import torch
from torchmetrics.wrappers import ClasswiseWrapper
from torchmetrics.classification import MulticlassAccuracy
metric = ClasswiseWrapper(MulticlassAccuracy(num_classes=3, average=None))
values = [ ]
for _ in range(3):
    values.append(metric(torch.randint(3, (20,)), torch.randint(3, (20,))))
fig_, ax_ = metric.plot(values)