EarlyStopper updates

[glenn-jocher]

Updates to EarlyStopping PR #4576 to address concerns in #4653:

• Default increased from 30 epochs to 100 epochs to minimize impact to existing workflows.
• Added stopper.possible_stop attribute to indicate possibility of stop next epoch, utilized to create plots and save checkpoints in case epoch is actually final epoch: final_epoch = (epoch + 1 == epochs) or stopper.possible_stop
• Fixed Multi-GPU bug (EarlyStopping completely disabled in Multi-GPU now, existing TODO inlined in README).

🛠️ PR Summary

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🌟 Summary

Improving early stopping logic in YOLOv5 training.

📊 Key Changes

• Modified the final epoch check to consider a possible stop signal from the EarlyStopping class.
• Refined the early stopping check to apply only to single-GPU training (RANK == -1 condition).
• Increased the default early stopping patience from 30 to 100 epochs.
• Added a possible_stop attribute to the EarlyStopping class for better anticipation of training completion.

🎯 Purpose & Impact

• 🎯 Purpose: To provide a more robust and clear early stopping mechanism, allowing training to stop earlier when no improvements are observed, and to help users anticipate the end of training.
• 🎉 Impact: Users benefit from faster training times when no further improvements are made, potentially saving resources. The clarity in training stopping conditions can also help in better managing long training sessions.