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

ConvLab/setsumbt-dst_nlu-multiwoz21-EnD2

SetSUMBT-dst-nlu-multiwoz21

Training procedure

Training hyperparameters

Framework versions

ConvLab/
setsumbt-dst_nlu-multiwoz21-EnD2