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So I used weka to determine my training accuracy and cross-validation accuracy. It has showed me that my training accuracy is 84.9167 % and my Cross validation accuracy is 83.9167 %
I also tried to use sklearn to determine my training and cross validation accuracy and gave me the following: 83.5% on training and 82.67% on cross validation accuracy.
Is the difference between training accuracy and cross validation accuracy enough to consider my model overfit?
Absolutely no. Difference between training and cross validation is expected in most scenarios as training use almost all the data and cross validation misses on some sample.
Overfitting happens when the difference between training and testing data is too high. In your case neither the diff is too high nor testing data is used.
