不需要focallosss，就用softmaxwithloss就行了，一旦出现cos _theta >1 ，表明训练失败了。
你可以把你的学习率贴出来看下。
您好作者，我的caffe里面自带的normalize.cpp，我对比了下，和模型中用到的不一样，把normalize，的实现换掉，之后再训练就是下面这种收敛状态（数据量较少5万，分类输出241，进行实验看看）
没有修改，normalize，出现最下面的输出状态

Iteration 120200, loss = 0.0135795
I1207 09:11:43.073189 39485 solver.cpp:259] Train net output #0: accuracy = 1
I1207 09:11:43.073204 39485 solver.cpp:259] Train net output #1: accuracy-t = 1
I1207 09:11:43.073215 39485 solver.cpp:259] Train net output #2: softmax_loss = 0.0135796 (* 1 = 0.0135796 loss)
I1207 09:11:43.073226 39485 sgd_solver.cpp:138] Iteration 120200, lr = 0.001
I1207 09:12:04.167598 39485 solver.cpp:358] Iteration 120250, Testing net (#0)
I1207 09:12:04.168140 39485 net.cpp:713] Ignoring source layer fc6_fc6_l2_0_split
I1207 09:12:04.168164 39485 net.cpp:713] Ignoring source layer fc6_margin_scale_fc6_margin_scale_0_split
I1207 09:12:04.168169 39485 net.cpp:713] Ignoring source layer accuracy-t
I1207 09:12:04.168174 39485 net.cpp:713] Ignoring source layer accuracy
I1207 09:12:27.587586 39485 solver.cpp:425] Test net output #0: softmax_loss = 19.0434 (* 1 = 19.0434 loss)
I1207 09:12:49.055404 39485 solver.cpp:243] Iteration 120300, loss = 0.0020926
I1207 09:12:49.055451 39485 solver.cpp:259] Train net output #0: accuracy = 1
I1207 09:12:49.055461 39485 solver.cpp:259] Train net output #1: accuracy-t = 1
I1207 09:12:49.055481 39485 solver.cpp:259] Train net output #2: softmax_loss = 0.00209277 (* 1 = 0.00209277 loss)
I1207 09:12:49.055502 39485 sgd_solver.cpp:138] Iteration 120300, lr = 0.001
I1207 09:13:32.064842 39485 solver.cpp:243] Iteration 120400, loss = 0.00121898
I1207 09:13:32.065098 39485 solver.cpp:259] Train net output #0: accuracy = 1
I1207 09:13:32.065114 39485 solver.cpp:259] Train net output #1: accuracy-t = 1
I1207 09:13:32.065126 39485 solver.cpp:259] Train net output #2: softmax_loss = 0.00121913 (* 1 = 0.00121913 loss)
I1207 09:13:32.065137 39485 sgd_solver.cpp:138] Iteration 120400, lr = 0.001
I1207 09:14:15.054962 39485 solver.cpp:243] Iteration 120500, loss = 0.284675
I1207 09:14:15.055132 39485 solver.cpp:259] Train net output #0: accuracy = 0.984375
I1207 09:14:15.055146 39485 solver.cpp:259] Train net output #1: accuracy-t = 1
I1207 09:14:15.055158 39485 solver.cpp:259] Train net output #2: softmax_loss = 0.284675 (* 1 = 0.284675 loss)
I1207 09:14:15.055166 39485 sgd_solver.cpp:138] Iteration 120500, lr = 0.001
I1207 09:14:58.101903 39485 solver.cpp:243] Iteration 120600, loss = 0.000106618
I1207 09:14:58.102113 39485 solver.cpp:259] Train net output #0: accuracy = 1
I1207 09:14:58.102126 39485 solver.cpp:259] Train net output #1: accuracy-t = 1
I1207 09:14:58.102138 39485 solver.cpp:259] Train net output #2: softmax_loss = 0.0001068 (* 1 = 0.0001068 loss)

没有修改正则化
I1207 09:22:27.955615 48074 solver.cpp:243] Iteration 0, loss = 46.6276
I1207 09:22:27.955641 48074 solver.cpp:259] Train net output #0: accuracy = 0
I1207 09:22:27.955648 48074 solver.cpp:259] Train net output #1: accuracy-t = 0
I1207 09:22:27.955668 48074 solver.cpp:259] Train net output #2: softmax_loss = 46.6276 (* 1 = 46.6276 loss)
I1207 09:22:27.955688 48074 sgd_solver.cpp:138] Iteration 0, lr = 0.01
I1207 09:23:08.346362 48074 solver.cpp:243] Iteration 100, loss = 36.1687
I1207 09:23:08.346518 48074 solver.cpp:259] Train net output #0: accuracy = 0
I1207 09:23:08.346529 48074 solver.cpp:259] Train net output #1: accuracy-t = 0
I1207 09:23:08.346537 48074 solver.cpp:259] Train net output #2: softmax_loss = 36.1687 (* 1 = 36.1687 loss)
I1207 09:23:08.346546 48074 sgd_solver.cpp:138] Iteration 100, lr = 0.01
I1207 09:23:51.725335 48074 solver.cpp:243] Iteration 200, loss = 34.4766
I1207 09:23:51.725507 48074 solver.cpp:259] Train net output #0: accuracy = 0
I1207 09:23:51.725520 48074 solver.cpp:259] Train net output #1: accuracy-t = 0.28125
I1207 09:23:51.725529 48074 solver.cpp:259] Train net output #2: softmax_loss = 34.4766 (* 1 = 34.4766 loss)
I1207 09:23:51.725538 48074 sgd_solver.cpp:138] Iteration 200, lr = 0.01
I1207 09:24:35.116875 48074 solver.cpp:243] Iteration 300, loss = 34.9371
I1207 09:24:35.117105 48074 solver.cpp:259] Train net output #0: accuracy = 0
I1207 09:24:35.117120 48074 solver.cpp:259] Train net output #1: accuracy-t = 0.328125
I1207 09:24:35.117130 48074 solver.cpp:259] Train net output #2: softmax_loss = 34.9371 (* 1 = 34.9371 loss)
I1207 09:24:35.117137 48074 sgd_solver.cpp:138] Iteration 300, lr = 0.01
I1207 09:24:58.669173 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.03431
I1207 09:24:59.103677 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.25812
I1207 09:24:59.536674 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.14654
I1207 09:24:59.536708 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.13745
I1207 09:24:59.536715 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.14452
I1207 09:24:59.536717 48074 cosin_add_m_layer.cpp:52] cos_theta > 1 ****** 1.10017

训练出的模型的效果如何？ #7

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