i see, thanks for the explanation, so basically it is initializing the weights to the weights which are saved instead of to the random ones, if i understand correctly? So in this case to prevent this behavior and start from random weights I should just change the name of output file with weights, right?
hyperparams are only for the task, not the model
@<1566596960691949568:profile|UpsetWalrus59> the hyperparameters will be the ones associated with the experiment. The input model you specified has a path to the actual weights file - this message basically means the same weights file is already registered in a model object and thus a new model object will not be created, and the existing one will be used as an input model
yes, i can see the hyperparams are reflecting correctly, but I mean it shouldn't start from previous model checkpoint if it is different run with different hyperparams
Hyperparameters are connected to the experiment so your config will be right 🙂
hm, but why it happens if my new model has different hyperparameters and is separate experiment with separate name? how to avoid this behavior?
Hi @<1566596960691949568:profile|UpsetWalrus59> , I think this basically means you have an existing model and it's using it as the starting point.