Hello, as you can see, I’m having a problem using a custom dataset.
I followed the instructions for creating a custom dataset in youtube. Then i created a project, selected the new dataset, and when i switch between tabs in the project, this error pops up.
I have checked the file in the file browser and i see no problem.
Is it possible for you to upload your project (export/import model) and dataset in the cloud version? That would help use investigate this issue better.
It seems that your train.csv has filepaths which do not exist in the filesystem. For example, following file mentioned in train.csv is not found in the dataset.
You may want to use a CNN based network. Either design it yourself or use AutoML/Pretrained models. Your image size is big so you may have to resize it to fit on GPU.
Enable augmentation since you have small dataset. Also turn on shuffle since it seems your validation dataset has mostly different classes than training.
Ok, enabling augmentation and taking a pretrained preprocess, I can get a wider range of results. This is completely coherent, because my current dataset is in fact, too small.
So the question is, is training accuracy value useless when my dataset is small?
For small dataset, a network can learn to remember all the input (if network is big enough) so you will get very good training accuracy but bad accuracy on data which network has not seen. Which is what is happening in your case.
In general, you should look at validation accuracy as a measure of if network has learned the features or not.