 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17071 16406 96.10 95.98 96.04 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.10 95.98 96.04 Avg2. 17094 17071 16406 96.10 95.98 96.04 Current max chunk-based F1: 96.06 (iteration 62) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 64 Log-likelihood = -85097.405987 Norm (log-likelihood gradient vector) = 4129.819106 Norm (lambda vector) = 73.983106 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17079 16724 97.92 97.84 97.88 i-np 19923 19923 19515 97.95 97.95 97.95 o 29640 29655 29299 98.80 98.85 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.22 98.21 98.22 Avg2. 66657 66657 65538 98.32 98.32 98.32 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17079 16413 96.10 96.02 96.06 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.10 96.02 96.06 Avg2. 17094 17079 16413 96.10 96.02 96.06 Current max chunk-based F1: 96.06 (iteration 62) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 65 Log-likelihood = -84705.684704 Norm (log-likelihood gradient vector) = 3777.912208 Norm (lambda vector) = 74.619642 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17014 16703 98.17 97.71 97.94 i-np 19923 20064 19602 97.70 98.39 98.04 o 29640 29579 29272 98.96 98.76 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.29 98.28 Avg2. 66657 66657 65577 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17014 16401 96.40 95.95 96.17 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.40 95.95 96.17 Avg2. 17094 17014 16401 96.40 95.95 96.17 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 66 Log-likelihood = -83989.675633 Norm (log-likelihood gradient vector) = 8184.378689 Norm (lambda vector) = 75.541164 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17041 16715 98.09 97.78 97.93 i-np 19923 20010 19571 97.81 98.23 98.02 o 29640 29606 29286 98.92 98.81 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.27 98.27 Avg2. 66657 66657 65572 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17041 16409 96.29 95.99 96.14 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.29 95.99 96.14 Avg2. 17094 17041 16409 96.29 95.99 96.14 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 67 Log-likelihood = -82987.077654 Norm (log-likelihood gradient vector) = 4992.697256 Norm (lambda vector) = 76.304196 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17080 16715 97.86 97.78 97.82 i-np 19923 19926 19504 97.88 97.90 97.89 o 29640 29651 29291 98.79 98.82 98.80 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.18 98.17 98.17 Avg2. 66657 66657 65510 98.28 98.28 98.28 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17080 16398 96.01 95.93 95.97 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.01 95.93 95.97 Avg2. 17094 17080 16398 96.01 95.93 95.97 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 68 Log-likelihood = -81292.919262 Norm (log-likelihood gradient vector) = 3292.160221 Norm (lambda vector) = 77.726323 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17089 16720 97.84 97.81 97.83 i-np 19923 19906 19495 97.94 97.85 97.89 o 29640 29662 29298 98.77 98.85 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.18 98.17 98.18 Avg2. 66657 66657 65513 98.28 98.28 98.28 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17089 16405 96.00 95.97 95.98 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.00 95.97 95.98 Avg2. 17094 17089 16405 96.00 95.97 95.98 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 69 Log-likelihood = -80011.457622 Norm (log-likelihood gradient vector) = 3434.224092 Norm (lambda vector) = 78.404025 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17096 16726 97.84 97.85 97.84 i-np 19923 19901 19496 97.96 97.86 97.91 o 29640 29660 29299 98.78 98.85 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.19 98.18 98.19 Avg2. 66657 66657 65521 98.30 98.30 98.30 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17096 16413 96.00 96.02 96.01 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.00 96.02 96.01 Avg2. 17094 17096 16413 96.00 96.02 96.01 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 70 Log-likelihood = -76926.294894 Norm (log-likelihood gradient vector) = 4665.836981 Norm (lambda vector) = 80.116906 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17156 16741 97.58 97.93 97.76 i-np 19923 19787 19413 98.11 97.44 97.77 o 29640 29714 29313 98.65 98.90 98.77 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.11 98.09 98.10 Avg2. 66657 66657 65467 98.21 98.21 98.21 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17156 16412 95.66 96.01 95.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.66 96.01 95.84 Avg2. 17094 17156 16412 95.66 96.01 95.84 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 71 Log-likelihood = -75153.312006 Norm (log-likelihood gradient vector) = 13047.681918 Norm (lambda vector) = 81.685866 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17102 16733 97.84 97.89 97.87 i-np 19923 19894 19492 97.98 97.84 97.91 o 29640 29661 29302 98.79 98.86 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.20 98.19 98.20 Avg2. 66657 66657 65527 98.30 98.30 98.30 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17102 16418 96.00 96.05 96.02 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.00 96.05 96.02 Avg2. 17094 17102 16418 96.00 96.05 96.02 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 72 Log-likelihood = -73699.515521 Norm (log-likelihood gradient vector) = 4278.585146 Norm (lambda vector) = 81.542108 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17068 16728 98.01 97.86 97.93 i-np 19923 19955 19540 97.92 98.08 98.00 o 29640 29634 29298 98.87 98.85 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.26 98.26 98.26 Avg2. 66657 66657 65566 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17068 16423 96.22 96.07 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.22 96.07 96.15 Avg2. 17094 17068 16423 96.22 96.07 96.15 Current max chunk-based F1: 96.17 (iteration 65) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 73 Log-likelihood = -73490.114464 Norm (log-likelihood gradient vector) = 2648.806701 Norm (lambda vector) = 81.263853 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17042 16717 98.09 97.79 97.94 i-np 19923 20010 19573 97.82 98.24 98.03 o 29640 29605 29287 98.93 98.81 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.28 98.28 Avg2. 66657 66657 65577 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17042 16416 96.33 96.03 96.18 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.33 96.03 96.18 Avg2. 17094 17042 16416 96.33 96.03 96.18 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 74 Log-likelihood = -73110.301035 Norm (log-likelihood gradient vector) = 3530.144753 Norm (lambda vector) = 81.384074 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17057 16717 98.01 97.79 97.90 i-np 19923 19986 19553 97.83 98.14 97.99 o 29640 29614 29284 98.89 98.80 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.24 98.25 98.24 Avg2. 