---
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: 30.20491240338149
---

<!-- 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: 0.3052
- Wer: 30.2049

## 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: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.4689        | 0.0210 | 1000  | 0.5616          | 48.2462 |
| 0.3234        | 0.0420 | 2000  | 0.4695          | 44.8210 |
| 0.3078        | 0.0630 | 3000  | 0.4184          | 38.8747 |
| 0.2845        | 0.0840 | 4000  | 0.3955          | 36.2861 |
| 0.2771        | 0.1050 | 5000  | 0.3720          | 35.5344 |
| 0.2459        | 0.1260 | 6000  | 0.3649          | 35.9415 |
| 0.2482        | 0.1470 | 7000  | 0.3499          | 34.3993 |
| 0.26          | 0.1680 | 8000  | 0.3389          | 32.9183 |
| 0.2128        | 0.1891 | 9000  | 0.3321          | 33.2493 |
| 0.2092        | 0.2101 | 10000 | 0.3215          | 31.4973 |
| 0.1942        | 0.2311 | 11000 | 0.3194          | 31.0465 |
| 0.1912        | 0.2521 | 12000 | 0.3184          | 31.2850 |
| 0.2199        | 0.2731 | 13000 | 0.3100          | 30.6395 |
| 0.1861        | 0.2941 | 14000 | 0.3059          | 30.8667 |
| 0.2344        | 0.3151 | 15000 | 0.3052          | 30.2049 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.2.0
- Datasets 2.19.2
- Tokenizers 0.19.1