---
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Uz - Aslon Khamidov -- with Uzbek Voice dataset
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 16.1
      type: mozilla-foundation/common_voice_16_1
      config: uz
      split: test
      args: 'config: uz, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 35.94645555236442
---

<!-- 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 Uz - Aslon Khamidov -- with Uzbek Voice dataset

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3910
- Wer: 35.9465

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.4411        | 0.0176 | 1000 | 0.5526          | 47.9128 |
| 0.327         | 0.0352 | 2000 | 0.4648          | 41.1885 |
| 0.2883        | 0.0528 | 3000 | 0.4286          | 37.6822 |
| 0.2777        | 0.0704 | 4000 | 0.4037          | 36.9479 |
| 0.2543        | 0.0880 | 5000 | 0.3910          | 35.9465 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.19.1