tenyyprn
/

qwen3-4b-structeval-exp15

@@ -2,206 +2,113 @@
 base_model: Qwen/Qwen3-4B-Instruct-2507
 library_name: peft
 pipeline_tag: text-generation
 tags:
-- base_model:adapter:Qwen/Qwen3-4B-Instruct-2507
 - lora
 - transformers
 ---
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-### Framework versions
-- PEFT 0.18.1

 base_model: Qwen/Qwen3-4B-Instruct-2507
 library_name: peft
 pipeline_tag: text-generation
+language:
+- en
+- ja
 tags:
 - lora
 - transformers
+- structured-output
+- structeval
+- csv-fix
+license: apache-2.0
 ---
+# Qwen3-4B StructEval Exp15 (CSV Fix)
+Exp13 (SFT+DPO) をベースに、CSV変換の問題を修正するための特化LoRAアダプター。
+## Overview
+| Item | Detail |
+|------|--------|
+| Base Model | Qwen/Qwen3-4B-Instruct-2507 |
+| Parent Adapter | Exp13 (SFT + DPO, merged) |
+| Purpose | CSV出力の「starting with header row」誤解釈を修正 |
+| Method | Merged Exp13 + 追加LoRA fine-tuning |
 ## Training Details
+### Strategy
+- Exp13 DPOアダプターをベースモデルにマージ
+- マージ後のモデルに対して、CSV修正用の小規模LoRAを追加学習
+### Hyperparameters
+| Parameter | Value |
+|-----------|-------|
+| Learning Rate | 5e-5 |
+| Epochs | 15 |
+| Batch Size | 1 |
+| Gradient Accumulation | 1 |
+| LoRA r | 8 |
+| LoRA alpha | 16 |
+| LoRA dropout | 0.05 |
+| Target Modules | q/k/v/o_proj, gate/up/down_proj |
+| Precision | fp16 |
+| Max Sequence Length | 2048 |
+| Optimizer | AdamW |
+| Seed | 3407 |
+### Training Data
+- CSV修正用データセット（6サンプル）
+- 「starting with header row」を正しく解釈し、ヘッダー+データ行を出力する学習
+### Hardware
+- NVIDIA DGX Spark (GB10 Blackwell GPU)
+- CUDA 12.1
+## Inference
+### System Prompt
+```
+You are a structured data expert. Output the requested format directly without any explanation, preamble, or markdown code blocks. Do not write ```json, ```yaml, ```toml, ```xml, ```csv or similar. Output only the raw structured data.
+```
+### Settings
+| Parameter | Value |
+|-----------|-------|
+| Temperature | 1e-7 (near-greedy) |
+| Max New Tokens | 4096 |
+| do_sample | False |
+### Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+import torch
+base_model_id = "Qwen/Qwen3-4B-Instruct-2507"
+adapter_id = "tenyyprn/qwen3-4b-structeval-exp15"
+tokenizer = AutoTokenizer.from_pretrained(base_model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    base_model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+model = PeftModel.from_pretrained(model, adapter_id)
+model = model.merge_and_unload()
+model.eval()
+```
+## Results
+Ensemble (Exp13 + Exp15) の公式コンペスコア: **0.781733**
+### Exp15 単体ローカル評価
+| Format | Score |
+|--------|-------|
+| JSON | High |
+| YAML | High |
+| XML | High |
+| CSV | Improved (fix applied) |
+| TOML | Challenging |
+## Related Models
+- Base: [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
+- Parent (Exp13 DPO): SFT + DPO trained adapter (merged into this model)
+## License
+Apache 2.0 (following base model license)