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README.md
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- hendrydong/preference_700K
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base_model:
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- microsoft/Phi-3-mini-4k-instruct
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---
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# phi-instruct-segment Model Card
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## Method
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The segment reward model assigns rewards to semantically meaningful text segments, segmented dynamically with an entropy-based threshold. It is trained on binary preference labels from human feedback, optimizing a Bradley-Terry loss function that aggregates segment rewards using the average function.
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<div align=center>
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</div>
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## Training
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- hendrydong/preference_700K
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base_model:
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- microsoft/Phi-3-mini-4k-instruct
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pipeline_tag: text-classification
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---
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# phi-instruct-segment Model Card
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- **Paper:** [Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
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](https://arxiv.org/abs/2501.02790)
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- **Model:** [yyqoni/Phi-3-mini-4k-instruct-segment-rm-700k](yyqoni/Phi-3-mini-4k-segment-ppo-60k](https://huggingface.co/yyqoni/Phi-3-mini-4k-instruct-segment-rm-700k)
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## Method
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The segment reward model assigns rewards to semantically meaningful text segments, segmented dynamically with an entropy-based threshold. It is trained on binary preference labels from human feedback, optimizing a Bradley-Terry loss function that aggregates segment rewards using the average function.
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## Architecture
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<div align=center>
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</div>
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## Training
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