While this is technically possible, it is not remotely practical and the downside risk of pushing out a borked model is much higher than the upside.
Training the model is expensive (obviously), but even if you are only training it slightly, running evaluations to determine whether the particular training checkpoint is at or above the quality bar is expensive, too.
Training the model is expensive (obviously), but even if you are only training it slightly, running evaluations to determine whether the particular training checkpoint is at or above the quality bar is expensive, too.