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google / uis-rnn

This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
https://arxiv.org/abs/1810.04719
Apache License 2.0
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I run the demo use toy data, found loss is negative number. #69

Closed Naminwang closed 4 years ago

Naminwang commented 4 years ago

Describe the question

I run the demo use toy data, found loss is negative number. Is that something wrong, or it is normal.

My background

Have I read the README.md file?

Have I searched for similar questions from closed issues?

Have I tried to find the answers in the paper Fully Supervised Speaker Diarization?

Have I tried to find the answers in the reference Speaker Diarization with LSTM?

Have I tried to find the answers in the reference Generalized End-to-End Loss for Speaker Verification?

wq2012 commented 4 years ago

Yes, loss is negative.