Fine-tuning the proxy-trained weights on the full dataset to measure "warm-start" acceleration.

Training a ResNet-50 and a Swin-Transformer solely on the data within 090101.7z .

Measuring the latency of extracting .7z archives versus standard .tar or raw image folders.

This paper explores the efficacy of using compressed data shards, specifically the 090101.7z subset, to achieve rapid model convergence in high-resolution image classification. We investigate whether a strategically sampled shard can serve as a high-fidelity proxy for the full ImageNet-1K dataset, reducing computational overhead during the initial architectural search phase.

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