metadata
language:
- en
license: apache-2.0
tags:
- t5-small
- text2text-generation
- dialog state tracking
- conversational system
- task-oriented dialog
datasets:
- ConvLab/sgd
metrics:
- Joint Goal Accuracy
- Slot F1
model-index:
- name: t5-small-dst-sgd
results:
- task:
type: text2text-generation
name: dialog state tracking
dataset:
type: ConvLab/sgd
name: SGD
split: test
revision: 6e8c79b888b21cc658cf9c0ce128d263241cf70f
metrics:
- type: Joint Goal Accuracy
value: 20.1
name: JGA
- type: Slot F1
value: 58.5
name: Slot F1
widget:
- text: >-
user: Hi, could you get me a restaurant booking on the 8th please?
system: Any preference on the restaurant, location and time?
user: Could you get me a reservation at P.f. Chang's in Corte Madera at
afternoon 12?
- text: >-
user: I need to book a dinner reservation for a date. Help me reserve a
table at a restaurant.
system: What time and location do you have in mind?
user: Something around 8 in the night should be fine. Oh, and look in the
San Jose area.
inference:
parameters:
max_length: 100
t5-small-dst-sgd
This model is a fine-tuned version of t5-small on Schema-Guided Dialog.
Refer to 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