---
base_model: Qwen/Qwen2.5-7B-Instruct
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- lora
- agent
- tool-use
- alfworld
- dbbench
---

# qwen25-7b-agent-exp02-C_alfv3_dbv4

This model is a fine-tuned version of **Qwen/Qwen2.5-7B-Instruct** using **LoRA + Unsloth**.

This repository contains the **full merged weights**.
No adapter loading is required.

## Training Objective

This adapter is trained to improve **multi-turn agent task performance**
on ALFWorld (household tasks) and DBBench (database operations).

Loss is applied to **all assistant turns** in the multi-turn trajectory.

## Training Configuration

- Base model: Qwen/Qwen2.5-7B-Instruct
- Data sources: ../../03_data/prepared/alfworld_v3_fixed, ../../03_data/prepared/dbbench_v4
- Method: LoRA (Unsloth)
- Max sequence length: 2048
- Epochs: 2
- Learning rate: 2e-06
- LoRA: r=64, alpha=128

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "curio184/qwen25-7b-agent-exp02-C_alfv3_dbv4"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
```

## Sources & Terms (IMPORTANT)

Training data: ../../03_data/prepared/alfworld_v3_fixed, ../../03_data/prepared/dbbench_v4

Dataset License: MIT License.
Compliance: Users must comply with the MIT license and the base model's original terms of use.
