Forecasting

I have data for 80 months. I use 69 months (train set) which I use to forecast 11 months (test set) into the future.
I have implemented lstm, prophet, naive bayes, sarimax, and an arima models to forecast. Of all these models, the best model accuracy (or error) I get is about 10% using MAPE or MAE as metrics of forecast accuracy (or error).
I am looking for some who can improve the forecast accuracy to be below 10%.
This work has to be done in R or Python.
If you are interested in this project, I am willing to share the data (69 months for training set + 11 months to test forecast accuracy) in order for you to determine if you want to take this project because I will not be able to pay you in full until I am able to actually test that your code does indeed product a 11 month forecast whose error is less than 10% according to mape.
In other words, I would have to verify that your code actual works according to the criteria I am stipulating - I cannot pay you if I do not know if your forecast meets the expectations I am seeking - i.e. if you cannot come with a forecast that is better than mine, it would not make sense for me to pay you for that.
Should you be interested in this, please be clear to mention your preferences on how you would like us to work on this or have further questions.