Comments (2)
I'm also curious what the optimal LR for smallNORB was -- got high accuracy for MNIST after ~8k iterations, but the loss is slowly increasing on smallNORB, so wondering what the optimal LR is
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Hi!
Have you fixed the problem? I'm running with mnist and the loss starts around 0.3 and jumps to 7.2 after 11000 iterations and stuck at 7.3 when finished at 55000. The testing accuracy is around 0.1 all the time. Really appreciate your help!
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Related Issues (20)
- SmallNORB Data Creation
- Issue:Calculate the “Mean“ and “Variance” in EM Routing
- How to add a dateset to the get_coord_add function HOT 4
- Strange jump in training loss and accuracy HOT 4
- get a different loss and accuracy curve HOT 2
- Shape of beta_v
- Training without reconstruction loss HOT 3
- tf.matmul slows training and causes low GPU usage.
- How to add a dataset to the Coord_add function ? HOT 1
- ValueError: ('Convolution not supported for input with rank', 2)
- batch from the data queue
- eval.py HOT 1
- Is there Something to be done after running download.sh for smallNORB data to be available? HOT 6
- smallNORB dataset urls error "connection forbidden"
- cifar10 parameters setting
- Wrong Results
- the mean and std of smallNORB dataset HOT 1
- Why we need coord_add function?
- why use "batch_squash = tf.divide(batch_x, 255.)" rather than just batch_x
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