我正在使用faceScrub数据集训练alexnet .caffemodel，我正在关注
事实是，当我训练模型时，我得到了这个输出：
I0302 10:59:50.184250 11346 solver.cpp:331] Iteration 0, Testing net (#0)
I0302 11:09:01.198473 11346 solver.cpp:398] Test net output #0: accuracy = 0.96793
I0302 11:09:01.198635 11346 solver.cpp:398] Test net output #1: loss = 0.354751 (* 1 = 0.354751 loss)
I0302 11:09:12.543730 11346 solver.cpp:219] Iteration 0 (0 iter/s, 562.435s/20 iters), loss = 0.465583
I0302 11:09:12.543861 11346 solver.cpp:238] Train net output #0: loss = 0.465583 (* 1 = 0.465583 loss)
I0302 11:09:12.543902 11346 sgd_solver.cpp:105] Iteration 0, lr = 0.001
I0302 11:14:41.847237 11346 solver.cpp:219] Iteration 20 (0.0607343 iter/s, 329.303s/20 iters), loss = 4.65581e-09
I0302 11:14:41.847409 11346 solver.cpp:238] Train net output #0: loss = 0 (* 1 = 0 loss)
I0302 11:14:41.847447 11346 sgd_solver.cpp:105] Iteration 20, lr = 0.001
I0302 11:18:25.848346 11346 solver.cpp:219] Iteration 40 (0.0892857 iter/s, 224s/20 iters), loss = 4.65581e-09
I0302 11:18:25.848526 11346 solver.cpp:238] Train net output #0: loss = 0 (* 1 = 0 loss)
I0302 11:18:25.848565 11346 sgd_solver.cpp:105] Iteration 40, lr = 0.001
并且它会继续保持不变。
我唯一怀疑的是，在人脸检测链接train_val.prototxt中，它在fc8_flickr图层中使用了num_output：2，所以我的.txt文件包含了这种格式的所有图像：
/media/jose/B430F55030F51A56/faceScrub/download/Steve_Carell/face/a3b1b70acd0fda72c98be121a2af3ea2f4209fe7.jpg 1
/media/jose/B430F55030F51A56/faceScrub/download/Matt_Czuchry/face/98882354bbf3a508b48c6f53a84a68ca6797e617.jpg 1
/media/jose/B430F55030F51A56/faceScrub/download/Linda_Gray/face/ca9356b2382d2595ba8a9ff399dc3efa80873d72.jpg 1
/media/jose/B430F55030F51A56/faceScrub/download/Veronica_Hamel/face/900da3a6a22b25b3974e1f7602686f460126d028.jpg 1
1是包含面部的类。如果我删除了1，它会卡在迭代0，测试网（＃0）。
对此有何见解？