LABEL_0 LABEL_1 LABEL_10 LABEL_11 LABEL_12 LABEL_13 LABEL_14 LABEL_15 LABEL_16 LABEL_17 LABEL_18 LABEL_19 LABEL_2 LABEL_3 LABEL_4 LABEL_5 LABEL_6 LABEL_7 LABEL_8 LABEL_9
---
tags:
- generated_from_keras_callback
model-index:
- name: CAP_coded_UK_statutory_instruments
  results: []
  
widget:
- text: "The National Health Service (Charges for Drugs and Appliances) (Scotland) Regulations 2007"
  example_title: "example 1"
- text: "The Inshore Fishing (Prohibited Methods of Fishing) (Luce Bay) Order 2015"
  example_title: "example 2"
  
---



# CAP_coded_UK_statutory_instruments

This model predicts the CAP code of parliamentary bills/instruments (https://www.comparativeagendas.net/pages/master-codebook)

The model is trained on ~40k UK Parliamentary Statutory Instruments from the UK House of Commons and the Scottish Parliament. 
The model is cased (case sensitive)

Any questions on the model and training data feel free to message me on twitter - @sachary_


- Train Loss: 0.1188
- Train Sparse Categorical Accuracy: 0.9688
- Validation Loss: 0.2032
- Validation Sparse Categorical Accuracy: 0.9556




The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.2167     | 0.9474                            | 0.2351          | 0.9444                                 | 0     |
| 0.1539     | 0.9592                            | 0.2076          | 0.9536                                 | 1     |
| 0.1188     | 0.9688                            | 0.2032          | 0.9556                                 | 2     |


### Framework versions

- Transformers 4.19.2
- TensorFlow 2.8.2
- Datasets 2.2.2
- Tokenizers 0.12.1
