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

cyrillic_turkic_langs

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
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Dataset used to train tatiana-merz/turkic-cyrillic-classifier