CODEWITHSUNDEEP
mxnet
Lolith
Lolith

Reputation: 33

MxNet: Accuracy falls to random prediciton after some iterations

When I was training a CNN to classify images of distorted digits varying from 0 to 9, the accuracy of training set and test set improved obviously.

Epoch[0] Batch [100] Train-multi-accuracy_0=0.296000
...
Epoch[0] Batch [500] Train-multi-accuracy_0=0.881900

In Epoch[1] and Epoch[2] the accuracy oscillate slightly between 0.85 and 0.95, however,

Epoch[3] Batch [300] Train-multi-accuracy_0=0.926400
Epoch[3] Batch [400] Train-multi-accuracy_0=0.105300
Epoch[3] Batch [500] Train-multi-accuracy_0=0.098200

Since then, the accuracy was around 0.1 which meant the network only gave random prediction. I repeated the training several times, this case occurred every time. What's wrong with it? Is the adapted learning rate strategy the reason?

model = mx.model.FeedForward(...,
                             optimizer = 'adam',
                             num_epoch = 50,
                             wd = 0.00001,
                             ...,
                             )

Upvotes: 0

Views: 80

Answers (1)

eric-haibin-lin
eric-haibin-lin

Reputation: 377

What exactly is the model you're training? If you're using the mnist dataset, usually a simple 2-layer MLP trained with sgd with give you pretty high accuracy.

Upvotes: 1

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