Skeptic vs paranormal subreddits

Classify a reddit as either from Skeptic subreddit or one of the "paranormal" subreddits (Paranormal, UFOs, TheTruthIsHere, Ghosts, ,Glitch-in-the-Matrix, conspiracytheories). [ver. 3.0.0]

Git repo URL: git://gonito.net/paranormal-or-skeptic / Branch: master
Run git clone --single-branch git://gonito.net/paranormal-or-skeptic -b master to get the challenge data
Browse at https://gonito.net/gitlist/paranormal-or-skeptic.git/master

Leaderboard

#	submitter	when	ver.	description	test-A Recall	test-A Precision	test-A F1.0	test-A Accuracy	test-A Likelihood	×
1	kubapok	2020-05-13 15:01	3.0.0	roberta large finetuning 1 epoch fairseq (may be finetuned still)	0.8117	0.8417	0.8264	0.8756	0.7525	2
2	[anonymized]	2020-04-22 23:10	3.0.0	Sklearn Logistic regression 1-3gram 1000iter probabilities	0.7011	0.7855	0.7409	0.8210	0.6767	8
3	[anonymized]	2020-06-15 13:51	3.0.0	docker lstm	0.7229	0.7618	0.7418	0.8164	0.6750	25
4	[anonymized]	2020-04-20 13:34	3.0.0	vowpal-wabbit probabilities	0.8340	0.7131	0.7688	0.8170	0.6650	20
5	[anonymized]	2020-04-27 14:45	3.0.0	first test vowpal vowpal-wabbit logistic-regression hyperparam	0.6543	0.7775	0.7106	0.8055	0.6621	22
6	[anonymized]	2020-04-23 08:32	3.0.0	ISI-33, probabilities probabilities	0.6729	0.7718	0.7190	0.8080	0.6586	11
7	[anonymized]	2020-04-26 14:07	3.0.0	Vowpal wabbit hyperparam change vowpal-wabbit logistic-regression hyperparam	0.6319	0.7984	0.7055	0.8075	0.6580	17
8	[anonymized]	2020-04-27 04:03	3.0.0	v2 probabilities	0.6846	0.7483	0.7150	0.8009	0.6482	74
9	[anonymized]	2020-04-21 21:22	3.0.0	NB sklearn with probo probabilities	0.3856	0.8610	0.5327	0.7531	0.6297	9
10	[anonymized]	2020-06-05 13:35	3.0.0	last-branch ready-made xgboost	0.4426	0.8181	0.5744	0.7607	0.6237	14
11	[anonymized]	2020-06-10 00:22	3.0.0	improved splitting naive-bayes multinomial baseline	0.7202	0.7448	0.7323	0.8078	0.6091	17
12	[anonymized]	2020-04-21 16:44	3.0.0	Add Likelihood to ready made NB probabilities	0.7479	0.7173	0.7323	0.8005	0.6074	18
13	[anonymized]	2020-06-09 10:58	3.0.0	probability probabilities	0.7862	0.7106	0.7465	0.8051	0.6062	23
14	[anonymized]	2020-05-18 13:56	3.0.0	improved naive-bayes multinomial baseline	0.7862	0.7106	0.7465	0.8051	0.6062	18
15	[anonymized]	2020-04-25 10:28	3.0.0	bayes prob probabilities	0.7846	0.7068	0.7436	0.8026	0.6035	16
16	[anonymized]	2020-06-03 16:27	3.0.0	ISI52 logistic-regression word2vec	0.6223	0.7410	0.6765	0.7828	0.5832	14
17	[anonymized]	2020-06-08 16:50	3.0.0	knn tf knn tf	0.2234	0.8434	0.3532	0.7015	0.5623	45
18	[anonymized]	2020-05-18 14:57	3.0.0	knn-tfidf-v5 knn tf-idf	0.3420	0.8654	0.4903	0.7405	0.5615	14
19	[anonymized]	2020-06-07 13:54	3.0.0	tf idf solution knn tf-idf	0.1319	0.9118	0.2305	0.6786	0.5547	11
20	p/tlen	2020-04-20 13:18	3.0.0	To probabilities null-model baseline	0.1048	0.8914	0.1875	0.6687	0.5282	4
21	[anonymized]	2020-04-27 14:27	3.0.0	Naive Bayes (probabilities) probabilities	0.7777	0.6992	0.7363	0.7968	0.5056	11
22	[anonymized]	2020-05-27 17:42	3.0.0	Stupid solution stupid baseline	0.0000	0.0000	0.0000	0.6351	0.0000	1
23	[anonymized]	2020-06-23 22:59	3.0.0	svm ready-made svm	0.6021	0.7685	0.6752	0.7886	0.0000	14
24	[anonymized]	2020-06-30 22:44	3.0.0	Upload files to 'test-A' self-made linear-regression gradient-descent	0.3362	0.5351	0.4129	0.6512	0.0000	11
25	[anonymized]	2020-12-16 11:46	3.0.0	working logistic-regression pytorch-nn	0.1729	0.3714	0.2359	0.5914	0.0000	1
26	[anonymized]	2020-06-09 20:02	3.0.0	Use Linear Regression V6 self-made linear-regression gradient-descent	0.4803	0.5953	0.5316	0.6912	0.0000	44
