# 1. Benchmark ## 1.1 Environment - We train the ViT on 1 node with 8 A100 gpus or 4 nodes with 32 A100 gpus. ## 1.2 DataSet - We train the ViT on ImageNet. ## 1.3 Benchmark | Model | Phase | Dataset | gpu | img/sec | Top1 Acc | Official | | --- | --- | --- | --- | --- | --- | --- | | ViT-B_16_224 |pretrain |ImageNet2012 |A100*N1C8 | 3583| 0.75196 | 0.7479 | | ViT-B_16_384 |finetune | ImageNet2012 | A100*N1C8 | 719 | 0.77972 | 0.7791 | | ViT-L_16_224 | pretrain | ImageNet21K | A100*N4C32 | 5256 | - | - | | |ViT-L_16_384 |finetune | ImageNet2012 | A100*N4C32 | 934 | 0.85030 | 0.8505 | # 2. Reference https://github.com/PaddlePaddle/PLSC/blob/master/task/classification/vit/README.md
