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--- |
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tags: |
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- generated_from_keras_callback |
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- politics |
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- agenda |
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- issues |
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- comparative agendas project |
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- political communication |
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- bills |
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- laws |
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- parliament |
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model-index: |
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- name: CAP_coded_US_Congressional_bills |
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results: [] |
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widget: |
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- text: >- |
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A bill to prohibt discrimination in employment because of race, color, |
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religion, national origin, or ancestry |
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example_title: example 1 |
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- text: >- |
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A bill to require the promulgation of regulations to improve aviation safety |
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in adverse weather conditions, and for other purposes. |
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example_title: example 2 |
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--- |
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This model predicts the issue category of US Congressional bills. |
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The model is trained on ~250k US Congressional bills from 1950-2015. |
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The issue coding scheme follows the Comparative Agenda Project: https://www.comparativeagendas.net/pages/master-codebook |
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The model is cased (case sensitive) |
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Train Loss: 0.1318; |
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Train Sparse Categorical Accuracy: 0.9268; |
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Validation Loss: 0.2439; |
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Validation Sparse Categorical Accuracy: 0.9161 |
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The following hyperparameters were used during training: |
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optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
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training_precision: float32 |
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### Training hyperparameters |
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### Framework versions |
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- Transformers 4.19.3 |
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- TensorFlow 2.8.2 |
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- Tokenizers 0.12.1 |
