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  3. Intermediate Deep Learning with PyTorch

Exercise

Evaluating forecasting models

It's evaluation time! The same LSTM network that you have trained in the previous exercise has been trained for you for a few more epochs and is available as net.

Your task is to evaluate it on a test dataset using the Mean Squared Error metric (torchmetrics has already been imported for you). Let's see how well the model is doing!

Instructions

100 XP
  • Define the Mean Squared Error metrics and assign it to mse.
  • Pass the input sequence to net, and squeeze the result before you assign it to outputs.
  • Compute the final value of the test metric assigning it to test_mse.