Model Overview

CharlesLi/llama_2_sky_o1_3_full is a 7 billion parameter language model developed by CharlesLi. It is a fine-tuned variant of the meta-llama/Llama-2-7b-chat-hf architecture, specifically adapted through training on a generator dataset.

Key Characteristics

• Base Model: Built upon the robust Llama-2-7b-chat-hf, inheriting its conversational and general language understanding capabilities.
• Fine-tuning Objective: Optimized using a generator dataset, suggesting an intended use case for text generation tasks.
• Performance: Achieved a validation loss of 0.6912 during its single-epoch training phase.
• Training Configuration: Utilized a learning rate of 2e-05, a total batch size of 32 (across 4 GPUs with gradient accumulation), and an Adam optimizer with a cosine learning rate scheduler.

Intended Use Cases

This model is suitable for applications requiring text generation, leveraging its fine-tuning on a generator dataset. Developers can explore its capabilities for tasks such as content creation, creative writing, or other generative AI applications, building on the strong foundation of the Llama 2 chat model.