<p>Fine-tuning is a very useful trick to achieve a promising accuracy compared to past manual feature. <a href="https://stackoverflow.com/a/36842553/1714410">@Shai</a> already posted a good tutorial for fine-tuning the Googlenet using Caffe, so I just want to give some recommends and tricks for fine-tuning for general cases.</p>

<p>In most of time, we face a task classification problem that new dataset (e.g. <a href="http://www.robots.ox.ac.uk/~vgg/data/flowers/102/" rel="nofollow noreferrer">Oxford 102 flower dataset</a> or <a href="http://www.robots.ox.ac.uk/~vgg/publications/2012/parkhi12a/" rel="nofollow noreferrer">Cat&amp;Dog</a>) has following four common situations <a href="http://cs231n.github.io/transfer-learning/" rel="nofollow noreferrer">CS231n</a>:</p>

<ol>
<li>New dataset is small and similar to original dataset.</li>
<li>New dataset is small but is different to original dataset (Most common cases)</li>
<li>New dataset is large and similar to original dataset.</li>
<li>New dataset is large but is different to original dataset.</li>
</ol>

<p>In practice, most of time we do not have enough data to train the network from scratch, but may be enough for pre-trained model. Whatever which cases I mentions above only thing we must care about is that do we have enough data to train the CNN?</p>

<p>If yes, we can train the CNN from scratch. However, in practice it is still beneficial to initialize the weight from pre-trained model.</p>

<p>If no, we need to check whether data is very different from original datasets? If it is very similar, we can just fine-tune the fully connected neural network or <a href="http://arxiv.org/pdf/1403.6382v3.pdf" rel="nofollow noreferrer">fine-tune with SVM</a>. However, If it is very different from original dataset, we may need to <a href="http://arxiv.org/pdf/1411.1792v1.pdf" rel="nofollow noreferrer">fine-tune the convolutional neural network to improve the generalization</a>.</p>
Fine Tuning of GoogLeNet Model
<p>I trained GoogLeNet model from scratch. But it didn't give me the promising results.<br>
As an alternative, I would like to do fine tuning of GoogLeNet model on my dataset. Does anyone know what are the steps should I follow? </p>