01Automated training configuration and hyperparameter optimization
02Framework-agnostic support for PyTorch, HuggingFace, and JAX
03Comprehensive post-training performance reports and recommendations
04Real-time anomaly detection for loss spikes and gradient norms
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06Mandatory logging integration with W&B, TensorBoard, or CSV