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On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines

, , and . Proceedings of the International Conference on Learning Representations, (2021)

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Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem., , and . CoRR, (2018)RobustBench: a standardized adversarial robustness benchmark., , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)SGD with Large Step Sizes Learns Sparse Features., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 903-925. PMLR, (2023)Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings., , , and . CoRR, (2023)Scaling Compute Is Not All You Need for Adversarial Robustness., , , , , and . CoRR, (2023)On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines., , and . ICLR, OpenReview.net, (2021)A Modern Look at the Relationship between Sharpness and Generalization., , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 840-902. PMLR, (2023)Square Attack: a query-efficient black-box adversarial attack via random search., , , and . CoRR, (2019)Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search., , , and . ECCV (23), volume 12368 of Lecture Notes in Computer Science, page 484-501. Springer, (2020)Why Do We Need Weight Decay in Modern Deep Learning?, , , and . CoRR, (2023)