chrisc36 / debias Goto Github PK

Hi,

I had a question regarding the PyTorch implementation of LearnedMixin.

def forward(self, hidden, logits, bias, labels):
    logits = logits.float()  # In case we were in fp16 mode
    logits = F.log_softmax(logits, 1)

    factor = self.bias_lin.forward(hidden)
    factor = factor.float()
    factor = F.softplus(factor)

    bias = bias * factor

    bias_lp = F.log_softmax(bias, 1)
    entropy = -(torch.exp(bias_lp) * bias_lp).sum(1).mean(0)

    loss = F.cross_entropy(logits + bias, labels) + self.penalty*entropy
    return loss

The forward function adds logits and bias variables, however, logits has been log-softmaxed whereas bias is not (bias seems to be raw logits from bias-only model). Should we really apply log-softmax to logits before sending into cross_entropy loss? Could you explain the reasoning behind this?

Thanks for a great repository!
The HANS download token seems to be broken. Can you please fix it?

This is the exception I'm getting:

requests.exceptions.HTTPError: 403 Client Error: Forbidden for url: https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FMNLI.zip?alt=media&token=50329ea1-e339-40e2-809c-10c40afff3ce