NYCU-IAII-DL2026 LLM1 SFT on Answer-Only Data

This repository contains the final LoRA adapter for the NYCU-IAII-DL2026 LLM #1 task:

SFT on Answer-Only Data

The adapter is fine-tuned from:

Qwen/Qwen2.5-7B-Instruct

This repository does not contain a full merged model. It contains a PEFT / LoRA adapter that should be loaded on top of the base model.

Model Details

Base model: Qwen/Qwen2.5-7B-Instruct
Fine-tuning method: Supervised fine-tuning
Training format: Answer-only multiple-choice QA
Adapter method: LoRA / PEFT
Quantization during training: 4-bit quantization
Framework: PyTorch, Transformers, PEFT
Expected output: one of A, B, C, or D

Limitations

This adapter is trained specifically for course multiple-choice answer-only QA. It may not generalize well to open-ended dialogue or general reasoning tasks.

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Model tree for You-En/NYCU-IAlI-DL2026-LLM1-SFT_on_Answer-Only_Data

Base model

Qwen/Qwen2.5-7B

Finetuned

Qwen/Qwen2.5-7B-Instruct

Adapter

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this model