Model Overview

The CharlesLi/llama_2_llama_2_code_math_3_full is a 7 billion parameter language model, fine-tuned from the meta-llama/Llama-2-7b-chat-hf base model. This fine-tuning process utilized a specific "generator dataset," suggesting an optimization for tasks involving content creation or generation.

Key Training Details

• Base Model: meta-llama/Llama-2-7b-chat-hf
• Parameter Count: 7 billion
• Training Objective: Fine-tuned on a "generator dataset."
• Observed Loss: Achieved a loss of 0.5628 on the evaluation set.
• Hyperparameters:
  • Learning Rate: 2e-05
  • Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
  • Epochs: 1
  • Batch Size: 4 (train/eval), total 32 (train), 16 (eval)

Intended Use Cases

While specific intended uses are not detailed, the fine-tuning on a "generator dataset" implies suitability for tasks where the model needs to produce coherent and relevant text, potentially for creative writing, summarization, or other generative applications. Users should consider its Llama-2 lineage for general language understanding and generation tasks, with an emphasis on its fine-tuned generative capabilities.