---
library_name: transformers
language:
- kk
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small KK - Kazakh - Fleurs Augmented
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Fleurs
      type: google/fleurs
      config: kk_kz
      split: test
      args: 'config: kk, split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 22.28911587634445
---

<!-- 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 KK - Kazakh - Fleurs Augmented

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2814
- Wer: 22.2891

## 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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3714        | 1.0   | 200  | 0.2556          | 23.7164 |
| 0.2797        | 2.0   | 400  | 0.2565          | 23.1212 |
| 0.1609        | 3.0   | 600  | 0.2644          | 22.2688 |
| 0.084         | 4.0   | 800  | 0.2738          | 22.3906 |
| 0.059         | 5.0   | 1000 | 0.2814          | 22.2891 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0