qwen3-4b-structured-output-lora-continued-v5-ver3
A LoRA adapter specialized for structured output generation
(JSON / YAML / XML / TOML / CSV) in long-input settings.
This repository provides a LoRA adapter fine-tuned from
Qwen/Qwen3-4B-Instruct-2507 using QLoRA (4-bit, Unsloth).
This adapter was trained in five stages using LoRA continuation:
structured_data_with_cot_dataset_512_v2 (initial fine-tuning) →
structured_data_with_cot_dataset_512_v5 (continued fine-tuning) →
structured-5k-mix-sft (continued fine-tuning) →
mixed training (continued fine-tuning) using structured-5k-mix-sft
as main data and structured-hard-sft-4k as auxiliary data.→
structured_data_with_cot_dataset_512_v5 (continued fine-tuning(retraining))
This repository contains LoRA adapter weights only.
The base model must be loaded separately.
Training Objective
This adapter is trained to improve structured output accuracy
(JSON / YAML / XML / TOML / CSV).
Loss is applied only to the final assistant output.
When output markers are present, intermediate reasoning (Chain-of-Thought) is masked.
Training Configuration
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Method: QLoRA (4-bit)
- Max sequence length: 1024
- Epochs: 2
- Learning rate: 5e-07
- LoRA: r=64, alpha=128
Usage
1from transformers import AutoModelForCausalLM, AutoTokenizer
2from peft import PeftModel
3import torch
4
5base = "Qwen/Qwen3-4B-Instruct-2507"
6adapter = "your_id/your-repo"
7
8tokenizer = AutoTokenizer.from_pretrained(base)
9model = AutoModelForCausalLM.from_pretrained(
10 base,
11 torch_dtype=torch.float16,
12 device_map="auto",
13)
14model = PeftModel.from_pretrained(model, adapter)
Sources & Terms (IMPORTANT)
- Training data (stage 1): u-10bei/structured_data_with_cot_dataset_512_v2
- Training data (stage 2): u-10bei/structured_data_with_cot_dataset_512_v5
- Training data (stage 3): daichira/structured-5k-mix-sft
- Training data (stage 4): mixed dataset
- Main: daichira/structured-5k-mix-sft
- Auxiliary: daichira/structured-hard-sft-4k
- Training data (stage 5): u-10bei/structured_data_with_cot_dataset_512_v5(Retraining)
Dataset License & Attribution
The following licenses apply to the training datasets used in this repository:
-
u-10bei structured_data_with_cot_dataset family
(e.g., structured_data_with_cot_dataset_512_v2, v4, v5, etc.):
Licensed under the MIT License.
Use of these datasets is permitted under the terms of the MIT License, provided that the copyright notice is retained.
-
daichira structured_ SFT datasets*
(structured-5k-mix-sft, structured-hard-sft-4k):
Licensed under the Creative Commons Attribution 4.0 International (CC-BY-4.0) license.
This license permits use, modification, and redistribution, including for commercial purposes, provided that appropriate attribution is given.
Attribution: please credit the original dataset authors (u-10bei, daichira) and link to the dataset pages when redistributing or publishing derived works.
Users must comply with:
- The license terms of each individual dataset listed above.
- The original license and terms of use of the base model (Qwen/Qwen3-4B-Instruct-2507).
This repository distributes LoRA adapter weights only and does not redistribute the original datasets.
