why my softmax loss echoing@9.5 , who can help me ?

[ghost]

net: "sphereface/sphereface_model.prototxt"

#文件总数:4686817 , 训练总数:4360447 , 验证总数:326370

test_iter: 5100 #326370 / 256
test_interval: 17033

base_lr: 0.05
lr_policy: "multistep"
gamma: 0.1

#17033
stepvalue: 34066
stepvalue: 85165
stepvalue: 136264
stepvalue: 170330
max_iter: 200000
iter_size: 2

display: 500
momentum: 0.9
weight_decay: 0.0005
snapshot: 2000
snapshot_prefix: "sphereface/modal"

solver_mode: GPU

I1218 09:44:23.435408 42442 solver.cpp:289] Solving SpherefaceNet-20
I1218 09:44:23.435416 42442 solver.cpp:290] Learning Rate Policy: multistep
I1218 09:44:23.438875 42442 solver.cpp:347] Iteration 0, Testing net (#0)
I1218 09:44:23.669739 42442 blocking_queue.cpp:49] Waiting for data
I1218 09:48:31.001149 42442 blocking_queue.cpp:49] Waiting for data
I1218 09:52:34.625572 42442 blocking_queue.cpp:49] Waiting for data
I1218 09:55:54.271853 42442 blocking_queue.cpp:49] Waiting for data
I1218 10:00:13.620533 42442 blocking_queue.cpp:49] Waiting for data
I1218 10:04:16.510815 42442 blocking_queue.cpp:49] Waiting for data
I1218 10:04:38.789021 42764 data_layer.cpp:73] Restarting data prefetching from start.
I1218 10:04:38.832135 42442 solver.cpp:414] Test net output #0: lambda = 11.936
I1218 10:04:38.832242 42442 solver.cpp:414] Test net output #1: softmax_loss = 11.2369 (* 1 = 11.2369 loss)
I1218 10:04:39.691632 42442 solver.cpp:239] Iteration 0 (-nan iter/s, 1216.21s/500 iters), loss = 9.59401
I1218 10:04:39.691682 42442 solver.cpp:258] Train net output #0: lambda = 806.452
I1218 10:04:39.691699 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.58034 (* 1 = 9.58034 loss)
I1218 10:04:39.691731 42442 sgd_solver.cpp:112] Iteration 0, lr = 0.05
I1218 10:15:29.681690 42442 solver.cpp:239] Iteration 500 (0.769271 iter/s, 649.966s/500 iters), loss = 9.75478
I1218 10:15:29.681933 42442 solver.cpp:258] Train net output #0: lambda = 8.2481
I1218 10:15:29.681959 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.59993 (* 1 = 9.59993 loss)
I1218 10:15:29.681974 42442 sgd_solver.cpp:112] Iteration 500, lr = 0.05
I1218 10:21:11.482547 42442 blocking_queue.cpp:49] Waiting for data
I1218 10:29:43.602144 42442 solver.cpp:239] Iteration 1000 (0.585557 iter/s, 853.888s/500 iters), loss = 9.61311
I1218 10:29:43.602360 42442 solver.cpp:258] Train net output #0: lambda = 5
I1218 10:29:43.602385 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.30922 (* 1 = 9.30922 loss)
I1218 10:29:43.602398 42442 sgd_solver.cpp:112] Iteration 1000, lr = 0.05
I1218 10:36:50.166695 42442 blocking_queue.cpp:49] Waiting for data
I1218 10:44:11.976773 42442 solver.cpp:239] Iteration 1500 (0.57581 iter/s, 868.342s/500 iters), loss = 9.77459
I1218 10:44:11.977003 42442 solver.cpp:258] Train net output #0: lambda = 5
I1218 10:44:11.977030 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.92095 (* 1 = 9.92095 loss)
I1218 10:44:11.977046 42442 sgd_solver.cpp:112] Iteration 1500, lr = 0.05
I1218 10:55:30.798585 42442 solver.cpp:464] Snapshotting to binary proto file sphereface/modal/sphereface_solver_iter_2000.caffemodel
I1218 10:55:32.176621 42442 sgd_solver.cpp:284] Snapshotting solver state to binary proto file sphereface/modal/sphereface_solver_iter_2000.solverstate
I1218 10:55:33.252632 42442 solver.cpp:239] Iteration 2000 (0.733945 iter/s, 681.25s/500 iters), loss = 9.62272
I1218 10:55:33.252786 42442 solver.cpp:258] Train net output #0: lambda = 5
I1218 10:55:33.252812 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.62173 (* 1 = 9.62173 loss)
I1218 10:55:33.252830 42442 sgd_solver.cpp:112] Iteration 2000, lr = 0.05
I1218 11:02:54.046000 42442 solver.cpp:239] Iteration 2500 (1.13436 iter/s, 440.777s/500 iters), loss = 9.63188
I1218 11:02:54.046308 42442 solver.cpp:258] Train net output #0: lambda = 5
I1218 11:02:54.046353 42442 solver.cpp:258] Train net output #1: softmax_loss = 9.62981 (* 1 = 9.62981 loss)
I1218 11:02:54.046381 42442 sgd_solver.cpp:112] Iteration 2500, lr = 0.05