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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- dialogue policy |
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- task-oriented dialog |
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--- |
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# lava-policy-multiwoz |
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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. |
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Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage. |
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## Training procedure |
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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. |
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### Training hyperparameters |
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The following hyperparameters were used during SL training: |
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- y_size: 10 |
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- k_size: 20 |
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- beta: 0.1 |
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- simple_posterior: true |
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- contextual_posterior: false |
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- learning_rate: 1e-03 |
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- max_vocab_size: 1000 |
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- max_utt_len: 50 |
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- max_dec_len: 30 |
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- backward_size: 2 |
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- train_batch_size: 128 |
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- seed: 58 |
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- optimizer: Adam |
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- num_epoch: 100 with early stopping based on validation set |
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The following hyperparameters were used during RL training: |
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- tune_pi_only: false |
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- max_words: 100 |
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- temperature: 1.0 |
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- episode_repeat: 1.0 |
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- rl_lr: 0.01 |
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- momentum: 0.0 |
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- nesterov: false |
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- gamma: 0.99 |
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- rl_clip: 5.0 |
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- random_seed: 38 |
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