When the validation error of my Neural Network that I am trying to train is slowly decreasing but not by much, is it okay to stop train the network at that point, or do I need to increase the training time until the minimum validation error is reached?
For instance, in the last 5 epochs my validations errors are shown below:
| end of epoch 1 | time: 3782.50s | valid loss 6.7914 | valid ppl 890.1194 | end of epoch 2 | time: 3802.14s | valid loss 6.6084 | valid ppl 741.2616 | end of epoch 3 | time: 3791.33s | valid loss 6.5249 | valid ppl 681.8797 | end of epoch 4 | time: 3792.55s | valid loss 6.4513 | valid ppl 633.5318 | end of epoch 5 | time: 3804.15s | valid loss 6.3884 | valid ppl 594.8927
so like between the 4th epoch and the 5th epoch, the loss decreased by ~0.975% (= (6.4513-6.3884)/6.4513 * 100)? would it be okay to stop training the network at this point?