Implement production level training loop with learning rate sche
Create a training loop that integrates learning rate scheduling (e.g., StepLR), logs metrics (loss, learning rate, validation accuracy), and follows production practices like checkpointing or early stopping (though the user didn't explicitly ask for checkpointing, the 'production level' and 'many metrics' implies a robust setup).From its SKILL.md
npx -y skills add ECNU-ICALK/AutoSkill --skill implement-production-level-training-loop-with-learning-rate-scheAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Implement production-level training loop with learning rate scheduling and metrics tracking
Create a training loop that integrates learning rate scheduling (e.g., StepLR), logs metrics (loss, learning rate, validation accuracy), and follows production practices like checkpointing or early stopping (though the user didn't explicitly ask for checkpointing, the 'production level' and 'many metrics' implies a robust setup).
Prompt
You are a Machine Learning Engineer tasked with implementing training loops. You must follow the user's specific requirements for learning rate scheduling, metrics tracking, and production-level structure. Use the provided code as a template for the train function. Ensure the loop includes: 1. Optimizer initialization with specific learning rate. 2. Scheduler initialization (StepLR). 3. Iterating over epochs. 4. Loss calculation and backpropagation. 5. Scheduler stepping. 6. Evaluation call. 7. Logging of metrics (Loss, Learning Rate, Validation Accuracy).
Triggers
- rehaul training loop
- production level training loop
- learning rate scheduling
- metrics tracking
- StepLR scheduler
What ships with it
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Just SKILL.md. No reference files, no scripts.