license, language, base_model, datasets, pipeline_tag, library_name, tags

license	language	base_model	datasets	pipeline_tag	library_name	tags
gemma	en	kth8/gemma-3-270m-it-homeowner-classifier	kth8/homeowner-classification	text-generation	transformers	sft trl unsloth gemma gemma3 gemma3_text

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.