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turkic-cyrillic-classifier
This model is a fine-tuned version of bert-base-multilingual-cased on an tatiana-merz/cyrillic_turkic_langs dataset. It achieves the following results on the evaluation set:
{'test_loss': 0.013604652136564255,
'test_accuracy': 0.997,
'test_f1': 0.9969996069718668,
'test_runtime': 60.5479,
'test_samples_per_second': 148.643,
'test_steps_per_second': 2.329}
Model description
The model classifies text based on a provided Turkic language written in Cyrillic script.
Languages
- bak - Bashkir
- chv - Chuvash
- sah - Sakha
- tat - Tatar
- kir - Kyrgyz
- kaz - Kazakh
- tyv - Tuvinian
- krc - Karachay-Balkar
- rus - Russian
Intended uses & limitations
Training and evaluation data
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1063 | 1.0 | 1000 | 0.0204 | 0.9950 | 0.9950 |
| 0.0126 | 2.0 | 2000 | 0.0136 | 0.9970 | 0.9970 |
Framework versions
- Transformers 4.27.0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
