I updated the rnn to support multiple hidden layers, as previously it had a single layer, so I had to update the forward and backwards passes as well as the adagrad to account for the multiple layers. I started off with two and tested it with a hidden size of 256, but I didn’t see any improvement, however I didn’t train it for as long. I am now in the process of implementing a variable number of layers from 1 to any number, so that the model can learn greater complexity, however this comes at the cost of much slower training. Currently the training on 2 layers is a decent slowdown compared to with 1 layer, as i also increased hidden size to 512. So far I have made the forward pass work for multiple layers (greater than 2) but the rest of it still only supports 2 layers.