loss和val_loss不更新
你好,感谢你提供的代码,我在跑VGG16,VGG19,AlexNet时都出现了结果不更新的情况,在ResNet50上结果正常,请问我该如何解决呢? Epoch 1/10 12992/12992 [==============================] - 108s 8ms/step - loss: 1.7006 - acc: 0.8902 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00001: val_loss improved from inf to 1.67843, saving model to ./checkpoints/VGG19/VGG19.h5 Epoch 2/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00002: val_loss did not improve from 1.67843 Epoch 3/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00003: val_loss did not improve from 1.67843 Epoch 4/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00004: val_loss did not improve from 1.67843 Epoch 5/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00005: val_loss did not improve from 1.67843 Epoch 6/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00006: val_loss did not improve from 1.67843
Epoch 00006: ReduceLROnPlateau reducing learning rate to 0.0004999999888241291. Epoch 7/10 12992/12992 [==============================] - 98s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00007: val_loss did not improve from 1.67843 Epoch 8/10 12992/12992 [==============================] - 99s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00008: val_loss did not improve from 1.67843 Epoch 9/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00009: val_loss did not improve from 1.67843 Epoch 10/10 12992/12992 [==============================] - 100s 8ms/step - loss: 1.7046 - acc: 0.8942 - val_loss: 1.6784 - val_acc: 0.8959
Epoch 00010: val_loss did not improve from 1.67843
调参数,学习率调小点
谢谢,请问运行preict.py后出现wrong label是什么情况呢,是图片.jpg的名字也必须是类名字吗?
图片名字可以随意,但是图片所在的”文件夹“的名字必须是类别的名字
wrong label说明是预测错啦,比如文件夹下面的全部都是1类,但是预测时有些图片被预测成了2类,wrong label是正常情况的
谢谢,但我还是不懂为什么学习率大反而不更新呢,学习率大变化幅度不是应该更大吗?