📄 trainlog.txt
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Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 37 Log-likelihood = -689.565855 Norm(log-likelihood gradient vector) = 166.555233 Norm(lambda vector) = 80.082637 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 512 95.88 96.79 96.33 o 725 749 721 96.26 99.45 97.83 i-np 691 662 651 98.34 94.21 96.23 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.83 96.82 96.82 Avg2. 1945 1945 1884 96.86 96.86 96.86 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 491 91.95 92.82 92.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.95 92.82 92.38 Avg2. 529 534 491 91.95 92.82 92.38 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 38 Log-likelihood = -629.807429 Norm(log-likelihood gradient vector) = 58.758443 Norm(lambda vector) = 81.957445 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 534 512 95.88 96.79 96.33 o 725 747 721 96.52 99.45 97.96 i-np 691 664 653 98.34 94.50 96.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.91 96.91 96.91 Avg2. 1945 1945 1886 96.97 96.97 96.97 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 491 91.95 92.82 92.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.95 92.82 92.38 Avg2. 529 534 491 91.95 92.82 92.38 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 39 Log-likelihood = -607.920013 Norm(log-likelihood gradient vector) = 48.497812 Norm(lambda vector) = 82.528934 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 537 513 95.53 96.98 96.25 o 725 750 722 96.27 99.59 97.90 i-np 691 658 649 98.63 93.92 96.22 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.81 96.83 96.82 Avg2. 1945 1945 1884 96.86 96.86 96.86 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 491 91.43 92.82 92.12 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.43 92.82 92.12 Avg2. 529 537 491 91.43 92.82 92.12 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 40 Log-likelihood = -562.102825 Norm(log-likelihood gradient vector) = 32.321593 Norm(lambda vector) = 84.285747 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 538 512 95.17 96.79 95.97 o 725 751 722 96.14 99.59 97.83 i-np 691 656 647 98.63 93.63 96.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.64 96.67 96.66 Avg2. 1945 1945 1881 96.71 96.71 96.71 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 538 489 90.89 92.44 91.66 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.89 92.44 91.66 Avg2. 529 538 489 90.89 92.44 91.66 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 41 Log-likelihood = -508.560227 Norm(log-likelihood gradient vector) = 39.517495 Norm(lambda vector) = 87.277170 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 530 508 95.85 96.03 95.94 o 725 743 719 96.77 99.17 97.96 i-np 691 672 656 97.62 94.93 96.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.75 96.71 96.73 Avg2. 1945 1945 1883 96.81 96.81 96.81 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 530 484 91.32 91.49 91.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.32 91.49 91.41 Avg2. 529 530 484 91.32 91.49 91.41 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 42 Log-likelihood = -486.672774 Norm(log-likelihood gradient vector) = 164.653400 Norm(lambda vector) = 91.083795 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 536 511 95.34 96.60 95.96 o 725 750 722 96.27 99.59 97.90 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.70 96.70 96.70 Avg2. 1945 1945 1882 96.76 96.76 96.76 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 536 488 91.04 92.25 91.64 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.04 92.25 91.64 Avg2. 529 536 488 91.04 92.25 91.64 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 43 Log-likelihood = -487.542661 Norm(log-likelihood gradient vector) = 60.751106 Norm(lambda vector) = 88.756574 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 537 511 95.16 96.60 95.87 o 725 750 722 96.27 99.59 97.90 i-np 691 658 648 98.48 93.78 96.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.64 96.65 96.64 Avg2. 1945 1945 1881 96.71 96.71 96.71 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 488 90.88 92.25 91.56 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.88 92.25 91.56 Avg2. 529 537 488 90.88 92.25 91.56 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 44 Log-likelihood = -469.798390 Norm(log-likelihood gradient vector) = 38.519398 Norm(lambda vector) = 89.675731 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 537 511 95.16 96.60 95.87 o 725 750 722 96.27 99.59 97.90 i-np 691 658 648 98.48 93.78 96.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.64 96.65 96.64 Avg2. 1945 1945 1881 96.71 96.71 96.71 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 488 90.88 92.25 91.56 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.88 92.25 91.56 Avg2. 529 537 488 90.88 92.25 91.56 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 45 Log-likelihood = -447.284542 Norm(log-likelihood gradient vector) = 31.830759 Norm(lambda vector) = 91.545305 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 537 512 95.34 96.79 96.06 o 725 749 722 96.40 99.59 97.96 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.74 96.76 96.75 Avg2. 1945 1945 1883 96.81 96.81 96.81 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 489 91.06 92.44 91.74 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.06 92.44 91.74 Avg2. 529 537 489 91.06 92.44 91.74 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 46 Log-likelihood = -440.430558 Norm(log-likelihood gradient vector) = 31.988613 Norm(lambda vector) = 93.639895 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 725 746 722 96.78 99.59 98.16 i-np 691 660 651 98.64 94.21 96.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.99 96.96 Avg2. 1945 1945 1887 97.02 97.02 97.02 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: 47 Log-likelihood = -439.727547 Norm(log-likelihood gradient vector) = 93.390461 Norm(lambda vector) = 97.525655 Iteration elapsed: 2 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 725 746 722 96.78 99.59 98.16 i-np 691 660 651 98.64 94.21 96.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.99 96.96 Avg2. 1945 1945 1887 97.02 97.02 97.02 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): 2 secondsIteration: 48 Log-likelihood = -435.807013 Norm(log-likelihood gradient vector) = 51.727578 Norm(lambda vector) = 100.255725 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 725 746 722 96.78 99.59 98.16 i-np 691 660 651 98.64 94.21 96.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.93 96.99 96.96 Avg2. 1945 1945 1887 97.02 97.02 97.02 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: 49 Log-likelihood = -422.232281 Norm(log-likelihood gradient vector) = 30.394636 Norm(lambda vector) = 99.185419 Iteration elapsed: 2 seconds Label-based performance evaluation:⌨️ 快捷键说明
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