callbacks.py

from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau, EarlyStopping, TensorBoard

# reduces learning rate on plateau
lr_reducer = ReduceLROnPlateau(factor=0.1,
                               cooldown= 10,
                               patience=10,verbose =1,
                               min_lr=0.1e-5)
# model autosave callbacks
mode_autosave = ModelCheckpoint("./weights/road_crop.efficientnetb0imgsize.h5", 
                                monitor='val_iou_score', 
                                mode='max', save_best_only=True, verbose=1, period=10)

# stop learining as metric on validatopn stop increasing
early_stopping = EarlyStopping(patience=10, verbose=1, mode = 'auto') 

# tensorboard for monitoring logs
tensorboard = TensorBoard(log_dir='./logs/tenboard', histogram_freq=0,
                          write_graph=True, write_images=False)

callbacks = [mode_autosave, lr_reducer, tensorboard, early_stopping]