from sklearn.model_selection import GridSearchCV
model_to_set = OneVsRestClassifier(SGDClassifier(loss='log', penalty='l1', class_weight="balanced"))
parameters = {
    "estimator__alpha": [10**-5,10**-4,  10**-3, 10**-1, 10**1]
}
model_tunning = GridSearchCV(model_to_set, param_grid=parameters, scoring='f1_micro',n_jobs=-1)
model_tunning.fit(x_train_multilabel, y_train)
print (model_tunning.best_score_)
print (model_tunning.best_params_)