Error trying to flicker train GoogleNet. PLEASE HELP!

[Joshua N Stanton]

Hi there! I am trying to flicker train Googlenet with 400 of my own images that are 244x244 (8bit). with a batch size of 10, on sli 780ti's.
can anyone tell me why i am getting this error? any help greatly appreciated!

I0705 12:47:30.249809  3185 net.cpp:217] conv1/7x7_s2 needs backward computation.

I0705 12:47:30.249819  3185 net.cpp:219] label_data_1_split does not need backward computation.

I0705 12:47:30.249828  3185 net.cpp:219] data does not need backward computation.

I0705 12:47:30.249836  3185 net.cpp:261] This network produces output loss1/loss1

I0705 12:47:30.249845  3185 net.cpp:261] This network produces output loss1/top-1

I0705 12:47:30.249853  3185 net.cpp:261] This network produces output loss1/top-5

I0705 12:47:30.249862  3185 net.cpp:261] This network produces output loss2/loss1

I0705 12:47:30.249869  3185 net.cpp:261] This network produces output loss2/top-1

I0705 12:47:30.249879  3185 net.cpp:261] This network produces output loss2/top-5

I0705 12:47:30.249888  3185 net.cpp:261] This network produces output loss3/loss3

I0705 12:47:30.249896  3185 net.cpp:261] This network produces output loss3/top-1

I0705 12:47:30.249903  3185 net.cpp:261] This network produces output loss3/top-5

I0705 12:47:30.250021  3185 net.cpp:274] Network initialization done.

I0705 12:47:30.280239  3185 solver.cpp:60] Solver scaffolding done.

I0705 12:47:30.285609  3185 caffe.cpp:129] Finetuning from /home/josh/caffe

/caffe_path/models/MYNET/bvlc_googlenet/bvlc_googlenet.caffemodel

I0705 12:47:30.366272  3185 upgrade_proto.cpp:52] Attempting to upgrade input

 file specified using deprecated V1LayerParameter: /home/josh/caffe/caffe_path

/models/MYNET/bvlc_googlenet/bvlc_googlenet.caffemodel

I0705 12:47:30.401607  3185 upgrade_proto.cpp:60] Successfully upgraded file 

specified using deprecated V1LayerParameter

F0705 12:47:30.406445  3185 net.cpp:765] Cannot copy param 0 weights from 

layer 'loss1/fc'; shape mismatch.  Source param shape is 1 1 1024 2048 

(2097152); target param shape is 1024 3200 (3276800). To learn this layer's 

parameters from scratch rather than copying from a saved net, rename the 

layer.

*** Check failure stack trace: ***

    @     0x7f5d07ca3daa  (unknown)

    @     0x7f5d07ca3ce4  (unknown)

    @     0x7f5d07ca36e6  (unknown)

    @     0x7f5d07ca6687  (unknown)

    @     0x7f5d082f0ca7  caffe::Net<>::CopyTrainedLayersFrom()

    @     0x7f5d082f9dc2  caffe::Net<>::CopyTrainedLayersFromBinaryProto()

    @     0x7f5d082f9e26  caffe::Net<>::CopyTrainedLayersFrom()

    @           0x407794  CopyLayers()

    @           0x407f95  train()

    @           0x4059bc  main

    @     0x7f5d06fb1f45  (unknown)

    @           0x4060f1  (unknown)

    @              (nil)  (unknown)

Aborted (core dumped)