---
widget:
- text: >-
    The third is the path length between long-range dependencies in the
    network. 
  example_title: Intent Classify
language:
- en
pipeline_tag: text-classification
---
This model is finetuned SciBERT model for context classification in scientific journals.
The model classifies intentions of the scientific text, based on the topic of their description.
It categorizes if the context explains the background, result or method of the paper.
The output classes based on the text are as follows:
</br>
Text describing related work, introduction and uses are classified as <b>background</b>
</br>
Methods and implementation details are classified as <b>method</b>
</br>
Results and analysis are classified as <b>result</b>
</br>
</br>
For finetuning, I have used dataset from Cohan et al. https://aclanthology.org/N19-1361.pdf