MiniCheck RoBERTa Large This is a fact checking model from our work: 📃 MiniCheck: Efficient Fact Checking of LLMs on Grounding Documents (EMNLP 2024, GitHub Repo) The model is based on RoBERTA Large that predicts a binary label 1 for supported and 0 for unsupported. The model is doing predictions on the sentence level . It takes as input a document and a sentence and determine whether the sentence is supported by the document: MiniCheck Model(document, claim) {0, 1} MiniCheck RoBERTa Large is fine tuned from the trained RoBERTA Large model from AlignScore (Zha et al., 2023) on 14K synthetic data generated from scratch in a structed way (more details in the paper). Model Variants We also have other three MiniCheck model variants: bespokelabs/Bespoke Minicheck 7B (Model Size: 7B) lytang/MiniCheck Flan T5 Large (Model Size: 0.8B) lytang/MiniCheck DeBERTa v3 Large (Model Size: 0.4B) Model Performance The performance of these models is evaluated on our new collected benchmark (unseen by our models during training), LLM AggreFact, from 11 recent human annotated datasets on fact checking and grounding LLM generations. MiniCheck RoBERTa Large outperform all exisiting specialized fact chec…
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