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Awesome GitHub RepositoriesAdaptive Schedulers
Schedulers that react to training metrics to adjust learning rates dynamically.
Distinguishing note: Focuses on metric-based feedback loops rather than fixed schedule patterns.
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Awesome Adaptive Schedulers GitHub Repositories
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- huggingface/pytorch-image-models
huggingface/pytorch-image-models
36,386View on GitHubThis project is a comprehensive library of state-of-the-art neural network architectures designed for image classification and feature extraction. It provides a complete deep learning training framework that supports distributed execution, allowing users to build, train, and fine-tune vision models using optimized schedulers and pre-configured training recipes. The library distinguishes itself through a modular backbone architecture that treats neural networks as decoupled feature extractors, enabling the retrieval of multi-scale outputs for downstream tasks like object detection and segmenta
Plateau learning rate scheduling reduces the learning rate when monitored metrics stop improving to stabilize the training process.
Pythonaugmixconvnextdistributed-training
