training updates
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train.py
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train.py
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@ -209,7 +209,7 @@ def train():
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# Start training
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# Start training
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nb = len(dataloader) # number of batches
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nb = len(dataloader) # number of batches
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n_burn = max(3 * nb, 500) # burn-in iterations, max(3 epochs, 300 iterations)
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n_burn = max(3 * nb, 500) # burn-in iterations, max(3 epochs, 500 iterations)
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maps = np.zeros(nc) # mAP per class
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maps = np.zeros(nc) # mAP per class
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# torch.autograd.set_detect_anomaly(True)
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# torch.autograd.set_detect_anomaly(True)
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results = (0, 0, 0, 0, 0, 0, 0) # 'P', 'R', 'mAP', 'F1', 'val GIoU', 'val Objectness', 'val Classification'
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results = (0, 0, 0, 0, 0, 0, 0) # 'P', 'R', 'mAP', 'F1', 'val GIoU', 'val Objectness', 'val Classification'
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