hppRC/llm-lora-classification
LLMとLoRAを用いたテキスト分類
Implements LoRA-based fine-tuning for Japanese LLMs on text classification by leveraging the final token embedding (rather than `[CLS]`) as the classification representation, accounting for unidirectional model architecture. Integrates with Hugging Face's `transformers` and `PEFT` libraries, evaluated on 7 Japanese LLM variants (rinna, CyberAgent) with systematic hyperparameter exploration across learning rates and input templates. Achieves 97.75% F1 on 9-class livedoor news classification, outperforming comparable BERT baselines despite using comparable model scales.
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98
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Language
Python
License
MIT
Category
Last pushed
Jul 22, 2023
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