readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - t5-small
  - text2text-generation
  - dialogue generation
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/multiwoz21
  metrics:
  - LM loss
  
  model-index:
  - name: t5-small-goal2dialogue-multiwoz21
    results:
    - task:
        type: text2text-generation
        name: dialogue generation
      dataset:
        type: ConvLab/multiwoz21
        name: MultiWOZ 2.1
        split: validation
        revision: 5f55375edbfe0270c20bcf770751ad982c0e6614
      metrics:
        - type: Language model loss
          value: 1.5253684520721436
          name: LM loss
    - task:
        type: text2text-generation
        name: dialogue generation
      dataset:
        type: ConvLab/multiwoz21
        name: MultiWOZ 2.1
        split: test
        revision: 5f55375edbfe0270c20bcf770751ad982c0e6614
      metrics:
        - type: Language model loss
          value: 1.515929937362671
          name: LM loss
  
  
  widget:
  - text: "You are traveling to Cambridge and looking forward to try local restaurants. You are looking for a particular attraction. Its name is called nusha. Make sure you get postcode and address. You are also looking for a place to dine. The restaurant should be in the expensive price range and should serve indian food. The restaurant should be in the centre. Make sure you get address"
  - text: "You want to book a taxi. The taxi should go to pizza hut fen ditton and should depart from saint john's college. The taxi should leave after 17:15. Make sure you get car type and contact number"
  
  inference:
    parameters:
      max_length: 1024
  
  ---
  
  # t5-small-goal2dialogue-multiwoz21
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [MultiWOZ 2.1](https://huggingface.co/datasets/ConvLab/multiwoz21).
  
  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: 32
  - eval_batch_size: 64
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - optimizer: Adafactor
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  