I’m not sure, if your new dataset only contains values in the larger range or just a few samples.
In the former case, you could try to normalize the target to a specific range (e.g. z-score) and revert the normalization for the actual prediction for your validation and test set.
In the latter case, this approach would also be possible, but I’m afraid the smaller values might be treated as noise and you might overfit on the larger values.