@inflationaaron 谢谢
@YRodT 3Q

@winglight2016 我是看的一篇论文上这么做的，他就达到了 60 多的准确率，不知道怎么搞得。
@Hzzone 这个数据本来就是乱的呀 你是说 batch 随机取吗？
@enenaaa 我等下试试 谢谢啦。
@ioiogoo 感谢感谢，我研究下，不会了再问您。
@takato 谢谢 我等下试试 我觉得改成 INCEPTION 模型应该也不错。
@glasslion 谢谢，我等下画个 confusion matrix 分析一下。
@Suddoo 我用的是 TF 框架，这个 FER2013 本来不就是乱着的吗？ shuffle 会有用吗？还有您说数据标准化，我已经标准化了，然后把最后 softmax 去掉了，不知道这样可以不可以，之前没标准化，最后加 SOFTMAX 准确率更低了

Epoch: 72, Test Loss= 0.018, Test Accuracy= 0.256
Epoch: 73, Batch: 0, Loss= 1.779, Training Accuracy= 0.240
Epoch: 73, Batch: 50, Loss= 1.774, Training Accuracy= 0.320
Epoch: 73, Batch: 100, Loss= 1.803, Training Accuracy= 0.220
Epoch: 73, Batch: 150, Loss= 1.802, Training Accuracy= 0.260
Epoch: 73, Batch: 200, Loss= 1.882, Training Accuracy= 0.180
Epoch: 73, Batch: 250, Loss= 1.808, Training Accuracy= 0.220
Epoch: 73, Batch: 300, Loss= 1.932, Training Accuracy= 0.160
Epoch: 73, Batch: 350, Loss= 1.811, Training Accuracy= 0.300
Epoch: 73, Batch: 400, Loss= 1.801, Training Accuracy= 0.300
Epoch: 73, Batch: 450, Loss= 1.775, Training Accuracy= 0.280
Epoch: 73, Batch: 500, Loss= 1.754, Training Accuracy= 0.280
Epoch: 73, Batch: 550, Loss= 1.737, Training Accuracy= 0.280
Epoch: 73, Test Loss= 0.018, Test Accuracy= 0.256
Epoch: 74, Batch: 0, Loss= 1.779, Training Accuracy= 0.240
Epoch: 74, Batch: 50, Loss= 1.774, Training Accuracy= 0.320
Epoch: 74, Batch: 100, Loss= 1.803, Training Accuracy= 0.220
Epoch: 74, Batch: 150, Loss= 1.802, Training Accuracy= 0.260
Epoch: 74, Batch: 200, Loss= 1.882, Training Accuracy= 0.180
Epoch: 74, Batch: 250, Loss= 1.808, Training Accuracy= 0.220
Epoch: 74, Batch: 300, Loss= 1.932, Training Accuracy= 0.160
Epoch: 74, Batch: 350, Loss= 1.811, Training Accuracy= 0.300
Epoch: 74, Batch: 400, Loss= 1.801, Training Accuracy= 0.300
Epoch: 74, Batch: 450, Loss= 1.775, Training Accuracy= 0.280
Epoch: 74, Batch: 500, Loss= 1.754, Training Accuracy= 0.280
Epoch: 74, Batch: 550, Loss= 1.737, Training Accuracy= 0.280
Epoch: 74, Test Loss= 0.018, Test Accuracy= 0.256