---
language:
- uz
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Uzbek
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 uz
      type: mozilla-foundation/common_voice_11_0
      config: uz
      split: test
      args: uz
    metrics:
    - name: Wer
      type: wer
      value: 25.785707218942715
---

<!-- 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 Uzbek

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 uz dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4357
- Wer: 25.7857

## 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: 32
- eval_batch_size: 16
- 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3621        | 1.03  | 1000 | 0.4819          | 32.3209 |
| 0.2378        | 2.07  | 2000 | 0.4413          | 29.0077 |
| 0.2342        | 4.01  | 3000 | 0.4224          | 27.3939 |
| 0.1286        | 5.04  | 4000 | 0.4357          | 25.7857 |
| 0.1192        | 6.08  | 5000 | 0.4727          | 27.2752 |
| 0.0147        | 8.02  | 6000 | 0.5230          | 26.7267 |
| 0.0425        | 9.05  | 7000 | 0.5336          | 26.3628 |
| 0.0059        | 10.08 | 8000 | 0.5658          | 26.8476 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2