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This model is a fine-tuned version SetSUMBT of roberta-base on MultiWOZ2.1. This model is a combined DST and NLU model and is a distribution distilled version of a ensemble of 5 models. This model should be used to produce uncertainty estimates for the dialogue belief state.

Refer to ConvLab-3 for model description and usage.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00001
  • train_batch_size: 3
  • eval_batch_size: 16
  • seed: 0
  • gradient_accumulation_steps: 1
  • optimizer: AdamW
  • loss: Ensemble Distribution Distillation Loss
  • lr_scheduler_type: linear
  • num_epochs: 50.0

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.8.0+cu110
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train ConvLab/setsumbt-dst_nlu-multiwoz21-EnD2

Evaluation results