66657 66657 65554 98.35 98.35 98.35 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17057 16418 96.25 96.05 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.05 96.15 Avg2. 17094 17057 16418 96.25 96.05 96.15 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 75 Log-likelihood = -72508.483059 Norm (log-likelihood gradient vector) = 3182.535531 Norm (lambda vector) = 81.818340 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16986 16676 98.17 97.55 97.86 i-np 19923 20149 19622 97.38 98.49 97.93 o 29640 29522 29231 99.01 98.62 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.19 98.22 98.21 Avg2. 66657 66657 65529 98.31 98.31 98.31 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16986 16359 96.31 95.70 96.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.31 95.70 96.00 Avg2. 17094 16986 16359 96.31 95.70 96.00 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 76 Log-likelihood = -72419.090659 Norm (log-likelihood gradient vector) = 17404.014852 Norm (lambda vector) = 84.933280 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17035 16700 98.03 97.70 97.86 i-np 19923 20041 19572 97.66 98.24 97.95 o 29640 29581 29262 98.92 98.72 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.20 98.22 98.21 Avg2. 66657 66657 65534 98.32 98.32 98.32 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17035 16390 96.21 95.88 96.05 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.21 95.88 96.05 Avg2. 17094 17035 16390 96.21 95.88 96.05 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 77 Log-likelihood = -71645.245250 Norm (log-likelihood gradient vector) = 6647.300441 Norm (lambda vector) = 82.882659 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17067 16727 98.01 97.85 97.93 i-np 19923 19960 19544 97.92 98.10 98.01 o 29640 29630 29296 98.87 98.84 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.26 98.26 Avg2. 66657 66657 65567 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17067 16424 96.23 96.08 96.16 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.23 96.08 96.16 Avg2. 17094 17067 16424 96.23 96.08 96.16 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 78 Log-likelihood = -70913.955428 Norm (log-likelihood gradient vector) = 3230.565489 Norm (lambda vector) = 83.513528 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17093 16736 97.91 97.91 97.91 i-np 19923 19912 19519 98.03 97.97 98.00 o 29640 29652 29307 98.84 98.88 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.26 98.25 98.25 Avg2. 66657 66657 65562 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17093 16431 96.13 96.12 96.12 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.13 96.12 96.12 Avg2. 17094 17093 16431 96.13 96.12 96.12 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 79 Log-likelihood = -69854.114849 Norm (log-likelihood gradient vector) = 3007.008254 Norm (lambda vector) = 84.827231 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17098 16739 97.90 97.92 97.91 i-np 19923 19902 19510 98.03 97.93 97.98 o 29640 29657 29309 98.83 98.88 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.24 98.25 Avg2. 66657 66657 65558 98.35 98.35 98.35 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17098 16430 96.09 96.12 96.10 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.09 96.12 96.10 Avg2. 17094 17098 16430 96.09 96.12 96.10 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 80 Log-likelihood = -68694.878130 Norm (log-likelihood gradient vector) = 3188.100689 Norm (lambda vector) = 85.665181 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17099 16736 97.88 97.91 97.89 i-np 19923 19910 19511 98.00 97.93 97.96 o 29640 29648 29306 98.85 98.87 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.24 98.24 98.24 Avg2. 66657 66657 65553 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17099 16419 96.02 96.05 96.04 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.02 96.05 96.04 Avg2. 17094 17099 16419 96.02 96.05 96.04 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 81 Log-likelihood = -65604.547092 Norm (log-likelihood gradient vector) = 5501.560439 Norm (lambda vector) = 88.210497 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17139 16751 97.74 97.99 97.86 i-np 19923 19843 19477 98.16 97.76 97.96 o 29640 29675 29316 98.79 98.91 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.22 98.22 Avg2. 66657 66657 65544 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17139 16438 95.91 96.16 96.04 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.91 96.16 96.04 Avg2. 17094 17139 16438 95.91 96.16 96.04 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 82 Log-likelihood = -63560.609856 Norm (log-likelihood gradient vector) = 8604.927665 Norm (lambda vector) = 89.661093 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17101 16736 97.87 97.91 97.89 i-np 19923 19924 19529 98.02 98.02 98.02 o 29640 29632 29299 98.88 98.85 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.26 98.26 Avg2. 66657 66657 65564 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17101 16431 96.08 96.12 96.10 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.08 96.12 96.10 Avg2. 17094 17101 16431 96.08 96.12 96.10 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 83 Log-likelihood = -63217.188080 Norm (log-likelihood gradient vector) = 2765.226023 Norm (lambda vector) = 88.928967 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17087 16730 97.91 97.87 97.89 i-np 19923 19961 19548 97.93 98.12 98.02 o 29640 29609 29285 98.91 98.80 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.26 98.26 Avg2. 66657 66657 65563 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17087 16428 96.14 96.10 96.12 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.14 96.10 96.12 Avg2. 17094 17087 16428 96.14 96.10 96.12 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 84 Log-likelihood = -62879.270144 Norm (log-likelihood gradient vector) = 2304.101650 Norm (lambda vector) = 88.815448 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17068 16718 97.95 97.80 97.87 i-np 19923 19999 19561 97.81 98.18 98.00 o 29640 29590 29275 98.94 98.77 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.25 98.24 Avg2. 66657 66657 65554 98.35 98.35 98.35 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17068 16411 96.15 96.00 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.15 96.00 96.08 Avg2. 17094 17068 16411 96.15 96.00 96.08 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 85 Log-likelihood = -62098.449596 Norm (log-likelihood gradient vector) = 3173.289175 Norm (lambda vector) = 89.168753 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17072 16723 97.96 97.83 97.89 i-np 19923 19996 19557 97.80 98.16 97.98 o 29640 29589 29272 98.93 98.76 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.25 98.24 Avg2. 