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README.md

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 ## Generation Logic & Sliding Windows (Important)
 
-The ultimate goal of **Model 0** is to accurately chunk continuous terminal recordings into distinct "events." The label the model must predict is the **boundary timestamp**—the exact moment one event ends and a new one begins.
+The goal of **Model 0** is to accurately chunk continuous terminal recordings into distinct "events." The label the model must predict is the **boundary timestamp**—the exact moment one event ends and a new one begins.
 
-To generate robust training data, we use a sliding window approach encompassing exactly **three consecutive boundary timestamps** (**T1**, **T2**, and **T3**) for each input:
+To generate training data, we use a sliding window approach encompassing exactly **three consecutive boundary timestamps** (**T1**, **T2**, and **T3**) for each input:
 
 * **T1 (The Anchor):** The known starting timestamp of the current event.
 * **T2 (The Target):** The actual event boundary the model must predict.