Keras: update model with a bigger training set

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I trained a model with Keras for text classification (supervised learning) using a training set. Let's say that there are 50.000 sentences in this training set.

During a week I collect 5.000 new sentences and I add them to the old training set.

If next week I want to train a new model with the new and bigger training set (50.000 old sentences + 5.000 new sentences), should I restart the training phase from the beginning, or can I take the old model and "update" it in some way to save some time?

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1 Answers

You can save/load model/weights. Check out this tutorial by Jason Brownlee.

After you loaded the weights, you can start training with the new dataset (the 55000 samples). As the 'training' is basically just updating weights, and you loaded your trained weights, you are now 'updating' the already trained model.

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