Increase dice score

username: thainamhoang
cooked: <p>Hi all, please be patient to me since I’m new to semantic segmentation.</p>
<p>I’m implementing U-Net based on its original paper. I’m using <a href="https://docs.monai.io/en/latest/losses.html#diceceloss" rel="noopener nofollow ugc">DiceCELoss</a> from MONAI. After 70 epochs with <code>batch_size=30</code> I got this result:<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/8/7/87577dc7ea0e0ba44e7e697eca034d8898776399.png" data-download-href="https://discuss.pytorch.org/uploads/default/87577dc7ea0e0ba44e7e697eca034d8898776399" title="Train Loss"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/8/7/87577dc7ea0e0ba44e7e697eca034d8898776399_2_580x500.png" alt="Train Loss" data-base62-sha1="jjhUhFWCo95gDxKhEUEdIiQNs0N" width="580" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/8/7/87577dc7ea0e0ba44e7e697eca034d8898776399_2_580x500.png, https://discuss.pytorch.org/uploads/default/original/3X/8/7/87577dc7ea0e0ba44e7e697eca034d8898776399.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/8/7/87577dc7ea0e0ba44e7e697eca034d8898776399.png 2x" data-dominant-color="F8F9FA"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Train Loss</span><span class="informations">782×674 38 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/c/f/cf9b5668db021e6727c9e1b7594482b9366e1ce1.png" data-download-href="https://discuss.pytorch.org/uploads/default/cf9b5668db021e6727c9e1b7594482b9366e1ce1" title="Val Dice"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/c/f/cf9b5668db021e6727c9e1b7594482b9366e1ce1_2_546x500.png" alt="Val Dice" data-base62-sha1="tCzE1nZ9584MgvhIWlR2wJzohfH" width="546" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/c/f/cf9b5668db021e6727c9e1b7594482b9366e1ce1_2_546x500.png, https://discuss.pytorch.org/uploads/default/original/3X/c/f/cf9b5668db021e6727c9e1b7594482b9366e1ce1.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/c/f/cf9b5668db021e6727c9e1b7594482b9366e1ce1.png 2x" data-dominant-color="FAFAFB"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Val Dice</span><span class="informations">746×682 26.7 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/6/d/6d8994723d7d94963a3219719ceeecc80c1b8a32.png" data-download-href="https://discuss.pytorch.org/uploads/default/6d8994723d7d94963a3219719ceeecc80c1b8a32" title="Val Loss"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/6/d/6d8994723d7d94963a3219719ceeecc80c1b8a32_2_567x500.png" alt="Val Loss" data-base62-sha1="fD0O58h0Wj3UPeBhjDb7IFhJmEy" width="567" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/6/d/6d8994723d7d94963a3219719ceeecc80c1b8a32_2_567x500.png, https://discuss.pytorch.org/uploads/default/original/3X/6/d/6d8994723d7d94963a3219719ceeecc80c1b8a32.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/6/d/6d8994723d7d94963a3219719ceeecc80c1b8a32.png 2x" data-dominant-color="FAFBFB"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Val Loss</span><span class="informations">770×678 26.6 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>From the graphs I can tell that, the train loss is kind of fluctuated around, however, the validation loss and dice score seem to be stable, and not gonna be improved soon.</p>
<p>Is there a way to solve this problem? Or is there any way that I can improve my dice score to around above 90%?</p>
<p>Thank you!</p>

username: tom
cooked: <p>Typical things to try:</p>
<ul>
<li>Change model arch (width / depth), why does your model not overfit the data?</li>
<li>Look at your results, find out something about the failure and see if there are systematic things your model gets wrong.</li>
<li>One black box thing that might help is learning rate schedules (eg decrease lr by multiplying with 1/3 after, say, 40 epochs).</li>
</ul>
<p>Best regards</p>
<p>Thomas</p>