kochan13/lora_agentbench_qwen2.5_7b_26030106_16bit

qwen2.5-7b-agent-trajectory-lora_26030106

This repository provides a model fine-tuned from Qwen/Qwen2.5-7B-Instruct using LoRA + Unsloth.

The LoRA weights have been merged into the base model and exported as a standalone model for inference.

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, enabling the model to learn environment observation, action selection, tool use, and recovery from errors.

Training Configuration

• Base model: Qwen/Qwen2.5-7B-Instruct
• Method: LoRA (full precision base)
• Max sequence length: 2048
• Epochs: 1
• Learning rate: 1.7e-06
• LoRA: r=64, alpha=128

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "kochan13/lora_agentbench_qwen2.5_7b_26030106_16bit"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto",
)

Sources & Terms (IMPORTANT)

Training data: kochan13/mixed-agent-dataset-merged-clean-dedup-dbweak_2x_2

Dataset License: MIT License. This dataset is used and distributed under the terms of the MIT License. Compliance: Users must comply with the MIT license (including copyright notice) and the base model's original terms of use.