log.txt

GPU Mode.
Split train-test sets / Load tf-idf model finished.
Load data finished.
Model init finished.
[1/600] rumor mean_loss: 0.5134 stance mean_loss: 1.0849
Accuracy: 91.3183%
Non-rumor precision: 87.0213% recall: 95.3380% f1: 0.9099
Rumor precision: 95.6803% recall: 87.8968% f1: 0.9162
[2/600] rumor mean_loss: 0.3776 stance mean_loss: 1.0688
Accuracy: 93.0332%
Non-rumor precision: 92.1277% recall: 93.9262% f1: 0.9302
Rumor precision: 93.9525% recall: 92.1610% f1: 0.9305
[3/600] rumor mean_loss: 0.3547 stance mean_loss: 1.0616
Accuracy: 92.8189%
Non-rumor precision: 91.7021% recall: 93.8998% f1: 0.9279
Rumor precision: 93.9525% recall: 91.7722% f1: 0.9285
[4/600] rumor mean_loss: 0.3415 stance mean_loss: 1.0572
Accuracy: 92.7117%
Non-rumor precision: 94.2553% recall: 91.5289% f1: 0.9287
Rumor precision: 91.1447% recall: 93.9866% f1: 0.9254
[5/600] rumor mean_loss: 0.3339 stance mean_loss: 1.0538
Accuracy: 92.9260%
Non-rumor precision: 94.0426% recall: 92.0833% f1: 0.9305
Rumor precision: 91.7927% recall: 93.8190% f1: 0.9279
[6/600] rumor mean_loss: 0.3297 stance mean_loss: 1.0508
Accuracy: 92.7117%
Non-rumor precision: 92.3404% recall: 93.1330% f1: 0.9274
Rumor precision: 93.0886% recall: 92.2912% f1: 0.9269
[7/600] rumor mean_loss: 0.3275 stance mean_loss: 1.0477
Accuracy: 93.1404%
Non-rumor precision: 93.6170% recall: 92.8270% f1: 0.9322
Rumor precision: 92.6566% recall: 93.4641% f1: 0.9306
[8/600] rumor mean_loss: 0.3265 stance mean_loss: 1.0442
Accuracy: 92.9260%
Non-rumor precision: 94.0426% recall: 92.0833% f1: 0.9305
Rumor precision: 91.7927% recall: 93.8190% f1: 0.9279
[9/600] rumor mean_loss: 0.3255 stance mean_loss: 1.0400
Accuracy: 93.1404%
Non-rumor precision: 94.6809% recall: 91.9421% f1: 0.9329
Rumor precision: 91.5767% recall: 94.4321% f1: 0.9298
[10/600] rumor mean_loss: 0.3250 stance mean_loss: 1.0343
Accuracy: 93.0332%
Non-rumor precision: 94.2553% recall: 92.0998% f1: 0.9317
Rumor precision: 91.7927% recall: 94.0265% f1: 0.9290
[11/600] rumor mean_loss: 0.3243 stance mean_loss: 1.0266
Accuracy: 92.9260%
Non-rumor precision: 93.8298% recall: 92.2594% f1: 0.9304
Rumor precision: 92.0086% recall: 93.6264% f1: 0.9281
[12/600] rumor mean_loss: 0.3240 stance mean_loss: 1.0164
Accuracy: 92.3901%
Non-rumor precision: 94.2553% recall: 90.9651% f1: 0.9258
Rumor precision: 90.4968% recall: 93.9462% f1: 0.9219
[13/600] rumor mean_loss: 0.3236 stance mean_loss: 1.0031
Accuracy: 92.6045%
Non-rumor precision: 93.8298% recall: 91.6840% f1: 0.9274
Rumor precision: 91.3607% recall: 93.5841% f1: 0.9246
[14/600] rumor mean_loss: 0.3233 stance mean_loss: 0.9872
Accuracy: 92.0686%
Non-rumor precision: 93.8298% recall: 90.7407% f1: 0.9226
Rumor precision: 90.2808% recall: 93.5123% f1: 0.9187
[15/600] rumor mean_loss: 0.3229 stance mean_loss: 0.9704
Accuracy: 92.3901%
Non-rumor precision: 91.7021% recall: 93.0886% f1: 0.9239
Rumor precision: 93.0886% recall: 91.7021% f1: 0.9239
[16/600] rumor mean_loss: 0.3230 stance mean_loss: 0.9535