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---
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license: mit
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---
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# diwank/silicone-deberta-pair
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`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.
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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**:
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```python
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[
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(0, 'acknowledge')
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(1, 'answer')
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(2, 'backchannel')
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(3, 'reply_yes')
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(4, 'exclaim')
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(5, 'say')
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(6, 'reply_no')
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(7, 'hold')
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(8, 'ask')
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(9, 'intent')
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(10, 'ask_yes_no')
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]
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```
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## Example:
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```python
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from simpletransformers.classification import (
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ClassificationModel, ClassificationArgs
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)
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model = ClassificationModel("deberta", "diwank/dyda-deberta-pair")
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convert_to_label = lambda n: [
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['acknowledge',
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'answer',
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'backchannel',
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'reply_yes',
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'exclaim',
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'say',
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'reply_no',
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'hold',
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'ask',
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'intent',
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'ask_yes_no'
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][i] for i in n
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]
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predictions, raw_outputs = model.predict([["Say what is the meaning of life?", "I dont know"]])
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convert_to_label(predictions) # answer
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```
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## Report from W&B
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https://wandb.ai/diwank/da-silicone-combined/reports/silicone-deberta-pair--VmlldzoxNTczNjE5?accessToken=yj1jz4c365z0y5b3olgzye7qgsl7qv9lxvqhmfhtb6300hql6veqa5xiq1skn8ys |
