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README.md
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model-index:
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- name: turkic-cyrillic-classifier
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results: []
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---
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This model card has been generated automatically according to the information the Trainer had access to. You
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# turkic-cyrillic-classifier
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0139
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- Accuracy: 0.9971
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## Model description
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-
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- Transformers 4.27.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: turkic-cyrillic-classifier
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results: []
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language:
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- ba
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- cv
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- sah
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- tt
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- ky
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- kk
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- tyv
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- krc
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- ru
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datasets:
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- tatiana-merz/cyrillic_turkic_langs
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pipeline_tag: text-classification
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# turkic-cyrillic-classifier
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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.
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It achieves the following results on the evaluation set:
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{'test_loss': 0.013604652136564255,
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'test_accuracy': 0.997,
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'test_f1': 0.9969996069718668,
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'test_runtime': 60.5479,
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'test_samples_per_second': 148.643,
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'test_steps_per_second': 2.329}
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## Model description
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The model classifies text based on a provided Turkic language written in Cyrillic script.
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## Intended uses & limitations
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## Training and evaluation data
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[cyrillic_turkic_langs](https://huggingface.co/datasets/tatiana-merz/cyrillic_turkic_langs/)
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.1063 | 1.0 | 1000 | 0.0204 | 0.9950 | 0.9950 |
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| 0.0126 | 2.0 | 2000 | 0.0136 | 0.9970 | 0.9970 |
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### Framework versions
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- Transformers 4.27.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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