I was taking part in a Hackathon and I was supposed to do regression in task-1 of two tasks and I want some clarification about the loss while doing regression. The Problem I m facing is like this when i trained the model and did regression (FNN) my RMSE value was around 5000-6000 even after all that feature engineering and now I m thinking is there any baseline of acceptable loss while doing regression problems.

Like if I m doing a simple regression task (for values in the range 0-1000 with sufficient examples in this range to do regression using ANN) then RMSE value of 0.7 seems good.

But what if I m doing a more complex task ( values ranges from 0 to 10-20 lacs with with not much examples say 500-400) and example being inconsistent.

What is the baseline that i should look while training for such cases or do tell if I m doing something super stupid to get this much RMSE