Twitter Sentiment Analysis

Guess the sentiment for texts in English. [ver. 1.0.0]

Git repo URL: git://gonito.net/twitter-sentiment-analysis / Branch: master

(Browse at https://gonito.net/gitlist/twitter-sentiment-analysis.git/master)

Leaderboard

# submitter when ver. description test-A Accuracy test-A Likelihood ×
1 kubapok 2020-05-20 08:31 1.0.0 roberta large finetunned 1 epoch 0.89950 0.77317 2
2 [anonymised] 2019-02-15 12:33 1.0.0 ulmfit-textbugger (adversarials created on 30% of trainset) 0.86008 0.72071 9
3 [anonymised] 2019-08-23 12:07 1.0.0 Wynik po 100000 cech ze stopwords, TfidfVectorizer, ngram=(1,3), LogisticRegression 0.82467 0.67126 173
4 [anonymised] 2019-06-11 15:26 1.0.0 vw script added vowpal-wabbit 0.81846 0.66975 5
5 [anonymised] 2019-06-08 15:10 1.0.0 Vowpal Wabbit logistic + ngram vowpal-wabbit 0.81529 0.66585 7
6 [anonymised] 2019-05-28 17:59 1.0.0 vw with -nn --ngram and linear regression vowpal-wabbit 0.81492 0.66244 5
7 Mikolaj Bachorz 2020-05-31 19:23 1.0.0 v5.1 ready-made svm 0.76850 0.61405 8
8 Jakub 452101 2020-05-29 10:46 1.0.0 ISI-89, xgboost, ready-made, sklearn, dockerfile ready-made xgboost 0.75775 0.59717 1
9 [anonymised] 2019-06-01 08:03 1.0.0 self-made_naive-bayes naive-bayes self-made 0.78696 0.59572 2
10 [anonymised] 2019-06-04 11:04 1.0.0 naive bayes - fine-tuned naive-bayes multinomial self-made probabilities 0.78404 0.59348 3
11 [anonymised] 2019-05-06 19:50 1.0.0 implement multinomial Naive Bayes ... on labs naive-bayes multinomial self-made 0.78242 0.59224 2
12 [anonymised] 2019-05-06 18:41 1.0.0 bayes with probabilities naive-bayes multinomial self-made 0.78242 0.59169 1
13 [anonymised] 2019-05-28 19:35 1.0.0 naive-one naive-bayes self-made 0.78404 0.59159 6
14 [anonymised] 2019-06-17 11:46 1.0.0 readymade_naive-bayes.py naive-bayes ready-made 0.78125 0.59135 7
15 [anonymised] 2019-05-19 11:35 1.0.0 naive-bayes-readymade naive-bayes ready-made 0.78125 0.59135 5
16 [anonymised] 2019-06-01 13:47 1.0.0 Solution naive-bayes self-made 0.78317 0.59102 2
17 [anonymised] 2019-06-04 22:16 1.0.0 solution 2e naive-bayes multinomial self-made 0.78242 0.59054 2
18 [anonymised] 2019-05-27 17:25 1.0.0 Naive bayes - selfmade2 naive-bayes self-made 0.78150 0.59042 7
19 [anonymised] 2019-05-06 16:39 1.0.0 naive bayes ZAJECIA naive-bayes multinomial self-made 0.78404 0.58889 2
20 Patryk Dolata 2020-05-06 14:03 1.0.0 ISI-048 probabilities with kenlm kenlm 0.77812 0.58818 1
21 klaganowski 2020-05-11 13:45 1.0.0 KenLM v1 kenlm 0.77804 0.58771 2
22 [anonymised] 2019-05-08 12:06 1.0.0 naive bayes naive-bayes multinomial self-made 0.78442 0.58313 2
23 [anonymised] 2019-06-09 11:22 1.0.0 Zajecia Bayes final4 naive-bayes multinomial self-made 0.78442 0.58313 4
24 [anonymised] 2019-05-26 13:40 1.0.0 naive bayes with bpe naive-bayes bpe 0.76496 0.57607 5
25 Yevheniia Tsapkova 2020-06-12 21:29 1.0.0 lstm solution lstm 0.76362 0.57162 1
26 Antoni 2020-05-18 15:31 1.0.0 isrtlm first try irstlm 0.75750 0.56999 1
