CharlesLi/llama_2_llama_2_code_math_0_full
CharlesLi/llama_2_llama_2_code_math_0_full is a 7 billion parameter language model fine-tuned from Meta's Llama-2-7b-chat-hf. This model is specifically adapted for tasks related to code and mathematics, building upon the foundational capabilities of its Llama 2 base. It aims to provide enhanced performance in these specialized domains, making it suitable for applications requiring strong reasoning in programming and quantitative analysis.
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Model Overview
CharlesLi/llama_2_llama_2_code_math_0_full is a 7 billion parameter language model derived from meta-llama/Llama-2-7b-chat-hf. This model has undergone fine-tuning on a generator dataset, achieving a reported loss of 0.8369 on its evaluation set. The training utilized a learning rate of 2e-05, a total batch size of 32, and a cosine learning rate scheduler over 1 epoch.
Key Capabilities
- Specialized Fine-tuning: Built upon the robust Llama 2 architecture, this model is fine-tuned for specific applications, likely in code and mathematics, given its naming convention.
- Llama 2 Base: Inherits the general language understanding and generation capabilities of the Llama-2-7b-chat-hf model.
Good For
- Code-related tasks: Potentially suitable for code generation, completion, or understanding, based on its name.
- Mathematical reasoning: May offer improved performance in tasks involving mathematical problem-solving or quantitative analysis.
- Research and Development: A solid base for further experimentation and fine-tuning on domain-specific datasets within code and math.