yujunzhou/SFT_Advanced_Risk_Situation_Aware_llama
The yujunzhou/SFT_Advanced_Risk_Situation_Aware_llama is an 8 billion parameter instruction-tuned Llama 3.1 model, fine-tuned by yujunzhou on the Advanced_Risk_Situation_Aware_llama dataset. This model is designed for advanced risk situation awareness, leveraging its 32768 token context length to process extensive information. It specializes in understanding and responding to complex scenarios related to risk, making it suitable for applications requiring nuanced situational analysis.
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Model Overview
The yujunzhou/SFT_Advanced_Risk_Situation_Aware_llama is an 8 billion parameter language model, fine-tuned from the meta-llama/Llama-3.1-8B-Instruct architecture. This model has been specifically adapted using the Advanced_Risk_Situation_Aware_llama dataset, indicating a specialization in processing and understanding complex risk-related scenarios.
Key Training Details
The fine-tuning process involved a learning rate of 1e-05 and a total training batch size of 128 over 10 epochs. It utilized an adamw_torch optimizer with a linear learning rate scheduler and a warmup ratio of 0.1. The training was conducted on 8 GPUs, accumulating gradients over 4 steps.
Potential Applications
Given its fine-tuning on a risk-aware dataset, this model is likely intended for applications requiring:
- Situational Awareness: Analyzing and interpreting complex scenarios to identify potential risks.
- Risk Assessment: Evaluating and understanding the implications of various risk factors.
- Decision Support: Providing insights for informed decision-making in high-stakes or uncertain environments.
Further details regarding specific model capabilities, intended uses, and limitations are not explicitly provided in the current model description.