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    $\begingroup$ Wow, 100 entries seems way too small to get valuable information. From my experience you can push up to 5000-6000 entries and it will not take too much time to train (around 15 minutes). Then you will have meaningful information to play with. $\endgroup$ Commented Aug 24, 2016 at 9:20
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    $\begingroup$ You seem to be overfitting to your small training data-set. You should add more data, like suggested by @LoulouChameau. If you insist on keeping the small data set for training, then from your graph, you should only train for around 10 epochs, because after that the validation error starts going up, then model starts overfitting and it looses the power to generalize. $\endgroup$ Commented Aug 24, 2016 at 10:57
  • $\begingroup$ Thank you for your comments. I have updated my post with a chart when training on a bigger dataset (4000 docs). It seems to behave similarly though $\endgroup$ Commented Aug 24, 2016 at 11:47
  • $\begingroup$ Overfitting still happens at 10 epochs, though. So. Don't train it for more than 10 epochs. $\endgroup$ Commented Aug 24, 2016 at 14:16
  • $\begingroup$ @GeneralAbrial. Yeah, but in that case the loss is still too big and the network does not learn anything useful in my problem. $\endgroup$ Commented Aug 25, 2016 at 0:13