📄 trainlog.txt_first-ordercrfs
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Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 528 507 96.02 95.84 95.93 o 725 751 720 95.87 99.31 97.56 i-np 691 666 651 97.75 94.21 95.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.55 96.45 96.50 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 528 483 91.48 91.30 91.39 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.48 91.30 91.39 Avg2. 529 528 483 91.48 91.30 91.39 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 50 Log-likelihood = -38.444442 Norm(log-likelihood gradient vector) = 1.977812 Norm(lambda vector) = 73.185847 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 528 507 96.02 95.84 95.93 o 725 751 720 95.87 99.31 97.56 i-np 691 666 651 97.75 94.21 95.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.55 96.45 96.50 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 528 483 91.48 91.30 91.39 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.48 91.30 91.39 Avg2. 529 528 483 91.48 91.30 91.39 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 51 Log-likelihood = -38.260265 Norm(log-likelihood gradient vector) = 1.769992 Norm(lambda vector) = 73.162521 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 725 752 720 95.74 99.31 97.49 i-np 691 666 651 97.75 94.21 95.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.50 96.39 96.45 Avg2. 1945 1945 1877 96.50 96.50 96.50 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 527 483 91.65 91.30 91.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.65 91.30 91.48 Avg2. 529 527 483 91.65 91.30 91.48 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 52 Log-likelihood = -37.788205 Norm(log-likelihood gradient vector) = 2.118656 Norm(lambda vector) = 72.911185 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 527 507 96.20 95.84 96.02 o 725 751 720 95.87 99.31 97.56 i-np 691 667 652 97.75 94.36 96.02 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.61 96.50 96.56 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 527 484 91.84 91.49 91.67 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.84 91.49 91.67 Avg2. 529 527 484 91.84 91.49 91.67 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 53 Log-likelihood = -37.244368 Norm(log-likelihood gradient vector) = 2.148515 Norm(lambda vector) = 72.443583 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 521 501 96.16 94.71 95.43 o 725 750 717 95.60 98.90 97.22 i-np 691 674 652 96.74 94.36 95.53 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.17 95.99 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 529 521 475 91.17 89.79 90.48 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.17 89.79 90.48 Avg2. 529 521 475 91.17 89.79 90.48 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 54 Log-likelihood = -42.169187 Norm(log-likelihood gradient vector) = 29.356289 Norm(lambda vector) = 70.920193 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 506 96.38 95.65 96.02 o 725 753 721 95.75 99.45 97.56 i-np 691 667 652 97.75 94.36 96.02 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.63 96.49 96.56 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 482 91.81 91.12 91.46 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.81 91.12 91.46 Avg2. 529 525 482 91.81 91.12 91.46 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 55 Log-likelihood = -37.105965 Norm(log-likelihood gradient vector) = 2.965066 Norm(lambda vector) = 72.206305 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 505 96.19 95.46 95.83 o 725 752 720 95.74 99.31 97.49 i-np 691 668 652 97.60 94.36 95.95 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.51 96.38 96.44 Avg2. 1945 1945 1877 96.50 96.50 96.50 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 481 91.62 90.93 91.27 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.62 90.93 91.27 Avg2. 529 525 481 91.62 90.93 91.27 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 56 Log-likelihood = -36.797557 Norm(log-likelihood gradient vector) = 1.816416 Norm(lambda vector) = 71.645192 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 506 96.38 95.65 96.02 o 725 751 720 95.87 99.31 97.56 i-np 691 669 653 97.61 94.50 96.03 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.62 96.49 96.55 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 482 91.81 91.12 91.46 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.81 91.12 91.46 Avg2. 529 525 482 91.81 91.12 91.46 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 57 Log-likelihood = -36.563681 Norm(log-likelihood gradient vector) = 1.266725 Norm(lambda vector) = 71.443987 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 524 505 96.37 95.46 95.92 o 725 752 720 95.74 99.31 97.49 i-np 691 669 653 97.61 94.50 96.03 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.42 96.50 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 524 481 91.79 90.93 91.36 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.79 90.93 91.36 Avg2. 529 524 481 91.79 90.93 91.36 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 1 secondsIteration: 58 Log-likelihood = -36.278542 Norm(log-likelihood gradient vector) = 1.686888 Norm(lambda vector) = 71.216319 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 524 505 96.37 95.46 95.92 o 725 752 720 95.74 99.31 97.49 i-np 691 669 653 97.61 94.50 96.03 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.58 96.42 96.50 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 524 481 91.79 90.93 91.36 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.79 90.93 91.36 Avg2. 529 524 481 91.79 90.93 91.36 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 59 Log-likelihood = -36.113565 Norm(log-likelihood gradient vector) = 1.879319 Norm(lambda vector) = 71.158713 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 506 96.38 95.65 96.02 o 725 752 720 95.74 99.31 97.49 i-np 691 668 653 97.75 94.50 96.10 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.63 96.49 96.56 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 483 92.00 91.30 91.65 ----- ------ ----- ----- ------- ------- ------------- Avg1. 92.00 91.30 91.65 Avg2. 529 525 483 92.00 91.30 91.65 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsIteration: 60 Log-likelihood = -35.882781 Norm(log-likelihood gradient vector) = 1.321788 Norm(lambda vector) = 71.168036 Iteration elapsed: 1 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 525 505 96.19 95.46 95.83 o 725 753 720 95.62 99.31 97.43 i-np 691 667 652 97.75 94.36 96.02 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.52 96.38 96.45 Avg2. 1945 1945 1877 96.50 96.50 96.50 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 525 482 91.81 91.12 91.46 ----- ------ ----- ----- ------- ------- ------------- Avg1. 91.81 91.12 91.46 Avg2. 529 525 482 91.81 91.12 91.46 Current max chunk-based F1: 91.89 (iteration 25) Training iteration elapsed (including testing & evaluation time): 2 secondsThe training process elapsed: 102 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 perfor⌨️ 快捷键说明
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