57 lines
1.9 KiB
Markdown
57 lines
1.9 KiB
Markdown
---
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language:
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- ja
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- en
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license: apache-2.0
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base_model: Qwen/Qwen2.5-7B-Instruct
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tags:
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- text-generation
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- agent
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- sql
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- alfworld
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- dbagent
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---
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# matsuo-llm-advanced-phase-f2a
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Fine-tuned from Qwen/Qwen2.5-7B-Instruct for agent tasks.
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## Training Configuration
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- LoRA: r=8, alpha=16 (Phase D identical)
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- lr: 1e-5, epochs: 0.3, batch: 4x4=16
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- Data: Spider/BIRD 2100 (60%) + Distilled 72B 500 (14%) + DBBench v4 700 (20%) + ALFWorld 200 (6%), 3500 samples
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## Data Composition
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- Spider/BIRD: 2100 samples (60%) - reduced from Phase D to accommodate distilled data
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- Distilled 72B: 500 samples (14%) - NEW: multi-turn DB conversations generated by Qwen2.5-72B-Instruct-AWQ
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- Generated from Spider/BIRD table schemas (not from AgentBench data)
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- Weak category emphasis (AGG-MAX, COUNT, INSERT, AGG-SUM)
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- Filtered by regex/sqlparse only (no LLM quality filtering)
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- DBBench v4: 700 samples (20%) - same as Phase D
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- ALFWorld v5: 200 samples (6%) - reduced from Phase D
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## Datasets
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- `u-10bei/dbbench_sft_dataset_react_v4` — Listed in the organizer-shared Phase B dataset list.
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Used as provided (no modification). Third-party synthetic SFT for DBBench format alignment;
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all tables, data, and queries are independently generated
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(per dataset description: "to avoid test data leakage").
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- `xlangai/spider` — CC BY-SA 4.0 (Yale/Columbia Spider project)
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- `birdsql/bird_mini_dev` — CC BY-SA 4.0 (HKU)
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- Official Phase B ALFWorld v5 dataset — Organizer-provided, used as provided.
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- Synthetic multi-turn data generated by Qwen2.5-72B-Instruct-AWQ (whitelisted model)
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## Compliance
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- Evaluation data not used in training: No analysis of evaluation test data was conducted.
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- LLM was not used for data quality filtering or selection.
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- Distilled data generated from whitelisted model (Qwen2.5-72B-Instruct-AWQ) using Spider/BIRD schemas only.
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- Filtering is regex/sqlparse only (non-LLM).
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- Inference code not modified.
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## Usage
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Compatible with vLLM v0.13.0+.
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