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whisper-small-en-hi

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3279
  • Wer: 24.0479

Model description

Two datasets are used for two different languages, for hindi mozilla-foundation/common_voice_11_0 is used and for english google/fleurs is used. with combination of two dataset wer has decreased significantly.

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: 3000

Training results

Training Loss Epoch Step Validation Loss Wer
0.059 2.52 1500 0.2881 24.7722
0.0084 5.03 3000 0.3279 24.0479

Framework versions

  • Transformers 4.33.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.13.3
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