我在Keras训练回归问题的神经网络.为什么输出只有一个Dimension,每个Epoch的精度始终显示为acc:0.0000e + 00？

像这样:

1000/199873 [..............................] - ETA:5s - 损失:0.0057 - acc:0.0000e + 00

2000/199873 [..............................] - ETA:4s - 损失:0.0058 - acc:0.0000e + 00

3000/199873 [..............................] - ETA:3s - 损失:0.0057 - acc:0.0000e + 00

4000/199873 [..............................] - ETA:3s - 损失:0.0060 - acc:0.0000e + 00 ...

198000/199873 [============================>.] - ETA:0s - 损失:0.0055 - acc:0.0000e + 00

199000/199873 [============================>.] - ETA:0s - 损失:0.0055 - acc:0.0000e + 00

199873/199873 [==============================] - 4s - 损失:0.0055 - acc:0.0000e + 00 - val_loss :0.0180 - val_acc:0.0000e …