I want to train a network and save the weights. Then use a new data set and resume training with the weights from the previous data set.
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ronald ogren
el 16 de Mzo. de 2018
Comentada: Moh. Saadat
el 29 de Ag. de 2022
It seems train always randomizes the weights when called. I can't seem to maintain the weights from the first training set.
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Sonam Gupta
el 28 de Mzo. de 2018
You can continue the training from weights obtained by previous data set by extracting the layers from the network's "Layers" property, and then passing it to "trainNetwork", as follows:
if true
% Train a network
net = trainNetwork(XTrain, YTrain, layers, options);
% Extract layers from the trained network
newLayers = net.Layers;
% Retrain the network, but start from where we left off
newNet = trainNetwork(XTrain, YTrain, newLayers, options);
'trainNetwork' will always use the weights that are stored in the layers which you pass in for training.
3 comentarios
Moh. Saadat
el 29 de Ag. de 2022
There is a small caveat to this: check that whether your output 'net' is a LayerGraph or a DAGNetwork. If it is not a LayerGraph, use layerGraph(net) instead of net.Layers.
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