python - 超高精度高损耗？

Question

我正在用多标签分类的一堆图像训练一维 CNN。我的准确率几乎是 100%，但同时损失了 ~5。发生了什么事？，任何帮助表示赞赏。

model = Sequential()
model.add(Conv1D(filters=128, kernel_size=3, activation='relu', input_shape=(137,236)))
model.add(Dropout(0.2))
model.add(Conv1D(filters=64, kernel_size=3, activation='relu'))
model.add(Dropout(0.2))
model.add(Conv1D(filters=64, kernel_size=3, activation='relu'))
model.add(Dropout(0.2))
model.add(Conv1D(filters=64, kernel_size=3, activation='relu'))
model.add(Dropout(0.2))
model.add(GlobalMaxPooling1D())
model.add(Dense(128, activation='relu'))
model.add(Dropout(0.1))
model.add(Dense(64, activation='relu'))
model.add(Dropout(0.1))
model.add(Dense(3, activation='softmax'))

model.compile(optimizer='adam', loss='mean_squared_logarithmic_error', metrics=['accuracy'])

训练：

标签： pythontensorflowkerasneural-network