README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - t5-small
  - text2text-generation
  - dialog state tracking
  - conversational system
  - task-oriented dialog
datasets:
  - ConvLab/multiwoz21
metrics:
  - Joint Goal Accuracy
  - Slot F1
model-index:
  - name: t5-small-dst-multiwoz21
    results:
      - task:
          type: text2text-generation
          name: dialog state tracking
        dataset:
          type: ConvLab/multiwoz21
          name: MultiWOZ 2.1
          split: test
          revision: 5f55375edbfe0270c20bcf770751ad982c0e6614
        metrics:
          - type: Joint Goal Accuracy
            value: 52.6
            name: JGA
          - type: Slot F1
            value: 91.9
            name: Slot F1
widget:
  - text: >-
      user: I would like a taxi from Saint John's college to Pizza Hut Fen
      Ditton.

      system: What time do you want to leave and what time do you want to arrive
      by?

      user: I want to leave after 17:15.
  - text: >-
      user: I want to find a moderately priced restaurant. 

      system: I have many options available for you! Is there a certain area or
      cuisine that interests you?

      user: Yes I would like the restaurant to be located in the center of the
      town.
inference:
  parameters:
    max_length: 100

t5-small-dst-multiwoz21

This model is a fine-tuned version of t5-small on MultiWOZ 2.1.

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• 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