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structeval-qwen3-4b-e-8-baseline-seq-e8

Text Generation
PEFT
Safetensors
English
qlora
lora
structured-output
Model card Files
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  1. .gitattributes +3 -0
  2. README.md +67 -0
  3. adapter_config.json +50 -0
  4. adapter_model.safetensors +3 -0
  5. added_tokens.json +28 -0
  6. checkpoint-400/adapter_config.json +50 -0
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.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ base_model: unsloth/Qwen3-4B-Instruct-2507
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+ datasets:
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+ - u-10bei/structured_data_with_cot_dataset_512_v2
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+ language:
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+ - en
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+ license: apache-2.0
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+ library_name: peft
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+ pipeline_tag: text-generation
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+ tags:
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+ - qlora
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+ - lora
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+ - structured-output
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+ ---
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+
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+ ＜【課題】ここは自分で記入して下さい＞
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+
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+ This repository provides a **LoRA adapter** fine-tuned from
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+ **unsloth/Qwen3-4B-Instruct-2507** using **QLoRA (4-bit, Unsloth)**.
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+
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+ This repository contains **LoRA adapter weights only**.
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+ The base model must be loaded separately.
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+
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+ ## Training Objective
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+
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+ This adapter is trained to improve **structured output accuracy**
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+ (JSON / YAML / XML / TOML / CSV).
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+
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+ Loss is applied only to the final assistant output,
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+ while intermediate reasoning (Chain-of-Thought) is masked.
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+
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+ ## Training Configuration
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+
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+ - Base model: unsloth/Qwen3-4B-Instruct-2507
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+ - Method: QLoRA (4-bit)
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+ - Max sequence length: 512
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+ - Epochs: 2
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+ - Learning rate: 2e-06
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+ - LoRA: r=64, alpha=128
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+ - NEFTune: 5.0
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+ - Data Cleaning: enabled
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ from peft import PeftModel
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+ import torch
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+
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+ base = "unsloth/Qwen3-4B-Instruct-2507"
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+ adapter = "your_id/your-repo"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(base)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ base,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+ model = PeftModel.from_pretrained(model, adapter)
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+ ```
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+
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+ ## Sources & Terms (IMPORTANT)
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+
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+ Training data: u-10bei/structured_data_with_cot_dataset_512_v2
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+
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+ Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License.
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+ Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.
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