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modified readme

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wsq3 2021-08-12 14:44:14 +08:00
parent 396499be56
commit 77620043c9
2 changed files with 8 additions and 4 deletions
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2
model_zoo/official/cv/yolov3_darknet53/README.md
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@ -340,7 +340,7 @@ For GPU device, distributed training example(8p) by shell script
bash run_distribute_train_gpu.sh dataset/coco2014 darknet53_backbone.ckpt
```
The above shell script will run distribute training in the background. You can view the results through the file `train_parallel[X]/log.txt`. The loss value will be achieved as follows:
The above shell script will run distribute training in the background. You can view the results through the file `train_parallel0/log.txt`. The loss value will be achieved as follows:
```log
# distribute training result(8p)

10
model_zoo/official/cv/yolov3_darknet53/README_CN.md
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@ -117,7 +117,9 @@ YOLOv3使用DarkNet53执行特征提取，这是YOLOv2中的Darknet-19和残差
--data_dir=./dataset/coco2014 \
--pretrained_backbone=darknet53_backbone.ckpt \
--is_distributed=0 \
--lr=0.1 \
--lr=0.001 \
--loss_scale=1024 \
--weight_decay=0.016 \
--T_max=320 \
--max_epoch=320 \
--warmup_epochs=4 \
@ -295,7 +297,9 @@ python train.py \
--data_dir=./dataset/coco2014 \
--pretrained_backbone=darknet53_backbone.ckpt \
--is_distributed=0 \
--lr=0.1 \
--lr=0.001 \
--loss_scale=1024 \
--weight_decay=0.016 \
--T_max=320 \
--max_epoch=320 \
--warmup_epochs=4 \
@ -331,7 +335,7 @@ bash run_distribute_train.sh dataset/coco2014 darknet53_backbone.ckpt rank_table
bash run_distribute_train_gpu.sh dataset/coco2014 darknet53_backbone.ckpt
```
上述shell脚本将在后台运行分布训练。您可以通过`train_parallel[X]/log.txt`文件查看结果。损失值的实现如下：
上述shell脚本将在后台运行分布训练。您可以通过`train_parallel0/log.txt`文件查看结果。损失值的实现如下：
```text
# 分布式训练示例(8卡)