Hi, initializing the weights of the output layer to zero seemed to work in my case. You can still look on public implementation of deep cfr such as :
  

      github.com
  

  
    deepmind/open_spiel/blob/master/open_spiel/python/pytorch/deep_cfr.py 1


    # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# See the License for the specific language governing permissions and
# limitations under the License.

"""Implements Deep CFR Algorithm.

See https://arxiv.org/abs/1811.00164.

The algorithm defines an `advantage` and `strategy` networks that compute
advantages used to do regret matching across information sets and to approximate



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or

  
      

      GitHub
  

  
    

GitHub - EricSteinberger/Deep-CFR: Scalable Implementation of Deep CFR and...

  Scalable Implementation of Deep CFR and Single Deep CFR - GitHub - EricSteinberger/Deep-CFR: Scalable Implementation of Deep CFR and Single Deep CFR


  

  
    
    
  

  


Hope that helps