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metadata
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

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 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