Unverified50% confidenceFactExact time
Training used a context length of 256 and a micro-batch size of 16 with gradient accumulation, and peak memory during the main training process was 1.54 GiB
1
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50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
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UnverifiedIn a classification task with nearly a thousand points, using a batch size of 30 can speed up training by approximately 33 times.76% similarUnverifiedTraining uses batch size 256, 400,000 steps, EMA 0.9999, linear learning rate decay over the final quarter, and torch.compile achieves a 2.4× speedup over eager mode.74% similar
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