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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- t5-small |
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- text2text-generation |
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- dialogue generation |
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- conversational system |
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- task-oriented dialog |
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datasets: |
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- ConvLab/multiwoz21 |
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metrics: |
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- LM loss |
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model-index: |
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- name: t5-small-goal2dialogue-multiwoz21 |
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results: |
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- task: |
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type: text2text-generation |
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name: dialogue generation |
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dataset: |
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type: ConvLab/multiwoz21 |
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name: MultiWOZ 2.1 |
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split: validation |
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revision: 5f55375edbfe0270c20bcf770751ad982c0e6614 |
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metrics: |
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- type: Language model loss |
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value: 1.5253684520721436 |
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name: LM loss |
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- task: |
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type: text2text-generation |
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name: dialogue generation |
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dataset: |
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type: ConvLab/multiwoz21 |
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name: MultiWOZ 2.1 |
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split: test |
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revision: 5f55375edbfe0270c20bcf770751ad982c0e6614 |
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metrics: |
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- type: Language model loss |
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value: 1.515929937362671 |
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name: LM loss |
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widget: |
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- 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" |
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- 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" |
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inference: |
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parameters: |
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max_length: 1024 |
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--- |
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# t5-small-goal2dialogue-multiwoz21 |
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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). |
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Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adafactor |
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- lr_scheduler_type: linear |
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- num_epochs: 10.0 |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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