readme: ---
  library_name: sklearn
  tags:
  - sklearn
  - skops
  - text-classification
  ---
  
  # Model description
  
  This is a logistic regression model trained with GPT-2 embeddings on imdb dataset.
  The notebook to generate this model is in this repository and in this [kaggle link](https://www.kaggle.com/code/unofficialmerve/scikit-learn-with-transformers-with-skops/notebook).
  
  ## Intended uses & limitations
  
  This model is trained for educational purposes.
  
  ## Training Procedure
  
  ### Hyperparameters
  
  The model is trained with below hyperparameters.
  
  <details>
  <summary> Click to expand </summary>
  
  | Hyperparameter                | Value                                                                                                             |
  |-------------------------------|-------------------------------------------------------------------------------------------------------------------|
  | memory                        |                                                                                                                   |
  | steps                         | [('embedding', HFTransformersLanguage(model_name_or_path='facebook/bart-base')), ('model', LogisticRegression())] |
  | verbose                       | False                                                                                                             |
  | embedding                     | HFTransformersLanguage(model_name_or_path='facebook/bart-base')                                                   |
  | model                         | LogisticRegression()                                                                                              |
  | embedding__model_name_or_path | facebook/bart-base                                                                                                |
  | model__C                      | 1.0                                                                                                               |
  | model__class_weight           |                                                                                                                   |
  | model__dual                   | False                                                                                                             |
  | model__fit_intercept          | True                                                                                                              |
  | model__intercept_scaling      | 1                                                                                                                 |
  | model__l1_ratio               |                                                                                                                   |
  | model__max_iter               | 100                                                                                                               |
  | model__multi_class            | auto                                                                                                              |
  | model__n_jobs                 |                                                                                                                   |
  | model__penalty                | l2                                                                                                                |
  | model__random_state           |                                                                                                                   |
  | model__solver                 | lbfgs                                                                                                             |
  | model__tol                    | 0.0001                                                                                                            |
  | model__verbose                | 0                                                                                                                 |
  | model__warm_start             | False                                                                                                             |
  
  </details>
  
  ### Model Plot
  
  The model plot is below.
  
  <style>#sk-c17251a9-68a0-4b34-a80a-a89592893866 {color: black;background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 pre{padding: 0;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-toggleable {background-color: white;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-c17251a9-68a0-4b34-a80a-a89592893866 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: lef