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README.md
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---
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license: mit
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---
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---
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license: mit
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datasets:
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- McGill-NLP/FaithDial
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widget:
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- knowledge: "A cardigan is a type of knitted garment (sweater) that has an open front."
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- response: "The old version is the regular one, knitted garment that has open front and buttons!"
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---
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## Overview
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**Model Description:** roberta-large-faithcritic is the [RoBERTa large model](https://huggingface.co/roberta-large) fine-tuned on the [FaithDial](https://huggingface.co/datasets/McGill-NLP/FaithDial) dataset. The objective is to predict whether an utterance is faithful or not, given the source knowledge.
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The hyperparameters are provided in [hparams.yml](hparams.yml). To know more about how to train a critic model, visit [our repo](https://github.com/McGill-NLP/FaithDial).
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("McGill-NLP/roberta-large-faithcritic")
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model = AutoModel.from_pretrained("McGill-NLP/roberta-large-faithcritic")
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knowledge = "A cardigan is a type of knitted garment (sweater) that has an open front."
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response = "The old version is the regular one, knitted garment that has open front and buttons!"
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input = tokenizer(knowledge, response)
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output = model(**input)
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```
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## Citation Information
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```bibtex
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@article{dziri2022faithdial,
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title={FaithDial: A Faithful Benchmark for Information-Seeking Dialogue},
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author={Dziri, Nouha and Kamalloo, Ehsan and Milton, Sivan and Zaiane, Osmar and Yu, Mo and Ponti, Edoardo and Reddy, Siva},
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journal={arXiv preprint, arXiv:2204.10757},
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year={2022},
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url={https://arxiv.org/abs/2204.10757}
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}
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```
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