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Near-Zero Token Embeddings Silently Stall Training in Gated Sequence Models

Read the original at HF Daily Papers

Summary

Near-zero token embeddings stall training in gated sequence models by amplifying gradients, causing FP32 clipping to overflow and zero current batch gradients.

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