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@Domojz You should change trainModel function (multi_training.py) in order to resume your training session and you have to store configurations once they are dumped during training, otherwise it won't be possible. All you need to do is to check in trainModel (or somewhere before, for example in main.py) whether or not you have dumped results, and if you do, use pickle to load 'em. The job is pretty straightforward, good luck!
Is it possible to resume training in any way?
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