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For two-models ensemble, we train the same network twice and save them as two models (due to different random seed training results during training), and infers the similarity matrix between image and text (which will be saved in the evaluation.py file as .npy file), average the two matrices to get the final test similarity matrix.
Generally, the bert-based model is trained twice for ensemble; the gru-based model is trained twice for ensemble. These two are separate.
你好,我想请教论文表1中的Two-Models Ensemble这一实验,不是很能理解,想请教一下作者,是哪两种model进行ensemble呢,以及对于bert和gru又如何做不同的ensemble?
非常感谢!
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