Update docs/features/runs/2_Analyzing Runs/3_artifacts.md

Author: Esther Quansah

docs/features/runs/2_Analyzing Runs/3_artifacts.md

@@ -15,13 +15,17 @@ Grid uploads your artifacts to long-term storage while your experiment is runnin
 :::note
 This may have two side effects, depending on how large and how many artifacts your code generates:
 
-- Grid may need to use extra memory while your experiment is running to sync your artifacts to long term storage
+1. Extra Memory Usage
+
+Grid may need to use extra memory while your experiment is running to sync your artifacts to long term storage.
   - Grid will only use extra memory to sync artifacts larger than 1 Gib
   - Grid will use 50 Mi of extra memory to sync artifacts larger than 1 Gib
   - Grid will not use more than 200 Mi of extra memory
   - If you are running memory intensive experiments *and* are generating artifacts over 1 Gib, it is recommended to use a larger instance type
-- Your experiment will not be marked `done` until Grid has finished syncing your artifacts to long-term storage
-  - If you are generating lots of artifacts per experiment, this may increase your experiment run times
+
+2. Increased run time
+
+Your experiment will not be marked `done` until Grid has finished syncing your artifacts to long-term storage. If you are generating lots of artifacts per experiment, this may increase your experiment run times.
 :::
 
 Try [hello.py](https://github.com/williamFalcon/hello/blob/main/hello.py) as an example, to see how artifacts are generated and saved.