CNN Model is not learning after some epochs

username: iran_boy
cooked: <p>Hello guys,<br>
I have implemented a object detection model from a research paper (code was included in github) and added some changes to it to create a new and better model for my master’s thesis.<br>
To compare them I use the whole Test dataset in the same inviroment with the same parameters and other stuff.<br>
My model is working pretty good and it gives me 90% accuracy while the original model only gives me 63%, Since I only use a portion of the data for training both models and think that must be the reason the original model has less accuracy compared to the score recorded in the research paper (%86).<br>
This is my model’s training losses, it has 5 losses and they seem to be stuck improving after some few epochs, based on the high results and the accurate predictions on the test set (I have checked it already the prediction BBoxes are so close to the GTs), my model may have reached a good local minimal or it is strugling to reach the best global minimal since there are 5 losses and their results seems to be converged in this point and not improving very good (learning steps is too low).<br>
I have checked varaiety of optimimzer and learning rate schedulers and find out they all act in the same way but AdamW and Cosing LR Scheduler are the best among all since they got the lowest loss anoung all.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/6/c/6cf1deea54130767dd867db4827e1505ce26e24b.jpeg" data-download-href="https://discuss.pytorch.org/uploads/default/6cf1deea54130767dd867db4827e1505ce26e24b" title="photo_2025-01-16_20-57-14"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/6/c/6cf1deea54130767dd867db4827e1505ce26e24b_2_626x500.jpeg" alt="photo_2025-01-16_20-57-14" data-base62-sha1="fxLLTB9FIOB9AP5WIiBYACRH7ZN" width="626" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/6/c/6cf1deea54130767dd867db4827e1505ce26e24b_2_626x500.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/6/c/6cf1deea54130767dd867db4827e1505ce26e24b_2_939x750.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/6/c/6cf1deea54130767dd867db4827e1505ce26e24b_2_1252x1000.jpeg 2x" data-dominant-color="F3F2F2"><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">photo_2025-01-16_20-57-14</span><span class="informations">1280×1022 300 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>As you can see there is no overfit and the losses keep decreasing and the model is realy big and I have gave the model 1500 images (500 per cls) and also doubled the results to 3000 (1000 per cls) and the loss just got a bit lower but the pattern was the same and it stuck after the same number of epochs.<br>
So I have some questions:<br>
Have my model reached the best score possible?<br>
Can’t it learn more?<br>
How to make it to learn more?</p>

username: mycul
cooked: <p>Hmmm… Knowing when your model reaches its max potential is a challenging question.</p>
<p>It might be worth trying a grid search on your hyperparameters to see if that improves anything, but I would really just suggest testing on different datasets to see if you get the same result! This might give you an idea of whether you’re done (your validation consistently plateaus)</p>
<p>When you’re done with your thesis, link it in here, it sounds like it’s pretty effective!</p>

username: iran_boy
cooked: <p>I have tested this model On two top Datasets and in each one, it gave me top scores compared to the original model, so these results made me wandering maybe my model is too good, or I am doing something wrong, so that’s why I need some suggestion to make sure this model is working good.<br>
In the meanwhile, I am testing the model with different backbones and making some changes to see if the loss pattern changes or not.<br>
Ok, I will link it here after that.</p>

username: mycul
cooked: <p>If this is for your thesis, I would recommend reaching out to your advisor for advice about your results! They will be able to spot something much better considering they know the full details of your project!</p>

username: iran_boy
cooked: <p>That would be possible If my supervisor actually knew what I’ve been doing all.<br>
In my country, most of the supervisors don’t meddle with the student’s affair, so my only option is ChatGPT and International communities. <img src="https://discuss.pytorch.org/images/emoji/apple/sweat_smile.png?v=12" title=":sweat_smile:" class="emoji" alt=":sweat_smile:" loading="lazy" width="20" height="20"></p>