Hi, I am trying to create a basic model that predicts if a pepper is mild, medium or hot just from an image. I followed a similar process as to the bear classifier (from lesson 2), downloaded the images from Google Images, placed them in 3 folders and used the same code to create a databunch:
tfms = get_transforms(flip_vert=True, max_lighting=0.1, max_zoom=1.1, max_warp=0.5, max_rotate=90)
data = ImageDataBunch.from_folder(path, train=".", valid_pct=0.2,
ds_tfms=tfms, size=224, num_workers=4).normalize(imagenet_stats)
Even though I specified I would like to use 20% of my data as a validation set, the above code only created the train set. I have done some reading and cannot figure out why this is happening, any suggesstions?