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roberta-pubhealth
hhhhzy/roberta-pubhealth
roberta-pubhealth is a text classification model from hhhhzy. Use it when you need a label for a piece of text. It is set up for transformers.
This model is a fine-tuned version of RoBERTa Base on the healthfact dataset. It achieves the following results on the evaluation set: - micro f1 (accuracy): 0.7137 - macro f1: 0.6056 - weighted f1: 0.7106 - samples p…
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- May 30, 2022
- Updated
- May 30, 2022
- SHA
- 6f7133ef
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Model card
From the Hugging Face model README
Roberta-Pubhealth model
This model is a fine-tuned version of RoBERTa Base on the health_fact dataset. It achieves the following results on the evaluation set:
- micro f1 (accuracy): 0.7137
- macro f1: 0.6056
- weighted f1: 0.7106
- samples predicted per second: 9.31
Dataset desctiption
PUBHEALTHis a comprehensive dataset for explainable automated fact-checking of public health claims. Each instance in the PUBHEALTH dataset has an associated veracity label (true, false, unproven, mixture). Furthermore each instance in the dataset has an explanation text field. The explanation is a justification for which the claim has been assigned a particular veracity label.
Training hyperparameters
The model are trained with the following tuned config:
- model: roberta base
- batch size: 32
- learning rate: 5e-5
- number of epochs: 4
- warmup steps: 0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- May 30, 2022
- Updated
- May 30, 2022