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README.md

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@@ -18,7 +18,7 @@ The final private LB score 0.892 was achieved by post processing on the model's
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* single [UNet](https://arxiv.org/abs/1505.04597) model with a [Squeeze-and-Excitation network](https://arxiv.org/abs/1709.01507) encoder
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* no ensembling, no pseudo labeling
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* [object context](https://arxiv.org/abs/1809.00916) in the decoders and in the base
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* symmetric extension of the [Lovasz hinge loss](https://arxiv.org/abs/1705.08790) function (+0.02 private LB):
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* symmetric extension of the [Lovasz hinge loss](https://arxiv.org/abs/1705.08790) function (+0.02 private LB improvement):
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```python
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def symmetric_lovasz(outputs, targets):
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return (lovasz_hinge(outputs, targets) + lovasz_hinge(-outputs, 1 - targets)) / 2

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