---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
language:
- uz
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Small Uz - Doniyor Halilov
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: uz
      split: test
      args: 'config: uz, split: test'
    metrics:
    - type: wer
      value: 54.74920162871594
      name: Wer
---

<!-- 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 - Doniyor Halilov

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0147
- Wer: 54.7492

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.612         | 0.0132 | 100  | 1.2551          | 69.5533 |
| 1.1271        | 0.0264 | 200  | 1.0147          | 54.7492 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1