📄 trainlog.txt_first-ordercrfs
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Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 484 90.13 91.49 90.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.13 91.49 90.81 Avg2. 529 537 484 90.13 91.49 90.81 Current max chunk-based F1: 91.46 (iteration 23) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 25 Log-likelihood = -103.559386 Norm(log-likelihood gradient vector) = 90.394022 Norm(lambda vector) = 73.102653 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 531 510 96.05 96.41 96.23 o 725 755 721 95.50 99.45 97.43 i-np 691 659 648 98.33 93.78 96.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.62 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 529 531 487 91.71 92.06 91.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.71 92.06 91.89 Avg2. 529 531 487 91.71 92.06 91.89 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 26 Log-likelihood = -91.745125 Norm(log-likelihood gradient vector) = 44.626039 Norm(lambda vector) = 68.802469 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 531 509 95.86 96.22 96.04 o 725 754 720 95.49 99.31 97.36 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.51 96.44 96.47 Avg2. 1945 1945 1877 96.50 96.50 96.50 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 531 486 91.53 91.87 91.70 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.53 91.87 91.70 Avg2. 529 531 486 91.53 91.87 91.70 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 27 Log-likelihood = -79.447151 Norm(log-likelihood gradient vector) = 22.889661 Norm(lambda vector) = 72.495937 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 529 507 95.84 95.84 95.84 o 725 754 720 95.49 99.31 97.36 i-np 691 662 649 98.04 93.92 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.36 96.41 Avg2. 1945 1945 1876 96.45 96.45 96.45 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 529 483 91.30 91.30 91.30 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.30 91.30 91.30 Avg2. 529 529 483 91.30 91.30 91.30 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 28 Log-likelihood = -71.829787 Norm(log-likelihood gradient vector) = 13.430452 Norm(lambda vector) = 76.062152 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 506 96.20 95.65 95.92 o 725 751 718 95.61 99.03 97.29 i-np 691 668 651 97.46 94.21 95.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.42 96.30 96.36 Avg2. 1945 1945 1875 96.40 96.40 96.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 481 91.44 90.93 91.18 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.44 90.93 91.18 Avg2. 529 526 481 91.44 90.93 91.18 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 29 Log-likelihood = -65.393911 Norm(log-likelihood gradient vector) = 9.980292 Norm(lambda vector) = 80.276019 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 506 96.20 95.65 95.92 o 725 751 718 95.61 99.03 97.29 i-np 691 668 651 97.46 94.21 95.81 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.42 96.30 96.36 Avg2. 1945 1945 1875 96.40 96.40 96.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 481 91.44 90.93 91.18 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.44 90.93 91.18 Avg2. 529 526 481 91.44 90.93 91.18 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 30 Log-likelihood = -61.507250 Norm(log-likelihood gradient vector) = 8.472733 Norm(lambda vector) = 82.998040 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 524 504 96.18 95.27 95.73 o 725 749 716 95.59 98.76 97.15 i-np 691 672 651 96.88 94.21 95.52 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.22 96.08 96.15 Avg2. 1945 1945 1871 96.20 96.20 96.20 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 524 477 91.03 90.17 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.03 90.17 90.60 Avg2. 529 524 477 91.03 90.17 90.60 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 31 Log-likelihood = -58.286402 Norm(log-likelihood gradient vector) = 6.376564 Norm(lambda vector) = 85.419719 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 523 502 95.98 94.90 95.44 o 725 748 714 95.45 98.48 96.95 i-np 691 674 649 96.29 93.92 95.09 ----- ------ ----- ----- ------- ------- ------------- Avg1. 95.91 95.77 95.84 Avg2. 1945 1945 1865 95.89 95.89 95.89 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 523 474 90.63 89.60 90.11 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.63 89.60 90.11 Avg2. 529 523 474 90.63 89.60 90.11 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 32 Log-likelihood = -59.919344 Norm(log-likelihood gradient vector) = 36.591886 Norm(lambda vector) = 85.985538 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 523 504 96.37 95.27 95.82 o 725 751 717 95.47 98.90 97.15 i-np 691 671 651 97.02 94.21 95.59 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.29 96.13 96.21 Avg2. 1945 1945 1872 96.25 96.25 96.25 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 523 477 91.20 90.17 90.68 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.20 90.17 90.68 Avg2. 529 523 477 91.20 90.17 90.68 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 33 Log-likelihood = -56.190608 Norm(log-likelihood gradient vector) = 14.192247 Norm(lambda vector) = 85.651501 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 506 96.20 95.65 95.92 o 725 750 717 95.60 98.90 97.22 i-np 691 669 650 97.16 94.07 95.59 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.32 96.21 96.26 Avg2. 1945 1945 1873 96.30 96.30 96.30 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 480 91.25 90.74 91.00 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.25 90.74 91.00 Avg2. 529 526 480 91.25 90.74 91.00 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 34 Log-likelihood = -53.788104 Norm(log-likelihood gradient vector) = 4.923837 Norm(lambda vector) = 86.108976 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 527 506 96.02 95.65 95.83 o 725 750 717 95.60 98.90 97.22 i-np 691 668 649 97.16 93.92 95.51 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.26 96.16 96.21 Avg2. 1945 1945 1872 96.25 96.25 96.25 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 527 480 91.08 90.74 90.91 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.08 90.74 90.91 Avg2. 529 527 480 91.08 90.74 90.91 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 35 Log-likelihood = -52.845123 Norm(log-likelihood gradient vector) = 4.296133 Norm(lambda vector) = 85.034060 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 504 96.00 95.27 95.64 o 725 749 717 95.73 98.90 97.29 i-np 691 671 650 96.87 94.07 95.45 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.20 96.08 96.14 Avg2. 1945 1945 1871 96.20 96.20 96.20 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 478 91.05 90.36 90.70 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.05 90.36 90.70 Avg2. 529 525 478 91.05 90.36 90.70 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 36 Log-likelihood = -50.905266 Norm(log-likelihood gradient vector) = 4.179070 Norm(lambda vector) = 83.328466 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 526 504 95.82 95.27 95.55 o 725 747 716 95.85 98.76 97.28 i-np 691 672 650 96.73 94.07 95.38 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.13 96.03 96.08 Avg2. 1945 1945 1870 96.14 96.14 96.14 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 526 478 90.87 90.36 90.62 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.87 90.36 90.62 Avg2. 529 526 478 90.87 90.36 90.62⌨️ 快捷键说明
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