films-synopsis-generator's Issues
Find out how to include pretrained word embeddings in the training
So far the network is not using any word embeddings like word2vec or GloVe. It could be interesting to compare results of that baseline against a net that makes use of them. I haven't figured out how to make them, basically because I used a lot of the code from this repo and he doesn't use it, although in the README.md
says that Pre-trained word embeddings can also be used..
This is the best spanish pretrained word embedding model that I have found, so I think we should use them.
Implement Beam Search
This should be useful https://gist.github.com/udibr/67be473cf053d8c38730
Use only most frequents words to build vocabulary
Use only top N frequent words to build vocabulary. We shouldn't take into account words that appear only a couple of times.
Train the first network (baseline)
Train a network and use it as baseline for further improvements. This code should be useful
Report statistics about the dataset
It would be nice to generate some statistics about the dataset. E.g.
- distribution of genres
- synopsys lengths (considering that we define our constant MAX_SYNOPSIS_LEN)
- (maybe using a python notebook)
Feel free to post some ideas
Make predicitons (generate synopsis)
Now that we have some trained weights, we should code the functions necessary to load them into the model and make actual predictions. Goal is to be able to check whether the generated synopsis start to make sense or not.
This code should be useful for doing so
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