Using Logloss as the loss_func in a Binary Classification with TabularList

I am currently using a dataset where you have to predict whether a basketball player made a shot or not. 0 or 1. The evaluation metric is meant to be log_loss. So how would I go about implemented log_loss within Tabular data? How do I go about using log_loss as the loss function for my TabularList?

At the moment I have:

data = (TabularList.from_df(df_train, cat_names=cat_names, cont_names=cont_names, procs=procs) .split_by_idx(list(range(len(df_train)-5000,len(df_train))))

With my Learner looking like:

learn = tabular_learner(data, layers=[1000, 200, 15], metrics=accuracy, emb_drop=0.1, callback_fns=ShowGraph)

I know I can adapt the loss function like so:

learn.loss_func = nn.BCELoss()

However when I do that it says my target is different from my input when I run learn.lr_find()

Any help would be really appreciated!!