ibm/roberta-large-vira-intents

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

1. base_model = 'roberta-large'
2. learning_rate=5e-6
3. per_device_train_batch_size=16,
4. per_device_eval_batch_size=16,
5. num_train_epochs=15,
6. load_best_model_at_end=True,
7. save_total_limit=1,
8. save_strategy='epoch',
9. evaluation_strategy='epoch',
10. metric_for_best_model='accuracy',
11. seed=123

Data collator

DataCollatorWithPadding