Leavingseason
deepFM issue with ml-1m dataset
Hi, I met with a strange problem while training deepFM model using ml-1m dataset: if enabling "is_use_fm_part" flag to True, the training process won't converge and the rmse value will become bigger and bigger(and the loss does decrease!). But if switching the flag off, just using dnn only, it seems ok. I only change the deepFM.py a little: For comparing the predicted rating with the GT value, I removed the softmax activation function for the last layer, and then output rmse error instead of auc.
i am not sure if you can receive this message, but i am on a travel to Melbourne now, unfortunately no wifi access. I have to check the code next weekend when i return China
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在 2017年8月17日，02:23，xray1111 <[email protected]mailto:[email protected]> 写道：
Hi, I met with a strange problem while training deepFM model using ml-1m dataset: if enabling "is_use_fm_part" flag to True, the training process won't converge and the loss will become bigger and bigger. But if switching the flag off, just using dnn only, it seems ok. I only change the deepFM.py a little: For comparing the predicted rating with the GT value, I removed the softmax activation function for the last layer, and then output rmse error instead of auc.
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@Leavingseason Sorry for late response, that problem may caused by a wrong when calcuating RMSE, I changed the code then it's fine. Thanks!
Hi @xray1111 , could you share the code to run the deepFM with ml-1m dataset. I am a unclear on how to create the values. Or a description about the S1_4 dataset would be great
