CharlesLi/llama_2_sky_safe_o1_4o_default_4000_100_full
The CharlesLi/llama_2_sky_safe_o1_4o_default_4000_100_full is a 7 billion parameter language model, fine-tuned from Meta's Llama-2-7b-chat-hf. This model was trained with a context length of 4096 tokens and optimized for general conversational tasks. It demonstrates a training loss of 0.5437, indicating its performance on the fine-tuning dataset. Its primary application is in chat-based interactions and general language generation.
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Model Overview
CharlesLi/llama_2_sky_safe_o1_4o_default_4000_100_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 aimed to adapt the model for specific conversational or generative tasks, as indicated by its origin from a chat-optimized base.
Key Characteristics
- Base Model: Fine-tuned from meta-llama/Llama-2-7b-chat-hf.
- Parameter Count: 7 billion parameters.
- Training Performance: Achieved a validation loss of 0.5437 on its evaluation set, with a training loss of 0.7377 at step 100.
- Training Configuration: Utilized a learning rate of 2e-05, a total batch size of 32, and trained for 1 epoch using Adam optimizer with a cosine learning rate scheduler.
Intended Use Cases
This model is suitable for applications requiring a Llama-2-7b-chat-hf derivative, particularly for tasks aligned with its fine-tuning objective. Given its chat-optimized base, it is generally well-suited for:
- Conversational AI and chatbots.
- General text generation and completion.
- Tasks benefiting from a fine-tuned Llama-2 architecture.