Exploding Gradient Problem
The Exploding Gradient Problem is an error during backpropagation training where gradients accumulate, resulting in unstable, massive parameter updates that prevent model weights from converging.
Frequently Asked Questions
How do you prevent exploding gradients?▼
By using gradient clipping (capping gradient value magnitudes) or employing weight initialization strategies like Xavier or He initialization.
What are the symptoms of exploding gradients?▼
Loss function values displaying `NaN` during training logs, or weights rapidly expanding to infinity.
Quick Facts
- CategoryModel Training
- Key ApplicationNeural network debugging, optimizer setup, and deep network configuration.
Coverage Trend12 Weeks
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