小编JIT*_*IRK的帖子

我正在使用 Tensorflow-gpu 后端在 Keras 中训练模型。任务是检测卫星图像中的建筑物。损失正在下降（这是好事），但方向是负的，并且准确性正在下降。但好的方面是，模型的预测正在改进。我担心的是为什么损失是负数。此外，为什么模型在改进而准确性却在下降？

from tensorflow.keras.layers import Conv2D
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Activation
from tensorflow.keras.layers import MaxPool2D as MaxPooling2D
from tensorflow.keras.layers import UpSampling2D
from tensorflow.keras.layers import concatenate
from tensorflow.keras.layers import Input
from tensorflow.keras import Model
from tensorflow.keras.optimizers import RMSprop


# LAYERS
inputs = Input(shape=(300, 300, 3))
# 300

down0 = Conv2D(32, (3, 3), padding='same')(inputs)
down0 = BatchNormalization()(down0)
down0 = Activation('relu')(down0)
down0 = Conv2D(32, (3, 3), padding='same')(down0)
down0 = BatchNormalization()(down0)
down0 = Activation('relu')(down0)
down0_pool = MaxPooling2D((2, 2), …