MCD_DA
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Published
20 hours ago •
mil-tokyo
mil-tokyo
Loss is becoming negative
Very nice work! During my training, I found that loss can become negative:
Train Epoch: 198 [0/100 (0%)] Loss1: 0.024868 Loss2: 0.022132 Discrepancy: 0.018226
Test set: Average loss: -0.0588, Accuracy C1: 9449/10000 (94%) Accuracy C2: 9509/10000 (95%) Accuracy Ensemble: 9554/10000 (96%)
recording record/usps_mnist_k_4_alluse_no_onestep_False_1_test.txt
Train Epoch: 199 [0/100 (0%)] Loss1: 0.012343 Loss2: 0.020431 Discrepancy: 0.030520
Test set: Average loss: -0.0581, Accuracy C1: 9419/10000 (94%) Accuracy C2: 9518/10000 (95%) Accuracy Ensemble: 9537/10000 (95%)
recording record/usps_mnist_k_4_alluse_no_onestep_False_1_test.txt
Do you think this is normal?
Very nice work! During my training, I found that loss can become negative:
Train Epoch: 198 [0/100 (0%)] Loss1: 0.024868 Loss2: 0.022132 Discrepancy: 0.018226 Test set: Average loss: -0.0588, Accuracy C1: 9449/10000 (94%) Accuracy C2: 9509/10000 (95%) Accuracy Ensemble: 9554/10000 (96%) recording record/usps_mnist_k_4_alluse_no_onestep_False_1_test.txt Train Epoch: 199 [0/100 (0%)] Loss1: 0.012343 Loss2: 0.020431 Discrepancy: 0.030520 Test set: Average loss: -0.0581, Accuracy C1: 9419/10000 (94%) Accuracy C2: 9518/10000 (95%) Accuracy Ensemble: 9537/10000 (95%) recording record/usps_mnist_k_4_alluse_no_onestep_False_1_test.txtDo you think this is normal?
have you solve this problem?and If my pytorch version is 0.4.1.could I get the same peformance?