66657 66657 65552 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17072 16420 96.18 96.06 96.12 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.18 96.06 96.12 Avg2. 17094 17072 16420 96.18 96.06 96.12 Current max chunk-based F1: 96.18 (iteration 73) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 86 Log-likelihood = -60101.886208 Norm (log-likelihood gradient vector) = 3626.853993 Norm (lambda vector) = 90.616544 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17080 16748 98.06 97.98 98.02 i-np 19923 19954 19554 98.00 98.15 98.07 o 29640 29623 29302 98.92 98.86 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.33 98.33 Avg2. 66657 66657 65604 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17080 16449 96.31 96.23 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.31 96.23 96.27 Avg2. 17094 17080 16449 96.31 96.23 96.27 Current max chunk-based F1: 96.27 (iteration 86) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 87 Log-likelihood = -57109.352885 Norm (log-likelihood gradient vector) = 3741.079215 Norm (lambda vector) = 92.831808 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17033 16708 98.09 97.74 97.92 i-np 19923 20171 19648 97.41 98.62 98.01 o 29640 29453 29196 99.13 98.50 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.21 98.29 98.25 Avg2. 66657 66657 65552 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17033 16413 96.36 96.02 96.19 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.36 96.02 96.19 Avg2. 17094 17033 16413 96.36 96.02 96.19 Current max chunk-based F1: 96.27 (iteration 86) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 88 Log-likelihood = -53987.778322 Norm (log-likelihood gradient vector) = 10973.331445 Norm (lambda vector) = 98.417892 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17062 16734 98.08 97.89 97.99 i-np 19923 20034 19590 97.78 98.33 98.06 o 29640 29561 29265 99.00 98.73 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.32 98.30 Avg2. 66657 66657 65589 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17062 16435 96.33 96.14 96.23 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.33 96.14 96.23 Avg2. 17094 17062 16435 96.33 96.14 96.23 Current max chunk-based F1: 96.27 (iteration 86) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 89 Log-likelihood = -55101.997759 Norm (log-likelihood gradient vector) = 4708.220442 Norm (lambda vector) = 94.923618 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17101 16751 97.95 97.99 97.97 i-np 19923 19956 19555 97.99 98.15 98.07 o 29640 29600 29288 98.95 98.81 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.32 98.31 Avg2. 66657 66657 65594 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17101 16458 96.24 96.28 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.24 96.28 96.26 Avg2. 17094 17101 16458 96.24 96.28 96.26 Current max chunk-based F1: 96.27 (iteration 86) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 90 Log-likelihood = -54082.420385 Norm (log-likelihood gradient vector) = 3832.996776 Norm (lambda vector) = 96.024669 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17105 16754 97.95 98.01 97.98 i-np 19923 19932 19546 98.06 98.11 98.09 o 29640 29620 29298 98.91 98.85 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.32 98.31 Avg2. 66657 66657 65598 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17105 16467 96.27 96.33 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.27 96.33 96.30 Avg2. 17094 17105 16467 96.27 96.33 96.30 Current max chunk-based F1: 96.30 (iteration 90) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 91 Log-likelihood = -53954.295541 Norm (log-likelihood gradient vector) = 2618.220256 Norm (lambda vector) = 95.999863 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17098 16749 97.96 97.98 97.97 i-np 19923 19928 19546 98.08 98.11 98.10 o 29640 29631 29305 98.90 98.87 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.32 98.32 Avg2. 66657 66657 65600 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17098 16461 96.27 96.30 96.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.27 96.30 96.29 Avg2. 17094 17098 16461 96.27 96.30 96.29 Current max chunk-based F1: 96.30 (iteration 90) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 92 Log-likelihood = -53802.811109 Norm (log-likelihood gradient vector) = 2204.439831 Norm (lambda vector) = 96.176995 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17078 16742 98.03 97.94 97.99 i-np 19923 19963 19566 98.01 98.21 98.11 o 29640 29616 29299 98.93 98.85 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.33 98.33 Avg2. 66657 66657 65607 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17078 16455 96.35 96.26 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.26 96.31 Avg2. 17094 17078 16455 96.35 96.26 96.31 Current max chunk-based F1: 96.31 (iteration 92) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 93 Log-likelihood = -53336.052958 Norm (log-likelihood gradient vector) = 2513.391375 Norm (lambda vector) = 97.028486 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17133 16771 97.89 98.11 98.00 i-np 19923 19857 19497 98.19 97.86 98.02 o 29640 29667 29320 98.83 98.92 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.30 98.30 Avg2. 66657 66657 65588 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17133 16471 96.14 96.36 96.25 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.14 96.36 96.25 Avg2. 17094 17133 16471 96.14 96.36 96.25 Current max chunk-based F1: 96.31 (iteration 92) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 94 Log-likelihood = -53190.115143 Norm (log-likelihood gradient vector) = 9085.967093 Norm (lambda vector) = 98.869593 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17106 16759 97.97 98.04 98.01 i-np 19923 19911 19532 98.10 98.04 98.07 o 29640 29640 29310 98.89 98.89 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.32 98.32 Avg2. 66657 66657 65601 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17106 16465 96.25 96.32 96.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.32 96.29 Avg2. 17094 17106 16465 96.25 96.32 96.29 Current max chunk-based F1: 96.31 (iteration 92) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 95 Log-likelihood = -52973.458084 Norm (log-likelihood gradient vector) = 5119.619307 Norm (lambda vector) = 97.953872 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17084 16748 98.03 97.98 98.00 i-np 19923 19956 19559 98.01 98.17 98.09 o 29640 29617 29299 98.93 98.85 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.33 98.33 Avg2. 66657 66657 65606 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17084 16459 96.34 96.29 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.34 96.29 96.31 Avg2. 