readme: ---
  language: ti
  widget:
  - text: "ድምጻዊ ኣብርሃም ኣፈወርቂ ንዘልኣለም ህያው ኮይኑ ኣብ ልብና ይነብር"
  - text: "ወአመ ሳብዕት ዕለት ቦዘወፅአ እምውስተ ሕዝብ ከመ ያስተጋብእ ወኢረከበ።"
  - text: "እሊ እግል ኖሱ አሳስ ተጠውር ወዐቦት ክምሰልቱ ሸክ ኢወትውዴ።"
  - text: "ኣኩኽር ፡ ልሽክክ ናው ጀረቢነዅስክ ክሙኑኽር ክራውል ሕበርሲድኖ ገረሰነኵ።"
  - text: "ነገ ለግማሽ ፍፃሜ ያለፉትን አሳውቀንና አስመርጠናችሁ እንሸልማለን።"
  tags:
  - geezlab
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: geezswitch-tiroberta
    results: []
  license: cc-by-4.0
  ---
  
  
  # TiRoBERTa-GeezSwitch
  
  This model is a fine-tuned version of [fgaim/tiroberta-base](https://huggingface.co/fgaim/tiroberta-base) on the [GeezSwitch](https://github.com/fgaim/geezswitch-data) dataset.
  
  It achieves the following results on the test set:
  
  - F1: 0.9948
  - Recall: 0.9948
  - Precision: 0.9948
  - Accuracy: 0.9948
  - Loss: 0.0222
  
  ## Training
  
  ### Hyperparameters
  
  The following hyperparameters were used during training:
  
  - learning_rate: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  - seed: 42
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  
  ### Citation
  
  If you use this model or the GeezSwitch model in your research, please cite as follows:
  
  ```markdown
  @inproceedings{fgaim2022geezswitch,
    title={GeezSwitch: Language Identification in Typologically Related Low-resourced East African Languages},
    author={Fitsum Gaim and Wonsuk Yang and Jong C. Park},
    booktitle={Proceedings of the 13th Language Resources and Evaluation Conference},
    year={2022}
  }
  ```
  