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你好,我用开源的SpatialNet和OSpatialNet分别训练了语音分离的模型,SpatialNet的表现确实非常惊艳,但是OSpatialNet出现训练时loss下降的比较正常,但是测试集中得到的结果非常差。猜测可能是出现过拟合的问题?
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您好,感谢关注我们的工作。对于oSpatialNet,我们主要遇到的主要问题是长度外推问题。泛化问题我们没有遇到,您这个是不是泛化问题需要进一步研究、分析
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好的,我再去研究研究
好吧,其实并不是过拟合的问题,而是训练和推理时模型的超参数不匹配导致的。训练时采用的MultiheadAttention的num_heads为4,而推理时采用的num_heads却是2,从而导致的推理结果差。。。
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你好,我用开源的SpatialNet和OSpatialNet分别训练了语音分离的模型,SpatialNet的表现确实非常惊艳,但是OSpatialNet出现训练时loss下降的比较正常,但是测试集中得到的结果非常差。猜测可能是出现过拟合的问题?
The text was updated successfully, but these errors were encountered: