---
library_name: transformers
language:
- tk
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small TK - Abdyrahman Gudratullayew
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: tk
      split: test
      args: 'config: tk, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 57.933673469387756
---

<!-- 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 TK - Abdyrahman Gudratullayew

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: 1.3114
- Wer: 57.9337

## 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0083        | 14.0845 | 1000 | 1.1117          | 60.3571 |
| 0.0003        | 28.1690 | 2000 | 1.2099          | 57.7041 |
| 0.0002        | 42.2535 | 3000 | 1.2640          | 58.0102 |
| 0.0001        | 56.3380 | 4000 | 1.2973          | 58.1378 |
| 0.0001        | 70.4225 | 5000 | 1.3114          | 57.9337 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0