Does ModelCheckpoint Callback Reset For Each

I’m running a classifier that is drawing data from two large datasets using two generators. I build one model and then train it in a loop that looks something like this:

myModelCheckpoint = ModelCheckpoint("dirname") for _ in range( nIterations ): x_train, y_train = getTrainingDataFromGenerators() x_train, y_train, ... epochs=10, callbacks=[myModelCheckpoint ]) 

What I want is for ModelCheckpoint to fire on the single best model over all nIterations. But it seems like it resets and starts over for each I’ve seen a model get saved for a particular val_acc that is lower than the best val_acc of the previous

Essentially I want a global ModelCheckpoint, not local to a particular Is that possible?

submitted by /u/Simusid
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