Thanks for your amazing work! I do the data-preprocess and train as the guide in the Readme.md I see the code set the seed for random、torch and np. I train the model with the SciERC dataset and early stop at epoch 229 , get the result: I train it with a RTX3090 GPU without any modify the code (same as the Readme.md) I see, in the paper, the result is: the F1 for the ent is 68.4 and i get 66.03 How to reproduce the result in the paper? Sincerely looking forward to your reply!

作者你好，感谢你们开源了代码，代码非常整洁易读。我注意到在论文中你们也提到UniRE无法处理overlap entity的情况，在阅读代码时，我发现这部分包含overlap的entity的句子似乎被直接扔掉了，我是根据 https://github.com/Receiling/UniRE/blob/4f59bea2997c8edb5d4659b1cfde9789d5965127/inputs/dataset_readers/ace_reader_for_joint_decoding.py#L174 这个，但我不确定我的理解是否是正确的。希望能得到你的解答，另外从https://github.com/Receiling/UniRE/blob/4f59bea2997c8edb5d4659b1cfde9789d5965127/entity_relation_joint_decoder.py#L281 这里看起来，似乎所有的数据集都被设定为train了，因此所有超过长度的句子也被直接扔掉了。所以我的疑问是 （1）会把test中含有overlap entity的句子直接扔掉了嘛；
（2）会扔掉在test中长度超过阈值的sample嘛？

When I test on scierc dataset, the following errors are reported: error message:

Traceback (most recent call last):
  File "entity_relation_joint_decoder.py", line 330, in <module>
    main()
  File "entity_relation_joint_decoder.py", line 316, in main
    model.load_state_dict(state_dict,False)
  File "/home/jsj201-9/anaconda3/envs/unire/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1407, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for EntRelJointDecoder:
        size mismatch for embedding_model.bert_encoder.bert_model.embeddings.word_embeddings.weight: copying a param with shapetorch.Size([31090, 768]) from checkpoint, the shape in current model is torch.Size([30522, 768]).

使用如下提供的流程和代码，以及ACE2004数据集进行处理

https://github.com/LorrinWWW/two-are-better-than-one/tree/master/datasets

① 执行python ace2json.py后生成了如下文件

② 执行python unify.py后在unified目录下生成了如下文件：

请问针对您的脚本命令./ace2004.sh ace2004_folder，以及split.py，我该使用哪一个路径作为ace2004_folder这一参数？谢谢！

当我训练SciERC时，发生如下错误，有人遇到过吗？ [2021-12-30 12:30:40,742 - entity_relation_joint_decoder.py - line:274 - INFO]: Load bert tokenizer successfully. Traceback (most recent call last): File "C:\Users\Administrator\Desktop\UniRE-master\entity_relation_joint_decoder.py", line 330, in main() File "C:\Users\Administrator\Desktop\UniRE-master\entity_relation_joint_decoder.py", line 295, in main ace_dataset.build_dataset(vocab=vocab, File "C:\Users\Administrator\Desktop\UniRE-master\inputs\datasets\dataset.py", line 78, in build_dataset instance_settting['instance'].count_vocab_items(counter, File "C:\Users\Administrator\Desktop\UniRE-master\inputs\instance.py", line 61, in count_vocab_items field.count_vocab_items(counter, sentences) File "C:\Users\Administrator\Desktop\UniRE-master\inputs\fields\token_field.py", line 39, in count_vocab_items for sentence in sentences: File "C:\Users\Administrator\Desktop\UniRE-master\inputs\dataset_readers\ace_reader_for_joint_decoding.py", line 37, in iter state, results = self.get_tokens(line) File "C:\Users\Administrator\Desktop\UniRE-master\inputs\dataset_readers\ace_reader_for_joint_decoding.py", line 90, in get_tokens logger.error("article id: {} sentence id: {} doesn't contain 'sentText'.".format(line['articleId'], line['sentId'])) KeyError: 'articleId'