Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Combination of multiple Deep Learning architectures for Offensive
  Language Detection in Tweets   This report contains the details regarding our submission to the OffensEval
2019 (SemEval 2019 - Task 6). The competition was based on the Offensive
Language Identification Dataset. We first discuss the details of the classifier
implemented and the type of input data used and pre-processing performed. We
then move onto critically evaluating our performance. We have achieved a
macro-average F1-score of 0.76, 0.68, 0.54, respectively for Task a, Task b,
and Task c, which we believe reflects on the level of sophistication of the
models implemented. Finally, we will be discussing the difficulties encountered
and possible improvements for the future.

35
The categories of this paper are: mtrl-th
9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph