ertghiu256/ministral-3-3b-glm-distillation

Model Card: Ministral-3-GLM-Distilled-R1

Model Overview

Model Name: Ministral-3-GLM-Distilled-R1 Base Model: mistralai/Ministral-3B Model Type: Causal Language Model (Text-Only) Architecture: Ministral-3 (3B parameters) – vision layers frozen Training Method: Supervised Fine-Tuning (SFT) + Group Relative Policy Optimization (GRPO)

Model Description

This model is a distilled reasoning engine fine-tuned from GLM-5.2 logic puzzles and reinforced with GRPO to produce concise, structured reasoning. It uses a [THINK]...[/THINK] block for reasoning and a [SOLUTION]...[/SOLUTION] block for the final answer.

The model is designed for tasks requiring:

• —Logical reasoning
• —Mathematical problem-solving
• —Step-by-step explanation
• —Concise, structured outputs

Model Details

Training Procedure

Phase 1: Supervised Fine-Tuning (SFT)

• —Dataset: ianncity/GLM-5.2-Logic-Puzzles + synthetic [THINK] examples
• —Filtering: Removed examples >2048 tokens
• —Loss: Converged from ~11.2 to ~0.38
• —Format: [THINK]...[/THINK] + final answer

Phase 2: GRPO Reinforcement Learning

• —Dataset: open-r1/Big-Math-RL-Verified-Processed (100 examples)
• —Reward Functions:
• —Format compliance (1.0 for exact [THINK]/[/THINK] tags)
• —Correctness (string match – improved in v2)
• —Hyperparameters:
• —Learning rate: 5e-6
• —num_generations: 4
• —KL beta: 0.001
• —Temperature: 0.8 (training)

Usage

Default System Prompt (Critical)

# HOW YOU SHOULD THINK AND ANSWER

First draft your thinking process (inner monologue) until you arrive at a response. Do NOT overthink, immediately stop if you are checking your answer more than 2 times. Format your response using Markdown, and use LaTeX for any mathematical equations. Write both your thoughts and the response in the same language as the input.

Your thinking process must follow the template below:
[THINK]Your concise thoughts, like working through an exercise on scratch paper. Be as casual and as long as you want until you are confident to generate the response to the user.[/THINK]
Here, provide a self-contained response.
Put your final short answer inside [SOLUTION] and [/SOLUTION]

Recommended Sampling Parameters

Strengths and Limitations

Strengths

• —Concise Reasoning: Outputs are ~1500 tokens – 2× shorter than the SFT version.
• —Structured Format: Consistently produces [THINK] and [SOLUTION] blocks.
• —Logic Puzzle Mastery: Handles ambiguity and multiple solutions well.
• —Self‑Correction: Can catch and fix errors in reasoning.

Limitations

• —Math Handling: Limited – reward function was string‑based (string match), not math‑aware.
• —Sampling Sensitivity: Output quality depends on specific sampling parameters.
• —Looping: Can over‑verify at low temperature; system prompt is critical.
• —Hallucination: May mis‑evaluate statements (e.g., calling true as false).

When to Use This Model

Training Costs

Considerations

• —This model is designed for reasoning tasks and should not be used for:
• —Medical diagnosis
• —Financial advice
• —Legal decisions
• —Generating harmful or deceptive content

• —Hallucinations are possible. Always verify critical outputs manually.

Uploaded finetuned model

• —Developed by: ertghiu256
• —License: apache-2.0
• —Finetuned from model : ertghiu256/ministral-3-3b-glm-distillation-test

This mistral3 model was trained 2x faster with Unsloth and Huggingface's TRL library.

<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>