---
language:
- uz
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- audio
- automatic-speech-recognition
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Tiny Uzbek
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0
      type: mozilla-foundation/common_voice_13_0
      config: uz
      split: test
      args: uz
    metrics:
    - name: Wer
      type: wer
      value: 36.79056163528213
pipeline_tag: automatic-speech-recognition
---

<!-- 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 Uzbek

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2981
- Wer Ortho: 47.7812
- Wer: 36.7906

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 50
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 0.2929        | 0.8   | 3000  | 0.3281          | 50.8851   | 40.4395 |
| 0.2194        | 1.59  | 6000  | 0.3110          | 49.2325   | 37.9320 |
| 0.177         | 2.39  | 9000  | 0.3003          | 47.8700   | 36.8366 |
| 0.1574        | 3.18  | 12000 | 0.2997          | 48.2291   | 37.0491 |
| 0.1524        | 3.98  | 15000 | 0.2958          | 47.2395   | 36.4400 |
| 0.1455        | 4.77  | 18000 | 0.2981          | 47.7812   | 36.7906 |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1