CharlesLi/llama_2_sky_safe_o1_llama_3_8B_default_4000_1000_full
The CharlesLi/llama_2_sky_safe_o1_llama_3_8B_default_4000_1000_full model is a 7 billion parameter language model, fine-tuned from Meta's Llama-2-7b-chat-hf. This model was fine-tuned on a generator dataset, achieving a validation loss of 0.6740. It is intended for general language generation tasks, building upon the Llama 2 architecture.
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Model Overview
This model, llama_2_sky_safe_o1_llama_3_8B_default_4000_1000_full, is a fine-tuned variant of the Meta Llama-2-7b-chat-hf base model. It leverages the Llama 2 architecture, which is known for its strong performance across various language understanding and generation tasks. The model has 7 billion parameters and was trained with a context length of 4096 tokens.
Training Details
The fine-tuning process involved a generator dataset, with training conducted over 1 epoch. Key hyperparameters included a learning rate of 2e-05, a total batch size of 32 (achieved with train_batch_size: 4 and gradient_accumulation_steps: 2), and the Adam optimizer. The training concluded with a validation loss of 0.6740.
Potential Use Cases
Given its foundation on Llama-2-7b-chat-hf and fine-tuning on a generator dataset, this model is likely suitable for:
- Text generation: Creating coherent and contextually relevant text.
- Chatbot applications: Engaging in conversational AI scenarios.
- Content creation: Assisting with drafting articles, summaries, or creative writing.