Eur-lex-documents
Eur-lex-documents multilabel long documents classification. Assign one, more than one or none labels to each doc. [ver. 2.0.2]
This is a long list of all submissions, if you want to see only the best, click leaderboard.
# | submitter | when | ver. | description | dev-0 Likelihood | dev-0 F1 | test-A Likelihood | test-A F1 | |
---|---|---|---|---|---|---|---|---|---|
31 | [anonymized] | 2022-09-24 18:06 | 2.0.2 | PetraRQ Classifier - 10k samples neural-network pytorch-nn roberta | 0.17 | 39.10 | 0.11 | 38.24 | |
32 | [anonymized] | 2022-09-24 18:06 | 2.0.2 | PetraRQ Classifier - 1k samples neural-network pytorch-nn roberta | 0.03 | 37.86 | 0.03 | 38.24 | |
34 | [anonymized] | 2022-09-24 18:05 | 2.0.2 | PetraRQ Classifier - 100 samples neural-network pytorch-nn roberta | 0.00 | 33.75 | 0.00 | 34.21 | |
33 | [anonymized] | 2022-09-23 15:00 | 2.0.2 | Roberta classifier - 1k samples neural-network roberta | 0.00 | 33.75 | 0.00 | 34.21 | |
9 | [anonymized] | 2022-09-22 09:09 | 2.0.2 | PetraRQ Classifier neural-network pytorch-nn roberta | 1.02 | 67.24 | 5.33 | 75.32 | |
8 | [anonymized] | 2022-09-13 22:56 | 2.0.2 | Fast text classifier - full dataset python fasttext | 0.00 | 79.68 | 21.75 | 81.80 | |
10 | [anonymized] | 2022-09-13 22:56 | 2.0.2 | Fast text classifier - 10k samples python fasttext | 0.00 | 63.57 | 8.81 | 67.87 | |
71 | [anonymized] | 2022-09-13 22:55 | 2.0.2 | Fast text classifier - 1k samples python fasttext | 0.00 | 21.35 | 0.00 | 24.47 | |
76 | [anonymized] | 2022-09-13 22:55 | 2.0.2 | Fast text classifier - 100 samples python fasttext | 0.00 | 0.00 | 0.00 | 0.00 | |
17 | [anonymized] | 2022-09-13 22:55 | 2.0.2 | XGBoost classifier - full dataset scikit-learn xgboost | 0.02 | 47.38 | 0.05 | 49.81 | |
19 | [anonymized] | 2022-09-13 22:54 | 2.0.2 | XGBoost classifier - 10k samples scikit-learn xgboost | 0.05 | 39.10 | 0.06 | 39.95 | |
47 | [anonymized] | 2022-09-13 22:54 | 2.0.2 | XGBoost classifier - 1k samples scikit-learn xgboost | 0.01 | 28.00 | 0.01 | 28.32 | |
69 | [anonymized] | 2022-09-13 22:54 | 2.0.2 | XGBoost classifier - 100 samples scikit-learn xgboost | 0.00 | 25.76 | 0.00 | 24.52 | |
67 | [anonymized] | 2022-08-24 20:09 | 2.0.2 | Random forest classifier - full dataset scikit-learn random-forest | 1.41 | 23.05 | 1.75 | 26.42 | |
46 | [anonymized] | 2022-08-24 20:09 | 2.0.2 | Random forest classifier - 10k samples scikit-learn random-forest | 0.25 | 31.24 | 0.27 | 30.22 | |
40 | [anonymized] | 2022-08-24 20:08 | 2.0.2 | Random forest classifier - 1k samples scikit-learn random-forest | 0.04 | 34.89 | 0.04 | 33.96 | |
48 | [anonymized] | 2022-08-24 20:08 | 2.0.2 | Random forest classifier - 100 samples scikit-learn random-forest | 0.01 | 28.16 | 0.01 | 28.09 | |
39 | [anonymized] | 2022-08-24 20:07 | 2.0.2 | SVM classifier - full dataset scikit-learn svm | 0.00 | 34.33 | 0.00 | 34.08 | |
50 | [anonymized] | 2022-08-24 20:06 | 2.0.2 | SVM classifier - 10k samples scikit-learn svm | 0.00 | 26.31 | 0.00 | 26.58 | |
75 | [anonymized] | 2022-08-24 20:05 | 2.0.2 | SVM classifier - 1k samples scikit-learn svm | 0.00 | 15.89 | 0.00 | 15.23 | |
70 | [anonymized] | 2022-08-24 20:05 | 2.0.2 | SVM classifier - 100 samples scikit-learn svm | 0.00 | 24.59 | 0.00 | 24.50 | |
61 | [anonymized] | 2022-08-24 20:01 | 2.0.2 | Naive bayes classifier - full dataset naive-bayes scikit-learn | 0.49 | 23.71 | 0.57 | 26.48 | |
44 | [anonymized] | 2022-08-24 20:01 | 2.0.2 | Naive bayes classifier - 10k samples naive-bayes scikit-learn | 0.05 | 31.57 | 0.05 | 30.34 | |
45 | [anonymized] | 2022-08-24 20:01 | 2.0.2 | Naive bayes classifier - 1k samples naive-bayes scikit-learn | 0.04 | 31.51 | 0.05 | 30.26 | |
