cs-552-2026-MMRF/safety_model
The cs-552-2026-MMRF/safety_model is a 2 billion parameter language model, fine-tuned from cs-552-2026-MMRF/15kDPO, with a 32768 token context length. This model is specifically optimized for safety-related applications, demonstrating a final validation loss of 0.0466. Its primary strength lies in its fine-tuned performance for specific safety tasks, making it suitable for content moderation and risk assessment.
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Model Overview
The cs-552-2026-MMRF/safety_model is a 2 billion parameter language model, fine-tuned from the cs-552-2026-MMRF/15kDPO base model. It features a substantial context length of 32768 tokens, enabling it to process and understand extensive inputs. The model was trained for 1 epoch with a learning rate of 2e-05 and a total batch size of 16, achieving a final validation loss of 0.0466.
Key Characteristics
- Base Model: Fine-tuned from
cs-552-2026-MMRF/15kDPO. - Parameter Count: 2 billion parameters.
- Context Length: Supports up to 32768 tokens.
- Performance: Achieved a validation loss of 0.0466, indicating strong performance on its evaluation set.
- Training: Utilized AdamW_Torch_Fused optimizer and a linear learning rate scheduler.
Potential Use Cases
While specific intended uses are not detailed in the README, the model's name and fine-tuning suggest an orientation towards safety-critical applications. Developers might consider this model for:
- Content Moderation: Identifying and flagging inappropriate or harmful content.
- Risk Assessment: Analyzing text for potential safety risks or compliance issues.
- Safety Policy Enforcement: Assisting in the application of predefined safety guidelines.