readme: ---
  language:
  - zh
  license: apache-2.0
  tags:
  - mt5-small
  - text2text-generation
  - dialog state tracking
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/crosswoz
  metrics:
  - Joint Goal Accuracy
  - Slot F1
  
  model-index:
  - name: mt5-small-dst-crosswoz
    results:
    - task:
        type: text2text-generation
        name: dialog state tracking
      dataset:
        type: ConvLab/crosswoz
        name: CrossWOZ
        split: test
        revision: 4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0
      metrics:
        - type: Joint Goal Accuracy
          value: 62.5
          name: JGA
        - type: Slot F1
          value: 90.4
          name: Slot F1
  
  widget:
  - text: "user: 你好，给我推荐一个评分是5分，价格在100-200元的酒店。\nsystem: 推荐您去北京布提克精品酒店。\nuser: 北京布提克精品酒店酒店是什么类型，有健身房吗？\nsystem: 北京布提克精品酒店评分是4.8分，是高档型酒店，没有健身房。\nuser: 给我推荐一个评分在4.5分以上，游玩时间在2小时 - 3小时的免费景点。"
  - text: "user: 您好，请帮我推荐个4.5分以上的景点游玩呗，最好把周边有什么酒店告诉我一下。\nsystem: 那我推荐您故宫，周边的酒店有北京天伦王朝酒店, 北京首都宾馆, 北京贵都大酒店。\nuser: 那请在故宫周边的酒店里，帮我找个评分在4.5分以上的店。\nsystem: 北京贵都大酒店符合您的要求。\nuser: 请帮我呼叫一辆从故宫到北京贵都大酒店的出租车，告诉我车型和车牌号。"
  
  inference:
    parameters:
      max_length: 100
  
  ---
  
  # mt5-small-dst-crosswoz
  
  This model is a fine-tuned version of [mt5-small](https://huggingface.co/mt5-small) on [CrossWOZ](https://huggingface.co/datasets/ConvLab/crosswoz).
  
  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: 0.001
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adafactor
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1