Difference between revisions of "Eosc/NorBERT3 corpus"

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(Sampling experiment)
 
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* Cleaning procedure from https://arxiv.org/abs/2112.11446
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== Workflow ==
* Deduplication https://github.com/ChenghaoMou/text-dedup/tree/main/text_dedup https://github.com/ekzhu/datasketch
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* [https://github.com/ChenghaoMou/text-dedup/tree/main/text_dedup De-duplication]: essentially, removing identical paragraphs using SimHash (similar to the NearDup approach in [https://aclanthology.org/2022.acl-long.577/ this paper], although they used MinHash; [https://pypi.org/project/mmh3/ MurMurHash] is another option).
* Two versions: baseline and wikipedia+NCC+NAK multiplied by two to match the C4 size
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* [https://arxiv.org/abs/2112.11446 Cleaning]
  
Todo: what is the size of NBDigital and should we use it?
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There are [https://github.com/ekzhu/datasketch other de-duplication packages]
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== Sampling experiment ==
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We plan to create two versions of the training corpus:
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* baseline (as is)
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* Wikipedia+NCC+NAK+NBDigital multiplied by two to match the C4 size (oversampling quality data)
 +
 
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== Vocabulary ==
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Starting with 50K, following NorBERT-2. May be later experiment with other values.
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== To Decide ==
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Q: The size of NBDigital is 662M tokens. Should we use it? It probably overlaps a lot with NCC.
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A: No, it isn't. Only 60 paragraphs out of total 18M in NCC are duplicates of paragraphs in NBDigital. Thus, we definitely should use it.
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Q: How should we split training corpora: one sentence per line, one paragraph per line, one document per line?
 +
 
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A: BERT assumes that there is one sentence per line.

Latest revision as of 18:50, 24 October 2022

Workflow

There are other de-duplication packages

Sampling experiment

We plan to create two versions of the training corpus:

  • baseline (as is)
  • Wikipedia+NCC+NAK+NBDigital multiplied by two to match the C4 size (oversampling quality data)

Vocabulary

Starting with 50K, following NorBERT-2. May be later experiment with other values.

To Decide

Q: The size of NBDigital is 662M tokens. Should we use it? It probably overlaps a lot with NCC.

A: No, it isn't. Only 60 paragraphs out of total 18M in NCC are duplicates of paragraphs in NBDigital. Thus, we definitely should use it.

Q: How should we split training corpora: one sentence per line, one paragraph per line, one document per line?

A: BERT assumes that there is one sentence per line.