czhang99/capsule-nlu

Joint Slot Filling and Intent Detection via Capsule Neural Networks (ACL'19) https://arxiv.org/abs/1812.09471

capsule-nlu's Issues

about the result

Training Epoch 1: 70it [21:39, 18.56s/it]
2023-04-30 22:07:22,768 : INFO : Step: 140
2023-04-30 22:07:22,770 : INFO : Epochs: 2
2023-04-30 22:07:22,770 : INFO : Slot Loss: nan
2023-04-30 22:07:22,770 : INFO : Intent Loss: nan
...
2023-04-30 22:08:42,015 : INFO : slot f1: 0
2023-04-30 22:08:42,015 : INFO : intent accuracy: 71.04377104377105
2023-04-30 22:08:42,015 : INFO : semantic error(intent, slots are all correct): 0.0
could you have a check why the result like this?

Performance issue in the definition of masked_routing_iter, capsule_masked.py(P1)

Hello, I found a performance issue in the definition of masked_routing_iter, capsule_masked.py, two tf.matmul and three tf.shape in line 82, 83 will be created repeatedly during program execution, resulting in reduced efficiency. I think they should be created before the loop.

Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.

why result on ATIS so low?

atis数据集模型参数应如何设置

我这边论文复现，snips数据集按照论文的参数设置，效果能达到预期效果，但是atis数据集的Overall Acc只能达到0.704，与之对应的Intent Acc只有0.776，并且训练过程intent loss 一直震荡不收敛，已经尝试了不同的学习率和优化器，效果均达不到论文水平，请问一下作者论文关于atis数据集的超参是怎么设置的，在此十分感谢！！

请问with intent predicting且without re-routing的效果怎么样呢？

对比实验中有without intent predicting，请问with intent predicting且without re-routing的效果怎么样呢？