📄 trainlog.txt
字号:
Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 538 512 95.17 96.79 95.97 o 725 748 722 96.52 99.59 98.03 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.72 96.76 96.74 Avg2. 1945 1945 1883 96.81 96.81 96.81 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): 3 secondsIteration: 50 Log-likelihood = -407.762496 Norm(log-likelihood gradient vector) = 19.678027 Norm(lambda vector) = 98.675566 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 725 748 722 96.52 99.59 98.03 i-np 691 659 649 98.48 93.92 96.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.72 96.76 96.74 Avg2. 1945 1945 1883 96.81 96.81 96.81 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: 51 Log-likelihood = -395.745090 Norm(log-likelihood gradient vector) = 20.766464 Norm(lambda vector) = 99.551565 Iteration elapsed: 3 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 725 747 721 96.52 99.45 97.96 i-np 691 662 650 98.19 94.07 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.68 96.70 96.69 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): 3 secondsIteration: 52 Log-likelihood = -368.102936 Norm(log-likelihood gradient vector) = 45.527162 Norm(lambda vector) = 103.718326 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 541 515 95.19 97.35 96.26 o 725 752 723 96.14 99.72 97.90 i-np 691 652 646 99.08 93.49 96.20 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.81 96.86 96.83 Avg2. 1945 1945 1884 96.86 96.86 96.86 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 541 493 91.13 93.19 92.15 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.13 93.19 92.15 Avg2. 529 541 493 91.13 93.19 92.15 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 53 Log-likelihood = -359.217619 Norm(log-likelihood gradient vector) = 68.098375 Norm(lambda vector) = 106.930981 Iteration elapsed: 3 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 725 749 722 96.40 99.59 97.96 i-np 691 658 648 98.48 93.78 96.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.68 96.72 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 529 538 489 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): 3 secondsIteration: 54 Log-likelihood = -357.663866 Norm(log-likelihood gradient vector) = 22.534039 Norm(lambda vector) = 105.223458 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 725 747 721 96.52 99.45 97.96 i-np 691 662 650 98.19 94.07 96.08 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.68 96.70 96.69 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): 3 secondsIteration: 55 Log-likelihood = -355.682217 Norm(log-likelihood gradient vector) = 17.408526 Norm(lambda vector) = 107.620719 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 725 748 721 96.39 99.45 97.90 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.61 96.59 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 487 90.69 92.06 91.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.69 92.06 91.37 Avg2. 529 537 487 90.69 92.06 91.37 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 56 Log-likelihood = -354.663624 Norm(log-likelihood gradient vector) = 39.336816 Norm(lambda vector) = 109.522797 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 539 513 95.18 96.98 96.07 o 725 748 721 96.39 99.45 97.90 i-np 691 658 648 98.48 93.78 96.07 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.68 96.73 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 529 539 489 90.72 92.44 91.57 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.72 92.44 91.57 Avg2. 529 539 489 90.72 92.44 91.57 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 57 Log-likelihood = -361.274244 Norm(log-likelihood gradient vector) = 29.799452 Norm(lambda vector) = 111.629217 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 725 748 721 96.39 99.45 97.90 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.61 96.59 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 487 90.69 92.06 91.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.69 92.06 91.37 Avg2. 529 537 487 90.69 92.06 91.37 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 58 Log-likelihood = -354.843561 Norm(log-likelihood gradient vector) = 33.393083 Norm(lambda vector) = 109.864393 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 725 748 721 96.39 99.45 97.90 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.61 96.59 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 487 90.69 92.06 91.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.69 92.06 91.37 Avg2. 529 537 487 90.69 92.06 91.37 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 59 Log-likelihood = -354.672323 Norm(log-likelihood gradient vector) = 38.094772 Norm(lambda vector) = 109.591104 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 725 748 721 96.39 99.45 97.90 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.61 96.59 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 487 90.69 92.06 91.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.69 92.06 91.37 Avg2. 529 537 487 90.69 92.06 91.37 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 60 Log-likelihood = -354.664311 Norm(log-likelihood gradient vector) = 39.076807 Norm(lambda vector) = 109.536994 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 725 748 721 96.39 99.45 97.90 i-np 691 660 648 98.18 93.78 95.93 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.61 96.59 Avg2. 1945 1945 1880 96.66 96.66 96.66 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 537 487 90.69 92.06 91.37 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.69 92.06 91.37 Avg2. 529 537 487 90.69 92.06 91.37 Current max chunk-based F1: 92.93 (iteration 24) Training iteration elapsed (including testing & evaluation time): 2 secondsThe training process elapsed: 160 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 532 516 96.99 97.54 97.27 o 725 744 723 97.18 99.72 98.43 i-np 691 669 660 98.65 95.51 97.06 ----- ------ ----- ----- ------- ------- ------------- Avg1. 97.61 97.59 97.60 Avg2. 1945 1945 1899 97.63 97.63 97.63 Chunk-⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -