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US_politicians_covid_skepticism
z-dickson/US_politicians_covid_skepticism
US_politicians_covid_skepticism is a text classification model from z-dickson. Use it when you need a label for a piece of text. It is set up for transformers.
probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jun 30, 2022
- Updated
- May 1, 2024
- SHA
- c979fd75
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
This model is a fine-tuned version of vinai/bertweet-covid19-base-uncased on a dataset of 10k tweets about COVID-19 policies from US legislators in the House and Senate.
The model is intended to identify skepticism of COVID-19 policies (i.e. masks, social distancing, lockdowns, vaccines etc.).
It's a pretty simple task but I used a grid search to optimize hyperparameters. The model uses the following hyperparamters:
Optimized Hyperparameters
- The best learning rate is: 9.928559980965476e-06
- The best weight decay is: 0.003083325125091835
- The best epoch is : 5
- The best train split is : 0.2864649363822965
Training
- Train Loss: 0.1007
- Train Sparse Categorical Accuracy: 0.9591
- Validation Loss: 0.0913
- Validation Sparse Categorical Accuracy: 0.9627
- Optimizer: Adam
- Starting Learn rate: 5e-07
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jun 30, 2022
- Updated
- May 1, 2024