---
base_model: Qwen/Qwen2.5-7B-Instruct
datasets:
- Yano/exp-0223-027-realobs-llmagent-alfworld-data
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- qlora
- lora
- merged
- alfworld
- agent
- realobs-llmagent
---

# exp-0223-027-realobs-llmagent-qwen2.5-7b

Fine-tuned from **Qwen/Qwen2.5-7B-Instruct** using **QLoRA (4-bit, Unsloth)**.

## Purpose

ALFWorld SFT combining real environment observations from experiment 016
with LLM-renarrated agent responses (strategic THOUGHTs + ACTION-dominant format).

## Key Design
- Environment responses (user): Real data from 016 (byte-exact preservation)
- Agent responses (assistant): LLM-renarrated (strategic THOUGHT, not template)
- Format: First turn THOUGHT+ACTION, subsequent ACTION-only, recovery THOUGHT after failures
- Failure patterns: Naturally inherited from 016's 72% failure-containing trajectories

## Training Configuration

- Base model: Qwen/Qwen2.5-7B-Instruct
- Method: QLoRA (4-bit), merged to 16-bit
- Max sequence length: 2048
- Epochs: 3
- Learning rate: 2e-05
- LoRA: r=64, alpha=128
- Collator: AllAssistantTurnsCollator (all turns supervised)