cross entropy loss max value

The cross entropy loss function for multiclass can be computed as: $$-\sum\limits_{i=1}^N y_i log \hat{y}_i$$ where $$y_i$$ is a class and $$\hat{y}_i$$ the estimated probability. The minimum value is $$0$$ (when the estimated probability is $$1$$ for the correct class). Has this function a maximum value? I think when the estimated probability is $$0$$ for the correct class, but what probabilities should the other classes to have?

It doesn't have a maximum value. When $$y_i=1$$, and $$\hat{y}_i=0$$, the loss is infinite. Or at least, we can say that as predicted probability for the true class goes towards $$0$$, the loss approaches towards infinity. Since the range of $$H(y,\hat{y})$$ is $$\mathbb{R}_{\geq 0}$$, and $$\infty \notin \mathbb{R}_{\geq 0}$$, we cannot say the function has a maximum (i.e. the maximum value should have been in its range). Probability values of other classes doesn't matter, because the corresponding $$y_j$$ are $$0$$.