|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- t5-small |
|
- text2text-generation |
|
- natural language understanding |
|
- conversational system |
|
- task-oriented dialog |
|
datasets: |
|
- ConvLab/tm1 |
|
- ConvLab/tm2 |
|
- ConvLab/tm3 |
|
metrics: |
|
- Dialog acts Accuracy |
|
- Dialog acts F1 |
|
|
|
model-index: |
|
- name: t5-small-nlu-tm1_tm2_tm3 |
|
results: |
|
- task: |
|
type: text2text-generation |
|
name: natural language understanding |
|
dataset: |
|
type: ConvLab/tm1, ConvLab/tm2, ConvLab/tm3 |
|
name: TM1+TM2+TM3 |
|
split: test |
|
metrics: |
|
- type: Dialog acts Accuracy |
|
value: 81.8 |
|
name: Accuracy |
|
- type: Dialog acts F1 |
|
value: 73.0 |
|
name: F1 |
|
|
|
widget: |
|
- text: "tm1: user: I would like to order a pizza from Domino's." |
|
- text: "tm2: user: I would like help getting a flight from LA to Amsterdam." |
|
- text: "tm3: user: Well, I need a kids friendly movie. I was thinking about seeing Mulan." |
|
|
|
inference: |
|
parameters: |
|
max_length: 100 |
|
|
|
--- |
|
|
|
# t5-small-nlu-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: 128 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 256 |
|
- optimizer: Adafactor |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10.0 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.11.0 |
|
|
