he paper uses image augmentations present in <a href="https://github.com/rwightman/pytorch-image-models">PyTorch Image Models (timm)</a> for training. We haven&#x27;t done this for simplicity - which causes our validation accuracy to drop.</p>

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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">18</span><span></span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">experiment</span>
<span class="linen