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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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- dialog state tracking |
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- conversational system |
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- task-oriented dialog |
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datasets: |
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- ConvLab/tm1 |
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- ConvLab/tm2 |
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- ConvLab/tm3 |
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metrics: |
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- Joint Goal Accuracy |
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- Slot F1 |
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model-index: |
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- name: t5-small-dst-tm1_tm2_tm3 |
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results: |
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- task: |
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type: text2text-generation |
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name: dialog state tracking |
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dataset: |
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type: ConvLab/tm1, ConvLab/tm2, ConvLab/tm3 |
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name: TM1+TM2+TM3 |
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split: test |
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metrics: |
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- type: Joint Goal Accuracy |
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value: 48.5 |
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name: JGA |
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- type: Slot F1 |
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value: 81.1 |
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name: Slot F1 |
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widget: |
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- text: "tm1: user: Hi there, could you please help me with an order of Pizza?\nsystem: Sure, where would you like to order you pizza from?\nuser: I would like to order a pizza from Domino's." |
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- text: "tm2: user: I need help finding a hotel in New Orleans.\nsystem: Okay.\nuser: I need something that's around $300 a night and it's a five star rating." |
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- text: "tm3: user: Hi, I'm hoping to see a movie tonight.\nsystem: Great, I can assist with that. What genre of film do you prefer.\nuser: I usually like comedies." |
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inference: |
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parameters: |
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max_length: 100 |
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--- |
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# t5-small-dst-tm1_tm2_tm3 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [Taskmaster-1](https://huggingface.co/datasets/ConvLab/tm1), [Taskmaster-2](https://huggingface.co/datasets/ConvLab/tm2), and [Taskmaster-3](https://huggingface.co/datasets/ConvLab/tm3). |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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 4.20.1 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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