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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# turkic-cyrillic-classifier
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/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](https://huggingface.co/datasets/tatiana-merz/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 |