27 [anonymised] 2019-05-07 12:37 1.0.0 Naive Bayes naive-bayes multinomial self-made 0.76388 0.56434 1
28 Artur Nowakowski 2019-05-06 16:44 1.0.0 naive bayes naive-bayes multinomial self-made 0.78271 0.55833 2
29 [anonymised] 2019-05-30 12:45 1.0.0 second commit, naive bayes, self-made naive-bayes self-made 0.78250 0.55808 4
30 [anonymised] 2019-05-06 16:44 1.0.0 bayes first try naive-bayes multinomial self-made 0.77975 0.55472 2
31 [anonymised] 2019-05-17 19:03 1.0.0 Most positives and most negatives words naive-bayes multinomial 0.78275 0.54941 5
32 [anonymised] 2019-05-07 16:38 1.0.0 classes naive-bayes multinomial self-made 0.78146 0.54912 2
33 [anonymised] 2019-05-07 21:27 1.0.0 lower() naive-bayes multinomial self-made 0.76379 0.54520 1
34 [anonymised] 2019-05-07 19:18 1.0.0 solution naive-bayes multinomial self-made 0.76362 0.54516 6
35 [anonymised] 2019-05-13 15:20 1.0.0 test-A naive-bayes multinomial self-made 0.75754 0.52830 6
36 Szymon Grad 2020-05-11 16:04 1.0.0 kenlm#15 kenlm 0.65150 0.52102 15
37 [anonymised] 2019-05-18 02:42 1.0.0 naive-bayes multino naive-bayes multinomial self-made 0.78675 0.50703 1
38 Bartosz 2020-05-25 19:37 1.0.0 IRSTLM v22 irstlm 0.59567 0.50327 23
39 p/tlen 2018-12-18 06:57 1.0.0 Null model stupid null-model 0.50267 0.50000 1
40 [anonymised] 2019-06-02 10:46 1.0.0 naiwny naive-bayes self-made 0.49733 0.38264 5
41 [anonymised] 2019-05-07 12:13 1.0.0 Bayes zajęcia naive-bayes multinomial self-made 0.78442 0.36763 1
42 [anonymised] 2019-06-01 14:35 1.0.0 naive bayes naive-bayes self-made 0.21725 0.00000 1
43 [anonymised] 2019-06-01 20:26 1.0.0 naive bayes ready made naive-bayes ready-made 0.78146 0.00000 1
44 [anonymised] 2019-06-01 17:34 1.0.0 my solution naive-bayes self-made 0.49742 0.00000 1
45 [anonymised] 2019-06-16 09:15 1.0.0 dk tw readymade naive-bayes self-made 0.50100 0.00000 1
46 [anonymised] 2019-05-24 09:09 1.0.0 NB sig 3 naive-bayes self-made 0.76638 0.00000 31
47 [anonymised] 2019-06-16 07:44 1.0.0 twitter ready made naive-bayes ready-made 0.76962 0.00000 2
48 [anonymised] 2019-06-16 09:05 1.0.0 Achievement07 naive-bayes ready-made 0.78267 0.00000 1
49 [anonymised] 2019-05-19 12:49 1.0.0 Bernoulii Bayes naive-bayes ready-made 0.78512 0.00000 1
50 [anonymised] 2019-05-31 18:30 1.0.0 twutter naive-bayes ready-made 0.77479 0.00000 2
51 [anonymised] 2019-05-29 16:48 1.0.0 bayes ready made naive-bayes ready-made 0.51829 0.00000 3
52 [anonymised] 2019-06-01 20:46 1.0.0 zadanie z twitterem naive-bayes self-made 0.21725 0.00000 2
53 [anonymised] 2019-06-01 16:51 1.0.0 bayes gotowy naive-bayes ready-made 0.78267 0.00000 3
54 [anonymised] 2019-05-19 11:31 1.0.0 tweety naive-bayes ready-made 0.78267 0.00000 2
55 [anonymised] 2019-05-19 12:11 1.0.0 tweet naive-bayes ready-made 0.78267 0.00000 1
56 [anonymised] 2019-06-02 08:33 1.0.0 Tweeter - self-made z zajęć 0.21725 0.00000 2
57 [anonymised] 2019-06-15 23:46 1.0.0 Twitter Bayes naive-bayes ready-made 0.78371 0.00000 1
58 Ivan Novgorodtsev 2020-06-21 16:20 1.0.0 roberta pretrained roberta 0.84529 0.00000 1