|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- t5-small |
|
- text2text-generation |
|
- dialog state tracking |
|
- conversational system |
|
- task-oriented dialog |
|
datasets: |
|
- ConvLab/multiwoz21 |
|
- ConvLab/sgd |
|
- ConvLab/tm1 |
|
- ConvLab/tm2 |
|
- ConvLab/tm3 |
|
metrics: |
|
- Joint Goal Accuracy |
|
- Slot F1 |
|
|
|
model-index: |
|
- name: t5-small-dst-multiwoz21_sgd_tm1_tm2_tm3 |
|
results: |
|
- task: |
|
type: text2text-generation |
|
name: dialog state tracking |
|
dataset: |
|
type: ConvLab/multiwoz21 |
|
name: MultiWOZ 2.1 |
|
split: test |
|
revision: 5f55375edbfe0270c20bcf770751ad982c0e6614 |
|
metrics: |
|
- type: Joint Goal Accuracy |
|
value: 53.1 |
|
name: JGA |
|
- type: Slot F1 |
|
value: 91.9 |
|
name: Slot F1 |
|
- task: |
|
type: text2text-generation |
|
name: dialog state tracking |
|
dataset: |
|
type: ConvLab/sgd |
|
name: SGD |
|
split: test |
|
revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f |
|
metrics: |
|
- type: Joint Goal Accuracy |
|
value: 20.6 |
|
name: JGA |
|
- type: Slot F1 |
|
value: 60.0 |
|
name: Slot F1 |
|
- 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: 48.6 |
|
name: JGA |
|
- type: Slot F1 |
|
value: 81.0 |
|
name: Slot F1 |
|
|
|
widget: |
|
- text: "multiwoz21: user: I would like a taxi from Saint John's college to Pizza Hut Fen Ditton.\nsystem: What time do you want to leave and what time do you want to arrive by?\nuser: I want to leave after 17:15." |
|
example_title: "MultiWOZ 2.1" |
|
- text: "sgd: 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?" |
|
example_title: "Schema-Guided Dialog" |
|
- 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." |
|
example_title: "Taskmaster-1" |
|
- 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." |
|
example_title: "Taskmaster-2" |
|
- 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." |
|
example_title: "Taskmaster-3" |
|
|
|
inference: |
|
parameters: |
|
max_length: 100 |
|
|
|
--- |
|
|
|
# t5-small-dst-multiwoz21_sgd_tm1_tm2_tm3 |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on [MultiWOZ 2.1](https://huggingface.co/datasets/ConvLab/multiwoz21), [Schema-Guided Dialog](https://huggingface.co/datasets/ConvLab/sgd), [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 |
|
|
