Why loss and val_loss vary for same value of lr, epoch, batch size and lr-decay?Keras difference beetween val_loss and loss during trainingLSTM Timeseries recursive prediction converge to same valueKeras intuition/guidelines for setting epochs and batch sizeWhy might a neural network consistently underestimate its target?Why is my Keras model not learning image segmentation?Bidirectional GRU: validation loss stuck on plateau diverges from well performing training losscustom loss in keras, problem with batch sizeGeting batch size in keras custom losspredict gives the same output value for every image (Keras)InvalidArgumentError: Conv2DCustomBackpropInput: input and out_backprop must have the same batch size
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Why loss and val_loss vary for same value of lr, epoch, batch size and lr-decay?
Keras difference beetween val_loss and loss during trainingLSTM Timeseries recursive prediction converge to same valueKeras intuition/guidelines for setting epochs and batch sizeWhy might a neural network consistently underestimate its target?Why is my Keras model not learning image segmentation?Bidirectional GRU: validation loss stuck on plateau diverges from well performing training losscustom loss in keras, problem with batch sizeGeting batch size in keras custom losspredict gives the same output value for every image (Keras)InvalidArgumentError: Conv2DCustomBackpropInput: input and out_backprop must have the same batch size
$begingroup$
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
$endgroup$
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
$endgroup$
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
$endgroup$
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
edited 43 secs ago
yamini goel
asked 33 mins ago
yamini goelyamini goel
214
214
add a comment |
add a comment |
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