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Whisper Small Hindi - Shripad Bhat

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: 0.3909
  • Wer: 21.4519

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4337 0.73 100 0.4874 47.5868
0.1894 1.47 200 0.3264 23.9482
0.1007 2.21 300 0.3101 22.5267
0.0984 2.94 400 0.3064 21.5723
0.0555 3.67 500 0.3325 22.0251
0.029 4.41 600 0.3439 21.4863
0.0163 5.15 700 0.3668 21.6468
0.0153 5.88 800 0.3756 21.4662
0.0081 6.62 900 0.3888 21.5035
0.0059 7.35 1000 0.3909 21.4519

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train shripadbhat/whisper-small-hi

Evaluation results