jmajkutewicz/zephyr-7b-dpo_ultrafeedback

Zephyr 7B SFT aligned with DPO on UltraFeedback with β=0.01

This repo contains LoRA adapter created by aligning Zephyr 7B SFT on the UltraFeedback Binarized dataset using Direct Preference Optimization (DPO). It was trained as a series of models for studying DPO alignment.

Model details

• —Base model: alignment-handbook/zephyr-7b-sft-full
• —Preference dataset: HuggingFaceH4/ultrafeedback_binarized
• —DPO beta: 0.01
• —Training framework: PEFT/LoRA

See the base model card for usage and chat template details.

Training hyperparameters

• —Epochs: 1
• —Batch size: 16
• —Learning rate: 1e-05
• —Learning rate scheduler: cosine
• —Learning rate warmup ratio: 0.1
• —Gradient accumulation: 2
• —LoRA:
• —rank: 64
• —alpha: 64
• —dropout: 0.05
• —target modules: [qproj, kproj, vproj, oproj, gateproj, upproj, down_proj]

License

This adapter is released under the Apache License 2.0.

Citation

If this work was helpful, please cite:

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