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---

license: mit
---


# diwank/silicone-deberta-pair

`deberta-large`-based dialog acts classifier. Trained on [silicone-merged](https://huggingface.co/datasets/diwank/silicone-merged): a simplified dialog act datasets from the silicone collection. 

Takes two sentences as inputs (one previous and one current utterance of a dialog). The previous sentence can be an empty string if this is the first utterance of a speaker in a dialog. **Outputs one of 11 labels**:

```python

[

    (0, 'acknowledge')

    (1, 'answer')

    (2, 'backchannel')

    (3, 'reply_yes')

    (4, 'exclaim')

    (5, 'say')

    (6, 'reply_no')

    (7, 'hold')

    (8, 'ask')

    (9, 'intent')

    (10, 'ask_yes_no')

]

```

## Example:

```python

from simpletransformers.classification import (

    ClassificationModel, ClassificationArgs

)



model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")

convert_to_label = lambda n: [

    ['acknowledge',

     'answer',

     'backchannel',

     'reply_yes',

     'exclaim',

     'say',

     'reply_no',

     'hold',

     'ask',

     'intent',

     'ask_yes_no'

    ][i] for i in n

]



predictions, raw_outputs = model.predict([["Say what is the meaning of life?", "I dont know"]])

convert_to_label(predictions)  # answer



```


## Report from W&B

https://wandb.ai/diwank/da-silicone-combined/reports/silicone-deberta-pair--VmlldzoxNTczNjE5?accessToken=yj1jz4c365z0y5b3olgzye7qgsl7qv9lxvqhmfhtb6300hql6veqa5xiq1skn8ys