Friction Reasoning Model

This model is fine-tuned to engage in productive disagreement, overthinking, and reluctance. It's based on DeepSeek-R1-Distill-Qwen-7B and trained on a curated dataset of disagreement, overthinking, and reluctance examples.

Model Description

  • Model Architecture: DeepSeek-R1-Distill-Qwen-7B with LoRA adapters
  • Language(s): English
  • License: Apache 2.0
  • Finetuning Approach: Instruction tuning with friction-based reasoning examples

Training Procedure

  • Hardware: NVIDIA RTX 4090 (24GB)
  • Framework: Unsloth + PyTorch
  • Training Time: 35 minutes
  • Epochs: 7 (early convergence around epoch 4)
  • Batch Size: 2 per device (effective batch size 8 with gradient accumulation)
  • Optimization: AdamW 8-bit
  • Learning Rate: 2e-4 with cosine schedule
  • Weight Decay: 0.01
  • Gradient Clipping: 0.5
  • Mixed Precision: bfloat16

Intended Use

This model is designed for:

  • Engaging in productive disagreement
  • Challenging assumptions constructively
  • Providing alternative perspectives
  • Deep analytical thinking
  • Careful consideration of complex issues

Limitations

The model:

  • Is not designed for factual question-answering
  • May sometimes be overly disagreeable
  • Should not be used for medical, legal, or financial advice
  • Works best with reflective or analytical queries
  • May not perform well on objective or factual tasks

Bias and Risks

The model:

  • May exhibit biases present in the training data
  • Could potentially reinforce overthinking in certain situations
  • Might challenge user assumptions in sensitive contexts
  • Should be used with appropriate content warnings

Citation

If you use this model in your research, please cite:

@misc{friction-reasoning-2025,
  author = {Leon van Bokhorst},
  title = {Mixture of Friction: Fine-tuned Language Model for Productive Disagreement, Overthinking, Uncertainty and Reluctance},
  year = {2025},
  publisher = {HuggingFace},
  journal = {HuggingFace Model Hub},
  howpublished = {\url{https://huggingface.co/leonvanbokhorst/deepseek-r1-mixture-of-friction}}
}

Acknowledgments

  • DeepSeek AI for the base model
  • Unsloth team for the optimization toolkit
  • HuggingFace for the model hosting and infrastructure
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