17094 17084 16459 96.34 96.29 96.31 Current max chunk-based F1: 96.31 (iteration 95) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 96 Log-likelihood = -51985.011248 Norm (log-likelihood gradient vector) = 2675.426670 Norm (lambda vector) = 99.397933 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17088 16747 98.00 97.97 97.99 i-np 19923 19965 19556 97.95 98.16 98.05 o 29640 29604 29291 98.94 98.82 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.32 98.31 Avg2. 66657 66657 65594 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17088 16452 96.28 96.24 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.28 96.24 96.26 Avg2. 17094 17088 16452 96.28 96.24 96.26 Current max chunk-based F1: 96.31 (iteration 95) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 97 Log-likelihood = -51279.947308 Norm (log-likelihood gradient vector) = 2187.029134 Norm (lambda vector) = 100.417868 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17078 16749 98.07 97.98 98.03 i-np 19923 19980 19569 97.94 98.22 98.08 o 29640 29599 29290 98.96 98.82 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.34 98.33 Avg2. 66657 66657 65608 98.43 98.43 98.43 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17078 16462 96.39 96.30 96.35 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.39 96.30 96.35 Avg2. 17094 17078 16462 96.39 96.30 96.35 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 98 Log-likelihood = -50563.558881 Norm (log-likelihood gradient vector) = 2294.189108 Norm (lambda vector) = 101.127657 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17106 16753 97.94 98.01 97.97 i-np 19923 19886 19505 98.08 97.90 97.99 o 29640 29665 29311 98.81 98.89 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.27 98.27 Avg2. 66657 66657 65569 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17106 16456 96.20 96.27 96.23 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.20 96.27 96.23 Avg2. 17094 17106 16456 96.20 96.27 96.23 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 99 Log-likelihood = -49698.375201 Norm (log-likelihood gradient vector) = 5694.612090 Norm (lambda vector) = 102.524342 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17053 16731 98.11 97.88 97.99 i-np 19923 20004 19581 97.89 98.28 98.08 o 29640 29600 29286 98.94 98.81 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.32 98.32 Avg2. 66657 66657 65598 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17053 16446 96.44 96.21 96.32 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.44 96.21 96.32 Avg2. 17094 17053 16446 96.44 96.21 96.32 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 100 Log-likelihood = -49049.626911 Norm (log-likelihood gradient vector) = 3347.748816 Norm (lambda vector) = 103.251056 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17072 16734 98.02 97.89 97.96 i-np 19923 19950 19546 97.97 98.11 98.04 o 29640 29635 29298 98.86 98.85 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.28 98.28 Avg2. 66657 66657 65578 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17072 16446 96.33 96.21 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.33 96.21 96.27 Avg2. 17094 17072 16446 96.33 96.21 96.27 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 101 Log-likelihood = -48927.175859 Norm (log-likelihood gradient vector) = 1936.711503 Norm (lambda vector) = 103.067447 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17090 16742 97.96 97.94 97.95 i-np 19923 19905 19518 98.06 97.97 98.01 o 29640 29662 29309 98.81 98.88 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.26 98.27 Avg2. 66657 66657 65569 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17090 16451 96.26 96.24 96.25 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.26 96.24 96.25 Avg2. 17094 17090 16451 96.26 96.24 96.25 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 102 Log-likelihood = -48792.885237 Norm (log-likelihood gradient vector) = 2236.832471 Norm (lambda vector) = 103.013437 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17087 16740 97.97 97.93 97.95 i-np 19923 19914 19522 98.03 97.99 98.01 o 29640 29656 29306 98.82 98.87 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.26 98.27 Avg2. 66657 66657 65568 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17087 16447 96.25 96.22 96.23 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.22 96.23 Avg2. 17094 17087 16447 96.25 96.22 96.23 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 103 Log-likelihood = -48396.625012 Norm (log-likelihood gradient vector) = 2254.097427 Norm (lambda vector) = 103.458231 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17100 16744 97.92 97.95 97.94 i-np 19923 19887 19509 98.10 97.92 98.01 o 29640 29670 29310 98.79 98.89 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.25 98.26 Avg2. 66657 66657 65563 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17100 16454 96.22 96.26 96.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.22 96.26 96.24 Avg2. 17094 17100 16454 96.22 96.26 96.24 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 104 Log-likelihood = -46613.460242 Norm (log-likelihood gradient vector) = 3433.117117 Norm (lambda vector) = 105.591622 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17108 16747 97.89 97.97 97.93 i-np 19923 19954 19548 97.97 98.12 98.04 o 29640 29595 29274 98.92 98.77 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.26 98.28 98.27 Avg2. 66657 66657 65569 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17108 16463 96.23 96.31 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.23 96.31 96.27 Avg2. 17094 17108 16463 96.23 96.31 96.27 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 105 Log-likelihood = -45118.756991 Norm (log-likelihood gradient vector) = 5595.781674 Norm (lambda vector) = 107.806478 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17076 16738 98.02 97.92 97.97 i-np 19923 19981 19572 97.95 98.24 98.10 o 29640 29600 29285 98.94 98.80 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.32 98.31 Avg2. 66657 66657 65595 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17076 16458 96.38 96.28 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.38 96.28 96.33 Avg2. 17094 17076 16458 96.38 96.28 96.33 Current max chunk-based F1: 96.35 (iteration 97) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 106 Log-likelihood = -44438.884059 Norm (log-likelihood gradient vector) = 2921.356449 Norm (lambda vector) = 107.781532 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17071 16744 98.08 97.95 98.02 i-np 19923 19969 19575 98.03 98.25 98.14 o 29640 29617 29300 98.93 98.85 98.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.35 98.35 98.35 Avg2. 66657 66657 65619 98.44 98.44 98.44 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17071 16470 96.48 96.35 96.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.48 96.35 96.41 Avg2. 17094 17071 16470 96.48 96.35 96.41 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 107 Log-likelihood = -44095.932527 Norm (log-likelihood gradient vector) = 1827.940140 Norm (lambda vector) = 107.781169 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17070 16739 98.06 97.92 97.99 i-np 19923 19965 19566 98.00 98.21 98.10 o 29640 29622 29297 98.90 98.84 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.32 98.32 Avg2. 