File size: 1,894 Bytes
4490708 5a7592e 4490708 672d32c 4490708 672d32c 4490708 672d32c 4490708 672d32c e90c4fc 4490708 e90c4fc 672d32c 4490708 672d32c 4490708 672d32c 4490708 672d32c 4490708 672d32c 4490708 672d32c 5a7592e 4490708 5a7592e 4490708 5a7592e 4490708 5a7592e 4490708 5a7592e 4490708 fa2a181 5a7592e 4490708 5a7592e 9cf6d72 4490708 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
---
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:
```
{'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.
## 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 |