Add grad_norm metrics
#1143
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Add grad_norm metrics
#1143
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facebook-github-bot
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the
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tianyu-l
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Apr 27, 2025
| @@ -394,7 +397,7 @@ def log( | |||
| color = self.color | |||
| logger.info( | |||
| f"{color.red}step: {step:2} " | |||
| f"{color.green}loss: {global_avg_loss:7.4f} " | |||
| f"{color.green}loss: {global_avg_loss:7.4f} gnorm: {grad_norm:.2f} " | |||
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I agree this metric would be helpful. Do you think it has to be in the terminal print, instead of staying in TB/W&B only for now?
If so, could you invent a new color in the Color class -- o/w it seems visually harder to recognize loss. Also nit: two spaces before after each column.
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What does this PR do?
This PR adds the
grad_normmetric to the logging metrics.Why this PR is important
Monitoring the gradient norm is crucial for detecting training stability and getting some optimization insights.