66657 66657 65602 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17070 16463 96.44 96.31 96.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.44 96.31 96.38 Avg2. 17094 17070 16463 96.44 96.31 96.38 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 108 Log-likelihood = -43751.992028 Norm (log-likelihood gradient vector) = 1729.326799 Norm (lambda vector) = 108.113823 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17053 16723 98.06 97.83 97.95 i-np 19923 20022 19584 97.81 98.30 98.05 o 29640 29582 29270 98.95 98.75 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.29 98.28 Avg2. 66657 66657 65577 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17053 16438 96.39 96.16 96.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.39 96.16 96.28 Avg2. 17094 17053 16438 96.39 96.16 96.28 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 109 Log-likelihood = -43440.173041 Norm (log-likelihood gradient vector) = 5563.038021 Norm (lambda vector) = 109.759704 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17096 16742 97.93 97.94 97.94 i-np 19923 19899 19515 98.07 97.95 98.01 o 29640 29662 29306 98.80 98.87 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.26 98.26 Avg2. 66657 66657 65563 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17096 16455 96.25 96.26 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.26 96.26 Avg2. 17094 17096 16455 96.25 96.26 96.26 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 110 Log-likelihood = -43207.551280 Norm (log-likelihood gradient vector) = 3283.170195 Norm (lambda vector) = 110.762420 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17089 16739 97.95 97.92 97.94 i-np 19923 19939 19540 98.00 98.08 98.04 o 29640 29629 29293 98.87 98.83 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.28 98.27 Avg2. 66657 66657 65572 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17089 16456 96.30 96.27 96.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.30 96.27 96.28 Avg2. 17094 17089 16456 96.30 96.27 96.28 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 111 Log-likelihood = -42988.245229 Norm (log-likelihood gradient vector) = 1941.950197 Norm (lambda vector) = 111.190196 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17083 16738 97.98 97.92 97.95 i-np 19923 19971 19557 97.93 98.16 98.04 o 29640 29603 29279 98.91 98.78 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.29 98.28 Avg2. 66657 66657 65574 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17083 16457 96.34 96.27 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.34 96.27 96.30 Avg2. 17094 17083 16457 96.34 96.27 96.30 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 112 Log-likelihood = -42784.838300 Norm (log-likelihood gradient vector) = 1596.482015 Norm (lambda vector) = 111.856001 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17086 16742 97.99 97.94 97.96 i-np 19923 19980 19563 97.91 98.19 98.05 o 29640 29591 29274 98.93 98.77 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.30 98.29 Avg2. 66657 66657 65579 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17086 16462 96.35 96.30 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.30 96.33 Avg2. 17094 17086 16462 96.35 96.30 96.33 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 113 Log-likelihood = -42429.899824 Norm (log-likelihood gradient vector) = 2154.015562 Norm (lambda vector) = 112.623182 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17079 16739 98.01 97.92 97.97 i-np 19923 19991 19567 97.88 98.21 98.05 o 29640 29587 29270 98.93 98.75 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.30 98.28 Avg2. 66657 66657 65576 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17079 16457 96.36 96.27 96.32 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.36 96.27 96.32 Avg2. 17094 17079 16457 96.36 96.27 96.32 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 114 Log-likelihood = -41640.083841 Norm (log-likelihood gradient vector) = 2438.687476 Norm (lambda vector) = 114.146964 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17003 16703 98.24 97.71 97.97 i-np 19923 20067 19604 97.69 98.40 98.04 o 29640 29587 29275 98.95 98.77 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.29 98.29 Avg2. 66657 66657 65582 98.39 98.39 98.39 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17003 16408 96.50 95.99 96.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.50 95.99 96.24 Avg2. 17094 17003 16408 96.50 95.99 96.24 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 115 Log-likelihood = -42486.922178 Norm (log-likelihood gradient vector) = 13601.518386 Norm (lambda vector) = 117.672966 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17047 16717 98.06 97.79 97.93 i-np 19923 20029 19581 97.76 98.28 98.02 o 29640 29581 29265 98.93 98.73 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.27 98.26 Avg2. 66657 66657 65563 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17047 16429 96.37 96.11 96.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.37 96.11 96.24 Avg2. 17094 17047 16429 96.37 96.11 96.24 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 116 Log-likelihood = -41230.811601 Norm (log-likelihood gradient vector) = 5711.648965 Norm (lambda vector) = 115.464626 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17065 16728 98.03 97.86 97.94 i-np 19923 19996 19566 97.85 98.21 98.03 o 29640 29596 29273 98.91 98.76 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.26 98.28 98.27 Avg2. 66657 66657 65567 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17065 16442 96.35 96.19 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.19 96.27 Avg2. 17094 17065 16442 96.35 96.19 96.27 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 117 Log-likelihood = -40549.995827 Norm (log-likelihood gradient vector) = 2572.012035 Norm (lambda vector) = 115.906253 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17082 16746 98.03 97.96 98.00 i-np 19923 19949 19554 98.02 98.15 98.08 o 29640 29626 29298 98.89 98.85 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.32 98.32 Avg2. 66657 66657 65598 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17082 16465 96.39 96.32 96.35 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.39 96.32 96.35 Avg2. 17094 17082 16465 96.39 96.32 96.35 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 118 Log-likelihood = -40091.355275 Norm (log-likelihood gradient vector) = 1524.393489 Norm (lambda vector) = 116.076800 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17096 16752 97.99 98.00 97.99 i-np 19923 19916 19536 98.09 98.06 98.07 o 29640 29645 29306 98.86 98.87 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.31 98.31 Avg2. 