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---
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: 28.258182136033867
---

<!-- 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 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: 0.2958
- Wer: 28.2582

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.429         | 0.66  | 2000  | 0.4073          | 38.0018 |
| 0.2671        | 1.32  | 4000  | 0.3378          | 31.0778 |
| 0.2511        | 1.98  | 6000  | 0.3102          | 29.2484 |
| 0.1539        | 2.64  | 8000  | 0.3022          | 30.0763 |
| 0.111         | 3.3   | 10000 | 0.2958          | 28.2582 |


### Framework versions

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