Does the TensorFlow save function automatically overwrite old models? If not, how does the save/load system work?
You can use
model.save('./model.h5')
which will save the model to a file
and
model = tf.keras.models.load_model('./model.h5')
to load the model
I've tried finding information regarding this online but the word overwrite does not show up at all in the official Tensorflow documentation and all the Stack Overflow questions are related to changing the number of copies saved by the model.
I would just like to know whether or not the save function overwrites at all. If I re-train a model and would like to re-run the save function will the newer model load in when I use the load_model function? Or will it be a model that is trained on the same data twice? Do older iterations get stored somewhere?