322 lines
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322 lines
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<meta property="og:description" content="This week I finished programming the basic CNN model using transfer learning. I decided to train it for 20 epochs to make sure there weren’t any runtime errors in my code. As I don’t own an Nvidia GPU (I have an AMD GPU), I couldn’t make use of the pytorch version that utilised CUDA to speed up processing. There is a RocM version of pytorch for AMD GPUs1 but RocM isn’t as mature as CUDA and only officially supports a small subset of Linux distributions." />
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<title>Week 6 | MMP | Oscar Pocock</title>
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<strong>Week 6</strong>
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<li><a href="#transfer-learning-model-architecture">Transfer learning model architecture</a>
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<li><a href="#simplified">Simplified</a></li>
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</li>
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<li><a href="#validation-and-train-loss-over-20-epochs">Validation and train loss over 20 epochs</a></li>
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<h1>
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<a href="/posts/week-6/">Week 6</a>
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</h1>
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<h5>March 13, 2022</h5>
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<p>This week I finished programming the basic CNN model using transfer learning. I decided to train it for 20 epochs to make sure there weren’t any runtime errors in my code. As I don’t own an Nvidia GPU (I have an AMD GPU), I couldn’t make use of the pytorch version that utilised CUDA to speed up processing. There is a RocM version of pytorch for AMD GPUs<sup id="fnref:1"><a href="#fn:1" class="footnote-ref" role="doc-noteref">1</a></sup> but RocM isn’t as mature as CUDA and only officially supports a small subset of Linux distributions. Therefore, for this model I trained on the COU for only 20 epochs just to make sure it ran successfully before trying to find some Nvidia compute.</p>
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<h2 id="transfer-learning-model-architecture">
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Transfer learning model architecture
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<a class="anchor" href="#transfer-learning-model-architecture">#</a>
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</h2>
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<h3 id="full">
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Full
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<a class="anchor" href="#full">#</a>
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</h3>
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<p>
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<img src="/transfer-cnn-arch.svg" alt="Transfer learning architecture" /></p>
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<h3 id="simplified">
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Simplified
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<a class="anchor" href="#simplified">#</a>
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</h3>
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<p>
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<img src="/transfer-cnn-arch-simpl.svg" alt="Simplified Transfer learning architecture" /></p>
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<h2 id="validation-and-train-loss-over-20-epochs">
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Validation and train loss over 20 epochs
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<a class="anchor" href="#validation-and-train-loss-over-20-epochs">#</a>
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</h2>
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<p>
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<img src="/20-epoch-plot.png" alt="plot of training and validation loss over 20 epochs" /></p>
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<section class="footnotes" role="doc-endnotes">
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<hr>
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<ol>
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<li id="fn:1" role="doc-endnote">
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<p>
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<a href="https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/">https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package/</a> <a href="#fnref:1" class="footnote-backref" role="doc-backlink">↩︎</a></p>
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</section>
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</article>
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<li><a href="#transfer-learning-model-architecture">Transfer learning model architecture</a>
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<ul>
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<li><a href="#full">Full</a></li>
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<li><a href="#simplified">Simplified</a></li>
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</ul>
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</li>
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<li><a href="#validation-and-train-loss-over-20-epochs">Validation and train loss over 20 epochs</a></li>
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