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what's the accuracy like?Here's the full log of my imagenet run on alexnetowtbnit has train loss reported per epoch as train_lossit has validation loss reported per epoch as test_loss
In your logs I see that the training accuracy and test accuracy after 29 epochs are 69.21 and 56.502 respectively. with a difference of 13 %
Can we consider this difference as an overfit? If no what should be the threshold beyond which we can claim the model overfits
On Thursday, November 19, 2015 at 1:23:41 PM UTC+5:30, Neelesh wrote:
I had used the Alexnet Model and not the AlexnetOWT. Let me check out with that and get back here
Thanks
Neelakandan
On Thursday, November 19, 2015 at 12:29:10 PM UTC+5:30, smth chntla wrote:
what's the accuracy like?Here's the full log of my imagenet run on alexnetowtbnit has train loss reported per epoch as train_lossit has validation loss reported per epoch as test_loss
On Thu, Nov 19, 2015 at 1:01 AM, Neelesh via torch7 <torch7+APn2wQfz7MHLXlgHmhDG5Le3E...@googlegroups.com> wrote:Have none experienced this ? I am curios to know the cause of this. Is it because of the Alexnet Model parameters ?
On Monday, November 16, 2015 at 5:06:13 AM UTC+5:30, Neelesh wrote:Hello all,
Wanted to explore and experience multi-gpu training
Came across https://github.com/soumith/imagenet-multiGPU.torch
So I kicked off by following the instructions and ventured into training the Alexnet Model on imagenet dataset against 2 Nvidia GPUs
I seem to see a huge gap between training and validation loss. (see the snapshot). Guess its a misfit
Has any one else experienced this ? Could anyone throw some light on what's causing this ?--
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yes this is an overfit. All imagenet models overfit.
what's the accuracy like?Here's the full log of my imagenet run on alexnetowtbnit has train loss reported per epoch as train_lossit has validation loss reported per epoch as test_loss