How to determine Number of neuron in hidden layer for classification
There is not a clear a answer for this question. You should try and evaluated how the models performs testing diffferents configurations. But, basically, the next two premises are followed:

More neurons per layer --&gt; more complex model, and probably you will
obtain better accuracy.
More hidden layers --&gt; more complex model, and again, probably you
will obtain better accuracy.
WARNING Both approaches increase the chance of overfitting by increasing the complexity of model. You need to carefully evaluate them through statistically robust model selection procedures e.g. cross-validation

Be aware that incrementing the complexity of the model will increase the computational process and , as mentioned, be careful with overfitting.
I recommend try a small number of neurons first, and then, try to increase step by step seeing if some improvement is achieved in the model.