TensorFlow高级应用:模型保存、加载与数据集处理
1. 训练过程中的回调与监控
在训练神经网络时,我们可以通过回调函数执行多种操作。例如,在训练30个周期后,我们可以查看验证集的损失和准确率:
print ('Loss evaluated on the validation dataset =',logs.get('val_loss'))
print ('Accuracy reached is', logs.get('acc'))
训练30个周期的输出示例如下:
Just finished epoch 0
Loss evaluated on the validation dataset = 0.3692033936366439
Accuracy reached is 0.9932
Just finished epoch 10
Loss evaluated on the validation dataset = 0.3073081444747746
Accuracy reached is 1.0
Just finished epoch 20
Loss evaluated on the validation dataset = 0.31566708440929653
Accuracy reached is 0.9992
我们还可以利用回调函数实现更多功能,如每隔几个周期保存模型、将准确率值保存到列表以便后续绘图等。
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