offbit / char-models

Character level models for sentiment analysis

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performances of rnn2.py

elasryidriss opened this issue · comments

Hi,
I realy like your post on creating level caracter models on your blog. I tried to run doc-rnn2.py without the chekpoint callback, but the accuarcy on the validation in the 10th epoch still 49.74%.
have you any suggesions to achieve the same performances as mentionned on your blog.
Thanx

Hi elasryidriss,
The reported accuracy seemed to be from doc-cnn4.py model. I'm still curious why the the rnn2.py doesn't improve and keeps around 49%.

Hi all,
I don't maintain the repository any more. It was just an instructional post.

The drop is a result of the version switch - keras from 1.0 -> 2.0 and tf 0.x -> 1.x .
Probably some of the the graph building is being done differently, and the internal implementation of layers changed.

I experience that there is a sensitivity to weight initialization. I can run the model (rnn2) after the version switch but only occasionally does it actually learn something and then, the result is as indicated in the tutorial (+80% acc.). Other times, it just hovers around 50% epoch in and epoch out...