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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/sgd |
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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-sgd |
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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/sgd |
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name: SGD |
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split: test |
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revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f |
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metrics: |
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- type: Joint Goal Accuracy |
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value: 20.1 |
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name: JGA |
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- type: Slot F1 |
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value: 58.5 |
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name: Slot F1 |
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widget: |
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- text: "user: Hi, could you get me a restaurant booking on the 8th please?\nsystem: Any preference on the restaurant, location and time?\nuser: Could you get me a reservation at P.f. Chang's in Corte Madera at afternoon 12?" |
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- text: "user: I need to book a dinner reservation for a date. Help me reserve a table at a restaurant.\nsystem: What time and location do you have in mind?\nuser: Something around 8 in the night should be fine. Oh, and look in the San Jose area." |
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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-sgd |
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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). |
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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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