对GoogLeNet 输出日志中的loss的理解
在GoogLeNet 网络进行训练时,日志文件中输出如下内容,该内容是在训练过程中的测试部分输出的(即test过程)
I0423 16:33:20.838305 19680 solver.cpp:404] Test net output #0: loss1/loss1 = 0.870371 (* 0.3 = 0.261111 loss)
I0423 16:33:20.838305 19680 solver.cpp:404] Test net output #1: loss1/top-1 = 0.696777
I0423 16:33:20.838305 19680 solver.cpp:404] Test net output #2: loss1/top-5 = 1
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #3: loss2/loss1 = 0.815625 (* 0.3 = 0.244688 loss)
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #4: loss2/top-1 = 0.677441
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #5: loss2/top-5 = 1
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #6: loss3/loss3 = 1.04691 (* 1 = 1.04691 loss)
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #7: loss3/top-1 = 0.589551
I0423 16:33:20.853930 19680 solver.cpp:404] Test net output #8: loss3/top-5 = 1
看到这么多loss,

本文详细解释了GoogLeNet训练过程中测试部分的日志输出,包括loss1/loss1、loss1/top-1、loss1/top-5等含义。作者指出,loss3/loss3是真正意义上的loss值,loss3/top-1表示最终层的精度。网络结构中中间的softmax损失层用于避免梯度消失,而top-1和top-5分别表示排名第一和前五的分类准确率。
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