readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - t5-small
  - text2text-generation
  - natural language generation
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/multiwoz21
  metrics:
  - Slot Error Rate
  - sacrebleu
  
  model-index:
  - name: t5-small-nlg-all-multiwoz21
    results:
    - task:
        type: text2text-generation
        name: natural language generation
      dataset:
        type: ConvLab/multiwoz21
        name: MultiWOZ 2.1
        split: test
        revision: 5f55375edbfe0270c20bcf770751ad982c0e6614
      metrics:
        - type: Slot Error Rate
          value: 5.4
          name: SER
        - type: sacrebleu
          value: 29.7
          name: BLEU
  
  widget:
  - text: "[inform][taxi]([destination][Pizza Hut Fen Ditton],[departure][Saint John's college])\n\nuser: "
  - text: "[request][taxi]([leave at][],[arrive by][])\n\nsystem: "
  
  inference:
    parameters:
      max_length: 100
  
  ---
  
  # t5-small-nlg-all-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) 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: 128
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 512
  - 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
  