Advice Needed for Training an Imbalanced Dataset AI Model: lr, Epochs, and Architecture
l’m developing an AI model to determine whether a question is ‘asktoask’ (true) or not (false). My dataset is imbalanced, with more examples of non-‘asktoask’ questions than ‘asktoask’ questions. I would appreciate suggestions on training parameters such as the learning rate (lr), the number of epochs, and the model architecture. What strategies or tips do you recommend for effectively training this model while handling class imbalance in the dataset? Your insights are welcome.