CharlesLi/llama_2_sky_o1_0_full
The CharlesLi/llama_2_sky_o1_0_full is a 7 billion parameter language model, fine-tuned from Meta's Llama-2-7b-chat-hf. This model is specifically fine-tuned on a generator dataset, indicating its optimization for text generation tasks. It maintains a context length of 4096 tokens, making it suitable for applications requiring coherent and extended text outputs.
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Model Overview
The CharlesLi/llama_2_sky_o1_0_full is a 7 billion parameter language model derived from Meta's Llama-2-7b-chat-hf architecture. This model has undergone specific fine-tuning on a generator dataset, suggesting its primary utility in text generation applications.
Key Characteristics
- Base Model: Fine-tuned from
meta-llama/Llama-2-7b-chat-hf. - Parameter Count: 7 billion parameters.
- Context Length: Supports a context window of 4096 tokens.
- Training Objective: Fine-tuned on a generator dataset, indicating a focus on text generation capabilities.
- Training Loss: Achieved a loss of 0.7307 on the evaluation set.
Training Details
The model was trained with a learning rate of 2e-05, a batch size of 32 (total, with gradient accumulation), and utilized an Adam optimizer. The training process involved 1 epoch with a cosine learning rate scheduler and a warmup ratio of 0.1.
Potential Use Cases
Given its fine-tuning on a generator dataset, this model is likely well-suited for tasks such as:
- Content creation and text generation.
- Creative writing and story generation.
- Dialogue generation or conversational AI components.
Further details on specific intended uses and limitations are not provided in the original model card.