📄 trainlog.txt_second-ordercrfs
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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: 92.67 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 25 Log-likelihood = -861.383280 Norm(log-likelihood gradient vector) = 235.042924 Norm(lambda vector) = 62.836552 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 725 748 721 96.39 99.45 97.90 i-np 691 663 651 98.19 94.21 96.16 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.82 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 529 534 489 91.57 92.44 92.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.57 92.44 92.00 Avg2. 529 534 489 91.57 92.44 92.00 Current max chunk-based F1: 92.67 (iteration 24) Training iteration elapsed (including testing & evaluation time): 4 secondsIteration: 26 Log-likelihood = -816.404322 Norm(log-likelihood gradient vector) = 88.485824 Norm(lambda vector) = 62.540339 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 725 750 721 96.13 99.45 97.76 i-np 691 661 651 98.49 94.21 96.30 ----- ------ ----- ----- ------- ------- ------------- 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: 92.67 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 27 Log-likelihood = -819.545850 Norm(log-likelihood gradient vector) = 68.374599 Norm(lambda vector) = 61.815911 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 725 748 721 96.39 99.45 97.90 i-np 691 663 651 98.19 94.21 96.16 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.82 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 529 534 489 91.57 92.44 92.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.57 92.44 92.00 Avg2. 529 534 489 91.57 92.44 92.00 Current max chunk-based F1: 92.67 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 28 Log-likelihood = -815.289658 Norm(log-likelihood gradient vector) = 76.728470 Norm(lambda vector) = 62.364822 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 532 512 96.24 96.79 96.51 o 725 748 721 96.39 99.45 97.90 i-np 691 665 655 98.50 94.79 96.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.04 97.01 97.03 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: 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 28) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 29 Log-likelihood = -820.899568 Norm(log-likelihood gradient vector) = 80.452025 Norm(lambda vector) = 61.822488 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 725 750 721 96.13 99.45 97.76 i-np 691 661 651 98.49 94.21 96.30 ----- ------ ----- ----- ------- ------- ------------- 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 28) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 30 Log-likelihood = -812.247001 Norm(log-likelihood gradient vector) = 63.768169 Norm(lambda vector) = 62.221532 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 725 747 721 96.52 99.45 97.96 i-np 691 663 653 98.49 94.50 96.45 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.03 97.04 97.03 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 494 92.34 93.38 92.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.34 93.38 92.86 Avg2. 529 535 494 92.34 93.38 92.86 Current max chunk-based F1: 92.93 (iteration 28) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 31 Log-likelihood = -812.014738 Norm(log-likelihood gradient vector) = 86.807824 Norm(lambda vector) = 62.715685 Iteration elapsed: 3 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 725 747 722 96.65 99.59 98.10 i-np 691 664 654 98.49 94.65 96.53 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.13 97.13 97.13 Avg2. 1945 1945 1890 97.17 97.17 97.17 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 534 495 92.70 93.57 93.13 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.70 93.57 93.13 Avg2. 529 534 495 92.70 93.57 93.13 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 32 Log-likelihood = -790.577997 Norm(log-likelihood gradient vector) = 79.817666 Norm(lambda vector) = 64.260061 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 523 506 96.75 95.65 96.20 o 725 740 718 97.03 99.03 98.02 i-np 691 682 660 96.77 95.51 96.14 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.85 96.73 96.79 Avg2. 1945 1945 1884 96.86 96.86 96.86 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 523 482 92.16 91.12 91.63 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.16 91.12 91.63 Avg2. 529 523 482 92.16 91.12 91.63 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 33 Log-likelihood = -780.392047 Norm(log-likelihood gradient vector) = 332.490741 Norm(lambda vector) = 70.993259 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 508 96.58 96.03 96.30 o 725 742 719 96.90 99.17 98.02 i-np 691 677 658 97.19 95.22 96.20 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.89 96.81 96.85 Avg2. 1945 1945 1885 96.92 96.92 96.92 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 485 92.21 91.68 91.94 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.21 91.68 91.94 Avg2. 529 526 485 92.21 91.68 91.94 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 34 Log-likelihood = -747.858696 Norm(log-likelihood gradient vector) = 174.580929 Norm(lambda vector) = 67.630867 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 533 513 96.25 96.98 96.61 o 725 751 724 96.40 99.86 98.10 i-np 691 661 651 98.49 94.21 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.05 97.02 97.03 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 533 490 91.93 92.63 92.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.93 92.63 92.28 Avg2. 529 533 490 91.93 92.63 92.28 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 4 secondsIteration: 35 Log-likelihood = -701.115857 Norm(log-likelihood gradient vector) = 74.109673 Norm(lambda vector) = 72.715337 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 533 513 96.25 96.98 96.61 o 725 751 724 96.40 99.86 98.10 i-np 691 661 651 98.49 94.21 96.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.05 97.02 97.03 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 533 490 91.93 92.63 92.28 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.93 92.63 92.28 Avg2. 529 533 490 91.93 92.63 92.28 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 36 Log-likelihood = -667.941347 Norm(log-likelihood gradient vector) = 49.907195 Norm(lambda vector) = 72.998816 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 725 752 724 96.28 99.86 98.04 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.94 96.92 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 529 534 489 91.57 92.44 92.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.57 92.44 92.00 Avg2. 529 534 489 91.57 92.44 92.00⌨️ 快捷键说明
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