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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 understanding
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+ - conversational system
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+ - task-oriented dialog
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+ datasets:
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+ - ConvLab/tm2
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+ metrics:
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+ - Dialog acts Accuracy
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+ - Dialog acts F1
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+
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+ model-index:
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+ - name: t5-small-nlu-tm2-context3
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+ results:
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+ - task:
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+ type: text2text-generation
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+ name: natural language understanding
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+ dataset:
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+ type: ConvLab/tm2
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+ name: Taskmaster-2
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+ split: test
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+ revision: cdc314b156e7f7ffa81a1e7398f1f8a2e86c0095
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+ metrics:
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+ - type: Dialog acts Accuracy
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+ value: 82.4
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+ name: Accuracy
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+ - type: Dialog acts F1
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+ value: 74.3
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+ name: F1
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+
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+ widget:
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+ - text: "user: Hi, I'm looking for a flight. I need to visit a friend.\nsystem: Hello, how can I help you? Sure, I can help you with that. On what dates?\nuser: I'm looking to travel from March 20th to 22nd."
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+ - text: "system: Anything else?\nuser: That should be everything.\nsystem: I found a flight for $424 on United Airlines.\nuser: Okay, is that for New York?"
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+
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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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+ ---
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+
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+ # t5-small-nlu-tm2-context3
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+
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+ This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [Taskmaster-2](https://huggingface.co/datasets/ConvLab/tm2) with context window size == 3.
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+
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+ Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage.
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 128
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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: 256
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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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+
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+ ### Framework versions
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+
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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