| | --- |
| | language: |
| | - en |
| | license: apache-2.0 |
| | tags: |
| | - t5-small |
| | - text2text-generation |
| | - dialog state tracking |
| | - conversational system |
| | - task-oriented dialog |
| | datasets: |
| | - ConvLab/tm1 |
| | - ConvLab/tm2 |
| | - ConvLab/tm3 |
| | metrics: |
| | - Joint Goal Accuracy |
| | - Slot F1 |
| |
|
| | model-index: |
| | - name: t5-small-dst-tm1_tm2_tm3 |
| | results: |
| | - task: |
| | type: text2text-generation |
| | name: dialog state tracking |
| | dataset: |
| | type: ConvLab/tm1, ConvLab/tm2, ConvLab/tm3 |
| | name: TM1+TM2+TM3 |
| | split: test |
| | metrics: |
| | - type: Joint Goal Accuracy |
| | value: 48.5 |
| | name: JGA |
| | - type: Slot F1 |
| | value: 81.1 |
| | name: Slot F1 |
| |
|
| | widget: |
| | - 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." |
| | - 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." |
| | - 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." |
| |
|
| | inference: |
| | parameters: |
| | max_length: 100 |
| |
|
| | --- |
| | |
| | # t5-small-dst-tm1_tm2_tm3 |
| |
|
| | 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). |
| |
|
| | Refer to [ConvLab-3](https://github.com/ConvLab/ConvLab-3) for model description and usage. |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 0.001 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adafactor |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10.0 |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.20.1 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.3.2 |
| | - Tokenizers 0.12.1 |
| | |
