M02.01 exercise - ValueError: too many values to unpack (expected 2) error

Hi communnity,

I cannot find why I get the error

'ValueError: too many values to unpack (expected 2)'

I checked the solution and the FAQ
Here is my code:

from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import make_pipeline
from sklearn.model_selection import cross_validate
from sklearn.svm import SVC

model=make_pipeline(StandardScaler(), SVC(kernel="rbf")) ## works fine

from sklearn.model_selection import ShuffleSplit

cv=cross_validate(model, data, target, cv=ShuffleSplit(random_state=0))## works fine

from sklearn.model_selection import validation_curve
import numpy as np

gamma=np.logspace(-3, 2, num=30)
train_scores, test_scores = validation_curve(
    model, data, target, param_name="svc__gamma", param_range=gamma,
    cv=cv, n_jobs=2)
error message:  ValueError: too many values to unpack (expected 2) error 

I tried with the learning curve as well and got the same error

Many thanks and great MOOC
Gabriel

The cv in the validation_curve corresponds to the results of the previous cross-validation instead of an instance to ShuffleSplit.