Unfortunately, I don’t know what would work the best, but am generally recommending to scale down the problem a bit and try to overfit a small data sample (e.g. just 10 samples) until the model achieves a (near) perfect accuracy. Once this is done, you might have a good starting point for the hyperparameters and might scale up the use case again.