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dqwang122 / HeterSumGraph

Code for ACL2020 paper "Heterogeneous Graph Neural Networks for Extractive Document Summarization"
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Question on the training, poor reproduced result #8

Closed yeliu918 closed 4 years ago

yeliu918 commented 4 years ago

Hi,

Thank you for providing this source code. I follow your instruction. However, the reproduced result it poor.

--cuda --gpu 0 --data_dir dataset/multinews/ --cache_dir cache/multinews/ --embedding_path glove/glove.42B.300d.txt --model HDSG --save_root output --log_root output/logfile --lr_descent --grad_clip -m 3

The training loss deceased very slow, from 14.99 to 12.67 after 14 Epoch. The best result on the training: Rouge1: p:0.568634, r:0.246242, f:0.331011 Rouge2: p:0.199369, r:0.084300, f:0.114196 Rougel: p:0.450906, r:0.220580, f:0.288866 Can you provide any command on how to train the network?

dqwang122 commented 4 years ago

Following the hyper-parameters provided in our paper, please make m=9 for MultiNews (Section 4.2) both in the validation phase during training and evaluation.

yeliu918 commented 4 years ago

Hi,

Thanks for the kind reply.