66657 66657 65594 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17096 16472 96.35 96.36 96.36 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.36 96.36 Avg2. 17094 17096 16472 96.35 96.36 96.36 Current max chunk-based F1: 96.41 (iteration 106) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 119 Log-likelihood = -39553.396633 Norm (log-likelihood gradient vector) = 2203.703674 Norm (lambda vector) = 116.530126 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17099 16756 97.99 98.02 98.01 i-np 19923 19917 19545 98.13 98.10 98.12 o 29640 29641 29309 98.88 98.88 98.88 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.34 98.34 98.34 Avg2. 66657 66657 65610 98.43 98.43 98.43 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17099 16485 96.41 96.44 96.42 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.41 96.44 96.42 Avg2. 17094 17099 16485 96.41 96.44 96.42 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 120 Log-likelihood = -38742.684263 Norm (log-likelihood gradient vector) = 2685.553985 Norm (lambda vector) = 117.418207 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17173 16779 97.71 98.16 97.93 i-np 19923 19802 19450 98.22 97.63 97.92 o 29640 29682 29308 98.74 98.88 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.22 98.22 98.22 Avg2. 66657 66657 65537 98.32 98.32 98.32 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17173 16476 95.94 96.38 96.16 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.94 96.38 96.16 Avg2. 17094 17173 16476 95.94 96.38 96.16 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 121 Log-likelihood = -37861.558271 Norm (log-likelihood gradient vector) = 10267.730141 Norm (lambda vector) = 120.064870 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17123 16762 97.89 98.06 97.97 i-np 19923 19881 19510 98.13 97.93 98.03 o 29640 29653 29303 98.82 98.86 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.28 98.28 Avg2. 66657 66657 65575 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17123 16481 96.25 96.41 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.41 96.33 Avg2. 17094 17123 16481 96.25 96.41 96.33 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 122 Log-likelihood = -38118.809631 Norm (log-likelihood gradient vector) = 4532.931122 Norm (lambda vector) = 118.357744 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17102 16755 97.97 98.02 97.99 i-np 19923 19934 19549 98.07 98.12 98.10 o 29640 29621 29293 98.89 98.83 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.32 98.32 Avg2. 66657 66657 65597 98.41 98.41 98.41 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17102 16486 96.40 96.44 96.42 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.40 96.44 96.42 Avg2. 17094 17102 16486 96.40 96.44 96.42 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 123 Log-likelihood = -37301.024393 Norm (log-likelihood gradient vector) = 2723.839065 Norm (lambda vector) = 119.326692 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17099 16751 97.96 97.99 97.98 i-np 19923 19961 19562 98.00 98.19 98.09 o 29640 29597 29280 98.93 98.79 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.32 98.31 Avg2. 66657 66657 65593 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17099 16479 96.37 96.40 96.39 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.37 96.40 96.39 Avg2. 17094 17099 16479 96.37 96.40 96.39 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 124 Log-likelihood = -36340.622838 Norm (log-likelihood gradient vector) = 1457.737819 Norm (lambda vector) = 120.642303 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17085 16743 98.00 97.95 97.97 i-np 19923 19976 19565 97.94 98.20 98.07 o 29640 29596 29278 98.93 98.78 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.31 98.30 Avg2. 66657 66657 65586 98.39 98.39 98.39 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17085 16465 96.37 96.32 96.35 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.37 96.32 96.35 Avg2. 17094 17085 16465 96.37 96.32 96.35 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 125 Log-likelihood = -35823.818240 Norm (log-likelihood gradient vector) = 1750.059148 Norm (lambda vector) = 121.395579 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17080 16740 98.01 97.93 97.97 i-np 19923 19983 19569 97.93 98.22 98.08 o 29640 29594 29279 98.94 98.78 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.31 98.30 Avg2. 66657 66657 65588 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17080 16460 96.37 96.29 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.37 96.29 96.33 Avg2. 17094 17080 16460 96.37 96.29 96.33 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 126 Log-likelihood = -35153.111551 Norm (log-likelihood gradient vector) = 1519.297340 Norm (lambda vector) = 122.521322 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17048 16724 98.10 97.84 97.97 i-np 19923 20005 19577 97.86 98.26 98.06 o 29640 29604 29283 98.92 98.80 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.30 98.30 Avg2. 66657 66657 65584 98.39 98.39 98.39 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17048 16441 96.44 96.18 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.44 96.18 96.31 Avg2. 17094 17048 16441 96.44 96.18 96.31 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 127 Log-likelihood = -34403.591307 Norm (log-likelihood gradient vector) = 4798.740314 Norm (lambda vector) = 124.578003 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17073 16741 98.06 97.93 98.00 i-np 19923 19960 19562 98.01 98.19 98.10 o 29640 29624 29298 98.90 98.85 98.87 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.32 98.32 98.32 Avg2. 66657 66657 65601 98.42 98.42 98.42 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17073 16463 96.43 96.31 96.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.43 96.31 96.37 Avg2. 17094 17073 16463 96.43 96.31 96.37 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 128 Log-likelihood = -33699.741252 Norm (log-likelihood gradient vector) = 1731.574805 Norm (lambda vector) = 125.597744 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17097 16751 97.98 97.99 97.98 i-np 19923 19916 19533 98.08 98.04 98.06 o 29640 29644 29304 98.85 98.87 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.30 98.30 98.30 Avg2. 66657 66657 65588 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17097 16469 96.33 96.34 96.34 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.33 96.34 96.34 Avg2. 17094 17097 16469 96.33 96.34 96.34 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 129 Log-likelihood = -33388.030274 Norm (log-likelihood gradient vector) = 1463.985356 Norm (lambda vector) = 126.353220 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17106 16754 97.94 98.01 97.98 i-np 19923 19902 19523 98.10 97.99 98.04 o 29640 29649 29304 98.84 98.87 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.29 98.29 Avg2. 