Is 0.1542 Mcfadden's Pseudo R2 acceptable in general? I am conducting logistic regression and got 0.1542 as pseudo R2, and it is based on Mcfadden's.
I've searched materials about this, because this is my first time that modelling logit models, and found that it has been mentioned 0.2~0.4 means 'excellent fit'.
Then can I think that it is very difficult getting high value of pseudo R2 compare to that of R2?(for example, ofc it depends on the field, but as we generally we talk about 0.6 has great fit...)
And if it's true, isn't there any matter if I think this is acceptable enough, although it is not that excellent? Or is there any table or materials that tells which pseudo R2 correspond to which R2?

Even in linear regression, such an $R^2$ value can be totally fine, so I would not immediately dismiss your logistic regression model due to poor performance.
I kind of like $R^2$-style measures, but a big drawback that I see to them is viewing them like grades in school, where $0.5$ is an $F$-grade that makes us sad while $0.9$ is an $A$-grade that makes us happy, even through, for some problems, $0.4$ is outstanding performance, while $0.9$ could be rather pedestrian performance for other problems.
Your performance is what it is. It is worse than a model that achieves $0.3$ and better than a model that achieves $0.1$. If it does something useful for you, that seems like a win. If your model is not useful, perhaps because competing models have achieved superior $R^2_{McFadden}$, then your performance is not good enough.
