b5e906b0b31d0de66caa51e4ae3bbad93303d1f5,cifar100.py,,,#,4

Before Change

// print("Model loaded.")

model.fit_generator(generator.flow(trainX, Y_train, batch_size=batch_size), samples_per_epoch=len(trainX), nb_epoch=nb_epoch,
                   callbacks=[ModelCheckpoint("weights/DenseNet-BC-100-12-CIFAR100.h5", monitor="val_acc", save_best_only=True,
                                              save_weights_only=True)],
                   validation_data=(testX, Y_test),
                   nb_val_samples=testX.shape[0], verbose=2)

After Change

lr_reducer      = ReduceLROnPlateau(monitor="val_loss", factor=np.sqrt(0.1),
                                    cooldown=0, patience=10, min_lr=0.5e-6)
early_stopper   = EarlyStopping(monitor="val_acc", min_delta=0.0001, patience=20)
model_checkpoint= ModelCheckpoint("weights/DenseNet-BC-100-12-CIFAR100.h5", monitor="val_acc", save_best_only=True,
                                  save_weights_only=True)

callbacks=[lr_reducer, early_stopper, model_checkpoint]


model.fit_generator(generator.flow(trainX, Y_train, batch_size=batch_size), samples_per_epoch=len(trainX), nb_epoch=nb_epoch,
                   callbacks=callbacks,

Instances