mathematical optimization – General::munfl – Precision lost in LinearModelFit

I am new to mathematica so I am confused regarding the loss of precision in LinearModelFit. In building a linear model with uora (1 or 2) and encodeSeverity (1,2 or 3)

lmfit = LinearModelFit(Transpose({
    uora, encodeSeverity}),
  {1, urbanOrRural},
  {urbanOrRural},
  NominalVariables -> urbanOrRural
  )

It seems fine but when I look at the ParameterTable and ANOVA Table, the precision is lossed and does not help me with my analysis.

In(11):= lmfit("ParameterTable")

During evaluation of In(11):= General::munfl: Exp(-93565.1) is too small to represent as a normalized machine number; precision may be lost.

During evaluation of In(11):= General::munfl: Exp(-1342.79) is too small to represent as a normalized machine number; precision may be lost.



In(12):= lmfit("ANOVATable")

During evaluation of In(12):= General::munfl: Exp(-1342.79) is too small to represent as a normalized machine number; precision may be lost.

enter image description here

The p-value is reported as 0. and I can’t find any help online regarding linear models.
Is there a way to improve the p-value and show it in these tables?
Can anyone help?
What am I doing wrong?