README.md

metadata

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
            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 on CrossWOZ both user and system utterances.

Refer to 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