Hugging Face Overview
Overview
This model, benhaotang/llama3.2-1B-physics-finetuned, is a specialized version of the 1 billion parameter Llama 3.2-Instruct model. It has been fine-tuned using LoRA (Low-Rank Adaptation) on the kejian/arxiv-physics-debug-v0 dataset, which is derived from arXiv physics papers. The primary goal of this model is to serve as a proof-of-concept for enhancing language models' understanding and generation capabilities within the physics domain.
Key Capabilities
- Physics Domain Specialization: Optimized for generating responses to questions related to physics concepts and theories.
- Compact Size: At 1 billion parameters, it offers a relatively lightweight solution for domain-specific tasks.
- Instruction Following: Inherits instruction-following capabilities from its Llama 3.2-Instruct base.
Training Details
The model was fine-tuned with a learning rate of 2e-5 over 3 epochs, using 8 gradient accumulation steps. The training was conducted on an Ubuntu 24.04 system with an RX7800XT GPU.
Good For
- Experimental Physics Q&A: Ideal for exploring the potential of smaller models in specialized scientific fields.
- Concept Prototyping: Useful for developers and researchers looking to test domain-specific fine-tuning strategies.
- Educational Tools: Can be a starting point for developing tools that explain physics concepts, though its output should be critically evaluated due to its experimental nature.