---
library_name: transformers
language:
- ug
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- THUGY20
metrics:
- 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: Wer
      type: wer
      value: 22.847080209043398
---

<!-- 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. -->

# 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 evaluation set:
- Loss: 0.3708
- Wer Ortho: 22.9277
- Wer: 22.8471
- Cer: 5.8681

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Cer    | Validation Loss | Wer     | Wer Ortho |
|:-------------:|:------:|:----:|:------:|:---------------:|:-------:|:---------:|
| 0.5311        | 0.8403 | 200  | 9.8849 | 0.5551          | 40.8203 | 40.8026   |
| 0.2102        | 1.6807 | 400  | 7.9473 | 0.4169          | 31.2599 | 31.2051   |
| 0.0712        | 2.5210 | 600  | 7.7075 | 0.3970          | 28.7094 | 28.7809   |
| 0.0227        | 3.3613 | 800  | 7.1401 | 0.3966          | 26.4656 | 26.4852   |
| 0.0109        | 4.2017 | 1000 | 6.7159 | 0.3661          | 24.5683 | 24.6218   |
| 0.0067        | 5.0420 | 1200 | 6.1440 | 0.3753          | 23.9434 | 24.0318   |
| 0.003         | 5.8824 | 1400 | 5.9610 | 0.3694          | 23.1822 | 23.2315   |
| 0.002         | 6.7227 | 1600 | 5.8850 | 0.3728          | 22.8925 | 22.9686   |
| 0.0017        | 7.5630 | 1800 | 5.8695 | 0.3708          | 22.8584 | 22.9394   |
| 0.0018        | 8.4034 | 2000 | 5.8681 | 0.3710          | 22.8471 | 22.9277   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0