How to train the best model about ml-tool-wear HOT 1 CLOSED

Good question! (and yes, I can understand you well)

I'm not sure if this will 100% work, but you can fix the hyper-parameters in the random search to match the best model I got. Give that a try. Change these in the code:

beta_value =params["beta_value"]
codings_size =params["codings_size"]
conv_layers =params["conv_layers"]   
start_filter_no =params["start_filter_no"] 
kernel_size_1 = params["kernel_size_1"]
dilations = params["dilations"]
earlystop_patience=params["earlystop_patience"]

The solution (fixing the hyperparameters) is a bit "hacky" -- I've since made it easier in my later work.

Also, a VAE is naturally not deterministic, so you can expect variability between models, even with the same hyperparameters between models.

Finally, try training a bunch more models. Eventually you should get one that is closer.

Hope this helps.

from ml-tool-wear.