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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: turkic-cyrillic-classifier
    results: []
language:
  - ba
  - cv
  - sah
  - tt
  - ky
  - kk
  - tyv
  - krc
  - ru
datasets:
  - tatiana-merz/cyrillic_turkic_langs
pipeline_tag: text-classification

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:

  • Loss: 0.0139
  • Accuracy: 0.9971
  • F1: 0.9971

Model description

The model classifies text based on a provided Turkic language written in Cyrillic script.

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
0.1087 1.0 1000 0.0206 0.9954 0.9954
0.0111 2.0 2000 0.0139 0.9971 0.9971

Framework versions

  • Transformers 4.27.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2