Cover Image

Early-stopping for Transformer model training

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Jing, Jiang, Hua, Li, Cheng, Xin, Siqian, Yang, Shuzhen
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Why pre-training is beneficial for downstream classification tasks?
by: Jiang, Xin, et al.
Published: (2024)

Graph Generative Pre-trained Transformer
by: Chen, Xiaohui, et al.
Published: (2025)

The Scaling Law for LoRA Base on Mutual Information Upper Bound
by: Zhang, Jing, et al.
Published: (2025)

GraphGPT: Generative Pre-trained Graph Eulerian Transformer
by: Zhao, Qifang, et al.
Published: (2023)

SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression
by: Zhang, Jing, et al.
Published: (2024)

Early stopping by correlating online indicators in neural networks
by: Ferro, Manuel Vilares, et al.
Published: (2024)

TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)

Constrained multi-fidelity Bayesian optimization with automatic stop condition
by: Foumani, Zahra Zanjani, et al.
Published: (2025)

Transformer in Touch: A Survey
by: Gao, Jing, et al.
Published: (2024)

xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein
by: Chen, Bo, et al.
Published: (2024)

TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer
by: Wang, Jiawei, et al.
Published: (2026)

A Pre-trained Reaction Embedding Descriptor Capturing Bond Transformation Patterns
by: Liu, Weiqi, et al.
Published: (2026)

Enhancing robustness of data-driven SHM models: adversarial training with circle loss
by: Yang, Xiangli, et al.
Published: (2024)

Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
by: Apicella, Andrea, et al.
Published: (2026)

Cross-domain Random Pre-training with Prototypes for Reinforcement Learning
by: Liu, Xin, et al.
Published: (2023)

LENS: Large Pre-trained Transformer for Exploring Financial Time Series Regularities
by: Xu, Yuanjian, et al.
Published: (2024)

PrefixGPT: Prefix Adder Optimization by a Generative Pre-trained Transformer
by: Ding, Ruogu, et al.
Published: (2025)

MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts
by: Lin, Xi Victoria, et al.
Published: (2024)

Physics-Guided Tiny-Mamba Transformer for Reliability-Aware Early Fault Warning
by: Li, Changyu, et al.
Published: (2026)

Priming: Hybrid State Space Models From Pre-trained Transformers
by: Chattopadhyay, Aditya, et al.
Published: (2026)

Self-Improving Pretraining: using post-trained models to pretrain better models
by: Tan, Ellen Xiaoqing, et al.
Published: (2026)

On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
by: Liu, Renpu, et al.
Published: (2024)

Layer Specialization Underlying Compositional Reasoning in Transformers
by: Liu, Jing
Published: (2025)

Graph Tokenization for Bridging Graphs and Transformers
by: Guo, Zeyuan, et al.
Published: (2026)

Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla Transformers
by: Cheng, Xin, et al.
Published: (2024)

Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning
by: Song, Ziyang, et al.
Published: (2024)

Are Transformers More Robust? Towards Exact Robustness Verification for Transformers
by: Liao, Brian Hsuan-Cheng, et al.
Published: (2022)

Heterogeneous Graph Pre-training Based Model for Secure and Efficient Prediction of Default Risk Propagation among Bond Issuers
by: Li, Xurui, et al.
Published: (2025)

Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
by: Wu, Yulun, et al.
Published: (2025)

Causal prompting model-based offline reinforcement learning
by: Yu, Xuehui, et al.
Published: (2024)

Task-Agnostic Pre-training and Task-Guided Fine-tuning for Versatile Diffusion Planner
by: Fan, Chenyou, et al.
Published: (2024)

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
by: He, Bowen, et al.
Published: (2026)

Traj-Transformer: Diffusion Models with Transformer for GPS Trajectory Generation
by: Zhang, Zhiyang, et al.
Published: (2025)

Pre-trained Language Models Improve the Few-shot Prompt Ability of Decision Transformer
by: Yang, Yu, et al.
Published: (2024)

Transformers trained on proteins can learn to attend to Euclidean distance
by: Ellmen, Isaac, et al.
Published: (2025)

Reinforcement Learning With Sparse-Executing Actions via Sparsity Regularization
by: Pang, Jing-Cheng, et al.
Published: (2021)

pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation
by: Zhao, Jiale, et al.
Published: (2025)

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
by: Fan, Tianyu, et al.
Published: (2024)

TripCast: Pre-training of Masked 2D Transformers for Trip Time Series Forecasting
by: Liao, Yuhua, et al.
Published: (2024)

Graph VQ-Transformer (GVT): Fast and Accurate Molecular Generation via High-Fidelity Discrete Latents
by: Zheng, Haozhuo, et al.
Published: (2025)