localized-ft/Llama-3.1-8B-school-of-reward-hacks-last-third-sft-seed3-epoch3
The localized-ft/Llama-3.1-8B-school-of-reward-hacks-last-third-sft-seed3-epoch3 is an 8 billion parameter Llama-3.1 instruction-tuned model developed by localized-ft. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for specific tasks related to reward hacking, building upon the Meta-Llama-3.1-8B-Instruct base model with an 8192 token context length.
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Model Overview
This model, localized-ft/Llama-3.1-8B-school-of-reward-hacks-last-third-sft-seed3-epoch3, is an 8 billion parameter Llama-3.1 instruction-tuned model developed by localized-ft. It is fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model and utilizes an 8192 token context length. The training process leveraged Unsloth and Huggingface's TRL library, which facilitated a 2x faster fine-tuning speed.
Key Characteristics
- Base Model: Fine-tuned from Meta-Llama-3.1-8B-Instruct.
- Training Efficiency: Benefits from Unsloth's optimizations for faster training.
- Context Length: Supports an 8192 token context window.
Intended Use Cases
This model is specifically fine-tuned for tasks related to "reward hacking," suggesting its application in research or development scenarios focused on understanding and manipulating reward mechanisms in AI systems. Developers interested in exploring the nuances of reward functions and their impact on model behavior may find this model particularly useful.