readme: ---
  language: eng
  tags:
  - bert
  license: apache-2.0
  
  widget:
  - text: "The hotel is very nicely located"
    example_title: "Example 1"
  - text: "The reception staff were extremely helpful and very welcoming"
    example_title: "Example 2"
  - text: "There is no balcony in the rooms on the mountain side"
    example_title: "Example 3"
  - text: "A bit pricey"
    example_title: "Example 4"
  ---
  
  # English Hotel Review MultiLabel Classification
  A model trained on English Hotel Reviews from Switzerland. The base model is the [bert-base-uncased](https://huggingface.co/bert-base-uncased). 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 | 77.78% | 77.78% | 77.78% |
  | Location | 95.45% | 95.45% | 95.45% |
  | Staff | 75.00% | 93.75% | 83.33% |
  | Unknown | 71.43% | 50.00% | 58.82% |
  | HotelOrganisation | 27.27% | 30.00% | 28.57% |
  | Food | 87.50% | 87.50% | 87.50% |
  | ReasonForStay | 63.64% | 58.33% | 60.87%|
  | GeneralUtility | 66.67% | 50.00% | 66.67% |
  | Accuracy |  |  | 74.00% |
  | Macro Average | 70.59%| 67.85% | 68.68% |
  | Weighted Average | 74.17% | 74.00% | 73.66% |
  
  ## Confusion Matrix
  ![Confusion Matrix](bert-base-uncased_English_classification.jpg)