tensorflow2.0——history保存loss和acc
作者:互联网
history包含以下几个属性:
训练集loss: loss
测试集loss: val_loss
训练集准确率: sparse_categorical_accuracy
测试集准确率: val_sparse_categorical_accuracy
my_model.compile(optimizer=opt,loss=tf.keras.losses.MSE) history=my_model.fit(train_high0_img,train_rain,validation_data=(test_high0_img,test_rain),epochs=epochs, validation_freq=1,batch_size=bat) # history包含以下几个属性: # 训练集loss: loss # 测试集loss: val_loss # 训练集准确率: sparse_categorical_accuracy # 测试集准确率: val_sparse_categorical_accuracy # acc = history.history['sparse_categorical_accuracy'] # val_acc = history.history['val_sparse_categorical_accuracy'] loss = history.history['loss'] val_loss = history.history['val_loss'] # print('acc:',acc) # print('val_acc:',val_acc) print('loss:',loss) print('val_loss:',val_loss)
标签:acc,loss,val,categorical,tensorflow2.0,accuracy,history 来源: https://www.cnblogs.com/cxhzy/p/15010266.html