| ## 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} | |
| } | |
| ``` | |