I am working on a time series project. The results of LSTM model which i am using varies a lot with the variation in seeds. I am wondering how can i make that model stable. Currently to get the reproducible result i am fixing the seed. Is there some way which i can implement to make it stable. The 5 Stratifiedfold MCC (Matthews correlation coefficient) score varies between 0.636 to 0.724 just by using different seeds (for weights initialization).
Any help would be appreciated.
The training dataset has 2904 instances only.