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The issue was that Moses was executed after pre_rules when use_moses = True, But when data set was pre tokenized with Moses (use_moses=False) the pre_rules were executed after.
So our wikipedia had the following processing:
- raw text
- Moses
- pre_rules
- split(' ') # fastai BaseTokenizer
- post_rules
- sentence piece
While mldoc had the following tokenziation
- raw text
- pre_rules
- Moses
- post_rules
- sentence piece
After fix I've retrained the classfiers (without finetuning) and I haven't notice huge changes in the performance. 4 languages received slight improvment 4 got a slight decrease in performance.