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tielectra-geezswitch – AI Model by fgaim | AlphaNeural AI

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fgaim/
tielectra-geezswitch

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text-classification

autotrain_compatible

endpoints_compatible

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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
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}
}