After the explanation of the choosing a learning rate part, I changed my path to my own dataset, and re-ran the cells using that data. I expected to see something similar to the dogs vs cats dataset, but I didn’t:
lr_find()was super quick, went to 100%, and only got to an accuracy of 0.6
learn.sched.plot_lr()is a linear line from 0 at 1 iteration, to 0.01 at 2 iterations
learn.sched.plot()has no line showing (axis are 10^0 to 10^1 learning rate, -0.04 to 0.04 loss)
I have a couple of thoughts why this might be:
- My data sets are very small (~50 training samples each, ~15 validation samples each)
- The accuracy I achieved previously on them is only ~72%
But I was wondering if somebody could help me understand a little more what’s going on and why this not-so-great dataset doesn’t work with the learning rate fitting code.