My Linear Regression Model Mean Absolute Error(MAE) is 0.29 and R2 0.20 , Is this a acceptable Model?

Under the usual conditions (that you probably satisfy), $R^2$ can be interpreted as the proportion of variance in $y$ explained by your model. This means that your model explains $20\%$ of the variance in $y$.

Mean absolute error is the mean amount by which your model predictions miss the observed values. This means that, on average, your model misses by $0.29$.

It’s up to you to put those numbers in context. These metrics aren’t equivalent to grades in school where being over $R^2=0.90$ is an $A$-grade and scoring $R^2=0.2$ is an $F$-grade. There are situations where the low $R^2$ (or high MAE) could be fantastic for your task, and there are situations where the high $R^2$ (or low MAE) could indicate rather pedestrian performance.