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whisper-small-Eng-1

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

  • Loss: 5.0620
  • Wer: 239.6

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • training_steps: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
7.156 0.01 5 6.9727 256.4
7.5392 0.02 10 5.0620 239.6

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train hashiikhan/whisper-small-Eng-1

Evaluation results