kth8/gemma-3-270m-it-homeowner-classifier-GGUF overview

---

license: gemma

language:

• en

base_model: kth8/gemma-3-270m-it-homeowner-classifier

datasets:

• kth8/homeowner-classification

pipeline_tag: text-generation

library_name: transformers

tags:

• sft
• trl
• unsloth
• gemma
• gemma3
• gemma3_text

---

!logo

A supervised fine-tune of unsloth/gemma-3-270m-it on the kth8/homeowner-classification dataset.

Inspired by https://www.teachmecoolstuff.com/viewarticle/fine-tuning-a-local-llm-to-categorize-questions

Use temperature=0.0 for optimal results.

Usage example

System prompt

Classify the homeowner question into a category from the list below.
The answer must be exactly one category name from the list in JSON format.
Choose the best category based on the meaning of the question.

Valid categories:
- appliances
- brick work
- car
- cooking
- doorbell
- electric
- fence
- fountain
- garden lights
- gutters
- hvac
- irrigation
- mosquito
- painting
- pool
- tree service
- water heater
- window service

User prompt

What is the CYA level supposed to be in the pool water?

Assistant response

{"category": "pool"}

Model Details

• Base Model: unsloth/gemma-3-270m-it
• Parameter Count: 268,098,176
• Precision: torch.bfloat16

Training Settings

PEFT

• Rank: 32
• LoRA alpha: 64
• Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
• Gradient checkpointing: unsloth

SFT

• Epoch: 1
• Batch size: 8
• Gradient Accumulation steps: 2
• Learning rate: 0.0002
• Optimizer: adamw_torch_fused
• Learning rate scheduler: cosine
• Warmup steps: 10
• Weight decay: 0.01

Training stats

• Date: 2026-06-17T01:06:10.026211
• GPU: NVIDIA L4
• Peak VRAM usage: 2.205 GB
• Global step: 126
• Training runtime (seconds): 334.7612
• Best validation loss: 0.013801434077322483

| Step | Training Loss | Validation Loss |

|------|---------------|-----------------|

| 0 | No log | 2.182445 |

| 12 | 1.131100 | 0.195152 |

| 24 | 0.122900 | 0.082139 |

| 36 | 0.076800 | 0.034620 |

| 48 | 0.075600 | 0.027673 |

| 60 | 0.039300 | 0.031881 |

| 72 | 0.038300 | 0.020789 |

| 84 | 0.031200 | 0.015834 |

| 96 | 0.018400 | 0.013921 |

| 108 | 0.030300 | 0.014498 |

| 120 | 0.023700 | 0.013801 |

Framework versions

• Unsloth: 2026.6.7
• TRL: 0.22.2
• Transformers: 4.56.2
• Pytorch: 2.11.0+cu128
• Datasets: 5.0.0
• Tokenizers: 0.22.2

License

This model is released under the Gemma license. See the Gemma Terms of Use and Prohibited Use Policy regarding the use of Gemma-generated content.