from torch import randn, randint
from torchmetrics.classification import MulticlassCohenKappa
metric = MulticlassCohenKappa(num_classes=3)
values = []
for _ in range(20):
    values.append(metric(randn(20,3).softmax(dim=-1), randint(3, (20,))))
fig_, ax_ = metric.plot(values)