regression best random_state

#x->independent variable
#y->dependent variable
#model->algorithm
def maxr2_score(model,x,y):
    max_r_score=0
    for r_state in range(42,101):
        
        x_train,x_test,y_train,y_test=train_test_split(x,y,random_state=r_state)
        model.fit(x_train,y_train)
        pred=model.predict(x_test)
        score=r2_score(y_test,pred)
        
        if score>max_r_score:
            max_r_score=score
            final_r_state=r_state
    print('max_r2_score is at random_state  ',final_r_state,'  which is  ',max_r_score)
    return final_r_state