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---
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 |