📄 trainlog.txt
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Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 532 493 92.67 93.19 92.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.67 93.19 92.93 Avg2. 529 532 493 92.67 93.19 92.93 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 25 Log-likelihood = -1163.592896 Norm(log-likelihood gradient vector) = 113.871440 Norm(lambda vector) = 59.674526 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 533 511 95.87 96.60 96.23 o 725 752 722 96.01 99.59 97.77 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.69 96.65 96.67 Avg2. 1945 1945 1881 96.71 96.71 96.71 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 533 487 91.37 92.06 91.71 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.37 92.06 91.71 Avg2. 529 533 487 91.37 92.06 91.71 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 26 Log-likelihood = -1156.189097 Norm(log-likelihood gradient vector) = 194.921013 Norm(lambda vector) = 59.270862 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 514 96.07 97.16 96.62 o 725 750 722 96.27 99.59 97.90 i-np 691 660 651 98.64 94.21 96.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.99 96.99 96.99 Avg2. 1945 1945 1887 97.02 97.02 97.02 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 493 92.15 93.19 92.67 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.15 93.19 92.67 Avg2. 529 535 493 92.15 93.19 92.67 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 27 Log-likelihood = -1154.162133 Norm(log-likelihood gradient vector) = 251.478948 Norm(lambda vector) = 60.697045 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 514 96.07 97.16 96.62 o 725 751 722 96.14 99.59 97.83 i-np 691 659 650 98.63 94.07 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.95 96.94 96.94 Avg2. 1945 1945 1886 96.97 96.97 96.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 492 91.96 93.01 92.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.96 93.01 92.48 Avg2. 529 535 492 91.96 93.01 92.48 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 28 Log-likelihood = -1085.814942 Norm(log-likelihood gradient vector) = 107.650993 Norm(lambda vector) = 62.122666 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 536 514 95.90 97.16 96.53 o 725 752 722 96.01 99.59 97.77 i-np 691 657 647 98.48 93.63 95.99 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.79 96.79 96.79 Avg2. 1945 1945 1883 96.81 96.81 96.81 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 536 491 91.60 92.82 92.21 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.60 92.82 92.21 Avg2. 529 536 491 91.60 92.82 92.21 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 29 Log-likelihood = -1046.357458 Norm(log-likelihood gradient vector) = 71.378414 Norm(lambda vector) = 64.555113 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 514 96.07 97.16 96.62 o 725 751 722 96.14 99.59 97.83 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.90 96.89 96.89 Avg2. 1945 1945 1885 96.92 96.92 96.92 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 491 91.78 92.82 92.29 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.78 92.82 92.29 Avg2. 529 535 491 91.78 92.82 92.29 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 30 Log-likelihood = -1014.180158 Norm(log-likelihood gradient vector) = 83.077154 Norm(lambda vector) = 66.953281 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 514 96.25 97.16 96.71 o 725 749 722 96.40 99.59 97.96 i-np 691 662 652 98.49 94.36 96.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.05 97.04 97.04 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 493 92.32 93.19 92.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.32 93.19 92.76 Avg2. 529 534 493 92.32 93.19 92.76 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 31 Log-likelihood = -948.361601 Norm(log-likelihood gradient vector) = 88.858259 Norm(lambda vector) = 70.010782 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 539 514 95.36 97.16 96.25 o 725 753 722 95.88 99.59 97.70 i-np 691 653 644 98.62 93.20 95.83 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.62 96.65 96.64 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 539 491 91.09 92.82 91.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.09 92.82 91.95 Avg2. 529 539 491 91.09 92.82 91.95 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 32 Log-likelihood = -925.508126 Norm(log-likelihood gradient vector) = 242.362625 Norm(lambda vector) = 74.051341 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 513 96.07 96.98 96.52 o 725 748 721 96.39 99.45 97.90 i-np 691 663 652 98.34 94.36 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.93 96.93 Avg2. 1945 1945 1886 96.97 96.97 96.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 493 92.32 93.19 92.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.32 93.19 92.76 Avg2. 529 534 493 92.32 93.19 92.76 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 33 Log-likelihood = -868.149846 Norm(log-likelihood gradient vector) = 75.192894 Norm(lambda vector) = 73.648661 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 513 96.07 96.98 96.52 o 725 748 721 96.39 99.45 97.90 i-np 691 663 652 98.34 94.36 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.93 96.93 Avg2. 1945 1945 1886 96.97 96.97 96.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 493 92.32 93.19 92.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.32 93.19 92.76 Avg2. 529 534 493 92.32 93.19 92.76 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 34 Log-likelihood = -847.340354 Norm(log-likelihood gradient vector) = 55.420929 Norm(lambda vector) = 73.377900 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 513 95.89 96.98 96.43 o 725 748 721 96.39 99.45 97.90 i-np 691 662 651 98.34 94.21 96.23 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.87 96.88 96.88 Avg2. 1945 1945 1885 96.92 96.92 96.92 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 492 91.96 93.01 92.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.96 93.01 92.48 Avg2. 529 535 492 91.96 93.01 92.48 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 35 Log-likelihood = -816.799250 Norm(log-likelihood gradient vector) = 64.737245 Norm(lambda vector) = 73.814475 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 513 96.07 96.98 96.52 o 725 748 721 96.39 99.45 97.90 i-np 691 663 652 98.34 94.36 96.31 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.93 96.93 Avg2. 1945 1945 1886 96.97 96.97 96.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 493 92.32 93.19 92.76 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.32 93.19 92.76 Avg2. 529 534 493 92.32 93.19 92.76 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 36 Log-likelihood = -766.649638 Norm(log-likelihood gradient vector) = 65.650185 Norm(lambda vector) = 75.802568 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 531 511 96.23 96.60 96.42 o 725 743 720 96.90 99.31 98.09 i-np 691 671 657 97.91 95.08 96.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.02 97.00 97.01 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 531 491 92.47 92.82 92.64 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.47 92.82 92.64 Avg2. 529 531 491 92.47 92.82 92.64⌨️ 快捷键说明
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