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If you want to continue training the model from a previous finetuned checkpoint you can use the
'load_at_start flag' in fit and set it to False. This isn't documented since I envisioned people would mostly use the finetuned model for inference.
So this should work for you now:
new_model.fit(X_train, y_train, load_at_start=False)
Regardless, what you found is a bug which I will fix. Will get back to you when its done. Thanks!
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