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@@ -32,7 +32,7 @@ Please cite our paper and kindly give a star for this repository if you use this
## Reproduce & Peformance
* Due to the small number of dataset samples (especially SEM16), please tune the parameter of *--seed* for better performance.
* Due to the small number of dataset samples (especially SEM16), the performance gap between different seeds will vary greatly, please tune the parameter of *--seed* for better performance.
* We have provided checkpoints that are superior or equal to the performance reported in the paper.
* Please Run python files in [run_checkpoints](/run_checkpoints), you can use the trained model for prediction, and the model can be downloaded from [Google drives](https://drive.google.com/drive/folders/1W-UIVfHVgsLycTZdEIb4gNhGKCBW2wKo?usp=sharing).
* We also use 5 random seeds to run the code directly without any other tuning parameters. The performance is as follows:
