Overfitting and pretrained models

fmsilver: <p>Looking for some knowledge from a more experienced person.</p>
<p>I have trained two models on the “torch.hub.load” alexnet, one with <em>pretrained=True</em> and one with <em>pretrained=False</em>.</p>
<p>I have then applied the Grad-Cam method on the results. My interpretation is that the <em>pretrained=True</em> is not overfitted, it identifies the object and provide nice shapes. While the <em>pretrained=False</em> identifies the object, but Iooking at the gradients indicate overfitting, since it is just a splash of tiny pixels within the area of the object. No real shapes can be seen here.</p>
<p>Am I correct, or is there a better opinion here? (Thank you for your time.)</p>
<p><strong>Pretrained = True:</strong><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/1/6/16bd0054c86b94cce18e4fcb478f531c80b88d89.png" data-download-href="https://discuss.pytorch.org/uploads/default/16bd0054c86b94cce18e4fcb478f531c80b88d89" title="pre_trained"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/1/6/16bd0054c86b94cce18e4fcb478f531c80b88d89_2_468x500.png" alt="pre_trained" data-base62-sha1="3f9r8J39anxDmmjLNsMJP2Fz1Fv" width="468" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/1/6/16bd0054c86b94cce18e4fcb478f531c80b88d89_2_468x500.png, https://discuss.pytorch.org/uploads/default/original/3X/1/6/16bd0054c86b94cce18e4fcb478f531c80b88d89.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/1/6/16bd0054c86b94cce18e4fcb478f531c80b88d89.png 2x" data-dominant-color="85828A"><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">pre_trained</span><span class="informations">532×568 248 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>
<strong>Pretrained = False:</strong><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/7/1/712e210f953d87a795d0ccc6d592ae501e17f16c.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/712e210f953d87a795d0ccc6d592ae501e17f16c" title="pre_trained_false"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/7/1/712e210f953d87a795d0ccc6d592ae501e17f16c_2_468x500.jpeg" alt="pre_trained_false" data-base62-sha1="g9eMH3RqVAqChQGHQ131k3AYva4" width="468" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/7/1/712e210f953d87a795d0ccc6d592ae501e17f16c_2_468x500.jpeg, https://discuss.pytorch.org/uploads/default/original/3X/7/1/712e210f953d87a795d0ccc6d592ae501e17f16c.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/7/1/712e210f953d87a795d0ccc6d592ae501e17f16c.jpeg 2x" data-dominant-color="858189"><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">pre_trained_false</span><span class="informations">532×568 124 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>