Initializing and updating numpy vstack and numpy hstack inside a for loop

Question

I need to create and save numpy arrays of all the models stacked vertically together as well as stacked horizontally together for the columns of actual and predicted values from my model. How can I do this inside a for loop which loops through each model? My code below does not seem to work and it does not stack them the way I want them as it seems to overwrite the previous model each time it loops! The created and saved np arrays (actual_values_all_models_vstacked, pred_values_all_models_vstacked,actual_values_hstacked, pred_values_hstacked) should be of the size [8032500, 1], [8032500, 1], [1147500, 7], [1147500, 7] accordingly.

    nmodel, nx, ny, nz = 7, 150, 150, 51
    layer_cells = nx*ny
    model_cells = nx*ny*nz
    all_data_cells_num = nx*ny*nz*nmodel
    total_cells =  np.arange(all_data_cells_num)


   def get_model_index(model_list,total_cells,model_cells ):
        model_index_array = np.array([])
       for i in model_list:
          model_index = total_cells[(i-1)*model_cells:model_cells*i]
          model_index_array = np.append(model_index_array, model_index)
       return model_index_array


   model_runs = ['RUN_01', 'RUN_02', 'RUN_03', 'RUN_04', 'RUN_05', 'RUN_06', 'RUN_07']
   model_list = [1, 2, 3, 4, 5, 6, 7]

       # Initializing: 
   actual_values_all_models_vstacked = np.zeros([8032500, 1])   # 7*150*150*51 = 8032500
   pred_values_all_models_vstacked = np.zeros([8032500, 1])       # 7*150*150*51 = 8032500

   actual_values_hstacked = np.zeros([1147500, 7])      # 150*150*51 = 1147500
   pred_values_hstacked = np.zeros([1147500, 7])       # 150*150*51 = 1147500



   for model_index in model_list:  

       run_name = model_runs[model_index-1]

       blind_model = [model_index]
       blind_model_idx = get_model_index(blind_model,total_cells,model_cells )
       blind_model_idx = np.array([int(i) for i in blind_model_idx]) 

       actual = np.arange(1147500)

       pred = np.arange(1147500)

       actual_pred = np.hstack((actual, pred))


       actual_values_all_models_vstacked = np.vstack(actual_pred[:, 1])   # assuming col 1 is actual 
       pred_values_all_models_vstacked = np.vstack(actual_pred[:, 2])  # assuming col 2 is pred vals

       actual_values_hstacked = np.hstack(actual_pred[:, 1])
       pred_values_hstacked = np.hstack(actual_pred[:, 2])