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auc images
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@ -6,5 +6,5 @@ AUC results for different epochs could be found at <https://huggingface.co/GuoLi
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E.g. for epoch 15 and avg 1, result log file is: <https://huggingface.co/GuoLiyong/himia_ctc_tdnn_baseline/blob/main/exp_max_duration_100/post/epoch_15-avg_1/log/log-auc-himia_aishell-2023-03-16-17-42-14>
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Corresponding ROC curve is: <https://huggingface.co/GuoLiyong/himia_ctc_tdnn_baseline/blob/main/exp_max_duration_100/post/epoch_15-avg_1/himia_aishell.pdf>
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Corresponding ROC curve is: <https://huggingface.co/GuoLiyong/himia_ctc_tdnn_baseline/blob/main/exp_max_duration_100/post/epoch_15-avg_1/himia_aishell.png>
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@ -10,8 +10,7 @@ Here is the result for epoch_15-avg_1(with the highest AUC).
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| ---- | ---- | ----|
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| AUC | 0.9597 |0.9292|
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HiMia-CW
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HiMia-Aishell
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@ -124,7 +124,7 @@ def main():
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output_path = Path(args.positive_score_file).parent
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logging.info(f"AUC of {args.legend} {output_path}: {roc_auc}")
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plt.savefig(f"{output_path}/{args.legend}.pdf", bbox_inches="tight")
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plt.savefig(f"{output_path}/{args.legend}.png", bbox_inches="tight")
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if __name__ == "__main__":
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