Yes, that might happen, as seen here:
weights = torch.tensor([0.01] * 100)
l = torch.multinomial(weights, 100, True)
print(l.unique().shape)
> torch.Size([59])

I’ve had better results using the WeightedRandomSampler than using a weight parameter in your loss function but ymmv.