krishnamraja13/gemma-4-e4b-opus46-reasoning

Gemma 4 E4B Opus4.6 Reasoning

A PEFT LoRA adapter fine-tuned on top of google/gemma-4-e4b-it using the Crownelius/Opus-4.6-Reasoning-2100x-formatted dataset.

This adapter is optimized for:

• structured step-by-step reasoning
• logic puzzles
• planning and decomposition
• algorithm explanations
• conceptual problem solving
• code reasoning workflows

The strongest improvements are visible on:

• multi-step logic puzzles
• algorithm design explanations
• state-tracking tasks
• proof-style conceptual reasoning

The adapter shows strongest gains on deliberate decomposition, planning, and educational reasoning prompts.

Base Model

• google/gemma-4-e4b-it

Dataset

• Crownelius/Opus-4.6-Reasoning-2100x-formatted

Training Setup

• PEFT LoRA fine-tuning
• 4-bit QLoRA loading
• 2 training epochs
• training max sequence length: 512 tokens
• gradient accumulation: 16
• trained on Google Colab T4

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Training Metrics

• training loss: 192.38
• validation loss: 11.95
• entropy: 3.91
• mean token accuracy: 0.0462
• train runtime: 5783 seconds
• train rows: 2010
• validation rows: 106

Example Use

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = AutoModelForCausalLM.from_pretrained(
    "google/gemma-4-e4b-it",
    device_map="auto"
)

model = PeftModel.from_pretrained(
    base_model,
    "krishnamraja13/gemma-4-e4b-opus46-reasoning"
)

tokenizer = AutoTokenizer.from_pretrained(
    "krishnamraja13/gemma-4-e4b-opus46-reasoning"
)

Requirements

Use a recent version of transformers with Gemma 4 support.

pip install -U transformers peft accelerate bitsandbytes

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Known Strengths

This adapter performs best on:

• logic riddles
• switch / state puzzles
• recursive explanation prompts
• dynamic programming intuition
• binary search reasoning
• linked list cycle detection explanations
• proof-style educational prompts
• intermediate reasoning scaffolds and invariant-based explanations

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Known Limitations

The adapter is stronger at:

• structured reasoning
• decomposition
• planning
• conceptual explanation

than strict symbolic algebra fidelity.

For exact equation solving, outputs may sometimes over-interpret terse symbolic prompts.

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License

This adapter is a derivative of Gemma 4 and follows the Gemma license terms.