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!
This exercise is part of the course
Intermediate Deep Learning with PyTorch
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
def evaluate_model(model):
# Define accuracy metrics
acc_alpha = ____(____, ____)
acc_char = ____(____, ____)