TPOT error for xgboost multiclass classificaion

While trying to use Tpot to get the best pipeline I am getting the following error

`Invalid classes inferred from unique values of y. Expected: [0 1 2 3 4 5], got [1 2 3 4 5 6]`

## Context of the issue

I am using the tpot 0.12.1 version and xgboost 2.0.1 version, in place of cv I am providing `StratifiedKFold(
n_splits=cv_folds, shuffle=False, random_state=params["random_state"]
)`

My data consists of 6 classes. I am aware of that this error comes due to the different splitting each time (using stratified split), some splits do not have all the labels in both groups. How can i resolve this in tpot?

still I am getting the following error.

`Invalid classes inferred from unique values of y. Expected: [0 1 2 3 4 5], got [1 2 3 4 5 6]`

Note: I am using label encoding as xgboost 2.0 version does not have in built label encoding.

May I know is there a way to resolve this error?