---
base_model: Qwen/Qwen3-4B-Instruct-2507
datasets:
- u-10bei/sft_alfworld_trajectory_dataset_v5
language:
- en
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- agentbench
- merged-model
- alfworld
- strict-action-copy
---

# qwen3-4b-instruct-2507-sft-v1

This repository provides a merged full model produced by supervised fine-tuning for ALFWorld-oriented action selection.

## Training Objective

Improve strict action selection reliability for ALFWorld-style prompts where the model must output one exact action line from `AVAILABLE ACTIONS`.

## Training Configuration

- Method: SFT (Unsloth LoRA) + merge to full model
- Base model ID: `Qwen/Qwen3-4B-Instruct-2507`
- LoRA: `r=16`, `alpha=32`, `dropout=0.05`
- LoRA target modules: `q_proj,k_proj,v_proj,o_proj,gate_proj,up_proj,down_proj`
- Max sequence length: `4096`
- Max steps: `350`
- Epochs: `1`
- Learning rate: `1.0e-6`
- Per-device train batch size: `1`
- Per-device eval batch size: `2`
- Gradient accumulation steps: `32`
- Effective global batch size: `32`
- Warmup ratio: `0.03`
- Weight decay: `0.01`
- Eval/Save steps: `50 / 50`

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "uchkw/qwen3-4b-instruct-2507-sft-v1"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
```

## Training Data / Sources & License (IMPORTANT)

- Primary source dataset:
  - `u-10bei/sft_alfworld_trajectory_dataset_v5`
- Data construction policy:
  - Converted trajectories into strict chat-style supervision with one-line action targets (`ACTION: ...`).
  - Trained with exact action matching against candidate action lists to improve action validity.
  - Added synthetic correction-style augmentation for common formatting and target-selection errors.
- Dataset scale (used for this merged model):
  - Train samples: `35950`
  - Validation samples: `1892`
  - Action coverage was balanced to avoid over-concentration on a few verbs.
- Sequence-length check:
  - No truncation observed at `max_seq_length=4096`.
- Compliance:
  - Follow the source dataset license on each dataset card.
  - Follow base model terms of use.