Understanding experiments in Continual Learning
In the figure, the class-accuracy for each of the two classes per task is shown (y-axis) as the number of different tasks learned is increased (x-axis).
So in the first graph, we see that as the model learns subsequent tasks (task 1: distinguishing 0-1, task 2: distinguishing 2-3, etc), the classification accuracy of the model on '0's remains near 100%, whereas the classification accuracy of the model on '1's decreases.