Use several models to train Imagenet
export CUDA_VISIBLE_DEVICES=6,7 && nohup python -u train.py \
--arch model_name \
--data_backend pytorch \
--epochs 150 \
--batch_size 256 \
--lr 0.05 \
--weight_decay 4e-5 \
--dropout 0.2 \
--drop_connect 0.2 \
--checkpoint your_path > xx.log 2>&1 &
| 模型 | accuracy (top-1) / % | running time (2 V100 GPUs) |
|---|---|---|
| EfficientNet_b0 | 74.1 | about 66 hours |
| MixNet_m | 73.15 | about 92 hours |
| MobileNet_v3 | 72.042 | about 52 hours |
| MNASNet_a1 | 72.342 | about 51 hours |
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