deeplearning4j : update a saved model

Question

I trained a model using deeplearning4j on a first part of my data and saved it.

ModelSerializer.writeModel(model, locationToSave, true);

Now, I want to train this saved model on the next part of data.

I loaded the model:

MultiLayerNetwork model = ModelSerializer.restoreMultiLayerNetwork("location");

and then I used to train it on the new data

model.fit(trainingDataIt);

but the model seems not fitting because I don't see the stat of each iteration

11:56:56.161 [ADSI prefetch thread] DEBUG o.n.l.memory.abstracts.Nd4jWorkspace - Steps: 4
11:59:30.072 [main] DEBUG o.d.d.iterator.AsyncDataSetIterator - Manually destroying ADSI workspace
11:59:30.123 [ADSI prefetch thread] DEBUG o.n.l.memory.abstracts.Nd4jWorkspace - Steps: 4
12:01:39.760 [main] DEBUG o.d.d.iterator.AsyncDataSetIterator - Manually destroying ADSI workspace
12:01:39.793 [ADSI prefetch thread] DEBUG o.n.l.memory.abstracts.Nd4jWorkspace - Steps: 4
12:03:46.496 [main] DEBUG o.d.d.iterator.AsyncDataSetIterator - Manually destroying ADSI workspace
12:03:46.551 [ADSI prefetch thread] DEBUG o.n.l.memory.abstracts.Nd4jWorkspace - Steps: 4

is it normal, or there is something wrong with my approach ?

Answer 1

您只需要在加载它并调用 fit 后调用 ModelSerializer.writeModel。