About learning loss of both training and validation loss for the FERPlus dataset

QUANG_HUY_CHU: <p>Hi everyone, I am doing a small project on the <a href="https://www.kaggle.com/datasets/ss1033741293/ferplus" rel="noopener nofollow ugc">FERPlus</a> dataset for a side project. As I trained with the model I built from scratch (PyTorch) I noticed something with my loss graph:<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/5/2/5276cdd2c59dff99abb8945ed12f90560ba5c832.png" data-download-href="https://discuss.pytorch.org/uploads/default/5276cdd2c59dff99abb8945ed12f90560ba5c832" title="image"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/5/2/5276cdd2c59dff99abb8945ed12f90560ba5c832_2_690x284.png" alt="image" data-base62-sha1="bLvGIoc8SVgbiXK2oG4KW6eSAMi" width="690" height="284" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/5/2/5276cdd2c59dff99abb8945ed12f90560ba5c832_2_690x284.png, https://discuss.pytorch.org/uploads/default/optimized/3X/5/2/5276cdd2c59dff99abb8945ed12f90560ba5c832_2_1035x426.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/5/2/5276cdd2c59dff99abb8945ed12f90560ba5c832.png 2x" data-dominant-color="FBFBFB"><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">image</span><span class="informations">1189×490 35.4 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>It seems that the loss does not decrease much and the validation loss fluctuates strongly. I looked up from yesterday and found a little bit of information about this problem, probably I am facing underfitting, and also the validation dataset is unrepresentative. Is it correct and is there any way to avoid this happening?</p>
<p>Here is my model and hyperparameter information:</p>
<p><em>About the dataset:</em></p>
<blockquote>
<p><strong>Name</strong>: FER2013Plus (Face Emotion Recognition 2013 Plus)<br>
<strong>Classes</strong>: 10 classes (8 emotions+ 1 Unknown+ 1 NotFace), each class value is ranged from 0 to 10 points, and all classes must be summed up to 10 points.<br>
<strong>Training size</strong>: 28557<br>
<strong>Validation size</strong>: 3578<br>
<strong>Test size</strong>: 3572</p>
</blockquote>
<p><em>Input image shape:</em> 48x48 GreyScale</p>
<p><em>Dataset Loader and Transformation step:</em></p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/0/d/0d97bf6b1fae5568b1e2ba787e769429108912ed.png" data-download-href="https://discuss.pytorch.org/uploads/default/0d97bf6b1fae5568b1e2ba787e769429108912ed" title="image"><img src="https://discuss.pytorch.org/uploads/default/original/3X/0/d/0d97bf6b1fae5568b1e2ba787e769429108912ed.png" alt="image" data-base62-sha1="1Wfk9MeH5CnpEI0fxx7zjv0NK9L" width="690" height="317" data-dominant-color="151920"><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">image</span><span class="informations">881×405 42 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><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/9/6/9672ab0d764129023d146e8c90d2fe249dc78fd5.png" data-download-href="https://discuss.pytorch.org/uploads/default/9672ab0d764129023d146e8c90d2fe249dc78fd5" title="image"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/9/6/9672ab0d764129023d146e8c90d2fe249dc78fd5_2_690x71.png" alt="image" data-base62-sha1="lsVilOtU9yi2PX3yKclemq0o15r" width="690" height="71" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/9/6/9672ab0d764129023d146e8c90d2fe249dc78fd5_2_690x71.png, https://discuss.pytorch.org/uploads/default/optimized/3X/9/6/9672ab0d764129023d146e8c90d2fe249dc78fd5_2_1035x106.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/9/6/9672ab0d764129023d146e8c90d2fe249dc78fd5.png 2x" data-dominant-color="151921"><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">image</span><span class="informations">1080×112 19.7 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></p>
<p><em>CNN Model:</em><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/b/e/be9ec2d1b1a55e93f58bc2afb11ce6553e30c2b9.png" data-download-href="https://discuss.pytorch.org/uploads/default/be9ec2d1b1a55e93f58bc2afb11ce6553e30c2b9" title="image"><img src="https://discuss.pytorch.org/uploads/default/original/3X/b/e/be9ec2d1b1a55e93f58bc2afb11ce6553e30c2b9.png" alt="image" data-base62-sha1="rciRwt1RWy7SddKUj8etQkSgcnn" width="429" height="500" data-dominant-color="272C38"><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">image</span><span class="informations">554×645 15.7 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></p>
<p><em>Hyperparams:</em><br>
<img src="https://discuss.pytorch.org/uploads/default/original/3X/a/4/a462511025f088e2e0b8269ba450e69e561af528.png" alt="image" data-base62-sha1="nscWKC6PKNw9087rKap5SJq4CYE" width="572" height="122"></p>
<p><em>Training and validation:</em><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/4/2/4256c56c48fdd3446c585abf45ad560f30eebca4.png" data-download-href="https://discuss.pytorch.org/uploads/default/4256c56c48fdd3446c585abf45ad560f30eebca4" title="image"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/4/2/4256c56c48fdd3446c585abf45ad560f30eebca4_2_690x454.png" alt="image" data-base62-sha1="9sRq0nouxa66YVs0HRe85rCGDWc" width="690" height="454" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/4/2/4256c56c48fdd3446c585abf45ad560f30eebca4_2_690x454.png, https://discuss.pytorch.org/uploads/default/optimized/3X/4/2/4256c56c48fdd3446c585abf45ad560f30eebca4_2_1035x681.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/4/2/4256c56c48fdd3446c585abf45ad560f30eebca4.png 2x" data-dominant-color="13171E"><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">image</span><span class="informations">1107×729 62.6 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>Anything in the comment is appreciated and helps me understand better for CV field. If I make any mistakes in the code, just point it out</p>
<p>Thanks, a lot.</p>