readme: ---
  license: mit
  ---
  
  # diwank/silicone-deberta-pair
  
  `deberta-base`-based dialog acts classifier. Trained on the `balanced` variant of the [silicone-merged](https://huggingface.co/datasets/diwank/silicone-merged) dataset: a simplified merged dialog act data from datasets in the [silicone](https://huggingface.co/datasets/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/silicone-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