---
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Tiny UZ - 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: 50.19916836282356
---

<!-- 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 Tiny UZ - Bahriddin Muminov

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5943
- Wer: 50.1992

## 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: Use OptimizerNames.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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.6528        | 0.0352 | 2000  | 0.8591          | 62.8798 |
| 0.5201        | 0.0704 | 4000  | 0.7052          | 56.4951 |
| 0.4258        | 0.1056 | 6000  | 0.6407          | 53.7817 |
| 0.4136        | 0.1408 | 8000  | 0.6057          | 50.5588 |
| 0.4164        | 0.1760 | 10000 | 0.5943          | 50.1992 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1