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Implementation of RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

Python 93.62% Shell 2.96% Perl 3.42%

chit-chat dialogue evaluation metric ruber rnn word2vec

ruber-and-bert-ruber's Introduction

RUBER

Implementation of RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

Using pre-trained word2vec embeddings to initialize bidirectional RNN.

Performance:

RUBER (10 times avg):
Unrefer Avg pearson: 0.36928, Unrefer Avg spearman: 0.36722 RUBER Avg pearson: 0.29075, RUBER Avg spearman: 0.28677
BERT-RUBER (10 times avg): Unrefer Avg pearson: 0.42702, Unrefer Avg spearman: 0.43126 RUBER Avg pearson: 0.42218, RUBER Avg spearman: 0.42163

It should be noted that this repo is not finished, I will push a tutorial few days later.

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wise-east leishenvictoria tensixchuan

ruber-and-bert-ruber's Issues

FileNotFoundError: [Errno 2] No such file or directory: 'data/src-train.embed'

Looking forward to your reply.

the correlation coefficient is negative

Hi, thanks for your helpful repo.

When i try to reproduce the experiment results as you mentioned, something seems wrong. The acc of ruber-unrefer on the test set is about 0.6, but the correlation coefficient of ruber-unrefer scores and human scores is negative. And the acc of bert-ruber-unrefer on the tset set is about 0.84, but the correlation coefficient of bert-ruber-unrefer scores and human scores is also negative. (i checked human scores, they are all normal)

I am really confused, do you have any idea about this situation? Look forward to your reply~

Could I get you 300's pairs to check whether I recover the model exactly?

It maybe include sample_300.txt sample_300_tgt.txt and pred.txt.

Looking forward to your reply~

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