Vertex-Math-0.5B (Q8_0)

Vertex-Math-0.5B is a compact mathematical reasoning language model fine-tuned from Qwen2.5-0.5B-Instruct using QLoRA. Optimized specifically for edge devices, offline mobile assistants, and resource-constrained environments, this model delivers rigorous step-by-step mathematical problem-solving while maintaining an ultra-lightweight footprint.

Model Details

Base Model: Qwen/Qwen2.5-0.5B-Instruct
Architecture: Qwen2 (0.5B parameters)
Training Dataset: HuggingFaceH4/MATH-500 (Filtered and token-length audited)
Quantization: Q8_0 (GGUF)
Developer: Denis Sanchez Leyva (Vertex Coders LLC)

Training Configuration & Hyperparameters

Method: QLoRA (Rank r=8, Alpha 16)
Target Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
Hardware: Local training on NVIDIA GTX 1650 (4GB VRAM)
Max Sequence Length: 1024 tokens
Optimizer: Paged AdamW 8-bit
Loss Function: Fused Cross-Entropy Loss
Epochs: 2 (80 steps)

Prompt Format

The model is trained using the ChatML template with a specialized system prompt enforcing step-by-step deductive reasoning:

<|im_start|>system
You are a compact mathematical reasoning engine optimized for mobile edge devices. Solve problems step by step with precision and conclude with '#### <final_answer>'.<|im_end|>
<|im_start|>user
[Your math problem here]<|im_end|>
<|im_start|>assistant