diff --git a/model_zoo/official/cv/vgg16/README.md b/model_zoo/official/cv/vgg16/README.md index f2a0dffc0a..9af14f4577 100644 --- a/model_zoo/official/cv/vgg16/README.md +++ b/model_zoo/official/cv/vgg16/README.md @@ -35,6 +35,7 @@ here basic modules mainly include basic operation like: **3×3 conv** and **2× # [Dataset](#contents) +Note that you can run the scripts based on the dataset mentioned in original paper or widely used in relevant domain/network architecture. In the following sections, we will introduce how to run the scripts using the related dataset below. #### Dataset used: [CIFAR-10]() @@ -340,8 +341,8 @@ after allreduce eval: top5_correct=45582, tot=50000, acc=91.16% | -------------------------- | ---------------------------------------------- |------------------------------------| | Model Version | VGG16 | VGG16 | | Resource | Ascend 910 ；CPU 2.60GHz，56cores；Memory，314G |NV SMX2 V100-32G | -| uploaded Date | 08/20/2020 |08/20/2020 | -| MindSpore Version | 0.5.0-alpha |0.5.0-alpha | +| uploaded Date | 10/28/2020 |08/20/2020 | +| MindSpore Version | 1.0.0 |1.0.0 | | Dataset | CIFAR-10 |ImageNet2012 | | Training Parameters | epoch=70, steps=781, batch_size = 64, lr=0.1 |epoch=150, steps=40036, batch_size = 32, lr=0.1 | | Optimizer | Momentum |Momentum | @@ -360,8 +361,8 @@ after allreduce eval: top5_correct=45582, tot=50000, acc=91.16% | ------------------- | --------------------------- |--------------------- | Model Version | VGG16 | VGG16 | | Resource | Ascend 910 | GPU | -| Uploaded Date | 08/20/2020 | 08/20/2020 | -| MindSpore Version | 0.5.0-alpha |0.5.0-alpha | +| Uploaded Date | 10/28/2020 | 10/28/2020 | +| MindSpore Version | 1.0.0 | 1.0.0 | | Dataset | CIFAR-10, 10,000 images |ImageNet2012, 5000 images | | batch_size | 64 | 32 | | outputs | probability | probability |