How many run should we implement on the machine learning model?
It depends on your problem, start with a big number (32 ?) then decrease if the model is stable / when you deal with stability.
You need to know that having multiple runs may be part of the solution: you can create an ensemble of models to get more stable models. Here again, the way to create an ensemble and the number of models you need to run to build an ensemble is determined experimentally. The main alternative to add stability to your model is trough regularisation (that really depend on the model you want to use).