66657 66657 65581 98.39 98.39 98.39 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17106 16466 96.26 96.33 96.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.26 96.33 96.29 Avg2. 17094 17106 16466 96.26 96.33 96.29 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 130 Log-likelihood = -33104.211371 Norm (log-likelihood gradient vector) = 1813.572903 Norm (lambda vector) = 127.392524 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17104 16756 97.97 98.02 97.99 i-np 19923 19920 19537 98.08 98.06 98.07 o 29640 29633 29299 98.87 98.85 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.31 98.31 98.31 Avg2. 66657 66657 65592 98.40 98.40 98.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17104 16472 96.30 96.36 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.30 96.36 96.33 Avg2. 17094 17104 16472 96.30 96.36 96.33 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 131 Log-likelihood = -32706.442040 Norm (log-likelihood gradient vector) = 1924.550495 Norm (lambda vector) = 129.235940 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17219 16777 97.43 98.15 97.79 i-np 19923 19705 19375 98.33 97.25 97.78 o 29640 29733 29315 98.59 98.90 98.75 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.12 98.10 98.11 Avg2. 66657 66657 65467 98.21 98.21 98.21 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17219 16456 95.57 96.27 95.92 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.57 96.27 95.92 Avg2. 17094 17219 16456 95.57 96.27 95.92 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 132 Log-likelihood = -34029.137156 Norm (log-likelihood gradient vector) = 13686.463285 Norm (lambda vector) = 134.412729 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17134 16760 97.82 98.05 97.93 i-np 19923 19858 19488 98.14 97.82 97.98 o 29640 29665 29302 98.78 98.86 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.24 98.24 98.24 Avg2. 66657 66657 65550 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17134 16465 96.10 96.32 96.21 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.10 96.32 96.21 Avg2. 17094 17134 16465 96.10 96.32 96.21 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 133 Log-likelihood = -32487.599325 Norm (log-likelihood gradient vector) = 3801.741186 Norm (lambda vector) = 130.631325 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17116 16751 97.87 97.99 97.93 i-np 19923 19906 19517 98.05 97.96 98.00 o 29640 29635 29288 98.83 98.81 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.26 98.25 Avg2. 66657 66657 65556 98.35 98.35 98.35 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17116 16467 96.21 96.33 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.21 96.33 96.27 Avg2. 17094 17116 16467 96.21 96.33 96.27 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 134 Log-likelihood = -32184.046844 Norm (log-likelihood gradient vector) = 1863.582477 Norm (lambda vector) = 132.354501 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17106 16741 97.87 97.93 97.90 i-np 19923 19934 19532 97.98 98.04 98.01 o 29640 29617 29278 98.86 98.78 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.25 98.24 Avg2. 66657 66657 65551 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17106 16457 96.21 96.27 96.24 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.21 96.27 96.24 Avg2. 17094 17106 16457 96.21 96.27 96.24 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 135 Log-likelihood = -31977.520120 Norm (log-likelihood gradient vector) = 1390.538308 Norm (lambda vector) = 133.083646 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17091 16737 97.93 97.91 97.92 i-np 19923 19964 19550 97.93 98.13 98.03 o 29640 29602 29274 98.89 98.77 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.27 98.26 Avg2. 66657 66657 65561 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17091 16453 96.27 96.25 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.27 96.25 96.26 Avg2. 17094 17091 16453 96.27 96.25 96.26 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 136 Log-likelihood = -31623.792635 Norm (log-likelihood gradient vector) = 1714.265460 Norm (lambda vector) = 134.121695 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17085 16738 97.97 97.92 97.94 i-np 19923 19962 19554 97.96 98.15 98.05 o 29640 29610 29282 98.89 98.79 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.29 98.28 Avg2. 66657 66657 65574 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17085 16462 96.35 96.30 96.33 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.30 96.33 Avg2. 17094 17085 16462 96.35 96.30 96.33 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 137 Log-likelihood = -31098.769452 Norm (log-likelihood gradient vector) = 1827.994653 Norm (lambda vector) = 135.773756 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17095 16736 97.90 97.91 97.90 i-np 19923 19930 19534 98.01 98.05 98.03 o 29640 29632 29291 98.85 98.82 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.25 98.26 98.26 Avg2. 66657 66657 65561 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17095 16456 96.26 96.27 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.26 96.27 96.26 Avg2. 17094 17095 16456 96.26 96.27 96.26 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 138 Log-likelihood = -30318.354393 Norm (log-likelihood gradient vector) = 2743.163503 Norm (lambda vector) = 139.551568 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17051 16717 98.04 97.79 97.92 i-np 19923 20010 19574 97.82 98.25 98.03 o 29640 29596 29274 98.91 98.77 98.84 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.26 98.27 98.26 Avg2. 66657 66657 65565 98.36 98.36 98.36 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17051 16428 96.35 96.10 96.22 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.10 96.22 Avg2. 17094 17051 16428 96.35 96.10 96.22 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 139 Log-likelihood = -29635.320895 Norm (log-likelihood gradient vector) = 4572.906114 Norm (lambda vector) = 143.767524 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17099 16735 97.87 97.90 97.89 i-np 19923 19927 19526 97.99 98.01 98.00 o 29640 29631 29286 98.84 98.81 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.24 98.23 Avg2. 66657 66657 65547 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17099 16449 96.20 96.23 96.21 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.20 96.23 96.21 Avg2. 17094 17099 16449 96.20 96.23 96.21 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 140 Log-likelihood = -29236.925841 Norm (log-likelihood gradient vector) = 1331.629668 Norm (lambda vector) = 143.241742 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17108 16736 97.83 97.91 97.87 i-np 19923 19916 19513 97.98 97.94 97.96 o 29640 29633 29283 98.82 98.80 98.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.21 98.21 98.21 Avg2. 66657 66657 65532 98.31 98.31 98.31 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17108 16443 96.11 96.19 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.11 96.19 96.15 Avg2. 