Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: WASSA@IITK at WASSA 2021: Multi-task Learning and Transformer Finetuning
  for Emotion Classification and Empathy Prediction   This paper describes our contribution to the WASSA 2021 shared task on
Empathy Prediction and Emotion Classification. The broad goal of this task was
to model an empathy score, a distress score and the overall level of emotion of
an essay written in response to a newspaper article associated with harm to
someone. We have used the ELECTRA model abundantly and also advanced deep
learning approaches like multi-task learning. Additionally, we also leveraged
standard machine learning techniques like ensembling. Our system achieves a
Pearson Correlation Coefficient of 0.533 on sub-task I and a macro F1 score of
0.5528 on sub-task II. We ranked 1st in Emotion Classification sub-task and 3rd
in Empathy Prediction sub-task

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The categories of this paper are: bayes-an
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The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
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The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
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The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: acc-phys
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The categories of this paper are: supr-con
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th