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By default the model trains with MAE, and you are evaluating with MSE, which explains the losses’ scale difference. And early stopping is one of the strongest regularizers with regressions and neural networks.

I've hardcoded

loss=MSE(),

valid_loss=MSE()

Hi @Oleksii Kaplenko! The validation loss is scaled back to the original scale of the data

Got it, thanks

hi @Oleksii Kaplenko just curious, how are you pulling your tensorboard plots?

@Rafael Correia Da Silva using fit() method creates lightning_logs folder, inside this folder lies tensorboard files for all runs, to see these charts I use command:

tensorboard --logdir ./lightning_logs

wow I was doing this stuff by hand 🤡 this is soo helpful, thanks!