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José Arenas
Mar 2, 2017, 6:21:57 AM3/2/17
to Caffe Users
I'm training an alexnet .caffemodel with faceScrub dataset, I'm following
Face Detection
Fine-Tuning
Thing is that when I'm training the model I get this output:
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
and it continues the same.
The only thing I am suspicious on is that in the Face Detection link train_val.prototxt it uses num_output: 2 in the fc8_flickr layer, so I have the .txt file with all the images in this format:
/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
With 1 being the class containing a face. If I remove the 1, it gets stuck in Iteration 0, Testing net (#0).
Any insight on this?
Face Detection
Fine-Tuning
Thing is that when I'm training the model I get this output:
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
and it continues the same.
The only thing I am suspicious on is that in the Face Detection link train_val.prototxt it uses num_output: 2 in the fc8_flickr layer, so I have the .txt file with all the images in this format:
/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
With 1 being the class containing a face. If I remove the 1, it gets stuck in Iteration 0, Testing net (#0).
Any insight on this?
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