17094 17108 16443 96.11 96.19 96.15 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 141 Log-likelihood = -29058.425425 Norm (log-likelihood gradient vector) = 1410.260705 Norm (lambda vector) = 143.247856 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 30 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17117 16744 97.82 97.95 97.89 i-np 19923 19900 19510 98.04 97.93 97.98 o 29640 29640 29290 98.82 98.82 98.82 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.23 98.23 98.23 Avg2. 66657 66657 65544 98.33 98.33 98.33 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17117 16455 96.13 96.26 96.20 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.13 96.26 96.20 Avg2. 17094 17117 16455 96.13 96.26 96.20 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 142 Log-likelihood = -28694.654793 Norm (log-likelihood gradient vector) = 1710.345324 Norm (lambda vector) = 143.839550 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17140 16759 97.78 98.04 97.91 i-np 19923 19871 19497 98.12 97.86 97.99 o 29640 29646 29296 98.82 98.84 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.24 98.25 98.24 Avg2. 66657 66657 65552 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17140 16465 96.06 96.32 96.19 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.06 96.32 96.19 Avg2. 17094 17140 16465 96.06 96.32 96.19 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 143 Log-likelihood = -27614.251456 Norm (log-likelihood gradient vector) = 2228.495265 Norm (lambda vector) = 146.240148 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 16964 16667 98.25 97.50 97.87 i-np 19923 20150 19614 97.34 98.45 97.89 o 29640 29543 29234 98.95 98.63 98.79 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.18 98.19 98.19 Avg2. 66657 66657 65515 98.29 98.29 98.29 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 16964 16361 96.45 95.71 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.45 95.71 96.08 Avg2. 17094 16964 16361 96.45 95.71 96.08 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 144 Log-likelihood = -28243.435028 Norm (log-likelihood gradient vector) = 14544.462950 Norm (lambda vector) = 151.950522 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 28 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17067 16734 98.05 97.89 97.97 i-np 19923 19976 19562 97.93 98.19 98.06 o 29640 29614 29289 98.90 98.82 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.29 98.30 98.30 Avg2. 66657 66657 65585 98.39 98.39 98.39 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17067 16452 96.40 96.24 96.32 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.40 96.24 96.32 Avg2. 17094 17067 16452 96.40 96.24 96.32 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 145 Log-likelihood = -27046.803029 Norm (log-likelihood gradient vector) = 5387.658053 Norm (lambda vector) = 148.682379 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 28 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17108 16750 97.91 97.99 97.95 i-np 19923 19922 19531 98.04 98.03 98.03 o 29640 29627 29292 98.87 98.83 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.28 98.28 Avg2. 66657 66657 65573 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17108 16466 96.25 96.33 96.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.33 96.29 Avg2. 17094 17108 16466 96.25 96.33 96.29 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 146 Log-likelihood = -27174.676490 Norm (log-likelihood gradient vector) = 2556.988814 Norm (lambda vector) = 147.464450 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17105 16749 97.92 97.98 97.95 i-np 19923 19921 19535 98.06 98.05 98.06 o 29640 29631 29295 98.87 98.84 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.29 98.29 Avg2. 66657 66657 65579 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17105 16467 96.27 96.33 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.27 96.33 96.30 Avg2. 17094 17105 16467 96.27 96.33 96.30 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 147 Log-likelihood = -26072.196675 Norm (log-likelihood gradient vector) = 1505.240310 Norm (lambda vector) = 150.812175 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17096 16745 97.95 97.96 97.95 i-np 19923 19931 19537 98.02 98.06 98.04 o 29640 29630 29295 98.87 98.84 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.29 98.28 Avg2. 66657 66657 65577 98.38 98.38 98.38 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17096 16463 96.30 96.31 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.30 96.31 96.30 Avg2. 17094 17096 16463 96.30 96.31 96.30 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 148 Log-likelihood = -25390.968305 Norm (log-likelihood gradient vector) = 1048.440000 Norm (lambda vector) = 152.778434 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17101 16741 97.89 97.93 97.91 i-np 19923 19944 19532 97.93 98.04 97.99 o 29640 29612 29280 98.88 98.79 98.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.24 98.25 98.24 Avg2. 66657 66657 65553 98.34 98.34 98.34 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17101 16452 96.20 96.24 96.22 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.20 96.24 96.22 Avg2. 17094 17101 16452 96.20 96.24 96.22 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds Iteration: 149 Log-likelihood = -24421.336831 Norm (log-likelihood gradient vector) = 1189.149549 Norm (lambda vector) = 155.984694 Log-likelihood and gradient computational time: 29 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17093 16738 97.92 97.92 97.92 i-np 19923 19882 19509 98.12 97.92 98.02 o 29640 29682 29323 98.79 98.93 98.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.28 98.26 98.27 Avg2. 66657 66657 65570 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17093 16454 96.26 96.26 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.26 96.26 96.26 Avg2. 17094 17093 16454 96.26 96.26 96.26 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 30 seconds Iteration: 150 Log-likelihood = -23907.973097 Norm (log-likelihood gradient vector) = 3407.667621 Norm (lambda vector) = 158.789673 Log-likelihood and gradient computational time: 28 seconds Training iteration elapsed: 29 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 17094 17102 16746 97.92 97.96 97.94 i-np 19923 19921 19526 98.02 98.01 98.01 o 29640 29634 29297 98.86 98.84 98.85 ----- ------ ----- ----- ------- ------- ------------- Avg1. 98.27 98.27 98.27 Avg2. 66657 66657 65569 98.37 98.37 98.37 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 17094 17102 16460 96.25 96.29 96.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.25 96.29 96.27 Avg2. 17094 17102 16460 96.25 96.29 96.27 Current max chunk-based F1: 96.42 (iteration 119) Training iteration elapsed (including evaluation time): 29 seconds The training process elapsed: 4413 seconds