Ultralytics Files

🌟 Summary

Ultralytics v8.4.30 is a focused stability release that fixes and hardens training resume behavior, making interrupted training runs much more reliable 🔄✅.

📊 Key Changes

• Main update (PR [#24027] by @glenn-jocher): Refactored resume logic in trainer.py to correctly restore training arguments from last.pt earlier in the resume flow.
• Better checkpoint arg handling: Resume now loads checkpoint config immediately and rebuilds runtime args from it more consistently.
• Safer dataset fallback: If the dataset path stored in a checkpoint is invalid, Ultralytics now falls back to the current data argument instead of failing unexpectedly.
• Override support preserved: Users can still override practical resume-time settings like imgsz, batch, device, workers, cache, freeze, val, and plots (plus related options).
• Clear augmentation warning retained: If custom Albumentations were used before, a warning reminds users to pass augmentations again when resuming, since they can’t be auto-restored exactly.
• Version bump: Package updated from 8.4.29 ➜ 8.4.30.

🎯 Purpose & Impact

• Purpose: Fix failing resume scenarios and make checkpoint restoration more robust after interruptions/crashes. 🛠️
• For users training large models: Fewer resume-related surprises, especially in long-running jobs on cloud/GPU servers. 🚀
• For teams/pipelines: More predictable restart behavior in automated training workflows (CI/CD, scheduled jobs, preemptible instances). 🤖
• No new model architecture/features in this tag: This release is about reliability and continuity, not new YOLO model capabilities. 📌

What's Changed

• ultralytics 8.4.30 Fix training resume by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/24027

Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.29...v8.4.30