Update README.md

README.md

@@ -121,7 +121,7 @@ We finetuned the base model (flan-t5-large) on multiple relevant tasks with stan
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-| Total                              | Challenge-proportional Mixture   | n/a                                        | 263,400         |
+| Total                              | Challenge-proportional Mixing    | n/a                                        | 263,400         |
 
 
 - Multi-instruction tuning: In the stage, we first created a task mixture using "challenge-proportional mixing" method. In a seperate pilot studie, for each task, we finetuned it on a base model and observed the number of samples when validation loss starts to rise. We mixed the samples of each task proportional to its optimal number of samples. A corpus is exhausted before upsampling if the number of total samples is smaller than its optimal number. We finetune with the task mixture (263,400 samples) with the aforementioned template.