I was working on hyperparameter optimization for neural network. I was running the model for 20 epochs. After figuring out the best hyperparameters, I ran the same model again alone (now no hyperparameter optimization) but I got different results. Not only that, I figured out that the value (accuracy) reached while performing hyperparameter optimization occured at the last epoch (20th). On the other hand, when I ran the same model again, I figured out that accuracy achieved was not until 200 epochs. Yet, the values were slightly less. Below is the figure:
Therefore, I would like to know what was the random seed chosen by tensorflow at that moment. As a result, I am not interested in setting the random seed to a certain constant, but I would like to see what was chosen by tensorflow.
Your help is much appreciated!!
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