Hi everyone,
I am doing a set of experiments on varying network hyperparameters and checking the effect on the accuracy on the model.
For this I have a list of set of hyperparameter values to compare with.
I want to train the model in a loop starting from scratch in each run in google colab and then log results of each run using mlflow.
Is there a way I can train from sratch in a loop without having to restart the jupyter kernel everytime?
Help will be really appreciated!
Thank you!!