The top1 accuracy and the top5 acuuracy are 54.762% and 78.1914%, respectively for our oneflow model after 90 epochs of training.
For reference, the top1 accuracy and the top5 accuracy are 54.6% and 78.33%, respectively for the model from the tensorflow benchmarks after 90 epochs of training.
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For reference, the top1 accuracy and the top5 accuracy are 54.6% and 78.33%, respectively for the model from the tensorflow benchmarks after 90 epochs of training.
#### 训练 VGG-16
```
export ENABLE_USER_OP=True
rm -rf core.*
rm -rf ./output/snapshots/*
DATA_ROOT=/dataset/ImageNet/ofrecord
#Please change this to your data root.
python3 cnn_benchmark/of_cnn_train_val.py \
--train_data_dir=$DATA_ROOT/train \
--val_data_dir=$DATA_ROOT/validation \
--train_data_part_num=256 \
--val_data_part_num=256 \
--num_nodes=1 \
--gpu_num_per_node=4 \
--model_update="momentum" \
--mom=0.9 \
--learning_rate=0.01 \
--loss_print_every_n_iter=10 \
--batch_size_per_device=128 \
--val_batch_size_per_device=128 \
--num_epoch=90 \
--use_fp16=false \
--use_boxing_v2=false \
--model="vgg" \
```
The top1 accuracy and the top5 acuuracy are 69.3359% and 89.1370%, respectively for our oneflow model after 90 epochs of training.
For reference, the top1 accuracy and the top5 accuracy are 71.5% and 89.9%, respectively for the model from the tensorflow benchmarks after 90 epochs of training.
