如何知道是否发生欠装或过度装配？

Question

如何知道是否发生欠装或过度装配？

stu*_*t17 -1 python machine-learning keras tensorflow

我正在尝试用两个类进行图像分类.我有1000张平衡类的图像.当我训练模型时,我得到的恒定验证精度低,但验证损失减少.这是过度拟合还是过度拟合的迹象？我还应该注意到,我正在尝试使用新类和不同的数据集重新训练Inception V3模型.

Epoch 1/10
2/2 [==============================]2/2 [==============================] - 126s 63s/step - loss: 0.7212 - acc: 0.5312 - val_loss: 0.7981 - val_acc: 0.3889

Epoch 2/10
2/2 [==============================]2/2 [==============================] - 70s 35s/step - loss: 0.6681 - acc: 0.5959 - val_loss: 0.7751 - val_acc: 0.3889

Epoch 3/10
2/2 [==============================]2/2 [==============================] - 71s 35s/step - loss: 0.7313 - acc: 0.4165 - val_loss: 0.7535 - val_acc: 0.3889

Epoch 4/10
2/2 [==============================]2/2 [==============================] - 67s 34s/step - loss: 0.6254 - acc: 0.6603 - val_loss: 0.7459 - val_acc: 0.3889

Epoch 5/10
2/2 [==============================]2/2 [==============================] -  68s 34s/step - loss: 0.6717 - acc: 0.5959 - val_loss: 0.7359 - val_acc: 0.3889

Epoch 6/10
2/2 [==============================]2/2 [==============================] - 107s 53s/step - loss: 0.6633 - acc: 0.5938 - val_loss: 0.7259 - val_acc: 0.3889

Epoch 7/10
2/2 [==============================]2/2 [==============================] - 67s 33s/step - loss: 0.6674 - acc: 0.6411 - val_loss: 0.7160 - val_acc: 0.3889

Epoch 8/10
2/2 [==============================]2/2 [==============================] - 105s 53s/step - loss: 0.6296 - acc: 0.6562 - val_loss: 0.7099 - val_acc: 0.3889

Epoch 9/10
2/2 [==============================]2/2 [==============================] - 67s 34s/step - loss: 0.5717 - acc: 0.8273 - val_loss: 0.7064 - val_acc: 0.4444

Epoch 10/10
2/2 [==============================]2/2 [==============================] - 103s 52s/step - loss: 0.6276 - acc: 0.6875 - val_loss: 0.7035 - val_acc: 0.4444

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