readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - dialogue policy
  - task-oriented dialog
  
  ---
  
  # lava-policy-multiwoz
  
  This is the best performing LAVA_kl model from the [LAVA paper](https://aclanthology.org/2020.coling-main.41/) which can be used as a word-level policy module in ConvLab3 pipeline.
  
  Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage.
  
  ## Training procedure
  The model was trained on MultiWOZ 2.0 data using the [LAVA codebase](https://gitlab.cs.uni-duesseldorf.de/general/dsml/lava-public). The model started with VAE pre-training and fine-tuning with informative prior KL loss, followed by corpus-based RL with REINFORCE.
  
  ### Training hyperparameters
  
  The following hyperparameters were used during SL training:
  - y_size: 10
  - k_size: 20
  - beta: 0.1
  - simple_posterior: true
  - contextual_posterior: false
  - learning_rate: 1e-03
  - max_vocab_size: 1000
  - max_utt_len: 50
  - max_dec_len: 30
  - backward_size: 2
  - train_batch_size: 128
  - seed: 58
  - optimizer: Adam
  - num_epoch: 100 with early stopping based on validation set
    
  The following hyperparameters were used during RL training:
  - tune_pi_only: false
  - max_words: 100
  - temperature: 1.0
  - episode_repeat: 1.0
  - rl_lr: 0.01
  - momentum: 0.0
  - nesterov: false
  - gamma: 0.99
  - rl_clip: 5.0
  - random_seed: 38
  
  