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README.md
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- Patronus AI
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- evaluation
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- hallucination-detection
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license:
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language:
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- en
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base_model: PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct
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pipeline_tag: text-generation
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---
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#
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This is quantized version of [PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct](https://huggingface.co/PatronusAI/Llama-3-Patronus-Lynx-8B-Instruct) created using llama.cpp
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Lynx is an open-source hallucination evaluation model. Patronus-Lynx-8B-Instruct was trained on a mix of datasets including CovidQA, PubmedQA, DROP, RAGTruth.
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The datasets contain a mix of hand-annotated and synthetic data. The maximum sequence length is 8000 tokens.
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## Model Details
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- **Model Type:**
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- **Language:** Primarily English
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- **Developed by:** Patronus AI
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### Model Sources
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## Training Details
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The model was finetuned for 3 epochs using H100s on dataset of size 2400. We use [lion](https://github.com/lucidrains/lion-pytorch) optimizer with lr=5.0e-7. For more details on data generation, please check out our Github repo.
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### Training Data
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The model was evaluated on [PatronusAI/HaluBench](https://huggingface.co/datasets/PatronusAI/HaluBench).
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It outperforms GPT-3.5-Turbo, GPT-4-Turbo, GPT-4o and Claude
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## Model Card Contact
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[@sunitha-ravi](https://huggingface.co/sunitha-ravi)
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- Patronus AI
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- evaluation
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- hallucination-detection
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license: cc-by-nc-4.0
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language:
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- en
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---
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# Model Card for Model ID
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Lynx is an open-source hallucination evaluation model. Patronus-Lynx-70B-Instruct was trained on a mix of datasets including CovidQA, PubmedQA, DROP, RAGTruth.
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The datasets contain a mix of hand-annotated and synthetic data. The maximum sequence length is 8000 tokens.
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## Model Details
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- **Model Type:** This is a quantized version of Patronus-Lynx-70B-Instruct.
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- **Language:** Primarily English
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- **Developed by:** Patronus AI
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- **Paper:** [https://arxiv.org/abs/2407.08488](https://arxiv.org/abs/2407.08488)
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- **License:** [ https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)
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### Model Sources
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## Training Details
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The model was finetuned for 3 epochs using 32 H100s on dataset of size 2400. We use [lion](https://github.com/lucidrains/lion-pytorch) optimizer with lr=5.0e-7. For more details on data generation, please check out our Github repo.
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### Training Data
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The model was evaluated on [PatronusAI/HaluBench](https://huggingface.co/datasets/PatronusAI/HaluBench).
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It outperforms GPT-3.5-Turbo, GPT-4-Turbo, GPT-4o and Claude-3-Sonnet.
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## Citation
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If you are using the model, cite using
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```
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@article{ravi2024lynx,
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title={Lynx: An Open Source Hallucination Evaluation Model},
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author={Ravi, Selvan Sunitha and Mielczarek, Bartosz and Kannappan, Anand and Kiela, Douwe and Qian, Rebecca},
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journal={arXiv preprint arXiv:2407.08488},
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year={2024}
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}
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```
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## Model Card Contact
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[@sunitha-ravi](https://huggingface.co/sunitha-ravi)
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