如何绘制Caffe网络训练曲线

如题所述

当我们设计好网络结构后,在神经网络训练的过程中,迭代输出的log信息中,一般包括,迭代次数,训练损失代价,测试损失代价,测试精度等。本文提供一段示例,简单讲述如何绘制训练曲线(training curve)。
首先看一段训练的log输出,网络结构参数的那段忽略,直接跳到训练迭代阶段:
I0627 21:30:06.004370 15558 solver.cpp:242] Iteration 0, loss = 21.6953
I0627 21:30:06.004420 15558 solver.cpp:258] Train net output #0: loss = 21.6953 (* 1 = 21.6953 loss)
I0627 21:30:06.004426 15558 solver.cpp:571] Iteration 0, lr = 0.01
I0627 21:30:28.592690 15558 solver.cpp:242] Iteration 100, loss = 13.6593
I0627 21:30:28.592730 15558 solver.cpp:258] Train net output #0: loss = 13.6593 (* 1 = 13.6593 loss)
I0627 21:30:28.592733 15558 solver.cpp:571] Iteration 100, lr = 0.01
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