Update README.md

README.md

@@ -162,13 +162,13 @@ factors were used to simulate messy text, and to reduce single character bias on
 - Random chance to change the casing of compatible language scripts, such as Latin and Cyrllic.
 - Low chance of simulating OCR and messy text with character mutation.
 
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 To generalize well on both the target language and code switching a circulumn is provided:
 - Pure documents 55%: Single language to learn its vocabulary
 - Homogenous 25%: Single language + one foreign sentence to learn simple code switching
 - Spliced 10%: A foreign sentence is centered between two same-language sentence, with the first sentence's punctuation stripped, and second sentence's forced to be lowercased.
 - Mixed 10%: Generic mix of any languages.
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 ### Training Data Breakdown
 | lang | train sentences | train tokens | eval sentences | eval tokens | all sentences | all tokens |
 | :--- | ---: | ---: | ---: | ---: | ---: | ---: |