from torch import rand, randint
from torchmetrics.classification import MultilabelFBetaScore
metric = MultilabelFBetaScore(num_labels=3, beta=2.0)
metric.update(randint(2, (20, 3)), randint(2, (20, 3)))
fig_, ax_ = metric.plot()