Model Overview

yujunzhou/SFT_Advanced_Risk_Situation_Aware_Qwen3-4B-Base is a fine-tuned version of the Qwen3-4B-Base model, developed by yujunzhou. This 4 billion parameter model is specifically adapted for tasks related to advanced risk situation awareness, leveraging a substantial 40960-token context window.

Key Characteristics

• Base Model: Built upon the robust Qwen3-4B-Base architecture.
• Specialized Fine-tuning: Trained on the Advanced_Risk_Situation_Aware_Qwen3-4B-Base dataset, suggesting a focus on identifying, analyzing, and responding to complex risk scenarios.
• Context Length: Features a 40960-token context length, enabling the processing of extensive inputs for detailed situational understanding.

Training Details

The model was trained with the following hyperparameters:

• Learning Rate: 1e-05
• Batch Size: A total training batch size of 128 (4 per device across 8 GPUs with 4 gradient accumulation steps).
• Epochs: 10.0 epochs.
• Optimizer: AdamW with standard betas and epsilon.

Potential Use Cases

This model is likely suitable for applications requiring:

• Risk Assessment: Analyzing complex data to identify potential risks.
• Situational Awareness: Processing large volumes of information to maintain an understanding of evolving situations.
• Specialized Language Understanding: Tasks where a deep comprehension of risk-related terminology and contexts is crucial.