readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - t5-small
  - text2text-generation
  - natural language generation
  - conversational system
  - task-oriented dialog
  datasets:
  - ConvLab/sgd
  metrics:
  - Slot Error Rate
  - sacrebleu
  
  model-index:
  - name: t5-small-nlg-sgd
    results:
    - task:
        type: text2text-generation
        name: natural language generation
      dataset:
        type: ConvLab/sgd
        name: SGD
        split: test
        revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f
      metrics:
        - type: Slot Error Rate
          value: 11.9
          name: SER
        - type: sacrebleu
          value: 29.6
          name: BLEU
  
  widget:
  - text: "[request][Restaurants_2]([time][],[restaurant_name][],[location][])\n\nsystem: "
  - text: "[confirm][Restaurants_2]([number_of_seats][2],[restaurant_name][P.f. Chang's],[location][Corte Madera],[time][12 pm],[date][March 8th])\n\nsystem: "
  
  inference:
    parameters:
      max_length: 100
  
  ---
  
  # t5-small-nlg-sgd
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [Schema-Guided Dialog](https://huggingface.co/datasets/ConvLab/sgd).
  
  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: 64
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 512
  - 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
  