Unverified50% confidenceFactExact time
The experiment trains a small MLP on a modular addition task modulo 97, with the training set making up only 35%, using full-batch training for a total of 20k steps.
1
Sources
50%
Confidence
Long-term
Relevance
10/26/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedTraining 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 GiB76% similarUnverifiedThe entire training process of MDT can be completed in under 20 minutes on a single GPU.73% similarUnverifiedCWAA的实验仅有5000个训练步和10M参数规模，无法证明其在大规模长训练下的表现73% 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.72% similarUnverifiedPost-training costs only 1–5% of the cost of training a large model from scratch, yet can yield a 20–50% performance improvement on target tasks.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1099229API
curl https://kongchang.com/api/v1/knowledge/claims/1099229MCP
get_claim(id=1099229)