67 lines
1.9 KiB
Markdown
67 lines
1.9 KiB
Markdown
---
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base_model: Qwen/Qwen3-4B-Instruct-2507
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datasets:
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- u-10bei/sft_alfworld_trajectory_dataset_v5
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- u-10bei/sft_alfworld_trajectory_dataset_v4
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- u-10bei/dbbench_sft_dataset_react_v4
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- u-10bei/dbbench_sft_dataset_react_v3
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- agent
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- tool-use
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- alfworld
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- dbbench
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---
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# qwen3-4b-agent-full-v3
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This repository provides a **fully fine-tuned model** based on
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**Qwen/Qwen3-4B-Instruct-2507**.
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Because this model underwent full parameter fine-tuning, this repository contains the **full model weights**.
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You can load it directly without needing to merge it with the base model.
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## Training Objective
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This model is trained to improve **multi-turn agent task performance**
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on ALFWorld (household tasks) and DBBench (database operations).
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Loss is applied to **all assistant turns** in the multi-turn trajectory,
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enabling the model to learn environment observation, action selection,
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tool use, and recovery from errors.
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## Training Configuration
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- Base model: Qwen/Qwen3-4B-Instruct-2507
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- Method: full
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- Max sequence length: 4096
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- Epochs: 2
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- Learning rate: 2e-06
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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base = "Qwen/Qwen3-4B-Instruct-2507"
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tokenizer = AutoTokenizer.from_pretrained(base)
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model = AutoModelForCausalLM.from_pretrained(
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base,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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```
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## Sources & Terms (IMPORTANT)
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Training data: u-10bei/sft_alfworld_trajectory_dataset_v4, u-10bei/sft_alfworld_trajectory_dataset_v5, u-10bei/dbbench_sft_dataset_react_v4, u-10bei/dbbench_sft_dataset_react_v3
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Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License.
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Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.
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