Catastrophic Forgetting on DQN

I'm trying to explore solving the shortest path algorithm using DQN i know we can solve it using the Q-tablebut I just wanted to explore using deep learning. I have a set of nodes that I extracted from OpenStreetMap. Each node has an id. I contracted a data frame that contains the edges and the weight between the edges, which represents the distance you can find it here, and the graph network looks like this

Now I wanted to train my DQN to find the shortest path between the node 1130166767 and 1731824802. You can find the code here as colab notebook

the problem here that the loss function is not decreasing over time, and some time is decreased to zero, wich is good, but also the mean reward is decreasing not increasing, which mean the agent can't find the right policy for the training

I read from these to comment reddit and this comment from this question on stack that it might be a problem of exploration and I tried all the suggestions here expect changing the model but nothing work

a small note I read a lot that it might be a problem of exploration, so I increased the amount of agent exploration like this, and it didn't work

Can someone help to find what the problem is?