Update README.md

README.md

@@ -68,7 +68,7 @@ In-batch negative loss was applied, and we did not use any distillation methods
 
 See the table below for an overview of results, vs previous Japanese-only models and the current multilingual state-of-the-art (multilingual-e5).
 
-Worth noting: JaColBERT is evaluated out-of-domain on all three datasets, whereas JSQuAD is partially (English version) and MIRACL & Mr.TyDi are fully in-domain for e5, likely contributing to their strong performance. In a real-world setting, I'm hopeful this could be bridged with moderate, quick (<2hrs) fine-tuning. 
+Worth noting: JaColBERT is evaluated out-of-domain on all three datasets, whereas JSQuAD is partially (English version) and MIRACL & Mr.TyDi are fully in-domain for e5, likely contributing to their strong performance. In a real-world setting, I'm hopeful this could be bridged with moderate, quick (>2hrs) fine-tuning. 
 
 (refer to the technical report for exact evaluation method + code. * indicates the best monolingual/out-of-domain result. **bold** is best overall result. _italic_ indicates the task is in-domain for the model.)