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Training_lr0.0005.log
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Training_lr0.0005.log
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INFO : class_names = ['Etat', 'Inland', 'International', 'Kultur', 'Panorama', 'Sport', 'Web', 'Wirtschaft', 'Wissenschaft']
INFO : ****** Current epoch: 1 ******
INFO : Training sample: 1656/ 8280 ...
INFO : Training sample: 3312/ 8280 ...
INFO : Training sample: 4968/ 8280 ...
INFO : Training sample: 6624/ 8280 ...
INFO : Training sample: 8280/ 8280 ...
INFO : Sample: 193/ 965 ...
INFO : Sample: 386/ 965 ...
INFO : Sample: 579/ 965 ...
INFO : Sample: 772/ 965 ...
INFO : Sample: 965/ 965 ...
INFO : NLL loss=0.73 ; accuracy=0.761
INFO : precision=[0.72, 0.63, 0.76, 0.6, 0.73, 0.95, 0.81, 0.79, 0.78]
Recall=[0.51, 0.76, 0.81, 0.55, 0.76, 0.87, 0.88, 0.74, 0.67]
INFO : F1_score=[0.6, 0.69, 0.78, 0.57, 0.74, 0.91, 0.84, 0.76, 0.72]
INFO : confusion_matrix=
[[ 34 6 5 8 6 2 4 2 0]
[ 1 65 1 2 9 1 2 4 1]
[ 1 0 113 2 14 1 5 3 1]
[ 6 2 2 29 6 1 4 0 3]
[ 1 17 12 4 143 0 2 8 2]
[ 1 0 6 1 4 87 0 1 0]
[ 2 3 5 0 2 0 137 4 2]
[ 0 9 4 0 8 0 13 95 0]
[ 1 1 1 2 4 0 3 3 31]]
INFO : validation_loss=0.73 ; best_validation_loss=inf
INFO : ****** Current epoch: 2 ******
INFO : Training sample: 1656/ 8280 ...
INFO : Training sample: 3312/ 8280 ...
INFO : Training sample: 4968/ 8280 ...
INFO : Training sample: 6624/ 8280 ...
INFO : Training sample: 8280/ 8280 ...
INFO : Sample: 193/ 965 ...
INFO : Sample: 386/ 965 ...
INFO : Sample: 579/ 965 ...
INFO : Sample: 772/ 965 ...
INFO : Sample: 965/ 965 ...
INFO : NLL loss=0.64 ; accuracy=0.807
INFO : precision=[0.79, 0.66, 0.81, 0.64, 0.82, 0.99, 0.81, 0.85, 0.83]
Recall=[0.67, 0.8, 0.88, 0.66, 0.79, 0.91, 0.91, 0.67, 0.85]
INFO : F1_score=[0.73, 0.72, 0.84, 0.65, 0.81, 0.95, 0.86, 0.75, 0.84]
INFO : confusion_matrix=
[[ 45 4 4 7 1 1 3 2 0]
[ 0 69 1 3 6 0 2 4 1]
[ 2 0 123 0 9 0 4 1 1]
[ 5 3 0 35 4 0 3 0 3]
[ 1 15 9 5 149 0 4 4 2]
[ 3 0 4 1 1 91 0 0 0]
[ 1 3 5 1 1 0 141 2 1]
[ 0 11 6 1 8 0 16 87 0]
[ 0 0 0 2 2 0 1 2 39]]
INFO : validation_loss=0.636 ; best_validation_loss=0.73
INFO : ****** Current epoch: 3 ******
INFO : Training sample: 1656/ 8280 ...
INFO : Training sample: 3312/ 8280 ...
INFO : Training sample: 4968/ 8280 ...
INFO : Training sample: 6624/ 8280 ...
INFO : Training sample: 8280/ 8280 ...
INFO : Sample: 193/ 965 ...
INFO : Sample: 386/ 965 ...
INFO : Sample: 579/ 965 ...
INFO : Sample: 772/ 965 ...
INFO : Sample: 965/ 965 ...
INFO : NLL loss=0.69 ; accuracy=0.808
INFO : precision=[0.79, 0.65, 0.83, 0.67, 0.82, 0.97, 0.85, 0.84, 0.72]
Recall=[0.67, 0.78, 0.85, 0.72, 0.79, 0.91, 0.88, 0.71, 0.93]
INFO : F1_score=[0.73, 0.71, 0.84, 0.69, 0.81, 0.94, 0.86, 0.77, 0.81]
INFO : confusion_matrix=
[[ 45 3 4 6 1 2 3 2 1]
[ 1 67 2 2 6 0 0 5 3]
[ 1 1 119 0 13 0 3 3 0]
[ 5 3 1 38 2 0 1 0 3]
[ 1 14 7 5 149 0 5 1 7]
[ 3 0 2 2 2 91 0 0 0]
[ 1 3 5 1 1 1 136 5 2]
[ 0 12 4 1 7 0 12 92 1]
[ 0 0 0 2 0 0 0 1 43]]
INFO : validation_loss=0.691 ; best_validation_loss=0.636
INFO : Early stopping