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satyansh0/PEFT-Benchmarking-results

Reproducibility and Benchmarking of Parameter-Efficient Fine-Tuning Methods for Transformer Models A reproducible empirical benchmark of Full Fine-Tuning, LoRA, AdaLoRA, Prefix Tuning, and IA³ across BERT-base and DistilBERT on three GLUE classification tasks. While numerous PEFT methods have been proposed to reduce the cost of fine-tuning large transformer models, existing evaluations are often conducted under different experimental settings, making direct comparison… See the full description on the dataset page: https://huggingface.co/datasets/satyansh0/PEFT-Benchmarking-results.

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