readme: ## Natural Don't Know Response Model
  
  Fine-tuned on [Google's T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) using a combination of a dependency-rule based data and [Quora Question Pairs(QQP)](https://huggingface.co/nlp/viewer/?dataset=quora) dataset for **Don't Know Response Generation** task.
  
  Additional information about this model:
  - Paper : [Saying No is An Art: Contextualized Fallback Responses for
  Unanswerable Dialogue Queries](https://arxiv.org/pdf/2012.01873.pdf)
  - Github Repo: https://github.com/kaustubhdhole/natural-dont-know
  
  #### How to use
  ```python
  from transformers import T5ForConditionalGeneration, T5Tokenizer
  model_name = "ashish-shrivastava/dont-know-response"
  model = T5ForConditionalGeneration.from_pretrained(model_name)
  tokenizer = T5Tokenizer.from_pretrained(model_name)
  
  input = "Where can I find good Italian food ?"
  input_ids = tokenizer.encode(input, return_tensors="pt")
  outputs = model.generate(input_ids)
  decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
  print(decoded_output) # I'm not sure where you can get good quality Italian food.
  
  ```
  
  #### Hyperparameters
  
  ```
  n_epochs = 2
  base_LM_model = "T5-base"
  max_seq_len = 256
  learning_rate = 3e-4
  adam_epsilon = 1e-8
  train_batch_size = 6
  ``` 
  
  #### BibTeX entry and citation info
  
  ```bibtex
  @misc{shrivastava2020saying,
        title={Saying No is An Art: Contextualized Fallback Responses for Unanswerable Dialogue Queries}, 
        author={Ashish Shrivastava and Kaustubh Dhole and Abhinav Bhatt and Sharvani Raghunath},
        year={2020},
        eprint={2012.01873},
        archivePrefix={arXiv},
        primaryClass={cs.CL}
  }
  ```
  