I'm training Machine Learning models on Python and using R squared metric from Scikit Learn to evaluate them. Id decided to play around with Scikit's r2_score function, feeding it a random array of same value as input y_true and and slightly different but same value array as y_predict. I was getting arbitrarily large (negative) values when the input length of array is 10 or more and 0 when the input length is less than 10.
from sklearn.metrics import r2_score
r2_score([213.91666667, 213.91666667, 213.91666667, 213.91666667, 213.91666667,
213.91666667, 213.91666667, 213.91666667, 213.91666667, 213.91666667],
[213, 214, 214, 214, 214, 214, 214, 214, 214, 214])
>>> -1.1175847590636849e+26
r2_score([213.91666667, 213.91666667, 213.91666667, 213.91666667,
213.91666667, 213.91666667, 213.91666667, 213.91666667, 213.91666667],
[213, 214, 214, 214, 214, 214, 214, 214, 214])
>>> 0