Comments (3)
For now, I made the parallelisation of the data preprocessing optional.
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Improved script. As part of the preprocessing, all articles (for a given date range) are written to a .txt file (each line has the article_id, article_text) by year. The script will then iterate over these files and return the article content.
from wordembeddingplayground.
Scripts seem to speed up training and is more memory efficient. Therefore closing the issue.
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Related Issues (15)
- Gender masking HOT 1
- Implement Lexicon Expansion
- Implement metadata-based filtering of articles HOT 1
- Test code for training models
- Write blog post introducing the project
- Write blog post explaining the results
- Make parametrizable training script
- Write Paper for DSH HOT 1
- Include model noise in computation minibatch bias
- Outline validation strategy HOT 2
- Include article Ids when exporting minibatch bias scores
- Include lexicon expansion HOT 1
- Package scripts
- Enrich metadata for selected newspapers HOT 2
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