Currently the whole code works almost perfect. Experiment parameters are specified under the general function and currently displays a summary graph once done with the experiments. Sometimes it just does not work but it may be a glitche of the development environment itself.
Currently trainingUnit.py creates models for each of the files and then they are stored. Currently the testing and validation F1 scores that we are obtaining are quite high however that is expected due to the random split done. The performance rates will fall once we move to personalized models.