--- license: apache-2.0 --- This is the LACIE fine-tuned version of Mistral-7B, finetuned according to our paper [LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models](arxiv.org/abs/2405.21028) This model is a fine-tuned version of [Mistral-7B base](https://huggingface.co/mistralai/Mistral-7B-v0.1) that has been finetuned using data from [TriviaQA](https://huggingface.co/datasets/mandarjoshi/trivia_qa). LACIE is pragmatic preference-based finetuning method that optimizes models to be better calibrated w.r.t. both implicit and explicit confidence statements. The preferences in the dataset are based on correctness and whether listener accepted to rejected the answer. For more details, please see our paper. ## Model Architecture The architecture is the same as Mistral-7B; the weights in this repo are adapter weights for Mistral.