Whisper Small Hi - Sanchit Gandhi

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4377
  • Wer: 32.9848

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: 32
  • 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
No log 0.0 1 2.2652 86.7857
0.1858 1.22 500 0.3301 39.7317
0.0881 2.44 1000 0.2966 34.9065
0.0457 3.67 1500 0.3160 33.8695
0.0195 4.89 2000 0.3571 33.9287
0.0047 6.11 2500 0.3913 33.4843
0.0014 7.33 3000 0.4186 32.9637
0.0005 8.56 3500 0.4286 33.0737
0.0005 9.78 4000 0.4377 32.9848

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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