cs-552-2026-group1/math_model

Math Model — Olympiad-Focused SFT Checkpoint

This model is a fine-tuned version of Qwen/Qwen3-1.7B for mathematical reasoning, developed for the CS-552 standard project math track.

The model was trained to solve competition-style mathematics problems and produce final answers in boxed LaTeX format.

Base Model

• Base model: Qwen/Qwen3-1.7B
• Fine-tuning method: LoRA supervised fine-tuning
• Target task: mathematical reasoning and short-answer competition problems

Training Data

The final submitted checkpoint was trained on approximately 25,165 examples from hard mathematical reasoning datasets:

Dataset / Source	Examples
Hendrycks MATH	4,759
OpenR1-Math-220k	7,999
NuminaMath-CoT	12,407
Total	25,165

The NuminaMath subset was filtered to focus on harder mathematical sources:

• Olympiads
• AoPS Forum
• AMC/AIME
• MATH

The OpenR1 subset was filtered to competition-relevant categories:

• Algebra
• Geometry
• Number Theory
• Combinatorics
• Inequalities

Training Details

Setting	Value
Base model	Qwen/Qwen3-1.7B
Fine-tuning method	LoRA
Epochs	1
LoRA rank	32
LoRA alpha	64
LoRA dropout	0.05
Learning rate	1e-4
Batch size	1
Gradient accumulation steps	8
Precision	bfloat16
Hardware	1 × NVIDIA A100 40GB
Training steps	3,146
Runtime	6,761 seconds
Tokens processed	14.7M
Final training loss	0.6114
Mean token accuracy	0.8302

Generation Configuration

The submitted generation configuration uses sampling:

{
  "do_sample": true,
  "temperature": 0.25,
  "top_p": 0.85,
  "top_k": 30
}