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You-En/NYCU-IAlI-DL2026-LLM1-SFT_on_Answer-Only_Data

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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:

text
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.