---
language:
- ko
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- haseong8012/child-10k
metrics:
- wer
- cer
model-index:
- name: >-
    openai/whisper-small-Ko-haseong8012/child-10k
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: haseong8012/korean-child-command-voice_train-0-10000_smaplingRate-16000
      type: haseong8012/korean-child-command-voice_train-0-10000_smaplingRate-16000
      args: 'config: ko, split: train, validation, test'
    metrics:
    - name: Wer
      type: wer
      value: 14.96458761708933
---

<!-- 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. -->

# openai/whisper-small-Ko-haseong8012/korean-child-command-voice_train-0-10000_smaplingRate-16000

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the haseong8012/korean-child-command-voice_train-0-10000_smaplingRate-16000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1613
- Wer: 14.9646
- Cer: 7.4814

## 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: 1.25e-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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.0098        | 4.0   | 1000 | 0.1831          | 18.0032 | 9.0777 |
| 0.0007        | 8.0   | 2000 | 0.1634          | 15.6271 | 7.7868 |
| 0.0002        | 12.0  | 3000 | 0.1611          | 15.2159 | 7.5300 |
| 0.0001        | 16.0  | 4000 | 0.1605          | 15.0331 | 7.5370 |
| 0.0001        | 20.0  | 5000 | 0.1613          | 14.9646 | 7.4814 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3