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Whisper medium Hi - Aa

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

  • Loss: 0.3556
  • Wer: 24.2275

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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0564 2.4450 1000 0.2346 26.9153
0.0159 4.8900 2000 0.2877 26.1619
0.0026 7.3350 3000 0.3198 24.9471
0.0002 9.7800 4000 0.3457 24.8074
0.0001 12.2249 5000 0.3556 24.2275

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Safetensors
Model size
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Tensor type
F32
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Finetuned from

Dataset used to train Aakali/whisper-medium-hi

Evaluation results