Disable loss rounding in training stats log

[AnMakc]

This PR disables unconditional rounding of the loss value to 4 digits in logged values. Effectively reverting part of #9491.

Closes #38032 (stale)

Motivation:

• Loss value may have very low absolute magnitude depending on model/data/objective function.
• No other values are rounded (e.g. eval/loss or grad_norm) which may result in confusion.
• Rounding is a display/formatting detail in this case and should not be done silently in non-UI code

Examples of undesired behavior that would be fixed with this PR:

Notebook outputs:

Wandb loss chart:

[Rocketknight1]

cc @SunMarc, but maybe formatting using something like %.4f so that it always displays 4 significant figures with an optional exponent would preserve the clean rendering but still work in cases when the loss is very small?

[AnMakc]

@Rocketknight1 Any rounding at this point introduces inconsistency between validation and training loss. We could not apply formatting here as we log numeric value, not string.

The main point is that any formatting is a representation detail that should be handled by the display-related code and we should not make assumptions on how it works as in most cases it is some external handler (wandb, trackio, ipython NB widget, etc.).