---
license: apache-2.0
base_model: kmd2525/v8_stage2_yaml-merged
tags:
  - structured-output
  - xml
  - sft
  - sequential-format-learning
language:
  - en
  - ja
---

# v8_stage3_xml-merged

## Model Description

This model is **Stage 3** of the Sequential Format Learning (v8 strategy) for structured data output.

### Training Strategy

Based on Person U's approach that achieved 0.84 on the leaderboard:
- Train one format at a time
- Merge LoRA to base model after each stage
- Use merged model as the base for the next stage

### Stage 3 Focus: XML

- **Format**: XML (500 samples)
- **Goal**: 95%+ parse success rate for XML with proper & escaping
- **Base Model**: `kmd2525/v8_stage2_yaml-merged` (Stage 2 merged model)

### Previous Stages

- Stage 1: JSON/CSV (800 samples) → JSON 100%, CSV 100%
- Stage 2: YAML (500 samples) → YAML 100%

### Training Parameters

- MAX_SEQ_LEN: 1024
- EPOCHS: 2
- Learning Rate: 3e-05
- LoRA R: 64, Alpha: 128

### Sequential Format Learning Pipeline

```
Stage 1: JSON/CSV (800) ✅
    ↓
Stage 2: YAML (500) ✅
    ↓
Stage 3: XML (500) ← This model
    ↓
Stage 4: Mixed/TOML (1000)
    ↓
Final Model → LB 0.8+
```

### Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("kmd2525/v8_stage3_xml-merged")
tokenizer = AutoTokenizer.from_pretrained("kmd2525/v8_stage3_xml-merged")
```

### Next Stage

Use this model as the base for Stage 4 (Mixed/TOML final tuning):
```python
os.environ["SFT_BASE_MODEL"] = "kmd2525/v8_stage3_xml-merged"
```