# RetroC2 temporal classification challenge

Guess the publication year of a Polish text. [ver. 1.0.0]

Git repo URL: `git://gonito.net/retroc2` / Branch: ` master`

Run `git clone --single-branch git://gonito.net/retroc2 -b master` to get the challenge data

Browse at `https://gonito.net/gitlist/retroc2.git/master`

## Leaderboard

# | submitter | when | ver. | description | test-A RMSE | × | |
---|---|---|---|---|---|---|---|

1 | kubapok | 2020-06-02 17:12 | 1.0.0 | linear layer on top of polish roberta- Adam lr 1e-07 | 13.328 | 12 | |

2 | Artur Nowakowski | 2019-04-19 07:52 | 1.0.0 | optimized word2vec + nn neural-network word2vec | 17.789 | 9 | |

3 | [anonymized] | 2020-05-18 05:20 | 1.0.0 | v2 fasttext | 17.989 | 2 | |

4 | p/tlen | 2017-05-31 04:49 | 1.0.0 | VW -nn 6 on up to 4-grams and [5-7] tokens stupid vowpal-wabbit neural-network | 19.501 | 16 | |

5 | [anonymized] | 2019-05-03 19:49 | 1.0.0 | BiLSTM w/o sorting | 23.225 | 42 | |

6 | s444383 | 2022-06-21 10:15 | 1.0.0 | new prediction | 23.268 | 3 | |

7 | s444417 | 2022-05-17 19:00 | 1.0.0 | linear regression self-made linear-regression | 23.438 | 3 | |

8 | s478855 | 2022-05-08 17:27 | 1.0.0 | s478855 self-made linear-regression | 23.456 | 1 | |

9 | s444501 | 2022-05-17 21:30 | 1.0.0 | s444501 linear-regression | 23.461 | 1 | |

10 | s444415 | 2022-05-19 15:06 | 1.0.0 | 444415 linear-regression | 23.507 | 1 | |

11 | [anonymized] | 2022-05-29 20:41 | 1.0.0 | Prześlij pliki do '' linear-regression | 23.507 | 1 | |

12 | s444455 | 2022-05-26 22:04 | 1.0.0 | regresja self-made linear-regression | 23.507 | 1 | |

13 | [anonymized] | 2022-05-14 17:03 | 1.0.0 | 478841 self-made linear-regression | 23.507 | 1 | |

14 | s444476 | 2022-05-01 11:59 | 1.0.0 | s444476 linear-regression | 23.507 | 1 | |

15 | s444354 | 2022-05-14 01:44 | 1.0.0 | s444354 self-made linear-regression | 23.515 | 2 | |

16 | Kamil Guttmann | 2022-05-17 18:42 | 1.0.0 | s444380 linear regression tf-idf linear-regression | 23.595 | 1 | |

17 | s444018 | 2022-05-17 21:32 | 1.0.0 | s444018 self-made linear-regression | 23.855 | 1 | |

18 | s444386 | 2022-05-09 13:38 | 1.0.0 | linear regresion 444386 linear-regression | 23.951 | 1 | |

19 | s444452 | 2022-05-09 19:43 | 1.0.0 | s444452 self-made linear-regression | 23.988 | 1 | |

20 | s444356 | 2022-05-17 20:52 | 1.0.0 | s444356 linear-regression | 24.032 | 1 | |

21 | Mikołaj Pokrywka | 2022-05-17 06:43 | 1.0.0 | 444463 linear-regression | 24.033 | 1 | |

22 | Marcin Kostrzewski | 2022-05-17 21:28 | 1.0.0 | Mean publication year, stop words removed. Trained on 50000 examples linear-regression scikit-learn stop-words | 24.204 | 1 | |

23 | [anonymized] | 2019-06-01 15:50 | 1.0.0 | tf ready-made linear-regression tf | 24.291 | 12 | |

24 | s409771 | 2022-05-16 17:35 | 1.0.0 | first solution linear-regression | 24.782 | 1 | |

25 | [anonymized] | 2022-05-17 22:07 | 1.0.0 | s478831 linear-regression | 24.816 | 1 | |

26 | Martyna Druminska | 2022-05-19 11:42 | 1.0.0 | my brilliant solution self-made linear-regression | 24.816 | 2 | |

27 | s478839 | 2022-05-17 23:12 | 1.0.0 | s478839 self-made linear-regression | 24.865 | 10 | |

