Repository of "An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction" (EMNLP-IJCNLP 2019)
Home Page: https://www.aclweb.org/anthology/D19-1119/
License: MIT License
Hello, thanks for the efforts in GEC. I download the files and run it as the instruction. However, I get 61.94 F0.5 on CoNLL-2014.
CORRECT EDITS : 1211
PROPOSED EDITS : 1779
GOLD EDITS : 2659
P = 0.68071950534
R = 0.455434373825
F_0.5 = 0.619437340153
Precision : 0.6807
Recall : 0.4554
F_0.5 : 0.6194
Hi, I am interested in your work. Could you provide the script to obtain the model pretlarge+sse+r2l?
hello,I also interested in your research,and I follow by steps,but don't know how to train
Is there any resource about R2L pre-trained model ?
will finetune script be provided
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