Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fine-Tuning Approach for Arabic Offensive Language Detection System:
  BERT-Based Model   The problem of online offensive language limits the health and security of
online users. It is essential to apply the latest state-of-the-art techniques
in developing a system to detect online offensive language and to ensure social
justice to the online communities. Our study investigates the effects of
fine-tuning across several Arabic offensive language datasets. We develop
multiple classifiers that use four datasets individually and in combination in
order to gain knowledge about online Arabic offensive content and classify
users comments accordingly. Our results demonstrate the limited effects of
transfer learning on the classifiers performance, particularly for highly
dialectal comments.

10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an
29
The categories of this paper are: funct-an
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con