Comments (2)
Yes it works for any document size. You must have not have prepared your dataset in the right format or you might have chosen a large learning rate. Also if you choose ReLU as the activation for the inference network for q_theta, make sure you normalize the bag of words input by setting the option bow_norm to 1.
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We just added the scripts to pre-process a dataset to the repo. Please check that out and let us know if you still have questions.
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Related Issues (20)
- perform bad on classifiction task HOT 3
- FileNotFoundError: [Errno 2] No such file or directory: 'data/20ng_embeddings.txt'
- How to get the topic vector? HOT 3
- rising KL_theta values
- 代码运行 HOT 1
- Is that true that a lot of repeated topics appear? HOT 7
- Topic Coherence Computation: Division by 45? HOT 2
- How to modify the code to number of topics other than 50? HOT 1
- Validation set loss is being calculated on the Test set.
- Negative coherence on short texts HOT 1
- Run ETM on my own dataset HOT 3
- How to obtain document-topic proportions (the thetas) for each document HOT 3
- a bug in test dataset splitting HOT 1
- evaluate
- Add predictive measure to utils.py
- dataset
- embedding HOT 3
- Confuse about the data loader function HOT 6
- read embedding matrix when not using trained embeddings HOT 1
- args.clip
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