DingXiaoH / RepVGG

RepVGG: Making VGG-style ConvNets Great Again
MIT License
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Training script inquiry #106

Open zw615 opened 1 year ago

zw615 commented 1 year ago

Hi Xiaohan, thanks for the great work!

I wonder if you could provide the original training script to reproduce the results of Table 5 (200 epochs with Autoaugment, label smoothing and mixup) in the RepVGG paper. It seems now the script in the README only includes the one for Table 4 (with epoch set to 300):

python -m torch.distributed.launch --nproc_per_node 8 --master_port 12349 main.py --arch [model name] --data-path [/path/to/imagenet] --batch-size 32 --tag train_from_scratch --output-dir /path/to/save/the/log/and/checkpoints --opts TRAIN.EPOCHS 300 TRAIN.BASE_LR 0.1 TRAIN.WEIGHT_DECAY 1e-4 TRAIN.WARMUP_EPOCHS 5 MODEL.LABEL_SMOOTHING 0.1 AUG.PRESET weak AUG.MIXUP 0.0 DATA.DATASET imagenet DATA.IMG_SIZE 224