Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy
Paper • 2205.11966 • Published
Model Description
This model is based on RoBERTa large (Liu, 2019), fine-tuned on a dataset of intent expressions available here and also on 🤗 Transformer datasets hub here.
The model was created as part of the work described in Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy . The model is released under the Community Data License Agreement - Sharing - Version 1.0 (link), If you use this model, please cite our paper.
The official GitHub is here. The script used for training the model is trainer.py.
Training parameters
- base_model = 'roberta-large'
- learning_rate=5e-6
- per_device_train_batch_size=16,
- per_device_eval_batch_size=16,
- num_train_epochs=15,
- load_best_model_at_end=True,
- save_total_limit=1,
- save_strategy='epoch',
- evaluation_strategy='epoch',
- metric_for_best_model='accuracy',
- seed=123
Data collator
DataCollatorWithPadding
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