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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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- natural language generation |
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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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- Slot Error Rate |
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- sacrebleu |
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model-index: |
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- name: t5-small-nlg-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: natural language generation |
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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: Slot Error Rate |
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value: 2.1 |
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name: SER |
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- type: sacrebleu |
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value: 51.5 |
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name: BLEU |
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widget: |
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- text: "tm1: [inform][pizza_ordering]([name.store][Domino's])\n\nsystem: " |
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- text: "tm2: [inform][restaurant-search]([name.restaurant][Via 313, the Violet Crown Social Club],[price_range][$8 per slice])\n\nsystem: " |
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- text: "tm3: [inform][movie]([name.movie][Star Wars],[name.movie][The Grudge])\n\nsystem: " |
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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-nlg-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: 8 |
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- total_train_batch_size: 512 |
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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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