Sane words challenge
Guess if a given word is a correct Polish word in a given domain. Additionally, you have the information on reported frequency of the word in source texts. [ver. 1.0.0]
Git repo URL: ssh://gitolite@gonito.net/sane-words / Branch: master
Run git clone --single-branch ssh://gitolite@gonito.net/sane-words -b master to get the challenge data
Browse at https://gonito.net/gitlist/sane-words.git/master
Leaderboard
| # | submitter | when | ver. | description | test-A F2.0 | × | |
|---|---|---|---|---|---|---|---|
| 1 | [anonymized] | 2018-01-26 10:59 | 1.0.0 | Fixed class weight neural-network | 0.46603 | 37 | |
| 2 | [anonymized] | 2019-11-30 18:59 | 1.0.0 | Neural net 512x256 one hot word python pytorch-nn | 0.44029 | 6 | |
| 3 | [anonymized] | 2018-02-09 15:52 | 1.0.0 | 'baseline' neural-network | 0.42429 | 12 | |
| 4 | [anonymized] | 2018-01-09 19:32 | 1.0.0 | max_word=80, batch_size=256, activition=relu, optymizer=rmsprob, nb_epoch=200 neural-network | 0.41575 | 3 | |
| 5 | [anonymized] | 2017-01-07 22:08 | 1.0.0 | approximate frequencies | 0.41393 | 8 | |
| 6 | p/tlen | 2016-12-27 09:14 | 1.0.0 | simple neural network with frequencies taken into account neural-network | 0.40410 | 25 | |
| 7 | Artur Nowakowski | 2019-12-03 21:43 | 1.0.0 | PyTorch simple NN python pytorch-nn | 0.33842 | 1 | |
| 8 | [anonymized] | 2019-12-04 09:02 | 1.0.0 | torch-nn python pytorch-nn | 0.33287 | 3 | |
| 9 | [anonymized] | 2019-12-04 19:29 | 1.0.0 | pytorch-nn more iterations python pytorch-nn | 0.33117 | 4 | |
| 10 | [anonymized] | 2019-11-27 18:11 | 1.0.0 | Simple nn solution with torch (stupid params???) python pytorch-nn | 0.32922 | 4 | |
| 11 | [anonymized] | 2019-12-04 21:56 | 1.0.0 | the best so far python pytorch-nn | 0.29350 | 11 | |
| 12 | [anonymized] | 2019-12-03 20:31 | 1.0.0 | pytorch neural network second solution python pytorch-nn | 0.29079 | 3 | |
| 13 | [anonymized] | 2019-12-04 08:28 | 1.0.0 | Pytorch nn, minibatch, improved previous solution python pytorch-nn | 0.28049 | 3 | |
| 14 | [anonymized] | 2019-11-27 09:35 | 1.0.0 | solution python linear-regression | 0.26632 | 3 | |
| 15 | [anonymized] | 2019-11-22 02:02 | 1.0.0 | 32x32 selfmade NN pytorch alpha -1.5 420k loop python linear-regression | 0.26247 | 4 | |
| 16 | [anonymized] | 2019-12-04 00:50 | 1.0.0 | NN pytorch python pytorch-nn | 0.25147 | 5 | |
| 17 | [anonymized] | 2019-11-26 21:36 | 1.0.0 | logistic regresion python linear-regression | 0.24328 | 1 | |
| 18 | [anonymized] | 2019-11-27 07:49 | 1.0.0 | solution 16N python linear-regression | 0.24304 | 1 | |
| 19 | [anonymized] | 2019-11-27 06:45 | 1.0.0 | LR with 16 neurons python linear-regression | 0.23550 | 6 | |
| 20 | [anonymized] | 2019-12-04 08:58 | 1.0.0 | fasttext + nn python pytorch-nn | 0.22230 | 1 | |
| 21 | [anonymized] | 2020-01-27 13:02 | 1.0.0 | 16 neurons and 1 layer lr python linear-regression | 0.22124 | 1 | |
| 22 | [anonymized] | 2019-12-04 10:09 | 1.0.0 | dev-0 update python neural-network pytorch-nn | 0.21551 | 4 | |
| 23 | [anonymized] | 2016-12-19 20:14 | 1.0.0 | random yolo with correct output file xD | 0.06709 | 2 |