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Why the loss appear in negative sign.?? on MAPNET #21
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Hi, that is normal. The loss becomes negative because of the formula we use
for the loss function.
On Thu, Aug 1, 2019 at 05:00 Ahmad Faraz Khan ***@***.***> wrote:
@samarth-robo <https://github.com/samarth-robo>, as you can see in this
screenshot, The loss turn into negative sign.? what is it mean.? when I try
to train MAPNET on my GPU Nvidia RTX2080ti with these parameters as below
n_epochs = 300
batch_size = 20
do_val = yes
seed = 7
shuffle = yes
num_workers = 5
snapshot = 50
val_freq = 50
max_grad_norm = 0
[image: Screenshot from 2019-08-01 16-55-29]
<https://user-images.githubusercontent.com/38114191/62291499-8530f280-b47d-11e9-924b-0bc157b8e9cc.png>
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Samarth Brahmbhatt
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@samarth-robo Thanx for replying, I have one more question. How many layers are there in mapnet Neural Network.? Can we change the layers? if Yes, How.? |
I don't remember exactly. I think we used resnet-34. All the network
architecture definitions are in `models.py`
On Mon, Aug 5, 2019 at 23:28 Ahmad Faraz Khan ***@***.***> wrote:
@samarth-robo <https://github.com/samarth-robo> Thanx for replying, I
have one more question.
How many layers are there in mapnet Neural Network.? Can we change the
layers? if Yes, How.?
?
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@samarth-robo Sir I didnt get the "Models.py" file in your repository. I only got Regards |
Sorry, I meant |
@samarth-robo, as you can see in this screenshot, The loss turn into negative sign.? what is it mean.? when I try to train MAPNET on my GPU Nvidia RTX2080ti with these parameters as below
n_epochs = 300
batch_size = 20
do_val = yes
seed = 7
shuffle = yes
num_workers = 5
snapshot = 50
val_freq = 50
max_grad_norm = 0
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