Comments (5)
I think the ratio used is 9, not 1.5. The script also removes sentences which are more than 80 tokens and less than 1 token.
from mlconvgec2018.
The parallel training data (NUCLE+Lang8) is cleaned https://github.com/nusnlp/mlconvgec2018/blob/master/data/prepare_data.sh#L94 so that only non-empty sentence pairs are retained.
from mlconvgec2018.
In many <incorrect, correct> pairs of lang-8 data, there are additional comments. If we feed this to our models as is, I think it will not be very useful.
I guess the current scripts for cleaning data does not remove additional comments provided along with correct sentences.
Is there any script which handles this problem?
from mlconvgec2018.
No, the current pre-processing pipeline does not involve any specific rules to remove additional comments. However, the clean-corpus-n.perl script (from Moses SMT toolkit) that is used within the preprocess.sh script removes source-target sentence pairs which are substantially different in terms of length.
from mlconvgec2018.
Thanks,
I see. Removing source-target pairs where len(target)> 1.5*len(source) rejects around 30% of data. :(
from mlconvgec2018.
Related Issues (20)
- Using interactive instead of generate to evaluate HOT 1
- Python error: <stdin> is a directory, cannot continue HOT 2
- the size of training dataset? HOT 2
- How to use language model (94Bcclm.trie)? HOT 2
- TypeError: iter() returned non-iterator of type 'NBestList' HOT 9
- An error about Compile and install PyTorch(0.2.0) HOT 5
- Accuracy of trained model? HOT 12
- Fairseq-py Installation Issue HOT 5
- About training data
- reranker error HOT 6
- pytorch version? HOT 3
- pre-trainined embeddings. HOT 1
- ImportError: cannot import name 'libbleu' HOT 4
- 'Levenshtein greater than source size' when training re-ranker HOT 1
- Output directory error while running run.sh in google colab HOT 1
- ImportError: cannot import name 'libbleu' from 'fairseq' HOT 3
- Requesting NUCLE dataset 3.2
- Error loading state_size in FConvModel : size mismatch in encoder-decoder weights
- General question: GEC data preprocessing
- Can this model be used for any language?
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