Whisper Small EN-BN ASR

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

  • Loss: 0.0514
  • Wer: 17.3903

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: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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_ratio: 0.03
  • training_steps: 8000

Training results

Training Loss Epoch Step Validation Loss Wer
0.1073 0.3811 1000 0.0995 31.1461
0.0831 0.7622 2000 0.0781 26.3300
0.0525 1.1433 3000 0.0689 24.3359
0.0435 1.5244 4000 0.0605 21.2507
0.0391 1.9055 5000 0.0543 19.3544
0.018 2.2866 6000 0.0564 18.5793
0.0175 2.6677 7000 0.0519 18.1804
0.0063 3.0488 8000 0.0514 17.3903

Framework versions

  • Transformers 4.50.3
  • Pytorch 2.4.1+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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Dataset used to train satarupa22/Wishper-small-asr-bn

Evaluation results