Guess the date of reddits
Guess a reddit date based on its text. [ver. 1.0.1]
This is a long list of all submissions, if you want to see only the best, click leaderboard.
| # | submitter | when | ver. | description | dev-0 MSE | test-A MSE | |
|---|---|---|---|---|---|---|---|
| 15 | kubapok | 2020-10-09 07:20 | 1.0.1 | tfidf + lr | 0.7556 | 0.7636 | |
| 2 | kubapok | 2020-06-20 19:08 | 1.0.1 | roberta english base with regressor head | 0.5433 | 0.5440 | |
| 20 | [anonymized] | 2020-05-18 14:01 | 1.0.1 | showin dates naive-bayes self-made | 0.9206 | 0.9327 | |
| 9 | [anonymized] | 2020-05-09 15:10 | 1.0.1 | vowpal wabbit vowpal-wabbit ready-made linear-regression | 0.6244 | 0.6027 | |
| 10 | [anonymized] | 2020-05-09 10:44 | 1.0.1 | vowpal wabbit vowpal-wabbit ready-made linear-regression | 0.6427 | 0.6182 | |
| 16 | [anonymized] | 2020-05-09 09:34 | 1.0.1 | vowpal wabbit vowpal-wabbit ready-made linear-regression | 0.7614 | 0.7776 | |
| 18 | [anonymized] | 2020-05-08 09:36 | 1.0.1 | vowpal wabbit vowpal-wabbit ready-made linear-regression | 0.7793 | 0.8079 | |
| 12 | [anonymized] | 2020-05-06 12:51 | 1.0.1 | vowpal wabbit vowpal-wabbit ready-made linear-regression | 0.7136 | 0.7156 | |
| 22 | [anonymized] | 2020-05-04 10:05 | 1.0.1 | split using bayes naive-bayes self-made | 1.0985 | 1.0873 | |
| 4 | [anonymized] | 2020-04-27 13:35 | 1.0.1 | Linear regression Vowpal Wabbit (non-sumo achievement) (450 passes, learning rate 0.25) vowpal-wabbit linear-regression hyperparam | 0.5713 | 0.5660 | |
| 11 | [anonymized] | 2020-04-26 12:02 | 1.0.1 | Repaired solution rule-based | 0.6893 | 0.6749 | |
| 5 | [anonymized] | 2020-04-25 09:00 | 1.0.1 | vowpal linear regression with learning rate 0.3 vowpal-wabbit linear-regression hyperparam | 0.5750 | 0.5703 | |
| 8 | [anonymized] | 2020-04-25 08:49 | 1.0.1 | vowpal linear regression with default params | 0.5874 | 0.5842 | |
| 30 | [anonymized] | 2020-04-19 16:05 | 1.0.1 | No score here, since it is not compatible with geval naive-bayes self-made | N/A | N/A | |
| 1 | kubapok | 2020-04-14 13:52 | 1.0.1 | lstm with recurrent dropout 3 epochs | 0.5460 | 0.5429 | |
| 29 | kubapok | 2020-04-14 13:50 | 1.0.1 | lstm with recurrent dropout 3 epochs | 0.5460 | N/A | |
| 28 | kubapok | 2020-04-14 13:29 | 1.0.1 | lstm with recurrent dropout | 0.5460 | N/A | |
| 14 | [anonymized] | 2020-04-08 17:54 | 1.0.1 | Much better, linear regression self-made linear-regression gradient-descent | 0.7337 | 0.7268 | |
| 13 | [anonymized] | 2020-04-08 07:44 | 1.0.1 | ... ready-made linear-regression | 0.0182 | 0.7175 | |
| 19 | [anonymized] | 2020-04-08 07:09 | 1.0.1 | ... | 0.0182 | 0.8333 | |
| 26 | [anonymized] | 2020-04-06 15:37 | 1.0.1 | probably bad, checking if commiting here works | 43.3605 | 41.7475 | |
| 17 | [anonymized] | 2020-04-06 14:18 | 1.0.1 | ... ready-made linear-regression | 0.0182 | 0.7800 | |
| 3 | kubapok | 2020-04-04 08:02 | 1.0.1 | lstm | 0.5506 | 0.5518 | |
| 27 | kubapok | 2020-04-04 08:00 | 1.0.1 | lstm | 0.5506 | N/A | |
| 6 | [anonymized] | 2020-04-03 18:40 | 1.0.1 | ISI-2019-016 linear regression 2 self-made linear-regression gradient-descent | 0.5887 | 0.5722 | |
| 24 | [anonymized] | 2020-04-02 19:15 | 1.0.1 | Second improve rule-based | 9.3735 | 9.4446 | |
| 23 | [anonymized] | 2020-04-02 19:15 | 1.0.1 | first try ready-made linear-regression | 0.0182 | 1.4449 | |
| 25 | [anonymized] | 2020-04-01 20:28 | 1.0.1 | Guess reddit date - first try for rule based | 16.1309 | 16.2173 | |
| 21 | [anonymized] | 2020-03-31 17:51 | 1.0.1 | self-made linear regression self-made linear-regression | 0.9579 | 0.9803 | |
| 7 | [anonymized] | 2020-03-30 15:07 | 1.0.1 | Mean from train baseline | 0.5906 | 0.5727 |