readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - roberta
  - classification
  - dialog state tracking
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/tm1
  - Convlab/tm2
  - Convlab/tm3
  metrics:
  - Joint Goal Accuracy
  - Slot F1
  
  model-index:
  - name: setsumbt-dst-tm123
    results:
    - task:
        type: classification
        name: dialog state tracking
      dataset:
        type: ConvLab/tm1
        name: TM1+TM2+TM3
        split: test
      metrics:
        - type: Joint Goal Accuracy
          value: 24.9
          name: JGA
        - type: Slot F1
          value: 65.5
          name: Slot F1
  
  ---
  
  # SetSUMBT-dst-tm1-tm2-tm3
  
  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 [Taskmaster1](https://huggingface.co/datasets/ConvLab/tm1), [Taskmaster2](https://huggingface.co/datasets/ConvLab/tm2) and [Taskmaster3](https://huggingface.co/datasets/ConvLab/tm3).
  
  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: 2
  - eval_batch_size: 8
  - seed: 0
  - gradient_accumulation_steps: 1
  - optimizer: AdamW
  - 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
  