number of weights in multinom

Dear colleagues,

In the function multinom (package nnet), I get the following message after training for a model with 9 inputs and 6 classes (output) :

# weights:  66 (50 variable)

I understand that there are 50 variables in the model,
but I don't understand the number 66. 
How can we interpret this number ?

Thank you very much.

Yours sincerely,
Franck Vermet.