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View Code? Open in Web Editor NEWcifar10数据集上进行图片分类,基于tensorflow框架,旨在探究不同的改进策略对分类准确率的影响,如何一步步得提高准确率
cifar10数据集上进行图片分类,基于tensorflow框架,旨在探究不同的改进策略对分类准确率的影响,如何一步步得提高准确率
很不错的repo,展示了不同模型优化技术的作用。
最近也是在跑CIFAR10的任务,不过用的是pytorch。
然后我的疑问是resnet系列的准确率是不是偏低一点?理论上resnet系列的准确率应该比VGG16好好一点的。
我这边跑的VGG16 的准确率可以到达93.49%,超过了你展示的resnet结果。我在想是不是resnet全部潜能没有发挥出来?
我的实验设置如下:
结构是官方VGG16,有加BN,Batch大小500,fc加dropout
SGD,余弦学习率,lr初始值0.1,半衰周期1200,最小学习率0.001。
权重衰减5e-4
输入图像padding再随机裁剪4像素,没有做白化。加水平镜像翻转
RT
文件和目录有点confusing,没找到。。
显示缺少self.accuray,self.images,self.labels,self.keep_prob等参数
Basic cnn spend one day on training on CPU, but it still doesn't finish.
VGG spend one night on training on GPU, but it still doesn't finish.
Is that normal?
您好,我在运行您的代码时有些文件,路径找不到,请您帮忙解答一下疑惑,非常感谢!
src/config/networks/resnet.yaml
backups/cifar10-v2/
'backups/cifar10-v5/'
貌似总体损失没有加上权重衰减的损失,难道是tf.layers.Conv2D在训练时权重时自动衰减?但在建立计算网络,好像并没有将衰减系数传入进去!
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