📄 trainlog.txt_second-ordercrfs
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Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 537 511 95.16 96.60 95.87 o 725 745 720 96.64 99.31 97.96 i-np 691 663 649 97.89 93.92 95.86 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.56 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 529 537 484 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: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 50 Log-likelihood = -347.581212 Norm(log-likelihood gradient vector) = 85.017965 Norm(lambda vector) = 95.259193 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 536 510 95.15 96.41 95.77 o 725 745 720 96.64 99.31 97.96 i-np 691 664 649 97.74 93.92 95.79 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.51 96.55 96.53 Avg2. 1945 1945 1879 96.61 96.61 96.61 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 536 484 90.30 91.49 90.89 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.30 91.49 90.89 Avg2. 529 536 484 90.30 91.49 90.89 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 51 Log-likelihood = -340.266358 Norm(log-likelihood gradient vector) = 42.425079 Norm(lambda vector) = 94.641463 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 52 Log-likelihood = -332.147850 Norm(log-likelihood gradient vector) = 17.862587 Norm(lambda vector) = 95.903938 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 53 Log-likelihood = -328.116509 Norm(log-likelihood gradient vector) = 23.584057 Norm(lambda vector) = 97.001603 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 746 720 96.51 99.31 97.89 i-np 691 664 649 97.74 93.92 95.79 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.47 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 483 90.28 91.30 90.79 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.28 91.30 90.79 Avg2. 529 535 483 90.28 91.30 90.79 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 54 Log-likelihood = -325.968180 Norm(log-likelihood gradient vector) = 26.475884 Norm(lambda vector) = 98.194726 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 4 secondsIteration: 55 Log-likelihood = -324.724076 Norm(log-likelihood gradient vector) = 25.924644 Norm(lambda vector) = 100.169912 Iteration elapsed: 2 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 538 509 94.61 96.22 95.41 o 725 746 721 96.65 99.45 98.03 i-np 691 661 645 97.58 93.34 95.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.28 96.34 96.31 Avg2. 1945 1945 1875 96.40 96.40 96.40 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 538 479 89.03 90.55 89.78 ----- ------ ----- ----- ------- ------- ------------- Avg1. 89.03 90.55 89.78 Avg2. 529 538 479 89.03 90.55 89.78 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 56 Log-likelihood = -337.228861 Norm(log-likelihood gradient vector) = 35.812257 Norm(lambda vector) = 102.519572 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 508 94.95 96.03 95.49 o 725 744 719 96.64 99.17 97.89 i-np 691 666 649 97.45 93.92 95.65 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.37 96.36 Avg2. 1945 1945 1876 96.45 96.45 96.45 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 481 89.91 90.93 90.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 89.91 90.93 90.41 Avg2. 529 535 481 89.91 90.93 90.41 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 57 Log-likelihood = -325.106948 Norm(log-likelihood gradient vector) = 22.043467 Norm(lambda vector) = 100.534948 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 508 94.95 96.03 95.49 o 725 744 719 96.64 99.17 97.89 i-np 691 666 649 97.45 93.92 95.65 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.35 96.37 96.36 Avg2. 1945 1945 1876 96.45 96.45 96.45 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 481 89.91 90.93 90.41 ----- ------ ----- ----- ------- ------- ------------- Avg1. 89.91 90.93 90.41 Avg2. 529 535 481 89.91 90.93 90.41 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 58 Log-likelihood = -324.752047 Norm(log-likelihood gradient vector) = 25.052547 Norm(lambda vector) = 100.240553 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 59 Log-likelihood = -324.727915 Norm(log-likelihood gradient vector) = 25.744913 Norm(lambda vector) = 100.184140 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsIteration: 60 Log-likelihood = -324.724782 Norm(log-likelihood gradient vector) = 25.887993 Norm(lambda vector) = 100.172801 Iteration elapsed: 3 seconds Label-based performance evaluation: Label Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- b-np 529 535 509 95.14 96.22 95.68 o 725 745 720 96.64 99.31 97.96 i-np 691 665 649 97.59 93.92 95.72 ----- ------ ----- ----- ------- ------- ------------- Avg1. 96.46 96.48 96.47 Avg2. 1945 1945 1878 96.56 96.56 96.56 Chunk-based performance evaluation: Chunk Manual Model Match Pre.(%) Rec.(%) F1-Measure(%) ----- ------ ----- ----- ------- ------- ------------- np 529 535 482 90.09 91.12 90.60 ----- ------ ----- ----- ------- ------- ------------- Avg1. 90.09 91.12 90.60 Avg2. 529 535 482 90.09 91.12 90.60 Current max chunk-based F1: 93.13 (iteration 31) Training iteration elapsed (including testing & evaluation time): 3 secondsThe training process elapsed: 185 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-bas⌨️ 快捷键说明
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