---
library_name: transformers
language:
- ug
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- cer
- wer
model-index:
- name: Whisper Small Fine-tuned with Uyghur Common Voice
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 15
      type: mozilla-foundation/common_voice_15_0
    metrics:
    - name: Wer
      type: wer
      value: 28.29947071879802
    - name: Cer
      type: cer
      value: 10.896777936451267
---

<!-- 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 Uyghur Common Voice

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Uyghur Common Voice dataset.

This model achieves the following results on the evaluation set:
- Loss: 1.5920
- Wer Ortho: 42.9701
- Wer: 28.2995
- Cer: 10.8968

## Training and evaluation data

The training was done using the combined train and dev set of common_voice_15_0 (11215 recordings, \~20hrs of audio). 

The testing was done using the test set of THUYG20 as the standard benchmark for Uyghur speech models.

## Training procedure

### 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss |  Epoch  | Step | Validation Loss | Wer Ortho |    Wer    |    Cer    |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:---------:|:---------:|
| 0.574400      | 0.7133  | 500  | 1.413890        | 59.765522 | 48.561550 | 17.639905 |
| 0.299600      | 1.4256  | 1000 | 1.283326        | 52.819004 | 41.377838 | 14.717958 |
| 0.130600      | 2.1398  | 1500 | 1.379338        | 52.265742 | 38.953389 | 16.260934 |
| 0.122500      | 2.8531  | 2000 | 1.313730        | 50.245894 | 36.494793 | 14.762585 |
| 0.060500      | 3.5663  | 2500 | 1.434626        | 47.589356 | 32.998976 | 12.185938 |
| 0.019500      | 4.2796  | 3000 | 1.526625        | 45.345570 | 30.975756 | 11.307346 |
| 0.015300      | 4.9929  | 3500 | 1.531676        | 44.120488 | 29.285470 | 11.690021 |
| 0.003300      | 5.7061  | 4000 | 1.592020        | 42.970054 | 28.299471 | 10.896778 |


### Framework versions

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