Help with implementing tabular_learner


I currently am working on a multi-variate classification problem where i have a target column with 6 possible outcomes. I am trying to implement the following however I believe there might be an issue with the learner (this is an assumption). The following is what i have implemented thus far:

dep_var = ‘target’
cont_names = cont_names
cat_names = cat_names
procs = [Normalize] #other pre-processing done in sklearn, just using normalize on contiuous values here

test = TabularList.from_df(df.iloc[test_index].copy(), path=path, cat_names=cat_names, cont_names=cont_names)

data = (TabularList.from_df(df, path=path, cat_names=cat_names, cont_names=cont_names, procs=procs)
#this shows the dataset

learn = tabular_learner(data, layers=[200,100], metrics=accuracy), 1e-2)

When I get here I see an issue with the model. The following is the output.
epoch: 0
train_loss: nan
accuracy: 0.098435
time: 00:43

Am i missing anything when doing training on 6 possible categories? Any direction would be greatly appreciated!

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