# Which neural network model to choose between different iterations?

I was running an experiment with neural networks and I could see that training the neural network model with the same input give different results on the test. This should be due to the different weight initializations. The question is how to choose a model from these iterations. Do we need to take the average of results or the best result or the take the average of weights and then retrain and get a single result?

• No I mean that the test set shouldn't be used for model selection. So you can train $N$ models on the training set using the same input data and different initializations. Evaluate those $N$ models on the validation set in order to determine the best one and then re-evaluate that best one on the test set to see if it is actually good. – Djib2011 Aug 26 at 12:41