Whisper Small eng - Himanshu

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

  • Loss: 0.5925
  • Wer: 17.9209

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0014 20.0 1000 0.5083 17.6574
0.0008 40.0 2000 0.5600 18.1552
0.0002 60.0 3000 0.5837 17.8917
0.0002 80.0 4000 0.5925 17.9209

Framework versions

  • Transformers 4.43.3
  • Pytorch 2.4.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Evaluation results