Comments (11)
支持的。可以参考这里的启动方法:
DocEE/scripts/reprod_all_exps.sh
Lines 31 to 38 in a32b6f8
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嗨您好,这两种指标不太一样。
一般事件论元抽取任务会假设事件检测的正确率为100%,而论文中的F1值是整个事件表的F1,可以理解为包含了事件类型的判断,是一个任务的整体F1值。在DocEE任务中,通常不会考虑单一的论元抽取性能。输出结果中的实体部分是指实体抽取结果,而非论元(不是所有的实体都是论元)。
overall下的overall指的是事件表填充的整体F1值。
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好滴!非常感谢!
我观察到您的代码中包含DCFEE的代码(dee/models/dcfee.py),请问是否可以运行这个模型(DCFEE)的代码呢?
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好滴!
31行中提到“DCFEE Baselines: DCFEE-O, DCFEE-M ”,请问这个脚本也是运行一次,就可以得到这两个模型(DCFEE-O, DCFEE-M)的结果吗
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抱歉时间太久有些记不得了,可以跑一轮试试看,我印象中是的。
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好滴!非常感谢!
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我尝试换了一个数据集运行了deppn模型,但最终得分非常低,只有百分之十几,请问这是正常的嘛?
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抱歉,当前代码对DEPPN的支持有问题,还是需要使用他们原生的代码跑实验:https://github.com/HangYang-NLP/DE-PPN
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我复现他的原生代码好像存在一些问题呀?您有没有复现成功过他的代码呀?
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您可以联系DE-PPN的作者帮忙解决该模型的复现问题
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Related Issues (20)
- 实验结果 HOT 4
- 相似度的一些问题 HOT 8
- 分布式训练 HOT 3
- importance分数 HOT 15
- deppn模型F1只有33 HOT 2
- "pred_results"中的classification得分 HOT 25
- 分句 (uncommon sentence cutoff in DuEE-fin) HOT 14
- Duee_Fin预测结果 HOT 2
- 测试集结果 HOT 2
- 单事件&多事件 HOT 3
- Greedy-Dec模型如何运行? HOT 6
- similarity calculation HOT 1
- pretrained model weight HOT 1
- 多事件 HOT 1
- 使用o2m格式的数据时,需要修改那些代码呢 HOT 1
- Potential performance issue: plotting slow in matplotlib == 3.3.0 HOT 1
- 请问老师怎么在自己的数据集上进行训练呢? HOT 14
- 关于ptpcg论文的一些问题 HOT 4
- 论文中的一个问题 HOT 3
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