Hi, sir. Thanks for your excellent idea!
Now I download your code and re-implement your experiment. But I get tow different results when all parameters are same in two experiment:
sh scripts/cifar10_cae.sh gpu cifar_cae 0 adam 0.0001 350 3 1 -1
sh scripts/cifar10_svdd.sh gpu cifar 0 adam 0.0001 150 0.1 1 1 0 cifar_cae/weights_final 3 1 -1
In first model, I got result:
Train objective: 0.12176
Train accuracy: 90.03%
Val objective: 0.11618
Val accuracy: 91.10%
Test objective: 0.13841
Test accuracy: 23.58%
Test AUC: 62.60%
and then, I set all parameters of the second model exactly the same as the first model, I got the result:
Train objective: 0.12050
Train accuracy: 90.02%
Val objective: 0.11537
Val accuracy: 90.80%
Test objective: 0.13548
Test accuracy: 22.60%
Test AUC: 62.23%
I got the same situation in other classes of cifar-10 dataset. In some class, the difference between the results of two identical models can even reach 2.3%.
I think that something wrong happened, but I don‘t know how to improve the result. I am looking forward to your reply!
Hi, sir. Thanks for your excellent idea!
Now I download your code and re-implement your experiment. But I get tow different results when all parameters are same in two experiment:
In first model, I got result:
Train objective: 0.12176
Train accuracy: 90.03%
Val objective: 0.11618
Val accuracy: 91.10%
Test objective: 0.13841
Test accuracy: 23.58%
Test AUC: 62.60%
and then, I set all parameters of the second model exactly the same as the first model, I got the result:
Train objective: 0.12050
Train accuracy: 90.02%
Val objective: 0.11537
Val accuracy: 90.80%
Test objective: 0.13548
Test accuracy: 22.60%
Test AUC: 62.23%
I got the same situation in other classes of cifar-10 dataset. In some class, the difference between the results of two identical models can even reach 2.3%.
I think that something wrong happened, but I don‘t know how to improve the result. I am looking forward to your reply!