我需要一些幫助來了解在 Keras 中擬合模型時(shí)如何計(jì)算準(zhǔn)確度。這是訓(xùn)練模型的樣本歷史：Train on 340 samples, validate on 60 samplesEpoch 1/100340/340 [==============================] - 5s 13ms/step - loss: 0.8081 - acc: 0.7559 - val_loss: 0.1393 - val_acc: 1.0000Epoch 2/100340/340 [==============================] - 3s 9ms/step - loss: 0.7815 - acc: 0.7647 - val_loss: 0.1367 - val_acc: 1.0000Epoch 3/100340/340 [==============================] - 3s 10ms/step - loss: 0.8042 - acc: 0.7706 - val_loss: 0.1370 - val_acc: 1.0000...Epoch 25/100340/340 [==============================] - 3s 9ms/step - loss: 0.6006 - acc: 0.8029 - val_loss: 0.2418 - val_acc: 0.9333Epoch 26/100340/340 [==============================] - 3s 9ms/step - loss: 0.5799 - acc: 0.8235 - val_loss: 0.3004 - val_acc: 0.8833那么，第一個(gè)時(shí)期的驗(yàn)證準(zhǔn)確度是 1 嗎？驗(yàn)證準(zhǔn)確率如何優(yōu)于訓(xùn)練準(zhǔn)確率？這些數(shù)字顯示了準(zhǔn)確性和損失的所有值：