https://github.com/cozek/memotion2020-code
https://github.com/cozek/memotion2020-code
classifier efficientnet kaggle memes notebook semeval-2020
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/cozek/memotion2020-code
- Owner: cozek
- Created: 2020-05-07T07:45:52.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-12-09T11:56:37.000Z (about 5 years ago)
- Last Synced: 2025-02-06T03:39:36.005Z (about 1 year ago)
- Topics: classifier, efficientnet, kaggle, memes, notebook, semeval-2020
- Language: Python
- Size: 18.6 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# memotion2020-code
[Memotion Analysis 2020](https://competitions.codalab.org/competitions/20629)
Paper link: https://www.aclweb.org/anthology/2020.semeval-1.152.pdf
This repo contains the base code used Team KAFK for the Memotion Analysis Task.
Since the data is publicly posted on Kaggle, we have released two notebooks containing the code for
our classifier and exploratory data analysis at Kaggle itself. Please find their links below.
Notebooks:
1. EDA Notebook: https://www.kaggle.com/coseck/memotion-eda
2. Classifier Notebook: https://www.kaggle.com/coseck/team-kafk-classification-models-for-task-a-and-b
Credits:
- RAdam : https://github.com/LiyuanLucasLiu/RAdam
- LookAhead: https://github.com/lonePatient/lookahead_pytorch
- Transformers: https://github.com/huggingface/transformers
- EffecientNet: https://github.com/lukemelas/EfficientNet-PyTorch
If you use our scripts please cite:
```
@inproceedings{das2020kafk,
title={KAFK at SemEval-2020 Task 8: Extracting Features from Pre-trained Neural Networks to Classify Internet Memes},
author={Das, Kaushik Amar and Baruah, Arup and Barbhuiya, Ferdous Ahmed and Dey, Kuntal},
booktitle={Proceedings of the Fourteenth Workshop on Semantic Evaluation},
pages={1148--1154},
year={2020}
}
```