27	[anonymized]	2020-05-04 13:16	3.0.0	linear regression gradient descent self-made linear-regression gradient-descent	0.3660	0.7845	0.4991	0.7319	0.0000	22
28	[anonymized]	2020-05-27 17:58	3.0.0	Stupid solution stupid baseline	0.0000	0.0000	0.0000	0.6351	0.0000	2
29	[anonymized]	2020-12-16 10:53	3.0.0	4 iteracje	0.1691	0.3693	0.2320	0.5914	0.0000	5
30	[anonymized]	2020-12-16 08:41	3.0.0	Moje genialne rozwiazanie logistic-regression pytorch-nn	0.0436	0.4000	0.0787	0.6271	0.0000	3
31	[anonymized]	2021-02-18 20:19	3.0.0	update + out, final logistic-regression pytorch-nn	0.1734	0.3730	0.2367	0.5920	0.0000	2
32	[anonymized]	2021-02-17 19:59	3.0.0	paranormal logistic-regression pytorch-nn	0.1729	0.3706	0.2358	0.5910	0.0000	2
33	Marcin Kostrzewski	2022-05-10 22:01	3.0.0	Add predictions naive-bayes	0.3718	0.7327	0.4933	0.7213	0.0000	1
34	Martyna Druminska	2022-05-28 13:44	3.0.0	my brilliant self-made neural-network word2vec pytorch-nn	0.4287	0.7133	0.5355	0.7286	0.0000	3
35	s444417	2022-05-18 08:59	3.0.0	fix output naive-bayes	0.6213	0.5458	0.5811	0.6731	0.0000	7
36	s443930	2022-06-22 21:37	3.0.0	s443930 transformer	0.4723	0.6794	0.5573	0.7261	0.0000	4
37	s409771	2022-05-25 20:59	3.0.0	first solution neural-network word2vec	0.5181	0.7356	0.6080	0.7562	0.0000	2
38	s478815	2022-06-14 22:10	3.0.0	478815 neural-network word2vec	0.5830	0.7282	0.6476	0.7684	0.0000	3
39	[anonymized]	2022-06-22 08:12	3.0.0	s478874 transformer	0.8027	0.6087	0.6924	0.7397	0.0000	6
40	ked	2022-05-24 21:35	3.0.0	s449288 - simple NN with GloVe vectors neural-network word2vec	0.6096	0.6945	0.6493	0.7597	0.0000	3
41	Cezary	2022-05-25 21:10	3.0.0	s470623 neural-network word2vec	0.4819	0.7067	0.5731	0.7380	0.0000	1
42	[anonymized]	2022-05-27 15:37	3.0.0	478841 results neural-network word2vec	0.6037	0.7143	0.6544	0.7673	0.0000	3
43	Jakub	2022-06-08 09:09	3.0.0	s434624 neural-network word2vec	0.0229	0.4433	0.0435	0.6330	0.0000	1
44	[anonymized]	2022-05-24 09:15	3.0.0	s478831 neural-network word2vec	0.6144	0.6082	0.6113	0.7149	0.0000	1
45	s444498	2022-05-11 21:45	3.0.0	s444498 naive-bayes	0.3223	0.7690	0.4543	0.7174	0.0000	2
46	Mikołaj Pokrywka	2022-05-24 21:43	3.0.0	s444463 neural-network word2vec	0.5197	0.7797	0.6237	0.7712	0.0000	2
47	s444517	2022-05-23 15:13	3.0.0	s444517 - PyTorch feed forward neural network self-made neural-network word2vec	0.3973	0.7155	0.5109	0.7224	0.0000	2
48	s478855	2022-06-22 11:35	3.0.0	s478855 - correct outs transformer	0.7234	0.7572	0.7399	0.8144	0.0000	3
49	s478840	2022-06-21 21:00	3.0.0	s478840 transformer	0.6468	0.6441	0.6454	0.7407	0.0000	5
50	s478846	2022-05-24 09:45	3.0.0	First solution neural-network word2vec	0.6766	0.7374	0.7057	0.7941	0.0000	1
51	s444356	2022-05-09 18:46	3.0.0	s444356 naive-bayes	0.3718	0.7327	0.4933	0.7213	0.0000	1
52	s444501	2022-05-10 14:11	3.0.0	s444501 naive-bayes	0.2968	0.8242	0.4364	0.7203	0.0000	1
53	Kamil Guttmann	2022-05-23 19:32	3.0.0	s444380 simple nn + word2vec neural-network word2vec	0.4676	0.7343	0.5713	0.7440	0.0000	3
54	[anonymized]	2022-05-08 20:10	3.0.0	444421 naive-bayes	0.2734	0.7823	0.4052	0.7071	0.0000	1
55	s444465	2022-05-23 14:54	3.0.0	s444465 neural-network word2vec	0.6059	0.7363	0.6647	0.7770	0.0000	2
56	s444018	2022-05-10 22:21	3.0.0	s444018 naive-bayes self-made	0.3835	0.8857	0.5353	0.7570	0.0000	2
57	Adam Wojdyła	2022-06-01 21:08	3.0.0	4444507 neural-network word2vec	0.4654	0.7184	0.5649	0.7384	0.0000	4
58	[anonymized]	2022-06-06 21:43	3.0.0	out dev neural-network word2vec	0.5229	0.7352	0.6111	0.7572	0.0000	1