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---
language:
- en
license: apache-2.0
tags:
- roberta
- classification
- dialog state tracking
- natural language understanding
- uncertainty
- conversational system
- task-oriented dialog
datasets:
- ConvLab/multiwoz21
metrics:
- Joint Goal Accuracy
- Slot F1
- Joint Goal Expected Calibration Error
model-index:
- name: setsumbt-dst-nlu-multiwoz21
results:
- task:
type: classification
name: dialog state tracking
dataset:
type: ConvLab/multiwoz21
name: MultiWOZ21
split: test
metrics:
- type: Joint Goal Accuracy
value: 51.8
name: JGA
- type: Slot F1
value: 91.1
name: Slot F1
- type: Joint Goal Expected Calibration Error
value: 12.7
name: JECE
---
# SetSUMBT-dst-nlu-multiwoz21
This model is a fine-tuned version [SetSUMBT](https://github.com/ConvLab/ConvLab-3/tree/master/convlab/dst/setsumbt) of [roberta-base](https://huggingface.co/roberta-base) on [MultiWOZ2.1](https://huggingface.co/datasets/ConvLab/multiwoz21).
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](https://github.com/ConvLab/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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