Volatile Predictions

Hi all, I am using FB Prophet to model an inventory management Time series problem, basically need to predict the Sales of a specific product on a given week.
The historic data for the sales have high seasonality, e.g. Sales were 0 in all months before Feb, but in Feb they started picking up and had 250 sales at its peak;
dummy sales numbers - **0, 0, 30,60,120,250,130,28,67,0.**
My projections look like **10, 15, 31000, 246, 13, 16.**
Could someone guide me on why this is the case?
My guess is that the model is not being able to account for seasonality and is predicting an exponential increase in sales, in a bell curve distribution.
I don't want to artificially set the max threshold on the output, but want the model to infer it from data.
**Hyperparameter tuning challenge** as the same piece of code will be used to train separate models for separate products in essentially a for loop.