Error in interpret plot losses

xpected object of scalar type Float but got scalar type Long for argument #2 ‘other’

#learn.load(‘stage-1-rn50-u5datablocks’)
interp = ClassificationInterpretation.from_learner(learn)

show most confused images (with min cut off = 2)

interp.most_confused(min_val=2)

or plot the full confusion matrix:

interp.plot_confusion_matrix(figsize=(17,12), dpi=60)

This is multilable classification using F1 s
f1_score = partial(fbeta, thresh=0.4, beta=1)

learn = create_cnn(
data,
resnet50,
cut=-2,
split_on=_resnet_split,
loss_func=FocalLoss(),
#F.binary_cross_entropy_with_logits,
path=path,
metrics=[f1_score],
)
i m using fit_one_cycle instead of fit…
Any help appreciable