Issue with Val accuracy never changing

I’m building a model that categorizes 1/2s of data at a 256 sample rate, the input has a shape of (128, 4) and is flattened. The output has 9 different classes. I can’t seem to correctly tune the hidden layers. As soon as I start training. Training accuracy jumps to 95is percent with a very low loss, but my Val accuracy is 0.1111, which is what I expect from guessing a random class, and my Val loss is always much much higher than training loss.

Should I use a different optimizer? Different activations? What are your Guy’s recommendations?