readme: ---
  language:
  - zh
  license: apache-2.0
  tags:
  - mt5-small
  - text2text-generation
  - natural language understanding
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/crosswoz
  metrics:
  - Dialog acts Accuracy
  - Dialog acts F1
  
  model-index:
  - name: mt5-small-nlu-all-crosswoz
    results:
    - task:
        type: text2text-generation
        name: natural language understanding
      dataset:
        type: ConvLab/crosswoz
        name: CrossWOZ
        split: test
        revision: 4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0
      metrics:
        - type: Dialog acts Accuracy
          value: 84.0
          name: Accuracy
        - type: Dialog acts F1
          value: 90.1
          name: 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。"
  - text: "system: 抱歉，为您搜索了一些经济型酒店都没有健身房。其他类型的一些酒店行吗？比如北京贵都大酒店、北京京仪大酒店这些也是很好的，就是价格高了一些。"
  
  inference:
    parameters:
      max_length: 100
  
  ---
  
  # mt5-small-nlu-all-crosswoz
  
  This model is a fine-tuned version of [mt5-small](https://huggingface.co/mt5-small) on [CrossWOZ](https://huggingface.co/datasets/ConvLab/crosswoz) both user and system utterances.
  
  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: 16
  - total_train_batch_size: 256
  - optimizer: Adafactor
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1