distilbert health tweet

distilbert-phmtweets-sutd

This model is a fine-tuned version of distilbert-base-uncased for text classification to identify public health events through tweets. The project was based on an Emory University Study on Detection of Personal Health Mentions in Social Media paper, that worked with this custom dataset.

It achieves the following results on the evaluation set:

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dibsondivya/distilbert-phmtweets-sutd")
model = AutoModelForSequenceClassification.from_pretrained("dibsondivya/distilbert-phmtweets-sutd")

Model Evaluation Results

With Validation Set

With Test Set

Reference for distilbert-base-uncased Model

@article{Sanh2019DistilBERTAD,
  title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter},
  author={Victor Sanh and Lysandre Debut and Julien Chaumond and Thomas Wolf},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.01108}
}