---
language:
- uz
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo - Bahriddin Muminov
  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: 25.073985739794963
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large v3 Turbo - Bahriddin Muminov

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2643
- Wer: 25.0740

## 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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3109        | 0.04  | 2000  | 0.4220          | 36.8942 |
| 0.2529        | 0.07  | 4000  | 0.3593          | 31.0915 |
| 0.2123        | 0.11  | 6000  | 0.3150          | 28.2694 |
| 0.1936        | 0.14  | 8000  | 0.2773          | 27.4353 |
| 0.1716        | 0.18  | 10000 | 0.2643          | 25.0740 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2