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View Code? Open in Web Editor NEW[IJCAI 2024] EAT: Self-Supervised Pre-Training with Efficient Audio Transformer
License: MIT License
[IJCAI 2024] EAT: Self-Supervised Pre-Training with Efficient Audio Transformer
License: MIT License
Hi! Thanks for your great work!
I wonder when the pre-training and fine-tuning code will be available.
Hi, Great work! I pre-trained the network using the provided script with the full AudioSet (unbalanced + balanced), similar to BEATs and AudioMAE. So my pre-training set is slightly larger than yours (1.93M samples). I trained for 10 epochs (40K updates) using the provided script. However, I am unable to reproduce the reported AS20K performance, achieving only around 35.8 mAP compared to the reported 40.2 mAP. I fine-tuned on AS20K using the shared pre-trained weights(EAT-base_epoch10.pt) and achieved the reported performance, so I don't think there is an issue with the dataset. Am I missing something here?
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