Wladastic/Mini-Think-Base-1B

MiniThink-1B-base

MiniThink-1B is an experiment to reproduce the "Aha!" moment in AI. Is is trained using a modified version of the method used in the Unsloth R1 training blog and the notebook provided for training LLama 3.1 8B to learn R1 reasoning .

MiniThink is a fine-tuned version of the unsloth/Llama-3.2-1B-Instruct model.

Model Details

• Base Model: unsloth/Llama-3.2-1B-Instruct
• Training: Fine-tuned using progressive LoRA (ranks: 16 → 32 → 64) with Unsloth's optimization framework
• Task: Mathematical and logical reasoning with explicit, step-by-step thought processes
• Training Data: GSM8K dataset enhanced with think-aloud prompting
• Input Format: Questions requiring detailed, structured reasoning
• Output Format: A comprehensive thinking process enclosed in <think> tags, followed by the final answer

Dataset used

The model was trained on a modified version of Openai's GSM8K dataset, which contains 8K math word problems with one-number answers. To improve the training results, the dataset was slightly modified to exclude comma or period-separated numbers.

System Prompt

The model is trained with the following system prompt to guide its reasoning process:

# Define special tokens for thinking process
THINK_START = "<think>"
THINK_END = "</think>"

SYSTEM_PROMPT = f"""Show your reasoning process using <think> tags, then provide your answer. For example:

Question: "Janet has 3 apples. She buys 2 more. How many apples does she have?"

{THINK_START}
Let me solve this step by step:
- Janet starts with 3 apples
- She buys 2 more apples
- I need to add: 3 + 2 = 5
Wait, let me verify:
- Initial apples: 3
- Added apples: 2
Yes, the total is 5 apples
{THINK_END}

5"""

Usage

The model expects a chat-like input and responds with a structured breakdown of its reasoning. For example:

Input:

Question: “Janet has 3 apples. She buys 2 more. How many apples does she have?”

Output:

<think>
Let me solve this step by step:
- Janet starts with 3 apples
- She buys 2 more apples
- I need to add: 3 + 2 = 5
Wait, let me verify:
- Initial apples: 3
- Added apples: 2
Yes, the total is 5 apples
</think>
5

Limitations

• Being a 1B-parameter model, its performance is naturally more limited compared to larger models.
• Optimized for mathematical and logical tasks; however, complex computations may occasionally yield errors.
• Always verify critical outputs.

Training

The model was trained using:

• Progressive LoRA: Gradually increasing ranks from 16 to 32 and finally 64
• Mixed Precision Training: Utilizing bf16 where supported for optimal performance
• GRPO (Guided Reward Policy Optimization): Implemented via the Unsloth framework for guided training
• Data: GSM8K dataset enriched with explicit think-aloud examples

License

This model adheres to the licensing terms of the base Llama-3.2 1B model. Please refer to Meta's Llama-3.2 1B license for details on usage terms and conditions.

Framework

Developed using the Unsloth Framework, this model leverages advanced techniques like GRPO and progressive LoRA optimization for efficient training and fine-tuning of large language models.