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whisper-small-clean_v6

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metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - lyhourt/clean_6
metrics:
  - wer
model-index:
  - name: whisper-small-clean_6-v6
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: lyhourt/clean_6
          type: lyhourt/clean_6
        metrics:
          - name: Wer
            type: wer
            value: 26.64601084430674

whisper-small-clean_6-v6

This model is a fine-tuned version of openai/whisper-small on the lyhourt/clean_6 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3768
  • Wer: 26.6460

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: 64
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1354 0.2 100 0.4427 34.7792
0.1115 0.4 200 0.3909 27.7304
0.1105 1.002 300 0.3762 27.8854
0.0392 1.202 400 0.3856 26.6460
0.0444 1.4020 500 0.3768 26.6460

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1