All Questions
Tagged with neural-network training
136
questions
1
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38
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How does seeing training batches only once influence the generalization of a neural network?
I am referring to this question/scenario Train neural network with unlimited training data but unfortunately I can not comment.
As I am not seeing any training batch multiple times I would guess that ...
- 13
2
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13
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What's the best way to incorporate momentum and regularization when training a neural network?
I want to implement the momentum algorithm to train a neural network, but I'm uncertain about where the regularization term should be incorporated. For ridge regularization, one option is to have:
$$
...
- 21
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18
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Loss increase while accuracy also increase [duplicate]
I'm training a fairly large classification model,and I'm having the below results.
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- 13
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51
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0
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1
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114
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Holding batch size constant, will a bigger dataset consume more GPU memory?
If you hold (mini) batch size constant (as well as everything else) but increase the number of examples (and therefore the number of training iterations), should you expect a (significant) increase in ...
- 101
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48
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How was the word2vec model trained?
Let's take the CBOW (continuous bag of words) model as the example.
Suppose that, there are $c$ context words, each of which is a one-hot encoding vector. So the total number of elements of input ...
- 56
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170
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Training loss is much higher than validation loss
I am trying to train a neural network with 2 hidden layers to perform a multi class classification of 3 different classes. There is a huge imbalance to the classes, with the distribution being around ...
0
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1
answer
39
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How to train the AI to recognize soldiers' allegiance by armband?
If I hypothetically want to train an AI to recognize enemy soldiers by the color of their armband (for example green armband), should I feed the AI with only green armband soldiers or should I also ...
- 101
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36
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Train/val/test approach for hyperparameter tuning
When looking to train a model, does it make sense to have a 60-20-20 train val test split, first hyper parameter tuning over the training dataset, using the validation set, picking the best model. ...
- 121
2
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2
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342
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Dynamically remove data from training dataset
I was wondering today if it would be a good approach to remove data dynamically from the training dataset when learning a neural network. Assuming a classification task, the approach would be ...
- 566
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1
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28
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kernel initializers and epochs
In a sample code like this (From Keras library):
model.add(Dense(13, input_dim=13, kernel_initializer='normal', activation='relu'))
the kernel values will be ...
- 894
1
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164
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What does that mean if the loss looks like this?
I have a problem. I have trained a model. And as you can see, there is a zigzag in the loss. In addition, the validation loss is increasing.
What does this mean if you only look at the training curve? ...
- 89
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31
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Why should you decide a re training of a machine learning model by a conversion rate or KPI and not randomly or according to perodic time?
Why is it more beneficial to automatically train a machine model by a conversion rate or by a KPI instead of by periodic time?
The following image shows an example of the conversion rate. However, as ...
- 89
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2
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3k
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0
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35
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What does the learning curve indicate?
I am training a deep learning model for traffic prediction. When I use 10 months of data for training (validation split: 10%) and 2 months for testing. The loss curve looks like this:
.
and the ...
