Update docs/Training-SAC.md

Co-Authored-By: andrewcoh <54679309+andrewcoh@users.noreply.github.com>

docs/Training-SAC.md

 replay buffer, and using this mini batch to update the models. Typically, this should be greater
 than 1. Note that setting `steps_per_update` lower will improve sample efficiency (reduce the number of steps required to train)
 but increase the CPU time spent performing updates. For most environments where steps are fairly fast (e.g. our example
-environments) `steps_per_update` equals the number of agents in the scene is a good balance. For slow environments (steps
+environments) `steps_per_update` equal to the number of agents in the scene is a good balance. For slow environments (steps
 take 0.1 seconds or more) reducing `steps_per_update` may improve training speed.
 We can also change `steps_per_update` to lower than 1 to update more often than once per step, though this is usually
 not neccessary.