Here is the result of the training:
74.00% [37/50 07:26<02:36]
epoch train_loss valid_loss exp_rmspe time
0 0.011315 0.003927 0.062056 00:12
1 0.017746 0.000746 0.026780 00:12
2 0.014916 0.001486 0.039329 00:12
3 0.015425 0.013706 0.109037 00:12
4 0.024731 0.006519 0.077436 00:11
5 0.026221 0.003306 0.059323 00:12
some epochs gave very low valid_loss but relatively high train_loss. Shall I pick or abandon them? I’m using following to train:
learn.fit_one_cycle(50, max_lr =1e-01,callbacks=[SaveModelCallback(learn,
monitor='valid_loss',
mode='min',
name='/content/gdrive/My Drive/goodmdl')])
Can we change the monitor to save an improvement on the combination of both valid_loss and train_loss?