The method for generating negative samples #14
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Compared to "making random negative samples", maybe it's better to have the model learn about "if it's 1, then it can't be 0, 2, 3, 4, etc.".
I changed the method for generating negative samples. And it did work, with an improvement of 3.5% on the test dataset.
But since this will lead the size to 10x compared with the original train dataset. And my GPU can't handle the whole dataset trained at once, so I added batch training as commented codes in the main().