Unverified50% confidenceFactExact time
Training 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.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
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UnverifiedThe Deformable DETR paper claims to reduce the training schedule from 500 epochs to approximately 50 epochs, achieving nearly a 10× speedup.76% similarUnverified仅调整 num_workers、pin_memory、prefetch_factor 三个 DataLoader 参数，相同 2000 步训练耗时从 633 秒降至 358 秒，运行时间缩短 43%73% similarUnverifiedAnthropic's peak compute consumption during model pre-training is under 200 megawatts, with a duration of approximately two months.70% similar
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