bert-event-extraction

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预测的arguments是使用的groundtruth吗？

3

阅读代码发现对arguments的预测依赖于grountruth，打印预测的arguments发现start_idx和end_idx都与groundtruth相同。请问是我使用的方式不对吗？

lezhu1234

have you tried to use bert to improve the performance of JMEE?

11

Hi, Thank you for sharing. I'm interested if you tried to use bert to improve the performance of JMEE. I try to reproduce JMEE,but I can't achieve the result of...

xiaoya6666

trigger跑到67分使用的是什么参数配置

2

我跑了50轮，最高trigger classification只有23的f1。不知道67分作者使用的是什么参数

scarydemon2

I'm a freshman in Event Extraction. I have learned your code. In the train.py, I think this is a multitask because the loss is the sum of triggers loss and...

RZFan525

head_indexes_2d是干什么用的

2

x是[batch_size，SEQ_LEN，768]的bert表达 有一句代码： for i in range(batch_size): x[i] = torch.index_select(x[i], 0, head_indexes_2d[i]) 请问这是在做什么？

Hanlard

mislabeled data

7

Hi, I'm try to reproduce your model. But my result is low. I have checked these labels that my model predicted and I found a lot of labels that was...

ThanhDucPham

Traceback (most recent call last): File "D:/pythonProject/bert-event-extraction-master/train.py", line 80, in model = Net( File "D:\pythonProject\bert-event-extraction-master\model.py", line 18, in __init__ self.entity_embed = MultiLabelEmbeddingLayer(num_embeddings=entity_size, embedding_dim=entity_embedding_dim, device=device) File "D:\pythonProject\bert-event-extraction-master\model.py", line 129, in __init__...

alwayslikethat

TypeError: new() received an invalid combination of arguments - got (NoneType, int), but expected one of: * (*, torch.device device) didn't match because some of the arguments have invalid types:...

alwayslikethat


snakecy

Two approaches to improve the performance

6

Hi, I read your code and found there are two problems that hinder the performance improvement. First, as I know, previous papers use head words of entity mentions as the...

Life-0-1