Default --data imagenette160 training (fastest)
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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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* Default --data `imagenette160` training (fastest) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update train.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update train.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update train.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Signed-off-by: Glenn Jocher glenn.jocher@ultralytics.com
🛠️ PR Summary
Made with ❤️ by Ultralytics Actions
🌟 Summary
Adjustment of default dataset and clarification on epoch argument in training scripts. 🎛️
📊 Key Changes
classify/train.pyfromcifar100toimagenette160.epochsargument in bothclassify/train.pyandtrain.pyto indicate it specifies the total training epochs.🎯 Purpose & Impact
epochsargument improves usability by making it clear to users what this parameter controls, potentially reducing confusion and errors when configuring training sessions.