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Exercise

Multi-output model evaluation

In this exercise, you will practice model evaluation for multi-output models. Your task is to write a function called evaluate_model() that takes an alphabet-and-character-predicting model as input, runs the evaluation loop, and prints the model's accuracy in the two tasks.

You can assume that the function will have access to dataloader_test. The following imports have already been run for you:

import torch
from torchmetrics import Accuracy

Once you have implemented evaluate_model(), you will use it in the following exercise!

Instructions 1/3

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  • Define acc_alpha and acc_char as multi-class Accuracy() metrics for the two outputs, alphabets and characters, with the appropriate number of classes each (there are 30 alphabets and 964 characters in the dataset).