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metadata
language:
  - id
license: apache-2.0
base_model: openai/whisper-small
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_9_0
metrics:
  - wer
model-index:
  - name: Whisper Small Indonesian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_9_0 id
          type: mozilla-foundation/common_voice_9_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 12.997469519208648

Whisper Small Indonesian

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3455
  • Wer: 12.9975

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.061 3.87 1000 0.2545 13.1907
0.0062 7.74 2000 0.3144 13.2229
0.0014 11.62 3000 0.3455 12.9975
0.0008 15.49 4000 0.3582 13.2551
0.0007 19.36 5000 0.3638 13.2827

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3