Getting low accuracy on keras pretrained word embeddings example Original blog post claims that it is possible to get 95% accuracy on the validation set (20 Newsgroup dataset) after only 2 epochs using pretrained word embeddings (glove.6B.100d). All code is located here. I did not changed anything in this example but getting only 40% accuracy on the validation set after 2 epochs and 75% after 10 epochs. I can't get to 95% accuracy even after 20 epochs. Switching from tensorflow to theano backend do not make any significant change. I'm using Keras 2.0.2, tensorflow-gpu 1.0.1, theano 0.9.0, python 2.7.12. What I'm doing wrong?
The code has been changed to remove headers.  See comment on github:

"Newsgroups message contains header like 'Newsgroups: alt.atheism', which inflates the accuracy to 0.95 (2 epochs).
After removing the header, the val accuracy is 0.47 (2 epochs) and 0.71 (10 epochs)."

https://github.com/fchollet/keras/pull/5585

This confused me for days!