28 | s478873 | 2022-05-17 11:14 | 1.0.0 | s478873 | 25.479 | 4 | |

29 | s478815 | 2022-05-17 21:27 | 1.0.0 | 478815 linear-regression | 26.113 | 4 | |

30 | s443930 | 2022-05-19 21:03 | 1.0.0 | s443930 linear-regression | 26.515 | 1 | |

31 | ked | 2022-04-29 14:01 | 1.0.0 | s449288 - simple linear regression with 10% of train dataset linear-regression | 26.550 | 2 | |

32 | [anonymized] | 2022-05-17 09:00 | 1.0.0 | 444421 linear-regression | 26.884 | 1 | |

33 | Adam Wojdyła | 2022-05-18 00:07 | 1.0.0 | 4444507 self-made linear-regression | 26.964 | 2 | |

34 | [anonymized] | 2019-06-04 15:41 | 1.0.0 | Vowpal Wabbit quadratic model + graph v2 vowpal-wabbit graph | 27.297 | 2 | |

35 | [anonymized] | 2019-06-04 12:03 | 1.0.0 | vw first encounter(loss function, -b 27, passes=20, quadratic model) vowpal-wabbit graph | 27.384 | 1 | |

36 | [anonymized] | 2019-05-06 15:05 | 1.0.0 | tfidf 50k words low reduction range ready-made linear-regression tf-idf | 27.708 | 16 | |

37 | [anonymized] | 2019-05-17 18:45 | 1.0.0 | Vowpal Wabbit - linear regression + graph vowpal-wabbit graph | 27.808 | 10 | |

38 | s478846 | 2022-05-11 13:27 | 1.0.0 | First solution linear-regression | 28.166 | 1 | |

39 | [anonymized] | 2019-04-15 20:33 | 1.0.0 | Basic ready-made solution with one column ready-made linear-regression tf-idf | 28.298 | 3 | |

40 | s478840 | 2022-05-16 12:56 | 1.0.0 | s478840 linear-regression | 28.809 | 1 | |

41 | [anonymized] | 2019-05-03 18:37 | 1.0.0 | 3000 words tf-idf self-made linear-regression tf-idf | 32.631 | 11 | |

42 | [anonymized] | 2019-05-09 23:19 | 1.0.0 | ready-made tf-df: a fix ready-made linear-regression tf-idf | 33.388 | 6 | |

43 | [anonymized] | 2019-04-16 16:36 | 1.0.0 | simple lin reg self-made linear-regression graph | 35.958 | 6 | |

44 | [anonymized] | 2019-04-08 19:59 | 1.0.0 | stupid solution rule-based | 38.177 | 3 | |

45 | [anonymized] | 2019-06-10 15:23 | 1.0.0 | graf self-made linear-regression graph | 39.246 | 10 | |

46 | [anonymized] | 2019-04-08 12:54 | 1.0.0 | Based on a list with years rule-based | 39.695 | 4 | |

47 | [anonymized] | 2019-04-08 15:24 | 1.0.0 | rulebased rule-based | 39.781 | 3 | |

48 | [anonymized] | 2019-04-15 18:39 | 1.0.0 | XXDDDD my solution self-made linear-regresion ADD CHARTS selfMadeLinearRegres_Solver.py self-made linear-regression graph | 39.904 | 6 | |

49 | [anonymized] | 2019-04-08 18:10 | 1.0.0 | my very simple solution3 rule-based | 40.838 | 5 | |

50 | [anonymized] | 2019-05-06 15:01 | 1.0.0 | My solution go.php rule-based | 42.687 | 1 | |

51 | [anonymized] | 2019-04-15 18:40 | 1.0.0 | excel plots :) self-made linear-regression graph | 42.991 | 6 | |

52 | [anonymized] | 2019-06-12 14:40 | 1.0.0 | wordlist 4 | 51.853 | 40 | |

53 | Jakub Eichner | 2022-06-07 21:46 | 1.0.0 | s478874 linear-regression | 52.826 | 3 | |

54 | [anonymized] | 2020-06-24 00:12 | 1.0.0 | xgboost solution ready-made xgboost | 54.317 | 2 | |

55 | [anonymized] | 2019-04-07 18:17 | 1.0.0 | most popular words in 10-year periods java rule-based | 57.981 | 1 |