---
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
- automatic-speech-recognition
- whisper
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Uzbek
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      args: 'config: uz, split: test'
    metrics:
    - type: wer
      value: 35.8660
      name: Wer
---

<!-- 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 Uzbek

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3776
- Wer: 35.8660

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 1500
- training_steps: 5500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.913         | 0.2   | 500  | 0.8213          | 62.5843 |
| 0.6404        | 0.4   | 1000 | 0.6082          | 51.8716 |
| 0.5734        | 0.6   | 1500 | 0.5458          | 48.0513 |
| 0.5051        | 0.8   | 2000 | 0.4846          | 43.8649 |
| 0.4407        | 1.0   | 2500 | 0.4483          | 41.3901 |
| 0.3436        | 1.2   | 3000 | 0.4321          | 41.0277 |
| 0.3092        | 1.4   | 3500 | 0.4184          | 40.1141 |
| 0.2861        | 1.6   | 4000 | 0.4091          | 39.9753 |
| 0.289         | 1.8   | 4500 | 0.3811          | 36.7950 |
| 0.2816        | 2.0   | 5000 | 0.3730          | 36.7102 |
| 0.1547        | 2.2   | 5500 | 0.3776          | 35.8660 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.1.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0