Whiser Small SNam

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

  • Loss: 1.0928
  • Wer: 48.4848

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: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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
0.0 1000.0 1000 0.6416 33.3333
0.0 2000.0 2000 0.8685 36.3636
0.0 3000.0 3000 0.9761 42.4242
0.0 4000.0 4000 1.0835 48.4848
0.0 5000.0 5000 1.0928 48.4848

Framework versions

  • Transformers 4.48.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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