42 | [anonymized] | 2022-08-24 20:01 | 2.0.2 | Naive bayes classifier - 100 samples naive-bayes scikit-learn | 0.00 | 32.52 | 0.00 | 32.88 | |
29 | [anonymized] | 2022-08-24 20:00 | 2.0.2 | Logistic regression classifier - full dataset logistic-regression scikit-learn | 0.00 | 38.21 | 0.00 | 39.24 | |
49 | [anonymized] | 2022-08-23 06:04 | 2.0.2 | Logistic regression classifier - 10k samples logistic-regression scikit-learn | 0.00 | 27.91 | 0.00 | 27.85 | |
74 | [anonymized] | 2022-08-22 22:40 | 2.0.2 | Logistic regression classifier - 1k samples logistic-regression scikit-learn | 0.00 | 16.04 | 0.00 | 15.68 | |
73 | [anonymized] | 2022-08-22 20:52 | 2.0.2 | Logistic regression classifier - 100 samples logistic-regression scikit-learn | 0.00 | 20.06 | 0.00 | 20.01 | |
11 | [anonymized] | 2022-07-15 06:59 | 2.0.2 | Roberta classifier - 10k samples neural-network roberta | 0.50 | 62.19 | 0.46 | 61.86 | |
43 | [anonymized] | 2022-07-15 06:58 | 2.0.2 | Roberta classifier - 100 samples neural-network roberta | 0.00 | 31.90 | 0.00 | 30.80 | |
18 | [anonymized] | 2022-07-15 06:58 | 2.0.2 | Roberta classifier - 1k samples neural-network roberta | 0.11 | 45.20 | 0.08 | 44.15 | |
1 | [anonymized] | 2022-07-15 06:57 | 2.0.2 | RoBERTa classifier - full dataset neural-network roberta | 13.24 | 85.61 | 15.97 | 87.04 | |
38 | [anonymized] | 2022-07-14 23:10 | 2.0.2 | SVM classifier - 10k samples svm | 0.00 | 34.33 | 0.00 | 34.08 | |
37 | [anonymized] | 2022-07-14 23:10 | 2.0.2 | SVM classifier - 1k samples svm | 0.00 | 34.33 | 0.00 | 34.08 | |
36 | [anonymized] | 2022-07-14 23:10 | 2.0.2 | SVM classifier - 100 samples svm | 0.00 | 34.33 | 0.00 | 34.08 | |
35 | [anonymized] | 2022-07-14 23:09 | 2.0.2 | SVM classifier - full dataset svm | 0.00 | 34.33 | 0.00 | 34.08 | |
7 | [anonymized] | 2022-07-14 23:01 | 2.0.2 | Fast text classifier - 10k samples fasttext | 0.00 | 79.68 | 21.75 | 81.80 | |
6 | [anonymized] | 2022-07-14 23:00 | 2.0.2 | Fast text classifier - 1k samples fasttext | 0.00 | 79.68 | 21.75 | 81.80 | |
5 | [anonymized] | 2022-07-14 23:00 | 2.0.2 | Fast text classifier - 100 samples fasttext | 0.00 | 79.68 | 21.75 | 81.80 | |
4 | [anonymized] | 2022-07-14 22:59 | 2.0.2 | Fast text classifier - full dataset fasttext | 0.00 | 79.68 | 21.75 | 81.80 | |
16 | [anonymized] | 2022-07-14 22:59 | 2.0.2 | XGBoost classifier - 10k samples xgboost | 0.02 | 47.38 | 0.05 | 49.81 | |
15 | [anonymized] | 2022-07-14 22:58 | 2.0.2 | XGBoost classifier - 1k samples xgboost | 0.02 | 47.38 | 0.05 | 49.81 | |
14 | [anonymized] | 2022-07-14 22:58 | 2.0.2 | XGBoost classifier - 100 samples xgboost | 0.02 | 47.38 | 0.05 | 49.81 | |
13 | [anonymized] | 2022-07-14 22:57 | 2.0.2 | XGBoost classifier - full dataset xgboost | 0.02 | 47.38 | 0.05 | 49.81 | |
66 | [anonymized] | 2022-07-14 22:56 | 2.0.2 | Random forest classifier - 10k samples random-forest | 1.41 | 23.05 | 1.75 | 26.42 | |
65 | [anonymized] | 2022-07-14 22:56 | 2.0.2 | Random forest classifier - 1k samples random-forest | 1.41 | 23.05 | 1.75 | 26.42 | |
64 | [anonymized] | 2022-07-14 22:55 | 2.0.2 | Random forest classifier - 100 samples random-forest | 1.41 | 23.05 | 1.75 | 26.42 | |
63 | [anonymized] | 2022-07-14 22:55 | 2.0.2 | Random forest classifier - full dataset random-forest | 1.41 | 23.05 | 1.75 | 26.42 | |
60 | [anonymized] | 2022-07-14 22:54 | 2.0.2 | Naive bayes classifier - 100 samples naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
59 | [anonymized] | 2022-07-14 22:54 | 2.0.2 | Naive bayes classifier - 10k samples naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
