Velnquix / Canada
Build an NLP experiment with limited labelled data
A small dataset makes careful evaluation more important. Start with a narrow task and a baseline that is easy to inspect.
Check the examples first
Look for duplicates, inconsistent labels and missing language varieties. Record what the dataset represents and which use cases remain outside its coverage.
Compare modest alternatives
Try a simple classifier alongside a suitable pretrained representation. Keep the validation procedure consistent and avoid choosing settings repeatedly on the final test set.
Document uncertainty
Small samples can produce unstable comparisons. Review errors with people familiar with the language and collect targeted examples before making broad claims about performance.