metadata
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- u-10bei/sft_alfworld_trajectory_dataset_v5
language:
- en
license: apache-2.0
library_name: peft
pipeline_tag: text-generation
tags:
- lora
- agent
- tool-use
- alfworld
- dbbench
exp001_baseline
This repository provides a merged model fine-tuned from Qwen/Qwen3-4B-Instruct-2507 using LoRA + Unsloth.
Training Objective
This model 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, enabling the model to learn environment observation, action selection, tool use, and recovery from errors.
Training Configuration
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Method: LoRA (full precision base)
- Max sequence length: 2048
- Epochs: 2
- Learning rate: 2e-06
- LoRA: r=64, alpha=128
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
model_id = "ekunish/exp001_baseline"
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/sft_alfworld_trajectory_dataset_v5
Dataset License: MIT License. Compliance: Users must comply with the MIT license and the base model's original terms of use.