Hey there, I’ve a strange issue (or simply I’m not able to create a proper ImageDataBunch
, we’ll see). The problem is that, training on the Kaggle dog breed identification dataset, counters say that I’m training on the validation set.
This is my split (it looks ok to me):
But when I train:
the model is training on the valid_ds
, isn’t it?
And when it validates… it validates on a sub-split of the valid_ds
, isn’t it?
My databunch is done this way:
data = (ImageList.from_folder(imgpath).split_by_rand_pct().label_from_folder().add_test_folder(imgpath+'/../test').transform(get_transforms(), size=img_size).databunch(bs=bs)).normalize(imagenet_stats)
So, I don’t know… the creation of the databunch looks ok, especially because the splits (as you can see above) are ok. So, what am I doing wrong?
Thanks! (Fast.ai is awesome!)
P.s. I forgot to mention that i re-arranged the original dataset in a hierarchy of folders named with classes labels, with each folder containing numbered images for each class.
Like this but with more images.