Error prevention programs
针对典型问题的防范措施：
- 梯度异常检测::
- exist
trainer.pyset up ingradient_norm_threshold: 1.0 - 启用自动缩放：
--auto-scale-lr - control
gradient_health_check.loglog file
- exist
- hardware compatibility::
- (of a computer) run
./scripts/hardware_check.shVerification Environment - 避免混用不同架构GPU
- NVLink连接优先于PCIe
- (of a computer) run
- 超参数验证::
- utilization
validate_config.py检查参数合理性 - 关键参数警戒值：
- 学习率＞0.001会触发警告
- batch_size超过VRAM80%自动调整
- utilization
故障恢复机制
内置的防护措施：
- 每1000steps自动保存checkpoint
- 异常中断后可通过
--resume-fromresumption - 内存溢出时自动激活gradient checkpointing
This answer comes from the articleOpen-Reasoner-Zero: Open Source Large-Scale Reasoning Reinforcement Learning Training PlatformThe
May not be reproduced without permission:AI productivity tools " 怎样避免强化学习训练中的常见错误配置？
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