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# SocBERT model
Pretrained model on 20GB English tweets and 72GB Reddit comments using a masked language modeling (MLM) objective.
The tweets are from Archive and collected from Twitter Streaming API.
The Reddit comments are ramdonly sampled from all subreddits from 2015-2019.
SocBERT-base was pretrained on 819M sequence blocks for 100K steps.
SocBERT-final was pretrained on 929M (819M+110M) sequence blocks for 112K (100K+12K) steps.
We benchmarked SocBERT, on 40 text classification tasks with social media data.
The experiment results can be found in our paper:
```
@inproceedings{socbert:2023,
title = {{SocBERT: A Pretrained Model for Social Media Text}},
author = {Yuting Guo and Abeed Sarker},
booktitle = {Proceedings of the Fourth Workshop on Insights from Negative Results in NLP},
year = {2023}
}
```
A base version of the model can be found at [SocBERT-base](https://huggingface.co/sarkerlab/SocBERT-base). |