Hi, I have a training set of 70 classes and 40 images/class (2800 in total), and a testing set of 350 in total.
What happens is that the loss becomes 0 when testing accuracy is still 58 %, and everything remains constant from this point. I’m using batchsize=5, learningrate=0.001, momentum=0.9. I’ve tried changing the three parameters but results get worst (loss becoming 0 with 30% accuracy, or loss never decreasing). How can I solve this? Just trying other values for this parameters?
Thank you!
[1,   560] loss: 4.250
Accuracy of the network on the test images: 2 %
[2,   560] loss: 4.210
Accuracy of the network on the test images: 2 %
[3,   560] loss: 3.903
Accuracy of the network on the test images: 5 %
[4,   560] loss: 3.469
Accuracy of the network on the test images: 15 %
[5,   560] loss: 2.995
Accuracy of the network on the test images: 20 %
[6,   560] loss: 2.351
Accuracy of the network on the test images: 25 %
[7,   560] loss: 1.795
Accuracy of the network on the test images: 40 %
[8,   560] loss: 1.247
Accuracy of the network on the test images: 40 %
[9,   560] loss: 0.865
Accuracy of the network on the test images: 44 %
[10,   560] loss: 0.572
Accuracy of the network on the test images: 45 %
[11,   560] loss: 0.376
Accuracy of the network on the test images: 46 %
[12,   560] loss: 0.279
Accuracy of the network on the test images: 46 %
[13,   560] loss: 0.163
Accuracy of the network on the test images: 44 %
[14,   560] loss: 0.151
Accuracy of the network on the test images: 46 %
[15,   560] loss: 0.107
Accuracy of the network on the test images: 54 %
[16,   560] loss: 0.015
Accuracy of the network on the test images: 58 %
[17,   560] loss: 0.001
Accuracy of the network on the test images: 58 %
[18,   560] loss: 0.000
Accuracy of the network on the test images: 58 %
[19,   560] loss: 0.000
Accuracy of the network on the test images: 59 %
[20,   560] loss: 0.000
Accuracy of the network on the test images: 59 %
[21,   560] loss: 0.000
Accuracy of the network on the test images: 59 %
[22,   560] loss: 0.000
Accuracy of the network on the test images: 59 %
[23,   560] loss: 0.000
Accuracy of the network on the test images: 59 %