---
library_name: transformers
language:
- ug
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- THUGY20
metrics:
- cer
- wer
model-index:
- name: Whisper Small Fine-tuned with THUYG20 Uyghur Dataset
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 'THUGY20: A free Uyghur speech database'
      type: THUGY20
    metrics:
    - name: Cer
      type: cer
      value: 4.927369689396644
    - name: Wer
      type: wer
      value: 17.940071709066075
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Fine-tuned with THUYG20 Uyghur Dataset

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the THUGY20: A free Uyghur speech database dataset.
It achieves the following results on the test set of THUGY20:
- Loss: 0.7473
- Wer Ortho: 18.0908
- Wer: 17.9401
- Cer: 4.9274

## Training procedure

Finetuning code avaiblable in https://github.com/ixxan/ug-speech

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     | Cer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:-------:|
| 0.3815        | 0.8058 | 500  | 0.7944          | 34.8819   | 34.7960 | 10.4265 |
| 0.1343        | 1.6116 | 1000 | 0.7441          | 28.3393   | 28.3550 | 8.3051  |
| 0.0646        | 2.4174 | 1500 | 0.7396          | 27.7378   | 27.5653 | 8.5366  |
| 0.0311        | 3.2232 | 2000 | 0.6984          | 25.1910   | 24.9445 | 7.5643  |
| 0.0176        | 4.0290 | 2500 | 0.6934          | 21.3709   | 21.2523 | 5.8316  |
| 0.0075        | 4.8348 | 3000 | 0.7654          | 20.5541   | 20.3603 | 5.7519  |
| 0.0023        | 5.6406 | 3500 | 0.7686          | 18.7582   | 18.5846 | 5.1923  |
| 0.0004        | 6.4464 | 4000 | 0.7473          | 18.0908   | 17.9401 | 4.9274  |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3