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README.md
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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#
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the trl-lib/kto-mix-14k and the chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5 datasets.
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It achieves the following results on the evaluation set:
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- Fg Logps/reference Kl: -20.2070
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- Fg Loss: 0.7365
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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# FactAlign-Phi-3-Mini
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This model is aligned with our **FactAlign** framework for improved long-form factuality, from [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct).
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For more information, please refer to our paper: [FactAlign: Long-form Factuality Alignment of Large Language Models](https://huggingface.co/papers/2410.01691).
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the trl-lib/kto-mix-14k and the chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5 datasets.
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It achieves the following results on the evaluation set:
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- Fg Logps/reference Kl: -20.2070
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- Fg Loss: 0.7365
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## Training procedure
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### Training hyperparameters
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