Very different loss on validation

[kamilkk852]

Just for testing I'm trying to overfit a very small dataset and I've set validation dataset to be the same as the training one, but I get very different loss progression for these stages. On training set it is constantly decreasing, but on validation after a few epochs it starts to increase. I do not use dropout. Shouldn't it be roughly the same?

[Alexander-H-Liu]

Hi @kamilkk852

In my experience, validation loss typically start growing within a short period. You should evaluate your model base on validation error rate instead. Also, using A LOT of data for training is one nature of end-to-end ASRs, they usually performed poorly on small corpus.