http://blog.csdn.net/wang4959520/article/details/51831637

我们在使用caffe训练过程中会生成.caffemodel和.solverstate文件，一个是模型文件，一个是中间状态文件（生成多少个取决于你自己设定的snapshot）。当训练过程中断，你想继续运行数据学习，此时只需要调用.solverstate文件即可。

使用方式代码，我使用的是.sh直接运行，配置和官方给的文件train_caffenet.sh差不多，稍微添加点内容就可以了。

上述配置根据个人文件路径实际情况相应修改即可。

The solverstate file, as its name conveys, stores the state of the solver and not any information related to classification results. The model is saved as caffemodel file, which you can use to obtain classification results for your data. If you want to fine-tune your network you may use a pre-trained caffemodel file. This will save time as your network does not need to learn from scratch. But, in case your present training needs to be halted, due to a power cut or an unexpected reboot, you may resume your training form the previous snapshot of the solverstate. The difference between using the solverstate and the caffemodel files is that the former allows you to complete your training in the pre-determined manner while the latter may require changes in certain training parameters such as the maximum number of iterations.