Comments (2)
The coder is the PyTorch implementation of the following repository: https://github.com/rainarch/DSNER
The issue that you mention is already addressed in the following paper and also proposed a solution:
https://www.aclweb.org/anthology/D19-6125/
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Hello, I have read the article you mentioned in the comment section, in which you used the difference of F score as a reward, which is very interesting. But I tried to repeat your experiment and found several problems. The first problem is that the article mentions that the NER model should be pre-trained before retraining, but you don't seem to have given a specific number of pre-training rounds in the article. The second problem is that when we update the selector with the difference of F score as a reward, the reward value is oscillating and doesn't converge, which means that the selector isn't picking the instance very well, thus leading to the poor performance of the NER model. I would appreciate it if you could give me some advice.
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Related Issues (5)
- Out of memory issue HOT 5
- ner.embed.pth HOT 5
- how to run lstm+crf+sl or lstm+crf HOT 2
- NEWS Dataset with low performance HOT 1
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