fgaim/tielectra-geezswitch

TiELECTRA-GeezSwitch

This model is a fine-tuned version of fgaim/tielectra-small on the GeezSwitch dataset.

It achieves the following results on the test set:

• —F1: 0.9844
• —Recall: 0.9844
• —Precision: 0.9845
• —Accuracy: 0.9844
• —Loss: 0.2190

Training

Hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: 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:

@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}
}