Megvii-BaseDetection / Megvii-BaseDetection/YOLOX
What should I do for this kind of training curve?
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Description
How to improve the training? My training dataset contains 16000 images and my model is yolox-s. The current training settings are:
--------------- transform config -----------------
self.mosaic_prob = 1.0
self.mixup_prob = 1.0
self.hsv_prob = 1.0
self.flip_prob = 0.5
self.degrees = 10.0
self.translate = 0.1
self.mosaic_scale = (0.1, 2)
self.mixup_scale = (0.5, 1.5)
self.shear = 2.0
self.enable_mixup = True
-------------- training config ---------------------
self.warmup_epochs = 5
self.max_epoch = 150
self.warmup_lr = 0
self.basic_lr_per_img = 0.01 / 64.0
self.scheduler = "yoloxwarmcos"
self.no_aug_epochs = 15
self.min_lr_ratio = 0.05
self.ema = True
self.weight_decay = 5e-4
self.momentum = 0.9
self.print_interval = 10
self.eval_interval = 10
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First steps
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Research direction
No repository file, test, or entry point is identified in the issue. Start by reviewing the reported training curve and the listed YOLOX-S transformation and training settings; the work is complete only when a specific, reproducible training improvement and its supporting evidence are established.
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Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100