Also: the majority of your parameters are in this one layer:
self.dense1 = nn.Linear(304, 36)
(304 in_channels) * (36 out_channels) = 10944
So, you might consider averagepooling to 1x1xChannels right before dense1. And, make dense1 a convolution with 304 in_channels, 36 out_channels, kernel_size of 1, and groups=32 or 64 or whatever number you like. That ought to bring your parameter count way down.