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---
language:
- zh
license: apache-2.0
tags:
- mt5-small
- text2text-generation
- dialog state tracking
- conversational system
- task-oriented dialog
datasets:
- ConvLab/crosswoz
metrics:
- Joint Goal Accuracy
- Slot F1
model-index:
- name: mt5-small-dst-crosswoz
results:
- task:
type: text2text-generation
name: dialog state tracking
dataset:
type: ConvLab/crosswoz
name: CrossWOZ
split: test
revision: 4a3e56082543ed9eecb9c76ef5eadc1aa0cc5ca0
metrics:
- type: Joint Goal Accuracy
value: 62.5
name: JGA
- type: Slot F1
value: 90.4
name: Slot F1
widget:
- text: "user: 你好,给我推荐一个评分是5分,价格在100-200元的酒店。\nsystem: 推荐您去北京布提克精品酒店。\nuser: 北京布提克精品酒店酒店是什么类型,有健身房吗?\nsystem: 北京布提克精品酒店评分是4.8分,是高档型酒店,没有健身房。\nuser: 给我推荐一个评分在4.5分以上,游玩时间在2小时 - 3小时的免费景点。"
- text: "user: 您好,请帮我推荐个4.5分以上的景点游玩呗,最好把周边有什么酒店告诉我一下。\nsystem: 那我推荐您故宫,周边的酒店有北京天伦王朝酒店, 北京首都宾馆, 北京贵都大酒店。\nuser: 那请在故宫周边的酒店里,帮我找个评分在4.5分以上的店。\nsystem: 北京贵都大酒店符合您的要求。\nuser: 请帮我呼叫一辆从故宫到北京贵都大酒店的出租车,告诉我车型和车牌号。"
inference:
parameters:
max_length: 100
---
# mt5-small-dst-crosswoz
This model is a fine-tuned version of [mt5-small](https://huggingface.co/mt5-small) on [CrossWOZ](https://huggingface.co/datasets/ConvLab/crosswoz).
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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