readme: ---
  language: de
  tags:
  - bert
  license: apache-2.0
  
  widget:
  - text: "Das Frühstück ist sehr gut, es gibt auch Laktosefreie Produkte."
    example_title: "Example 1"
  - text: "Das Personal ist sehr kompetent und sehr freundlich."
    example_title: "Example 2"
  - text: "Die Zimmer sind wie beschrieben sehr klein, vergleichbar mit einer Kreuzfahrtschiffkabine. "
    example_title: "Example 3"
  - text: "Scheinwerfer vor dem Zimmer ganze Nacht an und zu hell"
    example_title: "Example 4"
  ---
  
  # German Hotel Review Sentiment Classification
  A model trained on German Hotel Reviews from Switzerland. The base model is the [bert-base-german-cased](https://huggingface.co/bert-base-german-cased). The last hidden layer of the base model was extracted and a classification layer was added. The entire model was then trained for 5 epochs on our dataset.
  
  # Model Performance
  
  | Classes | Precision | Recall | F1 Score |
  | :--- | :---: | :---: |:---: |
  | Room | 84.62% | 88.00% | 86.27% |
  | Food | 79.17% | 82.61% | 80.85% |
  | Staff | 63.64% | 70.00% | 66.67% |
  | Location | 83.33% | 62.50% | 71.43% |
  | GeneralUtilitys | 76.92% | 76.92% | 76.92% |
  | HotelOrganisation | 26.67% | 30.77% | 28.57% |
  | Unknown | 25.00% | 16.67% | 20.00% |
  | ReasonForStay | 100.00% | 50.00% | 66.67% |
  | Accuracy |  |  | 69.00% |
  | Macro Average | 67.42% | 59.68% | 62.17% |
  | Weighted Average | 69.36% | 69.00% | 68.79% |
  
  ## Confusion Matrix
  ![Confusion Matrix](bert-base-german-cased_German_classification.jpg)
  