Why loss and val_loss vary for same value of lr, epoch, batch size and lr-decay?
$begingroup$
I am training a deep neural network in Keras. I have set the values of learning rate, learning rate decay, epochs and batch size.
(I am using fit_generator i.e data coming from a generator but without any kind of shuffling.)
Being said that my training shows highly differenttraining summary.
Sometimes it's like:
And other times it is
The two of the above images show the highly unpredictable behavior of model for the same values of all hyperparameters.
Can someone explain why this is happening?
keras predictive-modeling
asked 6 mins ago
yamini goelyamini goel
213
$endgroup$
add a comment |
$begingroup$
I am training a deep neural network in Keras. I have set the values of learning rate, learning rate decay, epochs and batch size.
(I am using fit_generator i.e data coming from a generator but without any kind of shuffling.)
Being said that my training shows highly differenttraining summary.
Sometimes it's like:
And other times it is
The two of the above images show the highly unpredictable behavior of model for the same values of all hyperparameters.
Can someone explain why this is happening?
keras predictive-modeling
asked 6 mins ago
yamini goelyamini goel
213
$endgroup$
add a comment |
$begingroup$
I am training a deep neural network in Keras. I have set the values of learning rate, learning rate decay, epochs and batch size.
(I am using fit_generator i.e data coming from a generator but without any kind of shuffling.)
Being said that my training shows highly differenttraining summary.
Sometimes it's like:
And other times it is
The two of the above images show the highly unpredictable behavior of model for the same values of all hyperparameters.
Can someone explain why this is happening?
keras predictive-modeling
asked 6 mins ago
yamini goelyamini goel
213
$endgroup$
I am training a deep neural network in Keras. I have set the values of learning rate, learning rate decay, epochs and batch size.
(I am using fit_generator i.e data coming from a generator but without any kind of shuffling.)
Being said that my training shows highly differenttraining summary.
Sometimes it's like:
And other times it is
The two of the above images show the highly unpredictable behavior of model for the same values of all hyperparameters.
Can someone explain why this is happening?
keras predictive-modeling
keras predictive-modeling
asked 6 mins ago
yamini goelyamini goel
213
asked 6 mins ago
yamini goelyamini goel
213
asked 6 mins ago
yamini goelyamini goel
213
asked 6 mins ago
yamini goelyamini goel
213
asked 6 mins ago
yamini goelyamini goel
213
213
add a comment |
add a comment |
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