I'm wanting to continue the training process for a model using new data.
I understand that you can continue training a Pytorch Lightning model e.g.
pl.Trainer(max_epochs=10, resume_from_checkpoint='./checkpoints/blahblah.ckpt') for example, if you last checkpoint is saved at epoch 5. But is there a way to continue training by adding different data?
To new users of Torch lightning, the new syntax looks something like this
trainer = pl.Trainer()
trainer.fit(model,data,ckpt_path = "./path/to/checkpoint")
Also since I don't have enough reputation to comment, if you have already trained for 10 epoch and you want to train for 5 more epoch, add the following parameters to the Trainer
trainer = pl.Trainer(max_epochs = 15)
Yes, when you resume from a checkpoint you can provide the new DataLoader or DataModule during the training and your training will resume from the last epoch with the new data.
trainer = pl.Trainer(max_epochs=10, resume_from_checkpoint='./checkpoints/blahblah.ckpt')
trainer.fit(model, new_train_dataloader)
max_epochs=5 or max_epochs=10? Reference: lightning.ai/forums/t/how-to-resume-training/432/8
DataModule during training be provided if we just load the model?