📄 trainlog.txt_second-ordercrfs
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----- ------ ----- ----- ------- ------- ------------- b-np 529 509 496 97.45 93.76 95.57 o 725 736 712 96.74 98.21 97.47 i-np 691 700 665 95.00 96.24 95.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.40 96.07 96.23 Avg2. 1945 1945 1873 96.30 96.30 96.30 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 509 463 90.96 87.52 89.21 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.96 87.52 89.21 Avg2. 529 509 463 90.96 87.52 89.21 Current max chunk-based F1: 90.13 (iteration 9) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 13 Log-likelihood = -2707.178789 Norm(log-likelihood gradient vector) = 799.844904 Norm(lambda vector) = 28.371674 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 725 750 721 96.13 99.45 97.76 i-np 691 672 657 97.77 95.08 96.40 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.88 96.73 96.81 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: 91.63 (iteration 13) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 14 Log-likelihood = -2356.891429 Norm(log-likelihood gradient vector) = 232.156997 Norm(lambda vector) = 28.929834 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 524 507 96.76 95.84 96.30 o 725 753 723 96.02 99.72 97.83 i-np 691 668 656 98.20 94.93 96.54 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.99 96.83 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 529 524 483 92.18 91.30 91.74 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.18 91.30 91.74 Avg2. 529 524 483 92.18 91.30 91.74 Current max chunk-based F1: 91.74 (iteration 14) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 15 Log-likelihood = -2272.541321 Norm(log-likelihood gradient vector) = 168.014964 Norm(lambda vector) = 29.541731 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 509 96.77 96.22 96.49 o 725 752 723 96.14 99.72 97.90 i-np 691 667 656 98.35 94.93 96.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.09 96.96 97.02 Avg2. 1945 1945 1888 97.07 97.07 97.07 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 486 92.40 91.87 92.13 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.40 91.87 92.13 Avg2. 529 526 486 92.40 91.87 92.13 Current max chunk-based F1: 92.13 (iteration 15) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 16 Log-likelihood = -2154.536170 Norm(log-likelihood gradient vector) = 188.420259 Norm(lambda vector) = 30.849715 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 530 509 96.04 96.22 96.13 o 725 753 722 95.88 99.59 97.70 i-np 691 662 650 98.19 94.07 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.70 96.62 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 529 530 483 91.13 91.30 91.22 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.13 91.30 91.22 Avg2. 529 530 483 91.13 91.30 91.22 Current max chunk-based F1: 92.13 (iteration 15) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 17 Log-likelihood = -1953.940354 Norm(log-likelihood gradient vector) = 173.428299 Norm(lambda vector) = 33.437022 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 533 510 95.68 96.41 96.05 o 725 758 723 95.38 99.72 97.51 i-np 691 654 646 98.78 93.49 96.06 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.61 96.54 96.58 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 533 488 91.56 92.25 91.90 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.56 92.25 91.90 Avg2. 529 533 488 91.56 92.25 91.90 Current max chunk-based F1: 92.13 (iteration 15) Training iteration elapsed (including testing & evaluation time): 4 secondsIteration: 18 Log-likelihood = -1888.312044 Norm(log-likelihood gradient vector) = 554.881303 Norm(lambda vector) = 41.341639 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 531 512 96.42 96.79 96.60 o 725 749 722 96.40 99.59 97.96 i-np 691 665 655 98.50 94.79 96.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.10 97.05 97.08 Avg2. 1945 1945 1889 97.12 97.12 97.12 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 531 489 92.09 92.44 92.26 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.09 92.44 92.26 Avg2. 529 531 489 92.09 92.44 92.26 Current max chunk-based F1: 92.26 (iteration 18) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 19 Log-likelihood = -1570.447923 Norm(log-likelihood gradient vector) = 171.378700 Norm(lambda vector) = 42.119822 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 725 752 723 96.14 99.72 97.90 i-np 691 660 652 98.79 94.36 96.52 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.06 97.02 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 529 533 490 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: 92.28 (iteration 19) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 20 Log-likelihood = -1481.665988 Norm(log-likelihood gradient vector) = 113.525147 Norm(lambda vector) = 42.827627 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 528 511 96.78 96.60 96.69 o 725 747 723 96.79 99.72 98.23 i-np 691 670 657 98.06 95.08 96.55 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.21 97.13 97.17 Avg2. 1945 1945 1891 97.22 97.22 97.22 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 528 486 92.05 91.87 91.96 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.05 91.87 91.96 Avg2. 529 528 486 92.05 91.87 91.96 Current max chunk-based F1: 92.28 (iteration 19) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 21 Log-likelihood = -1363.400577 Norm(log-likelihood gradient vector) = 130.652414 Norm(lambda vector) = 45.245676 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 532 513 96.43 96.98 96.70 o 725 751 724 96.40 99.86 98.10 i-np 691 662 653 98.64 94.50 96.53 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.16 97.11 97.14 Avg2. 1945 1945 1890 97.17 97.17 97.17 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 532 489 91.92 92.44 92.18 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.92 92.44 92.18 Avg2. 529 532 489 91.92 92.44 92.18 Current max chunk-based F1: 92.28 (iteration 19) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 22 Log-likelihood = -1263.401221 Norm(log-likelihood gradient vector) = 124.991112 Norm(lambda vector) = 47.711962 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 528 509 96.40 96.22 96.31 o 725 747 721 96.52 99.45 97.96 i-np 691 670 655 97.76 94.79 96.25 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.89 96.82 96.86 Avg2. 1945 1945 1885 96.92 96.92 96.92 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 528 486 92.05 91.87 91.96 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.05 91.87 91.96 Avg2. 529 528 486 92.05 91.87 91.96 Current max chunk-based F1: 92.28 (iteration 19) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 23 Log-likelihood = -1094.575487 Norm(log-likelihood gradient vector) = 98.800285 Norm(lambda vector) = 53.053250 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 532 510 95.86 96.41 96.14 o 725 751 722 96.14 99.59 97.83 i-np 691 662 650 98.19 94.07 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.73 96.69 96.71 Avg2. 1945 1945 1882 96.76 96.76 96.76 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 532 486 91.35 91.87 91.61 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.35 91.87 91.61 Avg2. 529 532 486 91.35 91.87 91.61 Current max chunk-based F1: 92.28 (iteration 19) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 24 Log-likelihood = -940.225424 Norm(log-likelihood gradient vector) = 144.274775 Norm(lambda vector) = 57.697336 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 725 749 723 96.53 99.72 98.10 i-np 691 661 652 98.64 94.36 96.45 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.08 97.08 97.08 Avg2. 1945 1945 1889 97.12 97.12 97.12 Chunk-based performance evaluation:⌨️ 快捷键说明
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