Error in fine-tuning.

[TriplePool]

Hi, thanks for the excellent work.
I'm trying to re-implement the experiments proposed in Noah.
However, I get trouble running the main.py and ged.py.
I have modified some paths in code, but I meet the followed issue when I try to generate the pretrained_model and start_point with the fine_tune.py:

At iterate  199    f=  2.04590D+00    |proj g|=  1.08076D-02
At iterate  200    f=  2.04586D+00    |proj g|=  1.08576D-02

           * * *

Tit   = total number of iterations
Tnf   = total number of function evaluations
Tnint = total number of segments explored during Cauchy searches
Skip  = number of BFGS updates skipped
Nact  = number of active bounds at final generalized Cauchy point
Projg = norm of the final projected gradient
F     = final function value

           * * *

   N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
 1158    200    222      1     0     0   1.086D-02   2.046D+00
  F =   2.0458561768646106     

STOP: TOTAL NO. of ITERATIONS REACHED LIMIT                 
/home/wbl/miniconda3/envs/mol_ret/lib/python3.7/site-packages/sklearn/neural_network/_multilayer_perceptron.py:500: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
  self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter)
Segmentation fault (core dumped)

Could you please help me with the above issue, or release the pretrained_model and start_point so that I can run the ged.py script?