58 | [anonymized] | 2022-07-14 22:53 | 2.0.2 | Naive bayes classifier - 1k samples naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
57 | [anonymized] | 2022-07-14 22:53 | 2.0.2 | Naive bayes classifier - full dataset naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
28 | [anonymized] | 2022-07-14 22:52 | 2.0.2 | Logistic regression classifier - 10k samples logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
27 | [anonymized] | 2022-07-14 22:49 | 2.0.2 | Logistic regression classifier - full dataset logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
26 | [anonymized] | 2022-07-14 22:49 | 2.0.2 | Logistic regression classifier - full dataset logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
25 | [anonymized] | 2022-07-14 22:48 | 2.0.2 | Logistic regression classifier - full dataset logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
62 | [anonymized] | 2022-07-11 22:21 | 2.0.2 | Logistic Regression 100 samples naive-bayes | 1.41 | 23.05 | 1.75 | 26.42 | |
24 | [anonymized] | 2022-07-11 22:20 | 2.0.2 | Logistic regression classifier logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
23 | [anonymized] | 2022-07-11 22:20 | 2.0.2 | Logistic regression classifier logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
22 | [anonymized] | 2022-07-11 22:19 | 2.0.2 | Logistic regression classifier logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
56 | [anonymized] | 2022-07-11 22:19 | 2.0.2 | Naive bayes classifier naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
55 | [anonymized] | 2022-07-11 22:19 | 2.0.2 | Naive bayes classifier naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
54 | [anonymized] | 2022-07-11 22:18 | 2.0.2 | Naive bayes classifier naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
53 | [anonymized] | 2022-07-11 22:18 | 2.0.2 | Naive bayes classifier naive-bayes | 0.49 | 23.71 | 0.57 | 26.48 | |
21 | [anonymized] | 2022-07-11 22:15 | 2.0.2 | Logistic regression classifier logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
30 | [anonymized] | 2022-06-21 06:05 | 2.0.2 | Logistic regression logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
2 | [anonymized] | 2022-05-15 21:08 | 2.0.2 | RoBERTa neural-network roberta | 7.80 | 84.88 | 10.49 | 86.68 | |
3 | [anonymized] | 2022-03-22 06:40 | 2.0.2 | Fast Text fasttext | 18.95 | 79.59 | 0.00 | 81.81 | |
12 | [anonymized] | 2022-03-15 01:35 | 2.0.2 | XGBoost xgboost | 0.00 | 47.38 | 0.00 | 49.81 | |
68 | [anonymized] | 2022-03-15 01:35 | 2.0.2 | Random forest random-forest | 1.44 | 22.89 | 1.77 | 26.26 | |
52 | [anonymized] | 2022-03-15 01:34 | 2.0.2 | Naive Bayes naive-bayes | 0.00 | 23.71 | 0.00 | 26.48 | |
20 | [anonymized] | 2022-03-15 01:33 | 2.0.2 | Logistic Regression logistic-regression | 0.00 | 38.21 | 0.00 | 39.24 | |
51 | [anonymized] | 2022-03-04 00:29 | 2.0.2 | Naive Bayes naive-bayes | 0.00 | 23.71 | 0.00 | 26.48 | |
41 | [anonymized] | 2022-03-04 00:28 | 2.0.2 | SVM svm | 0.00 | 33.99 | 0.00 | 33.77 | |
72 | [anonymized] | 2022-03-04 00:28 | 2.0.2 | Random forest random-forest | 1.43 | 21.35 | 1.76 | 24.43 | |
80 | [anonymized] | 2022-01-24 06:58 | 1.0.1 | Roberta base - new ds neural-network roberta-base | N/A | N/A | N/A | N/A | |
79 | p/tlen | 2022-01-15 13:26 | 1.0.1 | RoBERTa classifier neural-network roberta-base | N/A | N/A | N/A | N/A | |
78 | [anonymized] | 2022-01-14 07:30 | 1.0.1 | roberta-base neural-network roberta-base | N/A | N/A | N/A | N/A | |
77 | [anonymized] | 2021-12-26 11:49 | 1.0.0 | RoBERTa classifier neural-network roberta-base | N/A | N/A | N/A | N/A |