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roberta-finetuned-on-challam-yearpredict-before
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Jakub Pokrywka 7c44c3c23d hf linear layer, regular roberta finetunned firstly on roberta challam year prediction, then on wiki historian
2022-07-18 20:32:09 +00:00
challam_year_prediction_on_challam_model hf linear layer, roberta challam finetunned firstly on roberta challam year prediction, then on wiki historian 2022-07-18 20:18:08 +00:00
challam_year_prediction_on_roberta_base_model hf linear layer, regular roberta finetunned firstly on roberta challam year prediction, then on wiki historian 2022-07-18 20:32:09 +00:00
dev-0 hf linear layer, regular roberta finetunned firstly on roberta challam year prediction, then on wiki historian 2022-07-18 20:32:09 +00:00
hf_roberta_base hf roberta challam regression layer on top 2022-07-14 19:19:12 +00:00
mean_from_train mean from train 2022-02-12 19:46:31 +01:00
test-A hf linear layer, regular roberta finetunned firstly on roberta challam year prediction, then on wiki historian 2022-07-18 20:32:09 +00:00
train init 2022-02-12 19:14:40 +01:00
.gitignore init 2022-02-12 19:14:40 +01:00
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README.md change name 2022-02-12 19:30:51 +01:00

README.md

Wiki Historian En

Guess the masked date in an wikipedia article.

Only dates 1835-1935 are considered.

You should predict only one masked date in an article described as [DATEPREDICT]. [DATEMASK] are other masked dates. The predicted date should be in fractional year format.

Fractional year format:

Year is normalized as follows:

''' days_in_year = 366 if is_leap else 365 normalized = d.year + ((day_of_year-1) / days_in_year) '''

Directory structure

  • README.md — this file
  • config.txt — configuration file
  • train/ — directory with training data
  • train/in.tsv — input data for the train set
  • train/expected.tsv — expected (reference) data for the train set
  • dev-0/ — directory with dev (test) data
  • dev-0/in.tsv — input data for the dev set
  • dev-0/expected.tsv — expected (reference) data for the dev set
  • test-A — directory with test data
  • test-A/in.tsv — input data for the test set
  • test-A/expected.tsv — expected (reference) data for the test set