Fine-tuning pre-trained ResNet model with different learning rate
Fine-tuning Facebook Torch implementation of ResNet model with different learning rate. with learning rate 0.1 with learning rate 0.01 with learning rate 0.001
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One note for building Caffe RC3 on Ubuntu 14.04
When building Caffe RC3 on Ubuntu 14.04, you may run into this error: CXX/LD -o .build_release/tools/extract_features.bin CXX/LD -o .build_release/tools/device_query.bin CXX/LD -o .build_release/tools/net_speed_benchmark.bin CXX/LD -o .build_release/tools/test_net.bin //usr/lib/x86_64-linux-gnu/libunwind.so.8：对‘lzma_index_buffer_decode@XZ_5.0’未定义的引用 //usr/lib/x86_64-linux-gnu/libunwind.so.8：对‘lzma_index_size@XZ_5.0’未定义的引用 //usr/lib/x86_64-linux-gnu/libunwind.so.8：对‘lzma_index_uncompressed_size@XZ_5.0’未定义的引用 //usr/lib/x86_64-linux-gnu/libunwind.so.8：对‘lzma_stream_footer_decode@XZ_5.0’未定义的引用 解决方法是在~/.bashrc文件最后添加路径 export LD_LIBRARY_PATH=/lib/x86_64-linux-gnu/:$LD_LIBRARY_PATH
Some notes about building Caffe RC3 with Mac OS X 10.11.3, Anaconda, CUDA 7.5, cuDNN 4, Intel MKL and MATLAB R2015b
Environment: Mac OS X 10.11.3, Xcode 7.2, Anaconda Python 2.7.11, CUDA 7.5, cuDNN 4, Intel parallel_studio_xe_2016.1.043 mkl, homebrew boost 1.6.0, homebrew OpenCV 2.4.12, MATLAB R2015b. Note 1 : If your run into this problem afterwards "ld: warning: directory not found for option '-L/opt/intel/mkl/lib/intel64'", you can solve this problem as: cd /opt/intel/mkl/lib/ sudo ln -s . /opt/intel/mkl/lib/intel64 Suppose the environment is setup as above, first follow the official Caffe OS X Installation guide step by step. Then modify your .bash_profile file as: export PATH=/usr/local/bin:/Applications/MATLAB_R2015b.app/bin:/Developer/NVIDIA/CUDA-7.5/bin:$PATH export PATH="/Users/ylzhao/anaconda/bin:$PATH" export DYLD_LIBRARY_PATH=/Developer/NVIDIA/CUDA-7.5/lib:$DYLD_LIBRARY_PATH export DYLD_FALLBACK_LIBRARY_PATH=/usr/local/cuda/lib::$HOME/anaconda/lib:/usr/local/lib:/usr/lib:$DYLD_FALLBACK_LIBRARY_PATH export PYTHONPATH=/usr/local/lib/python