Minimum hardware to reproduce the work.

[zyang1580]

Minimum hardware to reproduce the work.

[zyang1580]

Thank you for your interest in our work. Our experiments have been conducted exclusively on the A100 machine. It is feasible to run on A40 and 3090 machines by reducing the batch size, but certain parameters may require corresponding adjustments.

[TianhaoShi2001]

In A40, with the dataset used in the original text, I reduced the train_batch_size to 16, resulting in a maximum memory usage of less than 40GB (about 33GB), making it runnable on A40. At this batch size, I set the min_lr parameter to 1e-4, achieving results close to those in the original text. If running on a 3090 GPU, it may require multi-GPU parallelism or further reduction of batch size to meet the GPU requirements, along with corresponding adjustments to the learning rate.