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Model: koguma-ai/dbbench-combined-baseline0301
Source: Original Platform

README.md

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+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+datasets:
+- u-10bei/dbbench_sft_dataset_react
+- u-10bei/dbbench_sft_dataset_react_v2
+- u-10bei/dbbench_sft_dataset_react_v3
+- u-10bei/dbbench_sft_dataset_react_v4
+language:
+- en
+license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- sft
+- agent
+- tool-use
+- dbbench
+- text-to-sql
+---
+
+# Qwen2.5-7B DB Bench Combined SFT (v1-v4)
+
+This repository provides a **merged full-weight model** fine-tuned from
+**Qwen2.5-7B-Instruct** using **LoRA + Unsloth**, then merged to 16bit.
+
+## Training Objective
+
+This model is trained to improve **DB Bench (database operation) performance**
+on the AgentBench evaluation benchmark. ALFWorld performance relies entirely
+on the base model's inherent capability (no ALFWorld training data used).
+
+Loss is applied to **all assistant turns** in the multi-turn trajectory,
+enabling the model to learn SQL generation, action selection, and error recovery.
+
+## Training Data
+
+- DB Bench v1 (u-10bei/dbbench_sft_dataset_react): ~750 samples
+- DB Bench v2 (u-10bei/dbbench_sft_dataset_react_v2): ~750 samples
+- DB Bench v3 (u-10bei/dbbench_sft_dataset_react_v3): ~750 samples
+- DB Bench v4 (u-10bei/dbbench_sft_dataset_react_v4): ~750 samples
+- Total: ~3,000 samples
+- **ALFWorld data intentionally excluded** to preserve base model performance
+
+## Training Configuration
+
+- Base model: Qwen/Qwen2.5-7B-Instruct
+- Method: LoRA → merged to 16bit
+- Max sequence length: 2048
+- Epochs: 2
+- Learning rate: 2e-6
+- LoRA: r=64, alpha=128
+- Batch size: 2, Gradient accumulation: 4 (effective batch 8)
+- Optimizer: AdamW (cosine scheduler)
+- Framework: Unsloth
+
+
+## Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "koguma-ai/dbbench-combined-baseline0301"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+```
+
+## Sources & Terms
+
+Training data: u-10bei/dbbench_sft_dataset_react (v1-v4)
+
+Dataset License: Apache-2.0. Users must comply with the Apache-2.0 license
+and the base model's original terms of use.
+
+## Limitations
+
+- Optimized for DB Bench tasks only
+- ALFWorld performance relies on base model capability
+- Weak categories: aggregation-MAX (16.7%), INSERT (33.3%)