fixed epoch for cancel pts
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@ -68,10 +68,9 @@ def train(model, optimizer, scheduler, loss_func, train_loader: DataLoader, st:
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else: end='\n'
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print(f"Training:", epoch_tracker.get_epoch_summary_str(), end=end)
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# cancel training if model is not good enough
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if len(training_cancel_points) > 0 and ep == training_cancel_points[0][0]:
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print(f"Checking training cancel point: epoch={ep}, point={training_cancel_points[0]}, accuracy={epoch_tracker.accuracies[-1]}")
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if len(training_cancel_points) > 0 and ep+1 == training_cancel_points[0][0]:
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if epoch_tracker.accuracies[-1] < training_cancel_points[0][1]:
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print(f"Training cancelled because the models accuracy={epoch_tracker.accuracies[-1]:.2f} < {training_cancel_points[0][1]} after {ep} epochs.")
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print(f"Training cancelled because the models accuracy={epoch_tracker.accuracies[-1]:.2f} < {training_cancel_points[0][1]} after {ep+1} epochs.")
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break;
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training_cancel_points.pop(0)
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