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# 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:

```
{'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](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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.1063        | 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
{"language": ["ba", "cv", "sah", "tt", "ky", "kk", "tyv", "krc", "ru"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["tatiana-merz/cyrillic_turkic_langs"], "metrics": ["accuracy", "f1"], "pipeline_tag": "text-classification", "widget": [{"text": "\u041a\u044b\u0440\u0430 \u0442\u044b\u0433\u044b\u043d"}], "model-index": [{"name": "turkic-cyrillic-classifier", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer ba cv sah tt ky kk tyv krc ru dataset:tatiana-merz/cyrillic_turkic_langs license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #ba #cv #sah #tt #ky #kk #tyv #krc #ru #dataset-tatiana-merz/cyrillic_turkic_langs #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

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:


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



### Framework versions


* Transformers 4.27.0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1



### 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 ### Framework versions


* Transformers 4.27.0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #ba #cv #sah #tt #ky #kk #tyv #krc #ru #dataset-tatiana-merz/cyrillic_turkic_langs #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.27.0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
TAGS
#transformers #pytorch #tensorboard #bert #text-classification #generated_from_trainer #ba #cv #sah #tt #ky #kk #tyv #krc #ru #dataset-tatiana-merz/cyrillic_turkic_langs #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.27.0
* Pytorch 1.13.1+cu116
* Datasets 2.10.1