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