I am able to view batches and connect a DataBunch to my model using a generic Learner object. The
lr_find() module works well, and I am able to train my model using the standard
However, I am now encountering a strange result while training: the training loss abruptly increases for the final 1% of training (e.g., minibatches 790-800 out of 800). The same phenomenon occurs whether I train for one epoch or for many. Below is an example of my training losses for one cycle (= 1 epoch), and the figure below that shows another example of training using the one cycle policy (= 2 epochs). Note that the batchsize was doubled in the second case, so that the total number of processed batches is unchanged from the first case.
Has anyone else experienced this? Thank you in advance for your help!