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The model exhibited a sharp rise in accuracy during training and maintained it throughout the last epoch. Yet, it is seen to have struggled in between the epochs, which goes to prove its learning process. The figure illustrates the accuracy of the model during the validation phase. With short rises and falls during the beginning epochs and a drop at the sixth, the model was seen to struggle in applying what it had learned to new data. However, there was a sharp rise after the sixth epoch, which is maintained or even bettered at the tenth epoch. It can be concluded that the hybrid model, throughout the epochs, learned to classify new instances in the validation split at a higher accuracy. For the losses in training, the model did quite well. It drastically reduced losses from the first epoch and consistently maintained a steady decrease to the last.
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IEEE/ICACT20260055 Slide.08
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